1. Tollgate files on all 5 phases of lean six sigma based on a simulated project on the Acuity Institute platform.
2. Certification exams of all 5 phases of lean six sigma on the Acuity Institute platform.
The exams can be completed by next month. This week I just need 2 files on define and measure phases bases on the project. But I would like 1 tutor to complete all 5 phases of the project.
In total 5 assignments and 5 exams.
ONLY RESPOND IF YOU HAVE DONE PROJECTS ON LEAN SIX SIGMA BEFORE.
1Copyright © 2016 Acuity Institute LLC. All rights reserved.
Lean Six Sigma
Green Belt
Course eBook
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2Copyright © 2016 Acuity Institute LLC. All rights reserved.
DISCLAIMER OF WARRANTY/LIMITATION OF LIABILITY
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Disclaimer of Warranty and Limitation of Liability
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No part of this publication may be reproduced, stored, or
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mechanical, photocopying, recording, or otherwise, without
permission from Acuity Institute LLC.
For information contact:
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Printed in the United States of America
Visit: www.acuityinstitute.com
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eBook Overview
Welcome to the eBook for the Acuity Institute Lean Six Sigma Green Belt Certification Program.
You will need the most recent version of Adobe Reader to view the eBook. We do not recommend viewing
the eBook with Adobe Acrobat.
We recommend becoming familiar with the eBook and its features. A few features include printing, viewing
notes, and capturing your comments.
For ease of use, we have included numerous bookmarks in the eBook so you can quickly access common
course concepts.
The eBook is for personal use only. Please do not use the eBook for presentations and training facilitation.
The eBook is for the intended parties only.
This eBook contains various exercises that are represented by the following icons:
General
ExercisesEXERCISE
1
Simco International Products Simulated Project.
When you see this icon you will be completing
an exercise within the simulation. We call these
exercises “deliverables”.
When you are done with the Deliverable you can
return to the course material by selecting the
“Go Back To Lesson” link.
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Course Objectives
2
Upon completion of this course, students will be able to:
Apply Lean Six Sigma and the DMAIC methodology
Apply skills in project management, process management, lean, change
management, and statistical analysis
Define their role in a successful Lean Six Sigma deployment
Recognize how to scope, define and lead Lean Six Sigma projects
Recognize how to transition projects from phase to phase
Complete projects
Present projects to peers, managers and senior leadership
Apply methods learned in the DMAIC process to business issues
Apply statistical analysis to determine the relationship between key inputs and
process outputs
Characterize the equation y = f(x)
Implement controls to sustain gains
Effectively manage team dynamics
Navigate statistical analysis software (SigmaXL or Minitab)
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Course Lessons
Define Measure Analyze Improve Control
1. Lean Six Sigma
Introduction
2. Define Overview
3. Project Charter
4. Project
Management
5. Process
Definition
6. Stakeholder
Management
7. Voice of
Customer
8. Measure
Overview
9. Identify
Measures
10. Data Collection
11. Describe &
Display Data
12. Baseline
Performance
13. Analyze
Overview
14. Root Cause
Analysis
15. Lean Process
Analysis
16. Graphical Data
Analysis
17. Statistical Data
Analysis
18. Identify Root
Causes
19. Improve
Overview
20. Identify &
Select
Solutions
21. Financial
Impact of
Solutions
22. Risk Planning
& Testing
23. Implement
Solution
24. Control
Overview
25. Process
Control
26. Response
Planning
27. Project
Documentation
The Lean Six Sigma Green Belt course contains 27 lessons, and 5 Simulated Project sections
(32 Project Deliverables)
3
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Lean Six Sigma Toolkit
The Lean Six Sigma Toolkit icon is periodically introduced in this eBook The toolkit icon
informs you that a Lean Six Sigma template is available for your use. The templates are
located in the “Lean Six Sigma Toolkit Templates” folder. To access the templates you will
need to download this folder onto your computer.
The Lean Six Sigma Toolkit assists practitioners in keeping focused on their project work and
not creating “templates”. The toolkit includes common templates used throughout the Lean Six
Sigma DMAIC phases. The templates are developed in common formats (MS Word, MS Excel
or MS PowerPoint).
Included Templates Solutions Benefits and Implications
Solutions Prioritization Matrix
Solutions Selection Matrix
Stakeholder Identification
Stakeholder Management Plan
Stakeholder Map
Standardized Procedures
Team Meeting Agenda
Team Profile
VOC Research Plan
XY Matrix
Pilot Plan
Process Monitoring Plan
Process Value Analysis
Project Charter
Project Storyboard
Quick Win Identification
Response Plan
Sigma Calculator
SIPOC
5 Whys
Communication Plan
CTQ Chart
Dashboard Measurement Plan
Data Collection Plan
DMAIC Project Plan
DMAIC Tollgate Presentation
FMEA
Force Field Diagram
Implementation Plan – Detailed
Implementation Plan – High Level
Template Name
4
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Acuity Institute Support
For product support questions please contact Acuity Institute at
support@acuityinstitute.com
Please visit www.acuityinstitute.com
for additional product and course offerings
5
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Lean Six Sigma Introduction
Lean Six Sigma Training
1
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By the end of this lesson, you will be able to:
Learn what Lean Six Sigma is
Learn about various Lean Six Sigma Improvement Methodologies
Learn what the Lean Six Sigma Roles and Responsibilities are
Overview – Objectives – Key Topics
2
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Experience with Other Quality InitiativesEXERCISE
Objective
Identify past experiences with other Quality or Process Improvement
initiatives.
Instructions
Answer the following questions:
What has been your experience with other Quality or Process
Improvement initiatives?
What was good about the other Quality or Process Improvement
initiatives you were involved in?
What struggles or challenges have you had with other Quality or Process
Improvement initiatives?
What could have made them better?
Prepare your findings.
3
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Please Do Not Proceed Forward
Experience with Other Quality InitiativesEXERCISE
4
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When you see this symbol, please do not continue forward in the materials until you have completed the exercise.
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Experience with Other Quality Initiatives
Discussion
EXERCISE
5
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Lean Six Sigma Training
Lean Six Sigma Overview
Lean Six Sigma Roles
Lean Six Sigma Improvement Methodologies
6
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Does your current performance meet customer expectations? Is there a
gap between what your company’s leaders want to achieve and the
organization’s ability to deliver it?
“Leaders who execute look for deviation from desired managerial
tolerances – the gap between the desired and actual outcome in everything
from profit margins to the selection of people for promotion… Like Six
Sigma, the discipline of execution doesn’t work unless people are
schooled in it and practice it constantly… Execution has to be part of an
organization’s culture…”
— Larry Bossidy, Former CEO of Allied Signal —
— Execution: The Discipline of Getting Things Done —
Vital Questions in an Increasingly
Competitive World
7
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Lean Six Sigma was developed out of necessity as a very rigorous and disciplined
approach for companies to improve products and services based on their customers’
expectations and requirements…an “outside looking in” approach. Lean Six Sigma has
many facets.
Lean Six Sigma Definition
Lean Six Sigma can improve profits and cut costs, but more importantly, it can
keep customers loyal as well as improve a company’s competitive advantage.
Goal
Vision
Philosophy
Benchmark
Methodology
Symbol
Metric
Tool
Process Focused
Business FocusedCustomer Focused
8
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Lean Six Sigma Definition
Lean Six Sigma uses a variety of tools and techniques to achieve superior
process performance, such as:
Customer Surveying (Voice of Customer)
Metric Identification and Collection
Baselining / Measuring Process Performance
Data Based Decision Making (Analysis and Statistics)
Lean Process Flow / Value Analysis
Benchmarking “Best In Class” Companies
Risk Analysis / Assessment
Implementation Planning / Management
Change Management
9
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A process is defined as a repetitive and systematic series of actions
or operations whereby one or more inputs from suppliers is used to
achieve an output of value to the customer (internal/external)
Input Output
Process
Actions
Process Model
What is a Process?
10
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I P O
The Work Process
I P O
The Improvement Process
Relationship of Work Process and
Improvement Process
11
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For every process there is a dependent variable called Y that we are
attempting to influence. The independent variables which determine
what happens to our Y are called the process X’s. Thus, we can boil
down every process into a simple formula:
Y = f(x1,x2,x3…xn)
The goal of Lean Six Sigma is to
understand the relationship between
our various Xs and our Y, so we can
manipulate the Xs to modify Y as desired,
then lock down the process so that Y
remains within the proper range and is
meeting customer requirements.
The Focus of Lean Six Sigma
12
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Lean Six Sigma Focuses on Reducing Variation
Variation Happens
All repetitive activities of a process have a certain amount of
fluctuation or variation
Variation is the “Voice of the Process”
When plotted, process variation becomes visible over time
Input, process, and output measures will have variation
Failure to understand variation could be costly
Time Frequency
13
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Why it’s Important to Understand Variation
PROCESS VARIATION INHIBITS OUR ABILITY TO MEET
CUSTOMER REQUIREMENTS
Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
A
Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
A
Variation
14
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Sigma is a Greek letter that is a statistical unit
of measurement used to define the standard
deviation of a population. It measures the
variability or spread of the data.
Sigma is a name given to indicate how much of the data falls within the
customers’ requirements. The higher the process sigma, the more
the process outputs, products and services, meet customers’
requirements – or, the fewer the defects.
“Sigma” Defined
15
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Defects are defined as not meeting customer requirements. Put simply, sigma is the measure of how far a process is away from achieving near perfect customer satisfaction. “6” Sigma is measured at near perfect… meeting customer expectations 99.99966% of the time.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
In this diagram, the Sigma is calculated by the number of occurrences
(defects) that fall outside of the customer requirement (for Process A).
Process B represents the optimal performance with no occurrences outside
of the requirement.
Optimal Performance
Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
B A
Customer
Requirement
“Sigma” Defined
16
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Process (A) has considerable variability or spread and is not meeting the critical customer requirement (identified by the defects). By reducing the variation of the Process (B), the process is more capable of meeting customer requirements and will lead to higher sigma performance and greater customer satisfaction.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
With performance at 2 Sigma:
ONLY 69.146% of products and/or services
meet customer requirements with 308,538
defects per million opportunities.
With performance at 4 Sigma:
99.379% of products and/or services meet
customer requirements…with 6,210 defects
per million opportunities.
With performance at 6 Sigma:
99.99966% – As close to flaw-free as a
business can get, with just 3.4 defects per
million opportunities.
Superior business
performance target
(common goal in
manufacturing
environments)
Realistic business
performance target for
transaction / service
industry
Most companies
processes perform at this
level or below prior to
improvement
Sigma Scale
17
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Most companies measured, prior to business performance improvement, perform around a 1 to 2 sigma, which equates to meeting customer expectations only 30.9% to 69.1% of the time.
These numbers are staggering and can be extremely detrimental to customer satisfaction with products and services. Although 6 Sigma is difficult to achieve in some industries, a 3.5 Sigma (meeting customer expectations 97.7% of the time) is realistic for most service related companies.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Why “6” Sigma?
When Processes Operate at less than 6 Sigma:
Two unsafe plane landings per day at
most major airports
500 incorrect surgical operations per
week
One hour unsafe drinking water per
month
16,000 pieces of mail lost every day
No electricity for 7 hours per month
Even if your goal is 99.0% quality… Your results would be:
18
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Lean Six Sigma is a framework to improve performance
Lean Six Sigma is not the solution for everything
Lean Six Sigma does apply to every function and business
Lean Six Sigma is not just about statistics
Lean Six Sigma is about Business Performance
Lean Six Sigma is not new work
Lean Six Sigma is a better way to work
Lean Six Sigma – What it is and What it is not
19
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Applying Lean Six Sigma
Lean Six Sigma can be applied to any process problem to achieve significant
improvement results. The following are a few examples…..
Results After
Applying Lean Six
Sigma
Application of
Lean Six Sigma
Core Process
Area
Operations – Claims
Payment
(Insurance Provider)
Reduced claims eligibility
determination errors to 5%
Saved over $1 MM per
year in cost avoidance
dollars
Inaccurate determination of
claims eligibility occurred
26% of the time resulting in
a loss of $1.1 MM per year.
Applied Lean Six Sigma to
identify root causes of
claims eligibility
determination errors.
HR – Staffing
(Employee Benefits
Provider)
Increased employee
retention by 20%
utilizing exit interview
data
Applied Lean Six Sigma to
identify root causes of high
employee turnover and loss
of high potential employees.
20
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Applying Lean Six Sigma
Results After
Applying Lean Six
Sigma
Core Process
Area
Application of
Lean Six Sigma
Sales
(Vehicle Service Contract
Provider)
Increased sales volume by
40%
Increased revenue by 35%
Sales run rate data indicated
by year end there would be a
110,000 shortfall between
actual contract sales volume
and the sales volume goal.
Applied Lean Six Sigma to
identify root causes of reduced
sales volume.
IT – QA/Testing
(Software
Development
Company)
Extended cycle time of the
software bug fixing process
drove increased costs of
releasing a new software
product.
Utilized Lean Six Sigma to
identify drivers of extended
cycle time.
Reduced average bug
fixing process time
from 16 to 5 business
days
21
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Companies Deploying Lean Six Sigma (a sample)
Motorola
Allied Signal
General Electric
Sony
Honda
Maytag
Raytheon
Bombardier
Canon
Polaroid
IBM
American Express
Dow
Lockheed Martin
Texas Instruments
DuPont
Toshiba Fidelity Investments
Johnson & Johnson
Bank of America
Nokia
Digital Electronics
Kodak
Jaguar
22
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Lean Six Sigma Training
Lean Six Sigma Overview
Lean Six Sigma Roles
Lean Six Sigma Improvement Methodologies
23
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Process
Management Kaizen DMAIC DFSS
Just Do
It
• Problem
identified and
solution is
known
• Implement a
fix and
establish a
dashboard to
continuously
monitor
process
• Process
performance is
unknown or not
understood
• Implement a
process
monitoring
dashboard to
decide what to do
next
• Problem
identified and
solution is
unknown.
• Small in scale
or urgency
needed for
process
improvement
• Initiate 2-5 day
Kaizen Event
to analyze the
process and
implement
improvements
• Existing
process is not
meeting
customer
requirements
or business
objectives
• Initiate a
DMAIC
project to
identify root
causes of the
problem and
initiate
breakthrough
improvements
• New product
or process
needs to be
designed or
significant
problems to
current
process exist
• Initiate DFSS
project to
design
processes to
meet
customer
requirements
Types of Improvement Methodologies
Lean
• Process is
inefficient and
contains
wasteful
activities
• Initiate a Lean
project to
identify non
value-add
activities and
remove waste
from the
process
24
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“Process Management” and “Just Do It”
Process Management
Manage processes more effectively by the collection, display,
and evaluation of process data.
Data is important in that it fuels the various problem solving
approaches, specifically the ability to execute Lean Six Sigma
projects.
Just Do It
Pinpoint process problem
Solution(s) already known
Implement solution(s)
Measure performance (ongoing Process Management)
25
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A Kaizen Event is a very concentrated team-
oriented effort to rapidly improve the
performance of a process.
Kaizen
Event
Team effort is coordinated over a brief period of time – typically
no more than 5 days.
A Kaizen Event can be very chaotic for a short period until
solutions can be implemented as numerous and major
improvements will be implemented at the same time.
Kaizen involves deliverables and activities prior to and right
after the Kaizen Event that must be completed to ensure
successful execution.
“Kaizen” Events
26
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“Lean”
Lean is utilized for the following purposes:
To reduce or eliminate capacity constraints of the
process
To reduce the lead time of the process
Step 1 Step 2 Step 3 Step 4
Bottleneck
Inputs Outputs
2 Days 10 Days 4 Days 6 DaysInputs Outputs
=22 Days
27
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“DMAIC” and “DFSS”
Define
Measure
Analyze
Improve
Control
Define
Measure
Analyze
Design
Verify
Continuous
Process
Improvement
(DMAIC)
CTQ Tree
ID Root Causes that drive
process performance
Design for Six
Sigma
(DFSS)
QFD
Optimized Design
across processes
Methodology and Primary Focus of Each Discipline
28
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Process
Management Kaizen
DMAIC
DFSS
Just Do It
Selecting the Lean Six Sigma Methodology
Lean
Process
performance
understood?
Can the
problem be
solved in less
than 5
days? Is it a
process flow
/ cycle time
problem?
Is it a
variation /
defect driven
problem?
Is a new
process or
redesign
required?
Is the
solution to
the problem
simple &
known?
Start
Yes
No
Explore Other Methodologies
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
29
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Improvement Techniques – Lean and Six Sigma
Combining Lean and Six Sigma is Best in Class
Six SigmaLean
Effect
Cause A
Cause D
Cause C
Cause B
Quality and Efficiency
Improvement
Efficiency
Improvement
30
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Lean Six Sigma DMAIC Methodology Defined
DMAIC is a
Common Lean Six
Sigma Problem
Solving
Methodology
ANALYZE
“Identify root cause for
performance shortfalls”
CONTROL
“Monitor new
processes or products”
IMPROVE
“Identify and implement
solutions”
MEASURE
“Measure current
performance”
DEFINE
“Identify customer
requirements”
31
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The focus of this course is the Lean Six Sigma DMAIC Methodology.
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Define Measure Analyze Improve Control
Project Charter
Project Management
Project Plan
Process Definition
SIPOC
As-Is Process
Map
Quick Win
Identification
Stakeholder
Management
Stakeholder Map
Stakeholder
Management Plan
Communication
Plan
Voice of Customer
Customer
Identification
VOC Research
Plan
Kano Analysis
CTQ Identification
Root Cause Analysis
Affinity Diagram
Fishbone Diagram
and/or 5 Why’s
Lean Process
Analysis
Lean Tools and
Measures
Graphical Data
Analysis
Histogram
Pareto Chart
Box Plots
Correlation
Analysis
Statistical Data
Analysis
Linear Regression
Multiple
Regression
Root Causes
Identified
Quick Win
Identification
Identify Measures
X/Y Matrix
Data Collection
Operational
Definitions
Measurement
Systems Analysis
(MSA)
Data Collection
Plan
Describe and Display
Data
Histogram
Pareto Chart
Pie Chart
Run Chart
Control Charts
Baseline Performance
Sigma
Performance
Yield
Process
Capability
Quick Win
Identification
Identify and Select
Solutions
Generate Solutions
Benchmarking
Solutions
Prioritization Matrix
Solution Selection
Matrix
To-Be Process Map
Financial Impact of
Solutions
Cost/Benefit Analysis
Risk Planning and
Testing
Failure Modes and
Effects Analysis
(FMEA)
Pilot Plan
Implement Solutions
Multi-Generational
Product Plan (MGPP)
Implementation Plan
Stakeholder
Management
Project Storyboard
Process Control
Control Charts
Process
Monitoring Plan
Dashboard
Response Plan
Project
Documentation
Process
Procedures
Replication
Opportunities
Solution Transfer
Plan
Key DMAIC Project Deliverables
32
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Lean Six Sigma Training
Lean Six Sigma Overview
Lean Six Sigma Roles
Lean Six Sigma Improvement Methodologies
33
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Champions
Black Belts
and Green
Belts
Master
Black Belts
Process Owners &
Project Sponsors Projects
Project Team
Members and
SMEs
Collaborative Effort
is the Key
Lean Six Sigma Roles
34
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Roles are structured to support project success and drive business performance results. It is critical to gain agreement of roles and time commitment early so teams can establish chemistry and focus on project deliverables.
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Champions / Executive Leadership
Monitors the external and internal factors affecting the business
Defines business strategy
Communicates the plan for business success
Champions Lean Six Sigma vision
Establishes improvement priorities and targets
Provides and aligns resources (Sponsors, Black Belts / Green
Belts), ensures cross-functional collaboration
Establishes accountability for results
Role modeling appropriate behaviors, change leader
Integrates Lean Six Sigma into business direction & plan
Markets Lean Six Sigma program and results
35
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Process Owners
Assists in identifying potential Lean Six Sigma projects
Approves and supports projects
Provides resources to serve as team members and subject mater
experts (SMEs) on projects
Approves changes in project scope and removes barriers
Owns the solution delivered by the project team
Responsible for supporting implementation of improvement
actions
36
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In many cases the Process Owner and Project Sponsor are the same person supporting the project.
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Project Sponsors
Provides and aligns resources (Black Belts / Green Belts, Team
Members), ensures cross-functional collaboration
Establishes improvement priorities, targets and accountability for
results
Role modeling appropriate behaviors, change leader
Ensures project is aligned with department and strategic
objectives
Approves all phases of Lean Six Sigma projects
Ensures project deliverables are being maintained and project is
on time and on budget
Approves changes in scope of the project, removes barriers
Markets Lean Six Sigma program and results
37
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In many cases the Process Owner and Project Sponsor are the same person supporting the project.
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Master Black Belt
Part-time or full-time position
Provides expertise on Lean Six Sigma tools and techniques,
including project management and change management
Provides strategic direction to leadership and project team
Identifies projects critical to achieving business goals
Is ultimately accountable for project success
Serves as main champion during change implementation
Identifies, trains, coaches and evaluates Black Belts / Green
Belts and Team Members
Ensures cross-functional & cross-team collaboration
Acts as Lean Six Sigma advisor to Champions, Sponsors and
Process Owners
38
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Black Belt
Full-time position
Provides direction and leadership for project team, manages
inter-project communications
Delivers results through application of Lean Six Sigma
methodologies
Provides skills training when needed
Accountable for reporting project progress and coordinating
communication to project stakeholders
Maintains all documentation from project, prepares and submits
deliverables
Manages implementation of solutions, ensures transition of
improved process to the business
Acts as a change catalyst
39
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Green Belt
Part-time position
Provides direction and leadership for project team, manages
inter-project communications
Delivers results through application of Lean Six Sigma
methodologies
Provides skills training when needed
Accountable for reporting project progress and coordinating
communication to project stakeholders
Maintains all documentation from project, prepares and submits
deliverables
Manages implementation of solutions, ensures transition of
improved process to the business
Acts as a change catalyst
40
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Project Team Members
Part-time position
Team player in application of Lean Six Sigma methodologies
Provides expertise and feedback to the project team
Is responsible for tasks within the team action plan
Delivers regular updates to team on status of action steps
Acts as a change catalyst
41
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In many organizations Project Team Members are referred to as “Yellow Belts”.
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Subject Matter Experts (SME)
As-needed position
Provides subject matter expertise and feedback to the project
team
Acts as a change catalyst
42
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Finance Analysts (also a SME)
Part-time role
Responsible for providing financial support to Lean Six Sigma
deployment
Provides standard, consistent guidelines for project valuation
Provides financial savings forecast for potential projects
Estimate project savings during the project execution
Track / validate actual project savings after project closure
43
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Project
Status
Phase
Potential Defined
Define
Active
Measure Improve /
Implement
Control
Realization
Ty
pi
ca
l L
ev
el
o
f E
ffo
rt Champion/Sponsor
Black Belt / Green Belt
Define
Project
& Scope
Select
Black Belt/Green
Belt
Project
Team
Kickoff
Develop, Sell, Pilot, and
Implement Solutions
Standardize and
Replicate Solutions
Master Black Belt
Analyze
Fi
na
l P
ro
je
ct
V
al
id
at
io
n
Process Owner
Project Team
In
iti
al
P
ro
je
ct
V
al
id
at
io
n
(B
y
B
B
o
r G
B
)
Pr
oj
ec
t A
ut
ho
riz
at
io
n
(A
ss
ig
ne
d
to
B
B
o
r G
B
)
DMAIC Project Deployment Effort Required
44
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What you learned during this lesson:
Summary of Lesson
Understanding what Lean Six Sigma is
Introduction to the various Lean Six Sigma Improvement
Methodologies
Understanding of what the Lean Six Sigma Roles and
Responsibilities are
45
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End of Lesson: Lean Six Sigma Introduction
Lean Six Sigma Training
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Define Phase
Lean Six Sigma Training
1
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Define Phase Overview
Lean Six Sigma Training
2
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Define establishes the project scope and
boundaries, the problem the team is improving and
the goals that will be achieved once improvements
have been implemented, the process that the team
is improving, and the customer requirements of the
process.
Define Phase Introduction
3
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Develop Project Charter for Business
Problem/Case, Roles and Project Plan
Key Characteristics of Effective Teams
Document and Understand the Current
Process
Identify Quick Win Opportunities
Understand How to Manage Stakeholders
Identify Customer Requirements (CTQ’s)
through Voice of Customer (VOC)
Voice of
Customer
Voice of
Customer
ANALYZE
CONTROL
IMPROVE
MEASURE
DEFINE
Define Phase Overview
4
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Define Phase Deliverables
Define Measure Analyze Improve Control
Project Charter
Project Management
Project Plan
Process Definition
SIPOC
As-Is Process
Map
Quick Win
Identification
Stakeholder
Management
Stakeholder Map
Stakeholder
Management Plan
Communication
Plan
Voice of Customer
Customer
Identification
VOC Research
Plan
Kano Analysis
CTQ Identification
Root Cause Analysis
Affinity Diagram
Fishbone Diagram
and/or 5 Why’s
Lean Process
Analysis
Lean Tools and
Measures
Graphical Data
Analysis
Histogram
Pareto Chart
Box Plots
Correlation
Analysis
Statistical Data
Analysis
Linear Regression
Multiple
Regression
Root Causes
Identified
Quick Win
Identification
Identify Measures
X/Y Matrix
Data Collection
Operational
Definitions
Measurement
Systems Analysis
(MSA)
Data Collection
Plan
Describe and Display
Data
Histogram
Pareto Chart
Pie Chart
Run Chart
Control Charts
Baseline Performance
Sigma
Performance
Yield
Process
Capability
Quick Win
Identification
Identify and Select
Solutions
Generate Solutions
Benchmarking
Solutions
Prioritization Matrix
Solution Selection
Matrix
To-Be Process Map
Financial Impact of
Solutions
Cost/Benefit Analysis
Risk Planning and
Testing
Failure Modes and
Effects Analysis
(FMEA)
Pilot Plan
Implement Solutions
Multi-Generational
Product Plan (MGPP)
Implementation Plan
Stakeholder
Management
Project Storyboard
Process Control
Control Charts
Process
Monitoring Plan
Dashboard
Response Plan
Project
Documentation
Process
Procedures
Replication
Opportunities
Solution Transfer
Plan
5
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End of Lesson: Define Phase Overview
Lean Six Sigma Training
6
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Project Charter Development
Project Selection
Define – Project Charter
Lean Six Sigma Training
Effective Teams
1
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By the end of this section, you will be able to:
Learn why developing a Lean Six Sigma project selection criteria
is important
Learn how to select Lean Six Sigma projects
Overview – Objectives – Key Topics
2
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Why Establish a Lean Six Sigma Project
Selection Process?
Ensure all business process issues from all possible
sources have been incorporated
Ensure alignment of potential improvement ideas with
business and customer satisfaction goals
Resource and time constraints require the business to
work on the most important issues first
3
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Select key
improvement areas that
will drive key
performance indicators
(KPIs), strategy, and
improve customer
satisfaction
Brainstorm
potential projects
Prioritize potential
projects
Select projects by
consensus of business
leaders
Active Projects Initiatives
Key Improvement Areas
A B EC D
Potential
Projects
________
________
Prioritize Prioritize Prioritize Prioritize Prioritize
Potential
Projects
________
________
Potential
Projects
________
________
Potential
Projects
________
________
Strategy
Customer
Requirements
Core
Processes
KPIs
Key Performance Indicators
KPIs
Potential
Projects
________
________
Project Identification
4
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L M H
Understanding of How to Solve the Problem
B
us
in
es
s
or
C
us
to
m
er
Im
pa
ct
“Boiling the
Ocean”
“Just Do It”
“Looking Good”
“Why Bother?”
H
M
L
Quick
Wins
Lean Six
Sigma
Projects
What Makes a Good Lean Six Sigma Project
Step 2: Project Identification
5
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High potential Lean Six Sigma
opportunity,
develop Project Charter
Potential Lean Six Sigma opportunity
Low potential Lean Six Sigma
opportunity
Prioritized list of Potential Projects
1
4
5
2
6
3
9
10
12
147
11
13
21
17
18
15
16
20
19
Low Medium High
Impact on Key Business Drivers
Lo
w
M
ed
iu
m
H
ig
h
Fi
na
nc
ia
l I
m
pa
ct
Step 3: Prioritize Potential Projects
8
6
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Lean Six Sigma Projects Selected
Low Medium High
Impact on Key Drivers
Lo
w
M
ed
iu
m
H
ig
h
Fi
na
nc
ia
l I
m
pa
ct
Step 4: Select Projects
21
17
18
15
16
20
19
Next Step: Assign
Black Belts / Green
Belts to the Projects
and Complete the
Individual Project
Charters
7
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What you learned during this section:
Summary of Section
Understand why developing a Lean Six Sigma project selection
criteria is important
Understand how to select Lean Six Sigma projects
8
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Project Charter Development
Project Selection
Define – Project Charter
Lean Six Sigma Training
Effective Teams
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By the end of this section, you will be able to:
Understand what a project charter is and why it’s important
Learn the steps and components for drafting a project charter
Learn the tips and traps for drafting each component of a charter
Learn how to calculate estimated project benefit
Gain experience applying effective criteria to developing the charter
Learn how to identify when you need to change your project scope
Overview – Objectives – Key Topics
10
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A project charter is a document that defines the
project initiative. It provides purpose, focus and
goals for an improvement project team.
Defines what is expected of the team
Clarifies the desired outcomes of the project
Keeps the team focused
Aligns the team with organizational objectives
Transfers the project from the Sponsor to the
improvement team
Definition:
Purpose:
Definition and Purpose of a Project Charter
Project Charter
11
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The project charter is the first deliverable a project team will undertake. The first draft of the project charter is completed by the Sponsor, Master Black Belt, and Black Belt / Green Belt. Once the project is initiated, the project charter is owned by the project team. The Sponsor will continually provide input and approve elements of the project charter throughout the project.
A project charter is often referred to as a “living document”, since it is continuously updated throughout the engagement of the project.
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Name the project
What is the business unit being impacted?
Identify the project primary resources
What is the timeline for the project?
When was the charter revised?
How will this project drive strategic initiatives and goals?
Why is it important to do now? Why is it a priority?
What customer (s) will benefit from this project (may also
include internal customers) and how?
Business Case
General Information1. Project Overview
2. Project Description
What problem is the project addressing?
Where and when does the problem occur?
What are the defects? (not meeting customer expectations)
Problem Statement
Elements of a Project Charter
12
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2. Project Description
(continued)
What are the high level goals?
What are the goals for the project? Starts with a verb (i.e.,
reduce time; eliminate defects; control costs; increase revenue).
Include measurable targets
How will we know if this project is successful?
Project Goals
What is the primary area or process that the project will be
focused on?
What process(s) / department(s) are included in the project?
What process(s) / department(s) are excluded in the project?
What are the boundaries of the process we are improving?
Process start point? Process stop point?
Project Scope
What are the potential dollar benefits from the project?
Separate hard savings (cost reduction, increase in profits) from
soft savings (cost avoidance, customer retention)
Estimated Benefit ($$)
Elements of a Project Charter
13
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Determine people who will be involved in the project
Their function in the business (i.e. VP of Sales, Risk
Manager, Customer Service Representative)
Their role on the project (Champion/Sponsor, Master Black
Belt, Black Belt / Green Belt, Team Member, Subject Matter
Expert/SME, Financial Analyst)
List the anticipated amount of time the resource will spend on
the project (hours per week)
Identify other resources that may be required; such as
contract IM/IT help, outside consultants, market research,
etc.
Includes ad hoc members such as HR, IM/IT, Finance
Project Resources
Complete a preliminary, high-level project plan with start &
completion dates for each phase
Project Milestones
3. Project Resources
4. Project Milestones
Elements of a Project Charter
14
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Resources should be approved by the Champion (and/or Sponsor) and direct managers of the employees that will participate on the team prior to project kick-off.
Guidelines for Milestones:
Dates should be tied directly to the DMAIC phases.
Project plan and timeline should be aggressive but realistic.
Should be approved by all team members and Champion (and/or Sponsor) and updated regularly.
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Defines the project name
Clearly distinguishes the project from other projects
Uses a name that is easy to remember
Documents the project primary area of focus and resources
assigned
Identifies the timeline of the overall project
Documents each time the charter is revised
Project Overview
15
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Explains/validates the project
Defines the “value-add” of the project
Explains the rationale for doing the project
Describes why it is important to the organization to do this
project now?
Indicates how internal/external customers will benefit
Describes potential consequences of not doing the project
Indicates the link between the project and current business
goals
Project Description – Business Case
16
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The business case describes the project and communicates the rationale for doing the project.
Typically, the business case is one area of the project charter that usually does not get revised or modified throughout the life of the project.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Pharmaceutical Provider
Pharmaceutical publications generate extensive publicity and marketing opportunities for our most important
drugs. These publications need to be released to the market place within crucial timelines from when the
drugs are to be sold. Currently, these publication releases are very time consuming and are not being
released until long after the new drugs have been distributed. This leads to loss of revenue due to the initial
and crucial advertising opportunities when the drugs are initially distributed.
Claims Processing Center
The Customer Inquiry process is an important touch point with our customers. Therefore, one of our
strategic objectives is to ensure the customer inquiry process is consistent in meeting our customer’s needs.
Customers have indicated that our customer inquiry process needs improvement. Currently, there is no
consistent approach or standard to handling customer inquiries. The handling and response to customer
inquiries varies a great deal from one customer service representative to another. This lack of consistency
leads to inaccurate handling of customer inquiries, rework, increased customer complaints, and ultimately
lost customers.
Telecommunications Provider
Customer survey results indicate that the timeliness of installing additional phone lines is critical to
satisfaction for our large business customers. Our large business customers are our most profitable
customer segment, therefore, meeting their requirements for the installation process is critical to our ability
to meet our annual profitability goals. Currently our installation process is meeting customer requirements
only 50% of the time. If we do not improve the timeliness of the installation process, we will continue to
receive customer complaints, lose customers, and lose revenue.
Business Case Examples
17
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The business case should describe the broad areas of the project and answer the question of why the project should be conducted. The business case should be written in such a way that it creates a compelling case for why the organization needs to do this project now.
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Identifies what problem the improvement project is addressing
Usually describes the “pain”, issue or problem
Can also describe an opportunity
Should be measurable
Identifies where and when problems occur
Defines what is not meeting customer expectations
Describes the magnitude and impact of the problem
Quantifies how large the problem is
Describes the impact presented by the problem
Project Description – Problem Statement
18
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We recommend including the baseline performance and capability (entitlement) of your current process in the problem statement.
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Tips:
Validate problem is based on data vs. perception or “gut feel”
Ensure the customers of the process and the organization think
working on this process is valuable and necessary
Traps:
Prejudging a root cause within the problem statement
Including a solution in the statement
Writing a statement that is too narrowly defined or too broadly
defined
Problem Statement Tips and Traps
19
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Pharmaceutical Publications
During the past year, publications have increased by a rate of 20% per
month. The time it takes to get a publication released is approximately 4
months. In addition, there are on average 4 drafts of each publication that
are created before it is approved for release. These problems lead to slow
market distribution and could lead to lost revenue if the publication is
released too late to have a positive impact on the new drug sales.
Claims Processing Center
Customer inquiries account for 65% of incoming claims calls. Currently, our
response time to these inquiries varies from 2 hours to 5 days. In addition,
approximately 10% of inquiry calls are call backs from customers who have
not received follow-up from their initial call. These problems are leading to
customer dissatisfaction with our services and ultimately loss of business.
Problem Statement Example
20
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Defines and clarifies the goals the project team is focused on
accomplishing
Includes measurable targets and completion date
Starts with a verb
Eliminate defects
Reduce time
Increase revenue
Decrease costs
If these goals are met the project is considered successful
Project Description – Project Goals
21
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Goal Statements Should be SMART !!
S – specific
M – measurable
A – attainable
R – relevant
T – time bound
Criteria for Developing Goal Statements
22
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Measurable
Assigns a quantifiable metric
for the goal
Attainable
While the goal should be a
stretch goal, it should also
have a high probability of
success given an assessment
of the potential resources,
timelines and challenges
Specific
A SMART goal identifies a
specific action driving a
specific outcome
Time Bound
The goal has an aggressive
but reasonable timeline for
meeting desired results
Relevant
The project goal should be
relevant to the organizational
strategy
Criteria for Developing Goal Statements
23
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Tips:
Should focus on the results that will drive and define project
success
Traps:
Including a solution as part of the project goals
Assigning blame in the statement
Goal Statement Tips and Traps
24
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Pharmaceutical Publications
Problem Statement – During the past year, publications have increased by a rate of 20% per
month. The time it takes to get a publication released is approximately 4 months. In addition,
there are on average 4 drafts of each publication that are created before it is approved for
release. This problems leads to slow market distribution and could lead to lost revenue if the
publication is released too late to have a positive impact on the new drug sales.
Goal Statement – Reduce publications release time by 50% and drafts to 1 for each
publication by August 30th.
Claims Processing Center
Problem Statement – Customer inquiries account for 65% of incoming claims calls.
Currently, our response time to these inquiries varies from 2 hours to 5 days. In addition,
approximately 10% of inquiry calls are call backs from customers who have not received
follow-up from their initial call. These problems are leading to customer dissatisfaction with
our services and ultimately loss of business.
Goal Statement – Reduce the response time <1 day and eliminate call backs from
customers by January 15th.
Problem and Goal Statement Examples
25
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Indicates the financial benefit of doing the project
What are the potential costs of not doing this project?
Quantify the potential financial impact and link to
business pain
Separate hard benefits (cost reduction, profit increase) from
soft benefits (cost avoidance, customer retention)
During the front-end of a project, detailed data and
information may not be available, so estimates may be
required at the beginning of a project
Updated and refined as the project proceeds and more data
becomes available
Project Description – Estimated Benefit
26
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One of the main goals of Lean Six Sigma is to improve the company’s
bottom line financial results over the long term
Capturing and reporting the financial benefits of the project are
important to determine:
Are we getting a return for our investment of valuable resources?
Are we having an impact on our key financial performance
measures?
How process improvements affect our organization’s financial
health and overall performance
Project benefits will be reported to the Leadership Team
The results must be verifiable and supported
Why the Estimated Project Benefit is Important
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To fully commit to and support a project, your Champion (and/or Sponsor) and other key stakeholders need to have at least a rough estimate of the projects impact. They then have an opportunity to buy into the project, or suggest revisions in scope or direction that will improve the business impact and estimated benefit.
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Hard Benefits - Improvements that result in real and measurable cost
or asset reductions.
Examples of Hard Benefits:
– Incremental revenues
– Cost reductions such as fewer headcount
Soft Benefits - Improvements that do not immediately reduce cost or
assets but provide benefits through improved process efficiency,
employee productivity, improved customer satisfaction, improved
competitiveness, etc.
Examples of Soft Benefits:
– Avoidance of lost sales
– Cost avoidance such as the need to hire 5 instead of 10
The Two Categories of Project Benefits ($$)
28
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Gross Hard Project Benefits
+
Gross Soft Project Benefits
Less: Project Implementation Costs
= Net Project Benefits
Net Project Benefits
Method to Calculate Estimated Project Benefits ($$)
29
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Hard benefits…such as:
Incremental Revenues…less Cost of
Goods Sold (COGS)
Cost Reductions
Soft benefits…such as:
Avoidance of lost sales…less COGS
Cost avoidance
Gross Hard Project Benefits
+
Gross Soft Project Benefits
Less: Project Implementation Costs
Implementation costs include...
Full-time resources assigned to the project
Consultants, contractors and temps
Other considerations for running the project
Implementation costs exclude…
Direct costs of Quality resources assigned
to the project prior to implementation
Gross Project Benefits
Net Project Benefits
Project Implementation Costs
Method to Calculate Estimated Project Benefits ($$)
30
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Reduce costs by 30%
($50,000 annually)
Reduce rework, increase
productivity per person
Reduce task time by 3
hours per week
10% increase in monthly
revenues ($725,000
annually)
Reduce re-work, speeds up
workflow cycle time
Reduce processing
accuracy defects
Reduce costs of potential
legal fees by 40% ($1.5
million annual impact)
Avoid legal costsEliminate compliance risk
20% increase in repeat
business ($2 million annual
impact)
Increase customer
satisfaction; increase
customer retention
Increase in on time delivery
and installation of phone
line from 80%-90%
Estimated dollar
impact of improvement
($$)
Benefit of ImprovementType of Improvement
Examples of Estimated Project Benefits ($$)
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Identifies the process the team will be focusing
on improving
Establishes project boundaries
Clarifies the process start and stop points
Clarifies which process(s) / department(s) are
included in the project
Identifies which process(s) / department(s) are
excluded from the project
Project Description – Project Scope
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Properly scoped projects are critical for success and optimal
benefit so pay attention to the following tips and traps:
Tips:
Avoid scopes that are too small to justify the manpower
commitment of a Lean Six Sigma project
Avoid too large of scopes which can take the team’s focus off the
key project objective and put the success of the project at risk
Traps:
Tendency in the beginning of the project to try to do too much
Overestimating the level of resource commitment
Overestimating the willingness of our stakeholders to embrace
radical change
Assigning blame in the statement
Project Scope Tips and Traps
33
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Be wary of scope creep!
Allowing the scope of your project to balloon can cause a team to lose
sight of the project objective and lead to project failure.
As a project’s scope increases linearly,
its complexity tends to increase
geometrically. It is therefore in our best
interest to keep our projects as
narrowly-focused as will yield significant
benefits.
Scope Creep
34
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There is a marked tendency at the outset of a Lean Six Sigma project to attempt to
do too much, to solve a problem so large and so profound that the effort involved
will be enormous. We call these types of initiatives “boiling the ocean” projects, as
they are likely to fail no matter how many resources are employed to work on them.
IF YOUR PROJECT...
Requires a project team of 6 or more
Requires either several pages of detailed
process mapping or process blocks which
are broad and cross-functional
Contains a problem statement which is not
specific to one issue
Has multiple Ys or customer requirements
Does not have a clear start and end point
Involves multiple Champions (and/or
Sponsors) from the highest levels of the
business
Requires more than a year of time to
complete start to finish
Encompasses multiple Lean Six Sigma
projects
REDUCE
THE
PROJECT
SCOPE!
Guidelines to Project Scope
35
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A problem which occurs far less frequently in Lean Six Sigma projects than “boiling
the ocean” projects, is the project that is so small in scope that it doesn’t yield
significant benefits or organizational impacts. If your project is too small in scope, it
may not be worth the investment of resources necessary to achieve its potential
benefits.
IF YOUR PROJECT...
Is not related to a strategic business
imperative
Has little or no impact on your customers
Project savings < cost to implement
Drives improvements which could be
implemented instantly without issue
Serves only to justify “common sense”
approach to problem
INCREASE
THE
PROJECT
SCOPE!
Guidelines to Project Scope
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To properly re-scope your project:
If the scope needs to be decreased: reexamine
your process map, business case, and problem
statement and consider breaking the project into
manageable pieces
If the scope needs to be increased: reexamine
your process map, business case, and problem
statement and cast your net wider for potential
improvements
Changing the Scope of Your Project
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Claims Processing Center
Area of Focus: New Claims Processing Process
Includes:
Claims Queue
Initial Claims
Reimbursement
Start: New claim is received from customer
Stop: Claim is approved and reimbursed or claim is denied
Excludes:
Denied Claims
Customer Complaints
Pharmaceutical Publications
Area of Focus: Publication Creation and Distribution Process
Includes:
Articles, Flyers, Marketing Materials
Review
Distribution
Start: Publication order is received
Stop: Publication is distributed
Excludes:
Publication Planning
Project Scope Examples
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Identifies all of the people that need to be involved on the project
team
Includes both formal members and satellite team members
(members involved in critical decisions, may help on key team
deliverables but not serve as a formal team member)
Identifies the resource’s functional role (VP Sales) in the organization
and their role on the project team (Champion)
Lists the anticipated amount of time the resource will spend on the
project (hours per week)
Should be approved by the Champion and direct managers of
employees that will participate on the project prior to kick-off
Project Resources
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A high level project plan with start and completion dates for each
phase
Critical points in the DMAIC process where progress is reviewed
Are reviewed at tollgate reviews
Negotiated with Champion/Process Owner based on
Scope of project
Complexity of project
Existence of relevant data
Amount of resource allocation
Project Milestones
40
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Guidelines for Milestones:
Dates should be tied directly to the DMAIC phases.
Project plan and timeline should be aggressive but realistic.
Should be approved by all team members and Champion and updated regularly.
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Most projects evolve, few are cast in stone from the beginning so the
charter is a living document
In each phase of DMAIC as you gather more data, the information in
the project charter can be further refined and updated
Be open to revising the scope, problem statement, and goal statement
as the team makes progress and learns more about the process they
are improving
Check with your Champion before making substantial changes to the
charter
Things to Keep in Mind when Developing a
Project Charter
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PROJECT DESCRIPTION
Business Case The Customer Inquiry process is an important touch point with our customers. Therefore, one of our
strategic objectives is to ensure the customer inquiry process is consistent in meeting our customer’s
needs. Customers have indicated that our customer inquiry process needs improvement. Currently,
there is no consistent approach or standard to handling customer inquiries. The handling and
response to customer inquiries varies a great deal from one customer service representative to
another. This lack of consistency leads to inaccurate handling of customer inquiries, rework, increased
customer complaints, and ultimately lost customers
Problem Statement Customer inquiries account for 65% of incoming claims calls. Currently, our response time to these
inquiries varies from 2 hours to 5 days. In addition, approximately 10% of inquiry calls are call backs
from customers who have not received follow-up from their initial call. These problems are leading to
customer dissatisfaction with our services and ultimately loss of business
Project Goals Reduce the response time <1 day and eliminate call backs from customers by January 15th
Estimated Benefits
($$)
Approximately $500K in hard savings (line charges, vendor charges) and $1.2MM in soft savings
(people time)
Project Scope Area of Focus: New Claims Processing Process
Includes: Claims Queue, Initial Claims, Reimbursement
Excludes: Denied Claims, Customer Complaints
Start Point: New claim is received from customer
Stop Point: Send notification to customer
Project Charter Example – Processing Center
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Pay particular attention to the measurable elements of the example above. The problems and benefits are concise and easily understood by the organization.
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Project Resources
Team Members Function in the Business Project Role
Time Dedicated to
Project (Hrs/Week)
Chris Matthews Claims Service Rep Black Belt / Green Belt 20
Donna Hillary Accounts Reimbursement Team Member 5
Jason Whitley Customer Service Rep Team Member 5
Clyde Mahoney Risk Assessment SME 2
Kristine Swanson Quality MBB 2
Suzy Maculvey VP, Claims Champion 1
Additional Support Finance, IT (resources to be named later)
Project Milestones
Milestone Phase Start Date Completion Date
Define January 1st February 14th
Measure February 11th In Progress
Analyze March 23rd April 9th - To Be Completed
Improve April 10th May 29th - To Be Completed
Control May 30th June 30th - To Be Completed
Closure July 1st August 1st - To Be Completed
Project Charter Example – Processing Center
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Pay particular attention to the measurable elements of the example above. The problems and benefits are concise and easily understood by the organization.
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Objective
Practice applying SMART criteria to various goal statements from project
charters.
Instructions
Utilize the SMART criteria to identify which of the following goal statements
on the following page are:
Specific
Measurable
Attainable
Relevant
Time Bound
Identify which element(s) of the SMART criteria is missing, if any.
Prepare your findings.
SMART Project Charter EXERCISE
44
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1. Reduce credit card resolution time by 75% in 2 weeks. In addition maintain
credit card resolution accuracy.
2. Improve the meeting room scheduling process.
3. Reduce failed installs by 30%
4. Achieve an 80% or greater small business customer retention rate by year
end.
5. Improve profitability.
6. Reduce late and early appliance deliveries in 6 months from the project kick
off date.
7. Reduce contract processing cycle time by 40% and reduce required
resources by 10% by July 06.
8. Decrease costs by end of year.
SMART Project Charter EXERCISE
45
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Please Do Not Proceed Forward
SMART Project Charter EXERCISE
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When you see this symbol, please do not continue forward in the materials.
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1. Reduce credit card resolution time by 75% in 2 weeks. In addition maintain
credit card resolution accuracy. (not attainable)
2. Improve the meeting room scheduling process. (not relevant)
3. Reduce failed installs by 30%. (not time bound)
4. Achieve an 80% or greater small business customer retention rate by year
end. (no change)
5. Improve profitability. (not specific, not time bound, don’t know if it’s
attainable because we don’t have enough info)
6. Reduce late and early appliance deliveries in 6 months from the project kick
off date. (no quantifiable goal, by what percent?)
7. Reduce contract processing cycle time by 40% and reduce required
resources by 10% by July 06. (no change)
8. Decrease costs by end of year. (not specific)
SMART Project Charter – Answers EXERCISE
47
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What you learned during this section:
Understanding of what a project charter is and why it’s important
Steps and components for drafting a project charter
Tips and traps for drafting each component of a charter
How to calculate estimated project benefit
Gained experience applying effective criteria to developing the charter
How to identify when you need to change your project scope
Summary of Section
48
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Project Charter Development
Project Selection
Define – Project Charter
Lean Six Sigma Training
Effective Teams
49
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By the end of this section, you will be able to:
Know the keys to successfully operating as a team
Identify critical team roles and responsibilities
Identify team member profiles and interpersonal styles
Understand guidelines to communicate effectively within the team
Understand the importance of utilizing a conflict-resolution process
Understand team decision making methods
Overview – Objectives – Key Topics
50
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“SMART” Charter
Project Goals and
Objectives
Clearly Identified Roles &
Responsibilities
Who does What
Team Procedures
How does the Team
Complete Deliverables
Effective
Teams
Key Characteristics of Effective Teams
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Roles and responsibilities are clear
Members agree on how to work together
and make decisions
Members leverage differences in team
member profiles and interpersonal styles
Communication is clear and honest
among the team
Members use a conflict-resolution
process
Keys to Operating as a Successful Project Team
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Formalized team roles enables the team to effectively avoid the “too
many chiefs” syndrome (too many leaders).
Team members work more effectively when they know what is
expected of them
Having clear roles and responsibilities creates an environment of
accountability
Lack of clear roles can cause expectations to not be met which
increases team conflict
Roles that are not clearly defined lead to work overlap or significant
gaps, resulting in rework or catch-up effort
Importance of Team Roles and Responsibilities
53
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Black Belt / Green Belt
Provide mentoring and Lean Six Sigma tool expertise support to team
Validate that the team is following DMAIC process
Facilitate team communication internally and with other teams and stakeholders
Work with team to overcome roadblocks and sources of resistance
Keeps project team on track, coordinates team activities
Process Owner
Provide input and encourage the team
Attend critical team meetings when input on critical decisions is required
Takes ownership for the implementation of the process improvement and is
accountable for process results after implementation
Team Meeting Roles and Responsibilities
54
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Team Members
Come prepared to meetings
Complete tasks assigned and report back to the team
Support team and any consensus decisions by the team
Master Black Belt
Attend critical team meetings
Provides guidance and coaching to the Black Belt / Green Belt
Team Meeting Roles and Responsibilities
55
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Facilitator (Usually Black Belt / Green Belt, but role can be rotated)
Creates team meeting agenda
Guides team through agenda, tests for consensus, and clarifies discussion points
Gather all team member’s input, ensures all are engaged and given the opportunity to
participate
Schedules, arranges and conducts meetings
Timekeeper
Keeps meetings focused and on track
Helps maintain time limits on the agenda
Scribe/Recorder
Maintains shared files (electronic and paper)
Records meeting minutes and action items
Team Meeting Roles and Responsibilities
56
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What is a team member profile?
How individuals translate information
How individuals accomplish key tasks
How individuals interact with others
How individuals influence others
How individuals react to change
Understanding Team Member Profiles
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Stays clear of
confrontation
Avoids difficult or
challenging
discussions
Risk adverse
Calls for caution and
is often critical
Tentative or
restrained
Often waits until the
last minute to
complete
deliverables/tasks
Hesitates in diving in
due to fear of failure
Works well under
pressure
Seeks alternative
ideas
Does not pay much
attention to detail
Characterized by
originality and
expressiveness
AvoiderCautiousProcrastinatorCreative
Often positive about
things
One who usually
expects a favorable
outcome
Requires information
and data to make
decisions
Focuses on details
Often over analyzing
things
Skilled at planning
Linear in thought
process
Enjoys the role of
“Gatekeeper”
Often completes
deliverables ahead
of schedule
Often takes control
of situations
Constantly pushing
for results
Sometimes individual
goals dominate
situations
OptimistAnalyzerTacticianDriver
Common Individual Behaviors
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Review the Individual Profiles among your team:
Do individuals share common behaviors?
If yes, should this be a concern?
If no, should this be a concern?
What behaviors may have a tendency to contradict each other?
What should the team do about this?
How can the team work effectively together given the various
Individual Profiles?
Developing a Team Profile
Team Profile
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Good communication practices for all team members:
Honest, candid team feedback
Balance positive and negative feedback
Support ideas with examples, information, data or pictures
Listening actively
Common communication mistakes to avoid:
Inadequate time for discussion
Faking understanding
Not paying attention to body language
Poor or ineffective communication can hinder team effectiveness
Team Communication Considerations
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Conflict is a normal part of team development, but here are some
guidelines…..
Tolerate conflict when it:
Enables ideas to be tested and built upon and is proving to be
constructive
Allows team members to gain a deeper understanding of one another
Increases creative thought
Increases involvement
Intervene to resolve conflict when it:
Team members become more concerned about “winning” the conflict
than communicating their point of view
Polarizes the team
Involves personal insult or attack
Disrespects the values of the organization
Team Conflict
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Talk through issues until a higher-level solution is
found and is supported by all team members
Openly discuss personal differences of opinion,
dealing with them directly but tactfully
Listen carefully to each person/group’s point of view
Clarify the core issue by separating areas of agreement from areas of
disagreement, then try to build small agreements to reach a compromise
To calm the agitation, have disagreeing team members write down their issues
and ideas before discussing with the group
Consider taking members who conflict outside of the meeting to mediate the
disagreement and come to a compromise
Team Conflict Management and Resolution
Techniques
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Method Description Effect
Non-intervention Avoids/Withdraws from addressing
situation
Does not solve problem
Smoothing De-emphasizes conflict, attempts to
smooth over
Short-term solution, can
resurface later
Compromising Giving up some things in exchange for
getting other things
Can provide resolution, but
can cause resentment
Forcing Forcing only one viewpoint High probability of conflict re-
emerging, increased
resentment
Collaborating Incorporates multiple viewpoints to gain
commitment from all
Long-term resolution
Confronting/
Problem Solving
Examine alternatives to find resolution
that meets everyone’s goals
Provides ultimate resolution
Methods to Deal with Conflict within the Team
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Decision making often requires time and effort to reach agreement within the
team. There are many internal and external influences that can delay the decision
making process. To assist you, the following are 5 potential options that a team
can utilize in making a decision.
Decide and Announce
Delegate with Constraints
Consensus
Gather Input from the Team and Decide
Gather Input from Others (influencers) and Decide
Decision Making
64
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What you learned during this section:
Know the keys to successfully operating as a team
Identify critical team roles and responsibilities
Identify team member profiles and interpersonal styles
Understand guidelines to communicate effectively within the team
Understand the importance of utilizing a conflict-resolution process
Understand team decision making methods
Summary of Section
65
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
End of Lesson: Define – Project Charter
Lean Six Sigma Training
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Tollgate Reviews
Meeting Planning
Project Planning
Define – Project Management
Lean Six Sigma Training
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Understand the importance of effective project planning
Learn tools for effective project planning
Understand how to develop a DMAIC Milestone plan for
your project
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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1. When is the project going to end?
2. What deliverables and tasks do I have to complete before the project is
completed?
3. Who is going to own completion of the project deliverables?
4. How are the Lean Six Sigma deliverables and tasks linked to one another?
5. How will the team members and other project resources allocate their time
to the project?
6. When are critical milestones supposed to be met?
Effective planning early in the project will help answer the
following questions:
Why Invest Time Planning?
3
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Start Date Stop Date
Milestone
A
Milestone
B
Milestone
C
Task
B
Task
A
Task
C
Task
D
Task
E
Task
F
Resources Aligned
Typical Project Planning Process
4
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Project planning is a set of milestones and activities that ends in
specific accomplishments.
Clear milestones and tasks
Start and end dates for each milestone, task, and sub-task
Resources aligned to tasks
Milestones of Lean Six Sigma
Project Planning Basics
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Milestones of Lean Six Sigma
Milestones – are key phases of the project where major deliverables are
completed and key decisions are made and approved by project stakeholders and
management. Each phase of Lean Six Sigma is considered a milestone.
Tasks – are the activities that are completed to reach the milestone. Tasks include
Charter, SIPOC, VOC. Every project plan should also have sub-tasks. Sub-tasks
are the detailed activities that the team will complete in order to finish the tasks. All
sub-tasks should use a verb-noun format, e.g., complete, deliver, check, collect,
etc.
Note: Both milestones and tasks/sub-tasks have start and end points to keep the
team aligned to the overall project timeline.
Project Planning Basics
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Milestone
Task
Sub-Tasks
Resources Completion
Dates
Predecessor
% Complete
Duration
Project Planning Elements
DMAIC Project
Plan
7
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Project Planning
Element
Definition
Resources The team members or other organizational
resources who will be responsible for completing
the tasks.
Duration The time in days that the milestone, task, and sub-
task is planned to take. This is based on the
calculation of the start date and end date.
% Complete The % complete of each milestone, task, and sub-
task. (Completion % should be updated regularly as
activities are completed on the project).
Predecessor The task or sub-task that proceeds the noted task
(A task marked with predecessors can not be
completed until the other tasks are completed).
Project Planning Elements Defined
8
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What you learned during this section:
The importance of effective project planning
Tools for effective project planning
How to develop a DMAIC Milestone plan for your project
Summary of Section
9
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Tollgate Reviews
Meeting Planning
Project Planning
Define – Project Management
Lean Six Sigma Training
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Understand the importance of effective meeting planning
Learn tools for effective meeting planning
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
11
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Objective
Identify effective meeting challenges and barriers in your organization.
Instructions
Identify current challenges and barriers to effective meetings in your
organization.
Prepare your findings.
Effective MeetingsEXERCISE
12
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Please Do Not Proceed Forward
Effective MeetingsEXERCISE
13
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When you see this symbol, please do not continue forward in the materials.
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Discussion
Effective MeetingsEXERCISE
14
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Effective meetings have the following characteristics:
The right people participating
Clear objectives
Understanding of objectives before meeting begins
Good facilitation of discussion, time, note taking
Good amount of breaks
Action items from meeting
Continuation from previous meeting(s) – if needed
Meeting Planning Basics
15
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Agenda Template:
Task Method Owner Time
Agenda Review Review Desired Outcomes & Tasks
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Key Agenda Elements:
– Meeting location, date, time
– Participants attending
– Desired outcomes of the meeting
– Tasks to be completed
– Method to complete each task (discussion, presentation, brainstorming, review, etc)
– Time and owner for each task
– Action items and minutes from previous meeting
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Meeting date, location, time, agenda with desired outcomes, and
materials that will be reviewed during the meeting should be sent to
participants at least 24 hours in advance of meeting
Allow ample time for agenda planning (a solid, organized agenda is
key to having a successful, productive meeting)
If difficult or challenging topics are to be discussed, meet with
participants ahead of time to get input and support for meeting
objectives
Have participants confirm participation by accepting meeting request
or obtain verbal during one-on-one meeting
Follow-up with completed tasks, next steps, and meeting minutes
should be sent out to participants no later than 24 hours after
meeting completion
Meeting Planning Tips
17
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The minutes should contain the following elements:
Outcomes of the meeting
Developed or updated materials
Action items and owners
Next steps
Next meeting schedule – location, date, time if planned
Each meeting should be followed up with minutes which document what
was discussed during the meeting and captures key action items.
Meeting Minutes
18
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What you learned during this section:
The importance of effective meeting planning
Tools for effective meeting planning
Summary of Section
19
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Tollgate Reviews
Meeting Planning
Project Planning
Define – Project Management
Lean Six Sigma Training
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By the end of this section, you will be able to:
Understand the purpose and importance of project tollgates
Know the process and guidelines for project tollgate reviews
Identify key deliverables required for each project tollgate review
Understand important considerations for tollgate review planning
Overview – Objectives – Key Topics
21
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DEFINE
MEASURE
ANALYZE
CONTROL
IMPROVE
A tollgate review is a checkpoint that ensures completion of each phase
of a DMAIC project.
Tollgate Purpose
DMAIC Tollgate
Presentation
22
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Sponsor (mandatory) – actively engaged in representing, supporting and
questioning the data and team members.
MBB (mandatory) – Sets expectation of tollgate process and objectives to
leadership. Engaged in supporting the team as needed.
Black Belt / Green Belt (mandatory) – leads presentation to leadership
and is overall accountable for presentation development and desired
outcomes of tollgate review.
Select Team Members (optional) – selected members actively participate
during review.
Champion (optional) – actively engaged in questioning the team for
completion of required tasks/objectives for each phase. Projects with cross-
team dependencies would have other teams’ champions participate.
Process Owner(s) (optional) – may attend all phases, but required for
Improve and Control phases.
Who Attends the Tollgate?
23
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DMAIC Deliverables for Tollgates
Define Measure Analyze Improve Control
Project Charter
Project Management
Project Plan
Process Definition
SIPOC
As-Is Process
Map
Quick Win
Identification
Stakeholder
Management
Stakeholder Map
Stakeholder
Management Plan
Communication
Plan
Voice of Customer
Customer
Identification
VOC Research
Plan
Kano Analysis
CTQ Identification
Root Cause Analysis
Affinity Diagram
Fishbone Diagram
and/or 5 Why’s
Lean Process
Analysis
Lean Tools and
Measures
Graphical Data
Analysis
Histogram
Pareto Chart
Box Plots
Multi-vari
Correlation
Analysis
Statistical Data
Analysis
Linear Regression
Multiple
Regression
Root Causes
Identified
Quick Win
Identification
Identify Measures
X/Y Matrix
Data Collection
Operational
Definitions
Measurement
Systems Analysis
(MSA)
Data Collection
Plan
Describe and Display
Data
Histogram
Pareto Chart
Pie Chart
Run Chart
Control Charts
Baseline Performance
Sigma
Performance
Yield
Process
Capability
Quick Win
Identification
Identify and Select
Solutions
Generate Solutions
Benchmarking
Solutions
Prioritization Matrix
Solution Selection
Matrix
To-Be Process Map
Financial Impact of
Solutions
Cost/Benefit Analysis
Risk Planning and
Testing
Failure Modes and
Effects Analysis
(FMEA)
Pilot Plan
Implement Solutions
Multi-Generational
Product Plan (MGPP)
Implementation Plan
Stakeholder
Management
Project Storyboard
Process Control
Control Charts
Process
Monitoring Plan
Dashboard
Response Plan
Project
Documentation
Process
Procedures
Replication
Opportunities
Solution Transfer
Plan
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In addition to the DMAIC deliverables, teams should be prepared to
review the following throughout the tollgate process:
Open issues/barriers for project
Action items from previous tollgate
Decisions from previous tollgate
Next steps for project
Define Measure Analyze Improve Control
DMAIC Deliverables for Tollgates
25
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Business Case is aligned with strategic objectives
Problem Statement and Goal Statement are clearly
defined and measurable (SMART)
Resources are identified and have been approved
DMAIC timeline is realistic
All segments have been completed
Relationships of S-I-P-O-C are clearly defined
Process start and end points are scoped properly for
project
Segments contain enough granularity for proper scoping
and identification of relationships.
Project Charter
SIPOC
As-Is Process Map
Process map reflects the true “as is” process
Was developed and validated with subject matter experts
Is at the appropriate level of detail to highlight quick win
opportunities
Define Tollgate Planning
26
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VOC research plan is documented and contains
necessary detail (customers, method, information to be
gathered, resources)
Customers have been selected that can provide feedback
to problem being fixed
Clear link between customer issues to needs to CTQ’s
CTQ’s are measurable and related to problem statement
in charter
Project plan contains all necessary milestones, tasks, and
sub-tasks to complete project
Timeline is realistic for project
Resources are aligned to tasks
VOC/CTQ’s
Project Plan
All customer/project/individual groups have been identified
Stakeholder Map, Stakeholder Management Plan
Communication methods and timings are relevant for each
customer/project/individual group
Stakeholder
Management Plan
Define Tollgate Planning
27
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Ensure coordination of
dependencies among all
transition projects
Share best practices/lessons
learned
Remove organizational barriers to
team success
Request funding to move forward
where applicable
Reward and recognize the team
efforts
Check for consistent understanding
of the project and its objectives
Monitor team progress for cost and
schedule compliance
Alignment to company strategy
Ensure data quality/integrity
Identify additional resource needs
Assist team with escalation of
issues and risks
Sponsor’s Guide for Tollgate Reviews
Be Prepared – Sponsor’s Tollgate Guidelines
28
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Challenge the purpose and objectives of the project
Determine if project goals are achievable and realistic
Ensure alignment between business case, objectives and problem
statement
Assess the impact on stakeholders
Determine if right customers have been included in VOC
Remove barriers to success
Champions Guide for Define Tollgate Review
Be Prepared – Champions Tollgate Guidelines
29
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The purpose and importance of project tollgates
The process and guidelines for project tollgate reviews
Key deliverables required for each project tollgate review
Key considerations for tollgate review planning
What you learned during this section:
Summary of Section
30
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
End of Lesson: Define – Project Management
Lean Six Sigma Training
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Process Mapping
Quick Wins
SIPOC
Process Overview
Define – Process Definition
Lean Six Sigma Training
1
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Understand the levels of processes in an organization
Learn the difference between core and enabling processes
Understand what an organizational process model is
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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A process is defined as a repetitive and systematic series of actions
or operations whereby one or more inputs from suppliers is used to
achieve an output of value to the customer (internal/external)
Input Output
Process
Actions
Process Model
What is a Process?
3
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There are various levels to all organizational processes.
LEVEL 1 High-Level Organizational Process
LEVEL 2 Sub-Processes
LEVEL 3 Activities
LEVEL 4, 5 Procedures and Tasks
Process Levels
4
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There are multiple levels of process – from the highest level organizational process (30,000 foot view) to the task steps (“worm’s eye” view).
Organizational Process
An organizational process is a macro-process, or a bundle of several processes which result in providing the customer with a product or service. An organizational process is all the functions and sequence of activities (regardless of where they reside in the organization), policies and procedures, and supporting systems required to meet a marketplace need through a specific strategy. It includes all functions involved in the development, production, and provision of specific products or services to particular customers.
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Core Process
A core process is one of the major processes required in managing the operation and
providing day to day services to the customer.
These are processes that are seen as having greater value by external customers
Examples: Service Claims, Develop Product
Key enabling
Processes that support one or more
other processes, typically by supplying
indirect inputs; do not usually have
direct impact on the external customer
Support the core processes and
enable a company to manage the
operation and provide day to day
services to the customer
Enabling processes often direct or
tune other processes
Examples: Finance, Info Technology
Types of Processes
Core Process
Sub-Process Sub-Process
E
N
A
B
L
I
N
G
E
N
A
B
L
I
N
G
E
N
A
B
L
I
N
G
E
N
A
B
L
I
N
G
5
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A core business process is one which is:
Closely linked to external customers at both the beginning of the
process and the end of the process
Closely tied to the organization’s core competencies
An integral part of the organization’s “identity” with
customers/markets
Key to achieving strategic objectives
4.0
Authorize
Claim
3.0
Process
Contract
5.0
Pay
Claim
1.0
Develop
Product
6.0
Service
Customers
2.0
Distribute
Product
Criteria For Identifying Core Processes
6
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A key enabling process is one which:
Typically supplies indirect inputs to the core process
The impact, positive or negative on the core process(es) is
potentially significant
Governs or “fine tunes” the core process
9.0
Legal
8.0
Human
Resources
10.0
Information
Technology
7.0
Finance
11.0
Risk
Management
Identifying Key Enabling Processes
7
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In an organization there are many enabling processes that exist in an organization. It is important to identify the “key” enabling processes or those that are most critical or impactful to the core processes for two reasons:
1) An enabling process can have an impact on the process the improvement team is focused on improving.
2) A DMAIC project can also be conducted on an enabling process as well as a core process.
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An organization is a chain of interwoven core and enabling processes, each of
which contributes to the product or service provided to the external customer.
The Process Chain is only as strong as its weakest link
Process Chain
Your Organization
CoreCoreCore
enabling enabling enabling
Internal
Suppliers /
Customers
Product/Process
Requirements
Product/Process
Outputs
8
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Each link represents a process, or work group within the organization. It may often be only the last link (process) that directly serves the external customer. Yet the product or service you provide to the next internal process customer has an effect on the external customer.
�
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CORE PROCESSES
KEY ENABLING
PROCESSES
2.1
Qualify
Customer
2.3
Complete
Census
2.2
Sell Product
1.3
Price
Product
1.2
Design
Product
3.1
Review
Packet
3.3
Audit
Contract
3.2
Enter
Contract
4.1
Evaluate
Eligibility
4.3
Authorize
Claim
4.2
Adjudicate
Claim
5.1
Review
Claim
5.3
Distribute
Payment
5.2
Settle
Claim
6.1
Route
Inquiry
6.3
Address
Inquiry
6.2
Gather
Information
7.1
Cash
Management
8.1
Manage
Employees
8.2
Recruit
Employees
9.1
Product Filing/
Approval
10.1
Manage
Network
11.1
Monitor
Risk
10.2
Deliver Tech.
Solutions
4.0
Authorize
Claim
3.0
Process
Contract
5.0
Pay
Claim
1.0
Develop
Product
6.0
Service
Customers
2.0
Distribute
Product
1.1
Collect Market
Data
9.0
Legal
8.0
Human
Resources
10.0
Information
Technology
7.0
Finance
11.0
Risk
Management
Example of Core & Enabling Process Model
9
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What you learned during this section:
Understand the levels of processes in an organization
Learn the difference between core and enabling processes
Understand what an organizational process model is
Summary of Section
10
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Process Mapping
Quick Wins
SIPOC
Process Overview
Define – Process Definition
Lean Six Sigma Training
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Understand the relationships of a process
Define the suppliers, inputs, process, outputs, and customers
of a process
Identify the boundaries of a process
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
12
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To develop a high-level view of the process
Developing an accurate “picture” of the process is
made easier by first understanding its elements
To avoid scope creep
Purpose of Developing a SIPOC
13
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Effective improvement requires information from the
entire Supplier-Customer Relationship
Elements Common to All Processes
Suppliers Inputs Process Outputs Customers
S I P O C
Process Map
SIPOC
14
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All company activities constitute a process. A process is defined as taking one or more inputs from suppliers and creating outputs, whether these are a service or product. The graphical display of these activities is known as process mapping.
Understanding business processes is made easier by first identifying the key components of a SIPOC: Suppliers, Inputs, Process, Outputs, and Customers.
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The products or services resulting from a process, which address a
customer’s need
Output
A process is a collection of activities that takes one or more kinds of
input and creates output that is of value to the customer
Process
Materials, resources, data, information, guidelines required to
execute your process
Input
The limits of a particular process, usually identified by the inputs and
outputs, identifies where the process starts and stops
Boundary
Whoever receives the output(s) of your process – may be internal or
external
Customer
Whoever provides the inputs to your processSupplier
SIPOC Elements
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1. Work backwards when completing the SIPOC
2. Start by identifying the customers first, then the process outputs
3. Identify the process start and stop points, then complete the remaining steps
4. Identify process steps – rapid brainstorming
Use your sticky notes
One step per note
Write big
Don’t worry about order
Don’t discuss in detail
Begin all steps with a verb
5. Finally, define the inputs and suppliers
6. The suppliers may be the customers as well
Steps to Complete a SIPOC
16
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Suppliers Inputs Process Outputs Customers
Customer
Collection
Agency
Customer
Complaint
Billing
Question
Statement
Question
Renewal or
New
Account
Set-up
Credit Card
Resolution
Accurate
Statement
Credit /
Debit to
Account
Credit Card
Customer
Collection
Agency
Accounts
Payables
Accounts
ReceivableUpdate Customer Data
Start Boundary
Stop Boundary
Receive
Customer Call Gather Data
Review History Identify Problem
Resolve
Problem
Call Center SIPOC Example
SIPOC
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In this call center example, all components of the SIPOC chain are identified and lead into the next segment, creating a visual depiction of the process stream. Only the high-level process steps are identified in the SIPOC.
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What you learned during this section:
The relationships of a process
The use of SIPOC to define suppliers, inputs, process, outputs,
and customers of a process
The identification of boundaries of a process
Summary of Section
18
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Process Mapping
Quick Wins
SIPOC
Process Overview
Define – Process Definition
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Understand the basic process mapping shapes
Document the detailed steps and activities of a process
Understand the concept of deployment flow charts
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
20
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Definition:
A process map is the graphical representation of the steps, actions, and operations that
constitute a process
Purpose:
In order to control or evaluate a process the team needs to have a clear picture of the current
process
Who develops it:
The team works with those who perform the process itself to map out the process
Basic Process Mapping Shapes
Start / Stop Point Task / Activity Decision Point Direction of Flow
What is a Process Map?
21
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Once the primary segments of the process are identified through the SIPOC, the team can further drill down into the detailed process steps.
Detailed process mapping is necessary to fully understand the flow and tasks that occur to produce the outputs to the customer. The process mapping shapes identified above are standard for most processes, however additional shapes are available for different processes.
Tips in sub-process mapping:
Involve the people who work directly in the process when completing the map.
Clarify the boundaries of the process first by identifying the start and stop points.
Brainstorm the steps that occur between the start and stop points using verbs (Review, Determine, Contact).
Combine and eliminate duplicate steps.
Organize steps into logical order using the direction of flow arrows.
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Describe how activities are being done
Identify where a team should measure in a process to evaluate
performance
Investigate where problems might occur
Aid in the re-design or improvement of a process
Help all stakeholders understand their part of the process and how it
fits into the process as a whole
To perform gap analysis against regional processes or potential
duplicate processes
Aid in training new people
Process Mapping Uses
22
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Example of “As-Is” Process
23
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Basic flowchart
Deployment flowchart (“swim lanes”)
Processing Administration Adjusters Payables
Start
Activity
Activi
ty
End30 5
70
20
Alternate Path flowchart
Activity
Activity
Types of Process Maps
24
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Indicates specific steps that
occur in a process
Indicates decision points
Illustrates rework loops,
bottlenecks, etc.
Clear start
point
Clear stop
point
Number
each step
Represents
Decision Point
1.
Activity
Yes
No
Yes
No
2.
Activity
3.
Activity
Basic Flowchart
25
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Key:
Percentage of time
task is done via
phone or e-mail
Task
Phone
70
30 E-mail
Indicates percentage of
Time one path of a process
is taken over another path
Start Activity
Activity
End30
70
Alternate Path Process Map
Activity
26
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In this technique, alternative “paths” are noted by split arrows. Teams can then note the relative percentages of time/incidents the process follows each path. This approach helps in the study of workload issues.
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Ordering
Dept.
Processing
Dept.
Delivery
Dept.
Customer
Start
Activity Activity
End
Decision
Activity Activity Activity
Activity Activity Activity
Decision Activity
Horizontal Deployment Flowchart
27
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Deployment Process Maps are useful for defining large or complex processes. The number of functions (or “bands”) are easily defined and can be layered vertically or horizontally. Initial horizontal maps are often done on walls so that time can stretch off to the right as far as necessary. Horizontal maps have the advantage that they can show the entire process in a continuous flow.
There are many software solutions that can assist you in creating process maps (example: Microsoft Visio). PowerPoint can also be used to create process maps.
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What you learned during this section:
The basic process mapping shapes
How to document the detailed steps and activities of a
process
The concept of deployment flow charts
Summary of Section
28
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Process Mapping
Quick Wins
SIPOC
Process Overview
Define – Process Definition
Lean Six Sigma Training
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Learn how to identify quick win opportunities
Practice applying quick win criteria
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
30
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Utilizing Lean Six Sigma techniques (i.e. process mapping) often uncovers many easy
and obvious improvement opportunities. These are referred to as “Quick Wins”. Teams
should be prepared to react to these opportunities and implement changes to the
process.
The criteria for defining an improvement opportunity as a “Quick Win” are:
Easy to Implement – the improvement does not require significant planning and
coordination
Reversible – the improvement is reversible (i.e. it is easy to go back to the original
process)
Fast to Implement – the improvement does not require a significant amount of time to
implement
Within the Team’s Control – the scope of the improvement is within the control of the
Team or Sponsor (i.e. the improvement does not cross multiple departments/areas within
the business)
Cheap to Implement – the improvement does not require a significant amount of capital
and/or resources to implement
Quick Win Opportunities
Quick Win
Identification
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We also recommend using “Lean” tools to identify Quick Win Opportunities. Lean tools will be introduced later in this course.
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What you learned during this section:
Understanding how to identify quick win opportunities
Understanding of how to apply the quick win criteria
Summary of Section
32
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
End of Lesson: Define – Process Definition
Lean Six Sigma Training
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Communication Planning
Stakeholder Analysis
Define – Stakeholder Management
Lean Six Sigma Training
1
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Identify the Stakeholders for the projects
Understand how to overcome resistance to change
Develop a Stakeholder Management Plan
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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Stakeholder Management should be done early and throughout the
initiative to continually influence key individuals. The process for
managing stakeholders is the following:
Identify
Stakeholders
Develop
Stakeholder Map
Develop
Stakeholder
Management Plan
Step 1 Step 2 Step 3
The Process for Managing Stakeholders
3
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Anyone who is
affected by the
process or product the
project team
is working
on.
Who is a Stakeholder?
4
Internal
Customers
External
Customers
Suppliers
Customers
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Identify
Stakeholders
Step 1
External Internal Suppliers
1. 10. 19.
2. 11. 20.
3. 12. 21.
4. 13. 22.
5. 14. 23.
6. 15. 24.
7. 16. 25.
8 16. 26.
9. 18. 27.
Identify All
Stakeholders
The Process for Identifying Stakeholders
Stakeholder
Identification
5
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Lean Six Sigma will be driven by the support from key individuals throughout the
organization. The project team’s communication and influence strategy needs to
focus not only on the individuals engaged directly in the initiative, but those
individuals who can have an impact on the success of implementation. These
individuals are often referred to as stakeholders. Stakeholders include executive
leadership, managers, process owners, or any individuals who have a “stake” in
the outcome of the teams efforts.
Team Members
Project Sponsor
Process Owner
Middle Management
Executive Leadership
Front Line Employees
Enabling Functions Supplier
Stakeholder Influence
6
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Step 2
Develop
Stakeholder Map
Impact of Change (from the Project)
In
flu
en
ce
o
n
Pr
oj
ec
t
Lo
w
M
ed
iu
m
H
ig
h
1. Place Stakeholder #s on the Stakeholder Map
2. Add Stakeholder Position
Stakeholder Position
Enthusiast
Neutral
Opponent
Low Medium High
9
4
5
6
8
3
7
6
1
2
The Process for Managing Stakeholders
Stakeholder
Map
7
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Give those most affected by change the
responsibility for implementing the change
Overcoming Resistance
8
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Planning to Deal with Resistance
Being aware of potential areas of resistance is a critical issue for the Lean Six Sigma project team. As a team progresses through its implementation, it should continuously identify ways in which resistance could occur.
One of the best ways to overcome resistance is if those impacted by the change take ownership for implementing the change. Not only does the project team have to deal with issues and consensus within the team, but it also has to seek a teamwork relationship with stakeholders, frontline employees, and managers. Ownership forces the resistance to be dealt with and resolved.
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Common Sources of Resistance
Determine Sources Of Resistance
Technical
Example: Lack of
skills to complete
required tasks
Cultural
Example: Locked into
the way it has always
been done
Political
Example: Difficulty
managing power and
authority
9
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Step 3
Develop
Stakeholder
Management Plan
Great action plans identify what, why, who, when and how. Preparing your
team’s stakeholder management plan will enable proactive change
management. The key elements of a stakeholder management plan are:
Stakeholder Who does the team need to focus on?
Objective What is the purpose/desired outcome of the action?
Action How will the purpose/desired outcome be achieved (i.e. meeting)?
Completion Date When will the action be completed?
Owner Who is responsible for following through with the action?
The Process for Managing Stakeholders
Stakeholder
Management
Plan
10
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What you learned during this section:
How to identify the Stakeholders for your project
Understand methods to overcome resistance to change
How to develop a Stakeholder Management Plan
Summary of Section
11
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
Communication Planning
Stakeholder Analysis
Define – Stakeholder Management
Lean Six Sigma Training
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Understand key considerations to making communication
effective
Understand the key elements of a Communication Plan
Develop a communication plan
Understand how to create an effective Elevator Speech
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
13
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The #1 Reason communication efforts fail to achieve the level of
understanding and influence intended is due to:
Emails, large meetings, print announcements, and
even videos alone tend to:
Be ignored
Fail to engage recipients in active thinking
Focus on “What’s in it for the company” rather
than credibly persuade “What’s in it for the
individual”
Method of Communication
Effective Communication
14
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Have a clear message
Involve and engage your audience
Be candid
Demonstrate, don’t lecture
Follow up
Communication of the improvement project message should be
80% Face to Face meetings
80%
20%
Face to Face
Company Wide
80%
20%
Face to Face
Company Wide
Project Communication
15
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Organizational communication is a change agent
The purpose of communication is not just to convey information, but to change
behavior. Project communication should change behavior by building support of
and buy-in toward the project’s objectives.
Communication is a two way process
Listening and encouragement of feedback is critical to understanding whether
project communication has been effective.
Craft communication in the interests and language of the target audience
To be effective, the message should be focused on the receiver of the
communication’s interests in both content and context.
Communication must be compelling and continuous
To be compelling consider creative ways to deliver your message. To be
remembered and internalized, communication needs to be continuous and
consistent.
Communication Considerations
16
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A Communication Plan should be developed early in the project. The basic steps and
components are as follows:
Target Audience:
Identify the project audience(s) – include internal and external stakeholder groups
The “What” (message):
Assess information needs – determine what groups need to know, want to know, and
expect. NOTE: Utilize project resources only on communicating information that
contributes to success or where a lack of communication can lead to failure
Identify key project messages, announcements, that need to be delivered on a
recurring basis
When:
Define when communications will be provided
The Method:
Identify the best media and methods available to communicate, e.g. face to face
meetings, presentations, email – remember people absorb information in different ways
Developing a Plan – What to Include
Communication
Plan
17
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Owner:
Assign responsibilities for creating and delivering the various types of communications
Approval Process:
Document the approval process needed for any of the communications
Feedback Loop:
Create internal and external feedback loops to help evaluate the effectiveness of
communications
Schedule tasks:
Schedule the work of communications and related dependencies into the project
schedule to ensure they are part of the overall plan
Update Process:
Define a process for updating/changing the Communications Plan
Developing a Plan – What to Include
18
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Audience What When Method Owner Required
Approval
Feedback
Loop
• Team
• Process
owner
Project
Kickoff
Project
start date
(June 5th)
Meeting Black Belt /
Green Belt
Sponsor Plus/delta
All
employees
Major
Milestone
Announce-
ments
As
completed
Email Black Belt
/Green Belt
Sponsor Survey
Questions
Communication Plan Example
19
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Make the Communication Plan readily accessible to the project team members.
Make sure project stakeholders buy into the Communication Plan.
Scale the Communication Plan to fit the complexity, duration, and size of the
project.
Update the Communication Plan when significant changes occur.
Periodically ask team members if they are getting the right information at the right
time.
Enter communication tasks in the project plan.
Be specific when assigning communication tasks – list responsible person(s).
Get proper approval before disseminating communication, when applicable.
Developing a Plan – For Best Results
20
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What is an elevator speech?
A tool used for helping team members practice articulating the project
vision, purpose and objectives in a clear, concise and meaningful way.
It’s a simple but effective communication method to help build project
support and buy-in from all members of the organization.
Elevator Speech
21
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Steps to develop an elevator speech for your project:
Imagine a chance meeting of a project team member with a key project
stakeholder on the elevator. The project team member has five floors (90
seconds) to articulate to the stakeholder the project vision and objectives.
Identify the key 4-7 bullet points that should be communicated to the
stakeholder while on the elevator ride. Some possible themes:
Problem statement/opportunity
Benefit to the organization
Current project status
What action others can take (show support, help communicate)
Team members practice reciting the elevator speech so the message is
delivered consistently among all members.
Elevator Speech
22
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What you learned during this section:
Key considerations to making communication effective
The key elements of a Communication Plan
How to develop a communication plan
How to create an effective Elevator Speech
Summary of Section
23
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
End of Lesson: Define – Stakeholder Management
Lean Six Sigma Training
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
How to Translate VOC into CTQ’s
What is Voice of Customer (VOC)
Who is the Customer
Define – Voice of Customer
Lean Six Sigma Training
1
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Understand the definition and types of customers
Identify and apply methods to segment customers
Understand methods to prioritize customers
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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It is our customers who determine whether or not our products and services
and our work output are considered quality or not. Therefore being focused
on the customer’s wants, needs and expectations is a central focus of Lean
Six Sigma.
Customer
Business/Shareholder
The Customer’s Role
3
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Identify
Customers
Review Charter
and SIPOC
Define
customers
Segment
customers
Develop
VOC
Research
Plan
Identify research
methods
Develop
research plan
Develop VOC
questions
Gather
Customer
Issues /
Needs
Collect VOC
Organize
customer issues
into needs
Translate
Issues /
Needs to
CTQ’s
Translate needs
into
requirements
(CTQ’s)
Set specification
limits
Voice of Customer (VOC) Process
4
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The Recipient of a Product or Service
External
Product/Service
Internal
Product/Service
Customer
Downstream in Process
Leadership/Management
Associates
Clients
End-Use Consumers
Regulators
Brokers
Shareholders
What is a Customer?
5
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While not every process will touch external customers directly, the more we can do �to make each process better, the more likely we’ll be able to exhibit “quality” to our customers in all we do. Remember, too, that “internal customer” partnerships are essential to smoothly-run processes.
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External Customers are groups or individuals external to the organization
who receive or are affected by our products and services.
Internal Customers are groups or individuals whose ability to perform a job is
impacted by the quality of products and services we provide to them, e.g.,
other processing departments, enabling departments (Finance), etc.
External
Customers
Direct Customers
Indirect Customers
Those who receive and use our
products and services.
Those who are affected by our
work, or who have authority over
us, but who may not actually use
our products or services
themselves, e.g., government
agencies, stakeholders, etc.
Definitions of the Types of Customers
6
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A process is a chain of internal suppliers and customers, each of whom
contributes to the product or service provided to the external customer.
The Process Chain is only as strong as its Weakest Link
Customer Process Chain
Your Organization
CoreCoreCore
enabling enabling enabling
Internal
Suppliers /
Customers
Product/Process
Requirements
Product/Process
Outputs
Customers
7
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Each link represents a process, or work group within the organization. It may often be only the last link (process) that directly serves the external customer. Yet the product or service you provide to the next internal process customer has an effect on the external customer.
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It may be necessary to segment customers so customer research is focused
on the most important customers.
Customers can be segmented by region, size, revenue, etc.
Region
Large
Medium
Small
Size of
Deal
Customer Segmentation
8
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If you have many different customers, segmenting them will help the team focus on the vital few and prioritize issues and needs (covered later in this section).
Examples include:
– Channel – direct vs. distribution
– Regional – North vs. South
– Price – high-end vs. low-end
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A process may have many customers
It is difficult to address all the needs of all the customers
There is a need to focus on the vital-few key customers
Customers who purchase the majority of products/services (external)
Customers who provide the most revenue (external)
Customers who use your output at a critical juncture in their process
(internal)
Once needs are addressed for the vital few, the project team can then focus
on the needs of the next layer of customers
Why is it necessary to prioritize customers?
Prioritizing Customers
9
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Prioritization Matrix – Credit Union Example
5 = Major Impact of Customer on Criterion. 3= Moderate Impact. 1= Small Impact. 0= No Impact
Customer Criteria Total
Large Dollar
Transactions
Large Volume
Transactions
Loans Certificates of
Deposit
Money Market
Funds
Large
Commercial
Customers
5 5 5 5 3 23
Small
Businesses
1 1 3 0 1 6
Retail
Customers
3 5 5 1 1 15
Elderly /
Disabled
0 0 1 5 5 11
Tellers 0 3 1 1 1 6
Federal
Examiners
1 0 0 1 1 3
Prioritizing Customers
10
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What you learned during this section:
The definition and types of customers
Methods to segment customers
Methods to prioritize customers
Summary of Section
11
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
How to Translate VOC into CTQ’s
What is Voice of Customer (VOC)
Who is the Customer
Define – Voice of Customer
Lean Six Sigma Training
12
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Understand how to develop a VOC research plan
Understand methods to collect data around customer
requirements
Develop effective VOC questions
Learn how to organize customer feedback into customer
needs
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
13
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A philosophy and approach of understanding the “voice” of customers through
continuous research
The term used to describe stated or unstated requirements that customers
have of products or services
Voice of Customer (VOC) is:
Product/Process
Outputs
What do customers want?
How do customers communicate with us?
Why should we listen to our customers?
What is most important?
How are we doing?
Where can we improve?
Voice of Customer Defined
14
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Understanding customers requirements is critical if real achievement of project success is to be validated. Voice of Customer is a useful method for identifying the customers of the process (either internal or external) and their requirements.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Identify
Customers
Review Charter
and SIPOC
Define
customers
Segment
customers
Develop
VOC
Research
Plan
Identify research
methods
Develop
research plan
Develop VOC
questions
Gather
Customer
Issues /
Needs
Collect VOC
Organize
customer issues
into needs
Translate
Issues /
Needs to
CTQ’s
Translate needs
into
requirements
(CTQ’s)
Set specification
limits
Voice of Customer (VOC) Process
15
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Focus Groups
Used to pull together a
group of similar customers
with a broad range of
opinions.
Surveys
Used as a comprehensive
data gathering technique.
Very valuable in gathering
and prioritizing
requirements.
Interviews
Used to ask probing
questions from one-on-one
sessions with customers.
Can be structured or
informal.
Market Research
Used to gather competitive
comparison data. This is
particularly useful if you want
to compare
strengths/weaknesses to
competitors.
Be a Customer
Used to gain first hand
experience from your
products and services as
your customers experience
them.
Customer Complaints
Used to gather initial issues
with products/services.
Usually come from a small
percentage of customers so
do not necessarily represent
majority of customers.
Research Methods to Collect VOC
16
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Complaints from Customers
Feedback from Internal Associate
Qualitative
InformationFrom
To QuantitativeInformation
Written Surveys
Telephone Interviews
VOC Progression
17
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The VOC process is the progression of taking qualitative feedback from customers and translating those into quantitative requirements. This process will lead the team through the necessary steps to ensure the requirements of the organization’s products and services are documented.
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1. Start Broad – What is important?
2. Get Specific – What does that mean?
3. Prioritize – How important is this?
Complaints
Requests
Observations
Focus Groups
Interviews
Surveys
Requirements
Needs
Issues
The “Funnel” Effect for VOC Research
18
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Elements of a Customer Research Plan
Customer Segments
to be Contacted
Identifies the groups
(internal and external)
that VOC data will be
collected from
Information to be
Gathered
Identifies the specific
VOC questions to be
used for each group
Data Collection
Method
Identifies the medium for
collecting the VOC (face
to face interview, focus
group, survey)
Customers to Contact
Identifies the # from each
group (external) or
specific individuals
(internal) that data will be
collected from
Project Team Owner
Assigns who on the
project team is
responsible for collecting
the VOC
VOC Completed
Tracks when the VOC is
complete
Develop Customer Research Plan
VOC Research
Plan
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Conducting customer research can be very time consuming for a project team. The time to complete the research and gather all of the input depends on:
The number of customers being researched
The availability of the customers
The number of team members who will conduct the research
The time available of the team members
Each element of the Customer Research Plan must be documented and agreed to by the team and Sponsor/Champion.
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Clearly define the objectives of the survey (use qualitative
information for developing objectives)
Draft questions that will meet objectives
Order questions appropriately (funnel from broad to specific)
1. Start Broad – What is important?
2. Get Specific – What does that mean?
3. Prioritize – How important is this?
Use a mix of open and close ended questions
Test the questions with a small sample of customers, then
review to ensure objectives are being met
Developing VOC Questions
20
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Pitfalls with developing questions:
Being too broad with questions can lead to non-measurable responses.
However, being too specific can bias or lead customer responses or lead to narrow issue identification.
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Sample Open Ended Questions:
What are the product/service features that are most important to
you? (primary and secondary)
What are your expectations relative to delivery dates?
How do we compare to our competitors?
What are some additional features that would enhance the
product or service?
Examples of Effective Questions to Gather VOC
21
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Open-Ended Questions:
Initial questioning to ensure interviewee isn’t being led to specific responses.
Allows the interviewer to probe for more specific answers.
Good for gathering exact responses to be used for presentations
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Sample Close Ended Questions:
Would you continue to buy other products/services from us?
Did we meet all of your service expectations?
How important are the product/service features you mentioned:
1. Not important at all
2. Below average importance
3. Average importance
4. Above average importance
5. Extremely important
6. Not Applicable
Yes No
1 2 3 4 5 6
Not Satisfied Moderately
Satisfied
Very Satisfied Not Applicable
Examples of Effective Questions to Gather VOC
22
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Close-Ended Questions:
Allows the interviewer to rank specific responses to questions.
Good for gathering rankings to be used for presentations.
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Objective
Practice identifying bias in questions.
Instructions
Review the questions below and determine how each one is biased.
Prepare your findings.
1. What service qualities, such as quick loan approval or excellent customer
service, are most important to you (external)?
2. When did you mail in your application (external)?
3. What department caused the most problems in your ability to process the
application (internal)?
4. What % of the time do you normally see the following types of errors (internal)?
Determining Question BiasEXERCISE
23
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Please Do Not Proceed Forward
Determining Question BiasEXERCISE
24
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When you see this symbol, please do not continue forward in the materials.
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1. What service qualities, such as quick loan approval or excellent customer
service, are most important to you (external)?
Question contains a narrow list of qualities. Neither may be the most
important to the customer.
2. When did you mail in your application (external)?
Too much subjectivity. Difficult to remember actual time for customer.
3. What department caused the most problems in your ability to process the
application (internal)?
Leading. There may have not been any problems. Also, focusing blame on
a particular group.
4. What % of the time do you normally see the following types of errors (internal)?
Over-generalization. Doesn’t get to the requirement or expectation. Not
based on actual data – assumptions.
Determining Question Bias – AnswersEXERCISE
25
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Identify
Customers
Develop
VOC
Research
Plan
Gather
Customer
Issues /
Needs
Translate
Issues /
Needs to
CTQ’s
Review Charter
and SIPOC
Define
customers
Segment
customers
Identify research
methods
Develop
research plan
Develop VOC
questions
Collect VOC
Organize
customer issues
into needs
Translate needs
into
requirements
(CTQ’s)
Set specification
limits
Voice of Customer (VOC) Process
26
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Qualitative data is different, it requires translation
Customer data can be overwhelming
Different voices heard at the same time
Customers often have difficulty in expressing requirements
Different “voices” from the same customer
Bias by the collector
Challenges and Key Issues with Gathering VOC
27
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Key Steps in Translating Qualitative Customer Feedback into Needs
1. Collect VOC
2. Probe for clear understanding
3. Identify key issue
4. Organize issues into central categories/themes
5. Translate into customer need in terms that make sense to the
organization
Organize Customer Feedback
28
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Organization Tool: Affinity Diagram
Customer
ResponseCustomer
ResponseCustomer
Response
Customer
Response
Customer
ResponseCustomer
Response
Customer
Response
Customer
Response
Customer
ResponseCustomer
ResponseCustomer
ResponseCustomer
ResponseCustomer
Response
Customer
ResponseCustomer
ResponseCustomer
Response
Customer
Response
Customer
Response
Customer
Response
Customer
ResponseCustomer
Response
Customer
Response
Customer
Response
Issues –
Hold Time Inaccurate Statement
Phone
Transfers
Process
DifficultIssue Category –
Organizing Customer Feedback
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Once VOC has been gathered, it is necessary to organize the feedback from the customers. Categorizing the issues will help bring out central themes for the team to focus on.
Instructions for Affinity Matrix:
Using raw VOC issues/feedback, write down the feedback on sticky notes.
Post the stick notes to a white board or flip chart paper.
Once completed, sort issues into 4-8 related groups.
Create a summary issue category for each issue group. Make sure everyone agrees to headings.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Examples of Translating Qualitative Information into Needs
Customer Issue Customer Need
“On hold too long”
“My statement is
inaccurate”
“I keep getting
transferred”
Reduce
Hold Time
Statement Accuracy
Resolve Problem 1st
Time
Organize Customer Feedback
30
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Guidelines for translating customer needs:
Combine feedback into central themes
Write the corresponding need, not the solution
Use terms that are measurable
Avoid words like “should” or “must”
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What you learned during this section:
How to develop a VOC research plan
Methods to collect data around customer requirements
How to develop effective VOC questions
How to organize and analyze customer feedback
Summary of Section
31
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
How to Translate VOC into CTQ’s
What is Voice of Customer (VOC)
Who is the Customer
Define – Voice of Customer
Lean Six Sigma Training
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Know how to translate customer needs into a measurable,
actionable customer requirement
Learn tools for analyzing and prioritizing customer
requirements
Understand how to identify customer specification limits
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
33
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Identify
Customers
Review Charter
and SIPOC
Define
customers
Segment
customers
Develop
VOC
Research
Plan
Identify research
methods
Develop
research plan
Develop VOC
questions
Gather
Customer
Issues /
Needs
Collect VOC
Organize
customer issues
into needs
Translate
Issues /
Needs to
CTQ’s
Translate needs
into
requirements
(CTQ’s)
Set specification
limits
Voice of Customer (VOC) Process
34
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Common Customer Requirements
Reliability
Durability
Features
Prestige
Usability
Failure Recovery
Product
Quality
Convenience
Accuracy
Speed/Timeliness
Treatment/Interaction
Tangibles
Failure Recovery
Service
Quality
Low Original Price
Value Ratio
Discounts/Sales
Total Costs
Frequent Buyer Plans
Terms, Tax
Price/
Value
What Matters to Customers?
35
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During the VOC process, customers may express their issues in the form of solutions or complaints, or the issue may be too general or abstract to glean any meaningful information from.
By conducting translation of VOC feedback, the “real” or hidden requirements being vocalized by the customers will be identified.
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Understanding customer requirements is essential to
assure the outputs of your processes meet the customer’s needs
To identify whether your organization’s processes are meeting
customer needs and expectations, these customer needs must be
translated into customer requirements that are measurable and
quantifiable
The term for a measurable and quantifiable customer requirement is
CTQ (Critical to Quality), because these are the characteristics of a
product or service that are “Critical to Quality” for the customer
What is a CTQ?
Defining Critical to Quality (CTQ’s)
36
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–
Dissatisfaction
Primary SatisfierDelighters
Must Be
Satisfaction
+
Service
Dysfunctional
Service
Fully
Functional
Prioritizing Customer Needs – Kano Analysis
37
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Kano Model developed by Professor Noriaki Kano.
Identified needs are not of equal importance to customers. The Kano analysis frames needs into must be’s, primary satisfiers, and delighters.
Kano’s theory is that for some customer needs, customer satisfaction is directly proportional to the extent to which the product or service is fully functional. The horizontal axis represents how fully functional a product or service is, whereas the vertical axis represents how satisfied a customer is.
Think about the following travel needs. Where would they fit on the Kano Analysis?
– In flight movie
– Hot meal
– On time flight arrival
– Safe landing
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Requirements Type Definition
Must Be – Priority #1 Requirement that can dissatisfy, but
cannot increase satisfaction
Primary Satisfiers – Priority #2 The more of these requirements that
are met, the more the customer is
satisfied
Delighters If the requirement is absent it does
not cause dissatisfaction, but it will
delight customers if present
Indifferent Customer is indifferent to whether
the feature is present or not
Reverse Feature actually causes
dissatisfaction
Kano Analysis Definitions
38
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Requirement Type Ease/Expense to Capture Approach to Use
Must Be Difficult, more expensive
Information is known but difficult
to access and organize
Customer complaints
One-on-One interviews
Focus groups
Delighters Very difficult and expensive
Information is unknown and
must be created or combined
from many unrelated sources
Carefully orchestrated focus
groups
Customer observation
Primary Satisfiers Easy and inexpensive
information
Information is known and can be
easily captured
Mail and phone surveys
Market research
Be a customer
Level of Effort to Capture Each Requirement Type
39
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Need Rating
~~~~~~~~ 4.2
~~~ 3.6
~~~~~ 1.2
~~~~~~~~~~ 2.4
~~~~~ 2.8
Q. How important are the
product/service features:
1. Not important at all
2. Below average importance
3. Average importance
4. Above average importance
5. Extremely important
Survey/Interview Feedback
Complaints from
Customers
Feedback from Internal
Associate
Qualitative Feedback
Determine priority
needs through
analysis of all
VOC methods
Must-Be
Requirements
Determining Priority Needs
40
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Prioritizing needs is based on combining qualitative feedback methods that are used to collect complaints and issues and the quantitative methods used by the team to drill down and understand the specific needs of the customers. In this example the team used two different criteria to evaluate each need . #1: The total number of customer responses per need. #2: The overall importance of the need to the customer. Each of the criteria had a maximum value of 2.5. When combined the highest rating is 5 for each need.
Prioritization Process:
Combine the importance rating responses for each need and calculate the average.
You can also add the satisfaction rating averages to the subsequent importance rating.
Avoid having the team prioritize the needs. Use your qualitative and quantitative analysis.
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CTQ’s are the translated customer needs into quantifiable and
measurable requirements of our products and services
Reduce
Hold Time
Process
Output
Characteristic
Measure
Target
Answer Call
<15 Seconds
Prioritized
Need
= Speed of Answer
= Customer call to
answer time
= <15 seconds
CTQ
Translating Must-Be Needs into CTQ’s
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Once CTQ’s have been identified, review and update the charter to align with your new findings. Once updated, remember to review with your project Sponsor/Champion.
Questions to consider are:
Is your problem and goal statements aligned with your CTQ’s?
Have you scoped your project to focus on the critical requirements of the customer?
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Once CTQ’s have been identified and documented, it may be necessary to develop
specification limits.
Specification limits (specs) are specific tolerances that the CTQ must fall within for the
customer to be satisfied with performance.
Example of CTQ’s and specification limits:
Pay Federal
filing fee by
12th of month
CTQ
6th of each
month
Lower Spec Limit
12th of each
month
Upper Spec Limit
Developing Specification Limits for CTQ’s
CTQ Chart
42
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Spec limits are separated into the lower spec limit and the upper spec limit. The upper spec limit is usually the CTQ defined in the VOC (i.e. 100% Accuracy, Answer Phone <15 seconds). However, sometimes a lower spec limit is also defined. This is particularly common in CTQ’s around delivery. (Example would be that the CTQ for delivery of a product is between 8AM-12PM. Anything below the lower spec limit or above the upper spec limit could lead to customer dissatisfaction)
Specification limits are also necessary in the Control Phase so tolerances to track process performance are documented and proactive action can be taken if process performance begins to near either the upper spec limit or the lower spec limit.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
What you learned during this section:
How to translate customer needs into a measurable,
actionable customer requirement
Tools for analyzing and prioritizing customer requirements
How to identify customer specification limits
Summary of Section
43
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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove
End of Lesson: Define – Voice of Customer
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Measure Phase
Lean Six Sigma Training
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Measure Phase Overview
Lean Six Sigma Training
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Measure identifies the measures that will be used to
baseline process performance and determine how
well processes are meeting customer requirements,
describes and displays variation in the process, and
calculates process performance through statistical
measures of sigma and yield.
Measure Phase Introduction
3
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Identify and Define Key Indicators of
Process Performance
Develop Data Collection Plan
Calculate Baseline Performance (Sigma)
Display Performance Data
Promote Productive Team and Change
Management Atmosphere
Population
of Calls
Population
of Calls
Sample
Pareto
Diagram
The types of complaints
received from customers
(January 1 – December
31)
DiscreteOutputTypes of
Complaints
Run ChartThe number of inbound
calls to the call resolution
group (January 1 –
December 31)
ContinuousInputNumber of
Customer
Calls
Measure
DisplayOperational
Definition
Type of
Data
Type of
Measure
Population
of Calls
Population
of Calls
Sample
Pareto
Diagram
The types of complaints
received from customers
(January 1 – December
31)
DiscreteOutputTypes of
Complaints
Run ChartThe number of inbound
calls to the call resolution
group (January 1 –
December 31)
ContinuousInputNumber of
Customer
Calls
Measure
DisplayOperational
Definition
Type of
Data
Type of
Measure
Defects: 102
Opportunities: 4
Units: 221
DPMO: 115,385
Sigma: 2.7
Defects: 102
Opportunities: 4
Units: 221
DPMO: 115,385
Sigma: 2.7
0 10 20 30 40 50
0
100
200
300
400
Days
Fr
eq
ue
nc
y
CTQ = 15 Days
N = 4267
Average = 22.18 Days
Measure Phase Overview
4
ANALYZE
CONTROL
IMPROVE
MEASURE
DEFINE
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Measure Phase Deliverables
Define Measure Analyze Improve Control
Project Charter
Project Management
Project Plan
Process Definition
SIPOC
As-Is Process
Map
Quick Win
Identification
Stakeholder
Management
Stakeholder Map
Stakeholder
Management Plan
Communication
Plan
Voice of Customer
Customer
Identification
VOC Research
Plan
Kano Analysis
CTQ Identification
Root Cause Analysis
Affinity Diagram
Fishbone Diagram
and/or 5 Why’s
Lean Process
Analysis
Lean Tools and
Measures
Graphical Data
Analysis
Histogram
Pareto Chart
Box Plots
Correlation
Analysis
Statistical Data
Analysis
Linear Regression
Multiple
Regression
Root Causes
Identified
Quick Win
Identification
Identify Measures
X/Y Matrix
Data Collection
Operational
Definitions
Measurement
Systems Analysis
(MSA)
Data Collection
Plan
Describe and Display
Data
Histogram
Pareto Chart
Pie Chart
Run Chart
Control Charts
Baseline Performance
Sigma
Performance
Yield
Process
Capability
Quick Win
Identification
Identify and Select
Solutions
Generate Solutions
Benchmarking
Solutions
Prioritization Matrix
Solution Selection
Matrix
To-Be Process Map
Financial Impact of
Solutions
Cost/Benefit Analysis
Risk Planning and
Testing
Failure Modes and
Effects Analysis
(FMEA)
Pilot Plan
Implement Solutions
Multi-Generational
Product Plan (MGPP)
Implementation Plan
Stakeholder
Management
Project Storyboard
Process Control
Control Charts
Process
Monitoring Plan
Dashboard
Response Plan
Project
Documentation
Process
Procedures
Replication
Opportunities
Solution Transfer
Plan
5
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End of Lesson: Measure Phase Overview
Lean Six Sigma Training
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Measure Relationships (X/Y)
Types of Measures
Measure – Identify Measures
Lean Six Sigma Training
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Understand and identify measures of the process
Identify the types of process indicators
Identify relationships between measures and CTQ’s
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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Selecting key output measures (Ys)
Collecting baseline data for key output (Ys), input
and process measures (Xs)
Studying the variation in the output measures (Ys)
Calculating the capability of
the process
Preparing for the Analyze
Phase
Focus of the Measure Phase
3
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I P O
I P O
The Work Process
The Improvement Process
Relationship of Work Process and
Improvement Process
4
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Dictionary says - “the dimensions,
capacity, or amount of something
ascertained by measuring”
A measure takes a concept such as time, error rate, length, width,
height, amount, percent, or duration, and describes it in terms of a
number (data)
Overall
At a specific point in the process
At a specific point in time
Over a period of time
What is a Measure?
5
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Process Effectiveness
The extent to which customer
requirements are met
Defect Rate
Accuracy
Actual/Plan
Cost per transaction
Time per activity
(Cycle Time)
Set up time for new customer needs
Cycle Time for special customer requests
Percentage of special requests not met
Process Efficiency
The internal allocation of
resources
Adaptability
The ability to quickly adapt to
changing requirements
Service Level(s)
Timeliness
Response Time
Output per unit
(Space, FTE, Time)
Process Yield
3 Process Measurement Categories
6
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There are two primary categories of measurements to determine process performance. They are Process Effectiveness and Process Efficiency. Adaptability is a process objective involving effectiveness and efficiency over time.
Process adaptability is an objective that a project team should aim for after effectiveness and efficiency goals have been achieved. A process that is adaptable to changing customer needs, and the ability to remain capable in spite of variation that may exist within ones customer group’s needs is said to be “robust”.
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Data
Continuous Discrete
Countable
Indivisible
No values possible between
whole units
Never fewer than 1
Counts in categories
Measurable
Divisible
Unit on scale is endlessly sub-divisible
Precision is limited only by the accuracy
of the measuring instrument
Measures variation of a characteristic
Examples
True/False
Yes/No
Satisfaction
(poor, good,
excellent)
Examples
Dimensions
Time
Currency
Two Types of Data
7
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A simple method to determine if your data is continuous is to ask the following question: Is the unit of data divisible? If yes, does the unit still retain a meaningful value. If yes, your data is continuous. Example, if you have 50 hours, the unit is hours, if you divide an hour in half you have 30 minutes, hence the unit is continuous because 30 minutes is of value. For discrete data, if you divide it in half it does not retain a meaningful value. Example, if you have 10 false answers on a survey, the unit is answers, if you divide an answer in half you have a half of an answer, which is not a meaningful value.
Individuals often misunderstand their data when they focus on the quantity of units in determining if they have continuous or discrete data. In the previous example the quantity is “10” false answers. In determining if the data is continuous or discrete you need to focus on the unit, which is answers, and not the quantity of answers “10”.
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Data type is often determined at the outset of identifying your process CTQ (Y). If your
Y is discrete, you will severely limit the tools available to you to Analyze and dissect
your process. Generally speaking, continuous Ys and Xs are preferred, as the
information provided by a given sample is typically greater with continuous data than
with discrete data. However, as long as your Y is continuous, statistical analysis tools
will largely remain available, even though your Xs might be discrete.
CONTINUOUS DATA ALLOWS
PROCESSES TO BE BROUGHT
INTO SHARP FOCUS
DISCRETE
Implications Based on the Type of Data
8
CONTINUOUS
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Objective
Practice identifying discrete and continuous data types.
Instructions
Identify if the following data descriptions are discrete or continuous.
1. The time it takes to schedule a meeting.
2. The difference between when a meeting is supposed to start and when it
actually starts.
3. The numbers on a telephone.
4. The questions on a survey.
5. The assortment of candy delivered during afternoon snack time of a
meeting.
6. The price of a ticket.
Prepare your findings.
Types of DataEXERCISE
9
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Please Do Not Proceed Forward
Types of DataEXERCISE
10
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When you see this symbol, please do not continue forward in the materials.
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1. The time it takes to schedule a meeting. (Continuous)
2. The difference between when a meeting is supposed to start and when it
actually starts. (Continuous)
3. The numbers on a telephone. (Discrete)
4. The questions on a survey. (Discrete)
5. The assortment of candy delivered during afternoon snack time of a
meeting. (Discrete)
6. The price of a ticket. (Continuous)
Types of Data – AnswersEXERCISE
11
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To understand how your processes are performing and to determine
whether they are meeting internal or external customer requirements
requires measuring the process.
In developing measures for your process, you must identify your
indicators…
What is an Indicator?
A measure
A measurement that indicates how well the process is
performing
Should describe both the condition of a part of a process and the
quality of the output or result of the entire process.
Identify Process Indicators
12
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Elements Common to All Processes
S I P O C
Suppliers Inputs Process Outputs Customers
Process Map
Process
Indicators
Quality
Indicators
Process and Measures
13
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Quality Indicators
Used to determine the quality of the output provided to customers
Assess the degree of conformance or non-conformance to CTQ (customer
requirement)
Are a lagging indicator, therefore, are not very useful in identifying reasons for
non-conformance
Process Indicators
Measures taken at critical points in the process to describe what the process is
doing
Can serve as early warning signs (leading indicator) that something is wrong
before the defect in the output occurs
Monitored to evaluate process stability
Monitored and taken corrective action on to avoid adverse impact on customers
Types of Indicators
14
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Output Measures
Measures that are
placed on your internal
processes. These are
the measures for
internal customers (i.e.
departments) or those
that influence output
measures.
Measures used to
determine how well
customer needs
and requirements
are met.
Measures that
are placed on
your suppliers to
ensure quality
inputs are
received.
Input Measures Process Measures
Process Indicators Quality Indicators
Linking Indicators to the Three Types of Measures
15
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Measures used to determine
how well customer needs
and requirements
are met.
Measures that are placed on
your internal processes. These
are the measures for internal
customers (i.e. departments)
or those that influence output
measures.
Measures that are placed
on your suppliers to
ensure quality inputs are
received.
Examples:
# of calls/hour taken by each
service rep
2nd year customer retention
figures
Total # of meals delivered
% customer complaints
Examples:
Availability of service personnel
Time required to perform credit
review
% of non-standard approvals
required
# of qualified applicants
Total cost of service delivery
Total overtime hours
Examples:
# of customer inquiries
Type of customer inquiries
# of orders
# of positions open
Type of position open
Accuracy of the credit
analysis
Timeliness of the contract
submitted for review
Output MeasuresProcess MeasuresInput Measures
Linking Indicators to the Three Types of Measures
16
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The Improvement Process
I P O C
1.
Measures
Output Measures to CTQ’s
17
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An output measure expresses the “voice of the process” because
changes in input or process conditions drive changes in the output
measure
A good output measure serves as the translation of the voice of the
customer
Changes in the values of a good output measure should predict changes
in the degree to which the process meets the customer need
As changes are made upstream (to the process or to the inputs to the
process), the output measure is a good indication of the success of
changes being made upstream in the process
Why Start Measurement with Output Measures?
18
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1. Make the output measure and the requirement as closely related as possible
For each customer requirement there should be a corresponding output
measure
Example:
Customer Requirement Customer Specification Output Measure
Timely delivery of
merchandise
0 late deliveries of
merchandise
# or % of late deliveries
Accurate statements 0 statements with errors # or % of inaccurate
statements
Guidelines for Developing Output Measures
19
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2. Measure at intervals that allow you to make useful judgments
Measure often enough to catch problems before too much damage has been
done, but balance this with time and cost to collect data.
3. Avoid using averages as quality output measures
Averages can be misleading.
Example:
When a vendor who is supposed to be paid 30 days after invoice date receives
a late payment (after 30 days), the contractor does not care about the
company’s claim that they pay all invoices on an average of 25 days after the
invoice date.
Guidelines for Developing Output Measures
20
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The Improvement Process
I P O C
2.
Measures
Process Measures to Output Measures
21
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1. Review the Process Map and Identify “Points of Pain”
Measure steps that experience has shown are problem area or “points of pain”.
Example: Areas of rework, long delay, or errors
Measure steps that have long cycle times
Measure where there is logical change or a decision point when the process moves from
one process customer to the next
P1 Inputs to the process
P2 “Rework loops – rework points
P3 At the end of major process
steps
P4 Hand-offs between departments
5
m
in
10
m
in
Customer
Payment
Processor
AP
Processor
Y
N
P1
P2
P4
P5
P3
P1
?
Guidelines for Developing Process Measures
(Critical X’s)
22
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2. Measure critical “Moments of Truth” (customer touch point)
Evaluate situations where a customer can leave a point of contact with the
company and can have either a positive or negative experience.
3. Ensure process measures are linked/correlated to output measures
These are the steps in the process that are leading indicators of downstream
performance of the final process output. These are the most important!
4. Include measuring critical inputs as part of your process measures
The timing and accuracy of inputs can have a great effect on the process,
including these measurements can be telling about the process.
Guidelines for Developing Process Measures
23
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The Improvement Process
I P O C
3.
Measures
Input Measures to Process Measures
24
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1. Review the process map and identify incoming “Points of Pain”
Measure inputs that experience has shown are problem area or “points of
pain”.
Example: # of documents, types of documents, or location of supplier
Measure where the inputs enter for the first time or throughout the process
2. Ensure input measures are linked/correlated to process measures
These are the inputs to the process that are leading indicators of
downstream performance of the final process output.
Guidelines for Developing Input Measures (Critical
X’s)
25
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Key: Little Relationship Moderate Relationship Strong Relationship
X/Y Matrix - Input/Process/Output Measures
Process: Bills Sent To Customer’s Home
Output
Measures
On Time Bill Delivery
# of Errors Per Bill
% Received Response
Time
# Of
Processing
# per Bill
%
Statements
Accurate
Input and
Process
Variables
Input/Process
Measures
Linking Output Measures to Process and
Input Measures
H
M
L
H
M:
M L L
L: H:
X/Y Matrix
26
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Selecting Input and Process Measures
1. List output measures.
2. List potential process and input measures.
3. Assess relationship between output measures and potential process and input � measures.
4. Select set measures for process monitoring.
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Process Check: Measures and DMAIC
Understand Core and Sub Processes
SIPOC
Develop Measures
Around SIPOC
Effectiveness
Efficiency
Customer Satisfaction
Measurement Criteria
Importance
Understandability
Sensitivity
Actionable
Accessibility
Customer Requirements
Cost Benefit of
Data Collection
Collect Data Establish Relationships
to Key Measures
Scatter Plots
Regression
Process/Output
Measures Matrix
Tree Diagram
Finalize Process
Measures
Dashboard
Determine Process
Measures with Best
Relationships
Narrow List of
Measures
Data Collection to
Select Measures
Judgment And
Linkage
Measure ControlAnalyze
Identify and Define
Universe of Potential
Measures
Narrow the Measures Down to the Critical Few
27
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Principles of Good Measures
The measure must be important
The measure must be easy to understand
The measure is sensitive to the right things and
insensitive to other things
The measure promotes appropriate analysis and action
The measure should be easy to get
28
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What you learned during this section:
What measures are
The types of process indicators
Method to document the relationships between measures
and CTQ’s
Summary of Section
29
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Measure Relationships (X/Y)
Types of Measures
Measure – Identify Measures
Lean Six Sigma Training
30
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By the end of this section, you will be able to:
Understand the statistical relationship of process and input
measures to outputs
Understand the focus of monitoring measures
Overview – Objectives – Key Topics
31
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Y relates to the outputs
X relates to the process and inputs
Identifying Xs that might explain
variation in the output measure
Collecting data efficiently:
both the Ys and the suspected Xs
Now we are
talking!!!!
Prepare for the Analyze Phase
32
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Process Variables
(Xs)
Input
Variables
(Xs)
Outputs
(Ys)
Process
X
X
X
X X X X
Y
Y
Y
Process Flow
Predictor and Response Variables
33
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Outputs (Ys)
Product or service produced or delivered by the process. Key measures include cycle time, CTQs and defects, customer satisfaction, cost, etc.
Process Variables (Xs)
Those variables that influence the output and are generally controllable by those who operate the process. Key measure might include timeliness of step-by-step processing of the unit, accuracy/reliability, availability of products and staff, service provider behaviors, etc.
Input Variables (Xs)
Materials and information used by the process to create the outputs. Inputs are often outside the control of the process operator.
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Input
Measures
Process
Measures
Output
Performance
Measures
Efficiency Measures
Cost per transaction
Time per activity
Amount of rework
Turnaround time
Variability of an activity
# of inbound items
Effectiveness Measures
Percent defective
Number of errors
Total response time
Invoice/billing accuracy
Revenue
X’s X’s Y’s
Monitoring and Controlling the Critical X’s
34
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To get results, should we focus our behavior on the Y or the X?
X1...Xn
Independent
Input or Process
Cause
Problem
Control
Response Predictor
x
x
x
xx
x
x
x
Y
Dependent
Output
Effect
Symptom
Monitor
Focus on the Process
35
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Understanding variation requires understanding the relationship between the process response (Y) and the process predictors (Xs).�� Y = f (X1, X2 , . . . , Xn )�
The process predictors (Xs) affect (drive) the process outputs (Y).
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For every process there is a dependent variable called Y that we are
attempting to influence. The independent variables which determine
what happens to our Y are called the process X’s. Thus, we can boil
down every process into a simple formula:
Y = f(X1,X2,X3…Xn)
Once we understand the relationship
between our various Xs and our Y, we can
monitor and manipulate the Xs if
necessary to modify Y as desired, then
lock down the process so that Y remains
within the proper range and is meeting
customer requirements.
Monitoring and Controlling the Critical X’s
36
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What you learned during this section:
The statistical relationship of process and input measures
to outputs
The focus of monitoring measures
Summary of Section
37
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
End of Lesson: Measure – Identify Measures
Lean Six Sigma Training
38
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Data Consistency and Stability
Collecting Data
Data Sampling
Operational Definitions
Measure – Data Collection
Lean Six Sigma Training
1
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Understand the importance of operational definitions
Understand the criteria for documenting operational
definitions
Develop sound definitions for measures
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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Data will help the team to:
Shift from “gut feel” understanding to
“Measurable” and “Quantifiable”
understanding
Support or disprove preconceived ideas
and theories
Determine a baseline of current process
performance
Document the history of the problem over
time
Develop metrics to measure the impact of
changes on a process
Identify and understand relationships that
might help explain process variation
Data Collection
3
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Data and measurement play vital roles in every business improvement initiative. The right metrics give the organization a fact based view of current process performance.
Think for a moment.
1. How well does your organization make decisions based on data?
2. How effective is your organization at meeting or exceeding customers expectations?
Data will help answer these questions.
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In developing your data collection plan you will need to define:
What you are trying to evaluate and measure
Whether you need to collect new data or if existing data can be used
How you will attach a value to what you are measuring
How will you collect the data
How frequently you will collect data
The appropriate sample size (if needed)
What data will the team collect
Guidelines for Developing Data Collection Plan
4
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Step 1
Develop
Operational
Definitions,
Procedures, &
Sample Size
Step 2
Plan for Data
Consistency and
Stability
Step 3
Collect
Data
Step 4
Continue
Improving
Measurement
Consistency
The Data Collection Process
5
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Purpose:
To remove ambiguity
Everyone who is collecting the data has the same
understanding
Identifies what to measure
Identifies how to measure
Reduces collector to collector variation to ensure that no matter
who does the measuring, the results are the same
Definition:
An operational definition is a precise description that tells how to
get a value for the characteristic you are trying to measure. It
includes what it is and how to measure it.
Operational Definitions and Procedures
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Definitions Must Have Specific Criteria
Everyone understands the definition and can use the definition to collect data
in the same way.
Example: If a team were measuring the time it takes to drive to work, the team would
need to agree on “what” to measure (how long the drive is, how much time it takes) and
agree on the method that will be used to measure it.
Definitions Must Have a Method for Measuring the Criteria
The definition describes how to get the value (either variable or continuous).
Example: The team would need to know how to calculate the length of the drive – is it in
miles or kilometers?
Definitions Must be Useful to the Customer and Team
The definition relates directly to the issue the customer is having with the
process.
Example: Are customers really interested in the distance of the drive or how long the
drive is?
Operational Definitions Guidelines
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How would you define these?
Office meeting “first thing in the morning”
On time flight departures
Computer downtime
Accurate bill
Measure Type of
Measure
Type of
Data
Operational Definition
What
Operational
Definition
How
Billing
Accuracy
Output Discrete Inaccurate = Bill with
any of the 5 fields not
matching customer
order form
Reconcile invoice
with customer order
for 5 fields
Example:
Examples of Why Operational Definitions are
Necessary
8
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What you learned during this section:
The importance of operational definitions
The criteria for documenting operational definitions
How to develop sound definitions for measures
Summary of Section
9
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Data Consistency and Stability
Collecting Data
Data Sampling
Operational Definitions
Measure – Data Collection
Lean Six Sigma Training
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By the end of this section, you will be able to:
Understand the importance of data sampling
Understand the uses of sampling in process and
population types
Overview – Objectives – Key Topics
11
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Statistical Inference is the process of drawing conclusions about a population
based on analysis of a portion of that population. Sampling is the process of
selecting the portion of the population to study.
SAMPLEPOPULATION
As it is the population we wish to study,
not merely a subset of it, there is an
inherent danger in sampling. If we are
to have confidence in our results, the
sample must be representative of the
overall population. The illustration
above shows a population (area under
the black line or top line) and a
representative sample (area under the
red line).
Fr
eq
ue
nc
y Pop.
Sample
m
(N = 5,000 People) (n = 100 People)
What is Sampling?
12
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Why Sampling is Necessary
Why Sample?
Data collection can be costly and timely
Sometimes data collection is a destructive process (ex. taste testing)
Sound conclusions can often be drawn from a relatively small amount of
data
Sample Frequency
Collect often enough to catch fluctuation
Better to collect several small samples over different times than one large
sample at a single point in time
Greater the instability (variability), greater the sampling frequency
13
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Process Sampling: predicting WHY a measure takes on certain values
We have a process that we want to measure, analyze or control
Establishing baseline performance of the process
Conducting a special study to improve the process
Ongoing monitoring to control the process
Population Sampling: estimating or characterizing the WHAT or HOW
MANY of a measure
We have a large population that we want to describe
Income level of a certain customer segment
% of customers who would purchase a new service
Reasons for being behind in credit card payments
2 Important Uses of Sampling
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25-30Control Chart
25Scatter Diagram
50Pareto Chart
50Histogram
100 and nP≥5Proportion Defective (P)
25-30Standard Deviation
5-10Average
Minimum Sample SizeTool or Statistic
Simple Sample Size Guidelines for
Process Sampling
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Monitor process frequency enough to catch it going from
good to bad
Better to collect several small samples over different
times than one large sample at a single point in time
Unstable process – more frequently
Stable process – less frequently
Covered in the
“Describe and
Display Data”
lesson
Simple Frequency Guidelines for Process Sampling
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Where to Sample
Locating your
“Sampling Sweet Spot”
Location in the process
where the process
variable affects the output
variable
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What you learned during this section:
The importance of data sampling
The uses of sampling in process and population types
Summary of Section
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Data Consistency and Stability
Collecting Data
Data Sampling
Operational Definitions
Measure – Data Collection
Lean Six Sigma Training
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By the end of this section, you will be able to:
Understand the importance of measurement system analysis
Understand the different measurement system analysis
techniques (accuracy, repeatability, reproducibility, stability)
Take the actions necessary to ensure the measurement
system functions properly
Overview – Objectives – Key Topics
20
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Plan for Data Consistency and Stability
Measurement systems must be validated to ensure that data is
consistently free from errors
Data is only as good as the process that measures it
Methodology must be developed to teach the measurement system to
ensure consistency and stability, also known as Gage R&R (Gage
R&R analysis quantifies the precision of a measurement system to
determine its acceptability)
Determine factors that could cause the measurement of an item to
vary
Find ways to reduce the effects of those factors
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Key Questions for Measurement System Analysis
How much variation is caused by the measurement system vs.
actual process variation?
How much error is considered allowable for this data?
What are the sources of the measurement error?
How can the error sources be eliminated or minimized?
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Guidelines for Measurement System Analysis
A Measurement System must be:
Accurate
Repeatable
Reproducible
Stable
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Issues when Validating a Measurement System
Why do a Gage R&R?
To determine if different workers across a given process use the
same criteria to determine “good” from “bad”
To assess work standards against customer requirements
To identify how well people are conforming to themselves
To identify how well people are conforming to a “known master”
To identify training, procedural, or standards gaps
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The difference between observed average measurement
and a master/standard.
Accuracy
Standard
Value
Observed
Average
Accuracy in Measurement Systems
Measurement System Accuracy
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This is the most common approach for correcting inaccuracy (or bias) in a measurement process. This is driven by the people or equipment “drifting” over time.
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Variation experienced when one person repeatedly measures
the same unit with the same measuring equipment.
(Minimum Variation)
Repeatability
Repeatability in Measurement Systems
Measurement System Repeatability
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Variation when two or more people measure the same
unit with the same measuring equipment.
Reproducibility
Data Collector 2
Data Collector 1
Reproducibility in Measurement Systems
Measurement System Reproducibility
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Variation obtained when the same person measures the
same unit with the same equipment over an extended
period of time.
Stability
Time 1
Time 2
Stability in Measurement Systems
Measurement System Stability
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Develop a master standard for everyone to utilize
Train data collectors together
Define each measure (operational definitions)
Test for accuracy, repeatability, reproducibility early and make
changes to system accordingly
Audit the process frequently (stability)
Improving the Measurement System
29
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What you learned during this section:
The importance of measurement system analysis
The different measurement system analysis techniques
(accuracy, repeatability, reproducibility, stability)
How to take the actions necessary to ensure the
measurement system functions properly
Summary of Section
30
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Data Consistency and Stability
Collecting Data
Data Sampling
Operational Definitions
Measure – Data Collection
Lean Six Sigma Training
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By the end of this section, you will be able to:
Understand the elements of a data collection plan
Understand the purpose of data collection forms
Determine the benefits of using existing data collection
methods or developing new methods
Develop elements of a data collection plan for your project
Overview – Objectives – Key Topics
32
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Communicate the purpose (what and why) to the data collectors and
process participants
Train everyone who will be collecting data
Make data collection procedures error proofed (consistency and
stability)
Oversee data collection and perform a pilot test (check in frequently
with collectors)
Begin Data Collection
33
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Measure
Specify the name of what
you are measuring (billing
accuracy, billing cycle time).
Type of Data
Discrete or Continuous.
Type of Measure
Specify whether it is an
output, input or process
measure.
Operational Definition
Define what is being
measured, how it will be
measured, and how it will be
recorded
Sample
- Number to be sampled
- Where in the process to
sample
- Frequency
Display
- What tool or tools will you
use to display the data
Data Collection Plan Elements
Data Collection
Plan
34
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Sample 100
Calls
Sample 225
Statements
Population of
Calls
Population of
Calls
Population of
Calls
Sample
HistogramThe average hold time per
hour / day / week / month
(January 1 – December 31)
ContinuousProcessHold Time
Average
Pareto
Diagram
The types of complaints
received from customers
(January 1 – December 31)
DiscreteOutputTypes of
Complaints
Run ChartThe number of inbound
calls to the call resolution
group (January 1 –
December 31)
DiscreteInputNumber of
Customer
Calls
Call
Resolution
Statement
Accuracy
Measure
Pie ChartThe % of calls resolved
without transfer to another
department (March 1 –
June 31)
DiscreteProcess
Pareto
Diagram
The inaccurate fields for
each statement (March 1 –
June 31)
DiscreteOutput
DisplayOperational DefinitionType of
Data
Type of
Measure
Data Collection Plan Example
35
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Data Collection Forms
A Data Collection Form:
Defines exactly what is to be measured
Standardizes data collection between different people
Makes it easier to keep track of data
Data Collection Form Considerations:
Descriptions of data that is being collected
Space to record the data
Space for comments
Space to keep track of stratification factors
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Loan # Location
Inaccurate Fields
Notes
Incomplete
Application
Wrong
Amount
Address
Incorrect
No
Signature
A1234 Chicago X Missing address
A2234 Chicago X
B3432 London X
A3487 Chicago X X
B9872 London X
B2903 London X
Totals 1 3 2 1
Check Sheets
A type of data collection form that helps collect the data
Standardizes the data collection to ensure consistency if more than one
person will be collecting
Data Collection Form Example – Check Sheet
37
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Guidelines for determining the cost/benefit trade off for data
collection
Can the new data be generated through systems modifications?
Can data collection efforts be easily integrated into existing work
processes?
Is all the data being collected necessary to calculate key process
measures?
Can some existing data collection efforts
be curtailed because they do not add
value?
Cost/Benefits of Data Collection
38
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Check to make sure measurements are stable
Review the measurement procedures periodically to
ensure consistency
Check to see if the data looks reasonable
Continue Improving Measurement Consistency
39
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Keep in mind that data collection costs time and money. Ask yourself:
Is it worth it?
Know how you will use the data before launching a large collection. Ask yourself:
Can we test it through a quick pilot?
How we will gather and use the data?
Data is the output of a measurement process. Ask yourself:
How can I apply my process perspective to the issue of measurement
quality?
Data Collection Summary Points
40
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What you learned during this section:
The elements of a data collection plan
The purpose of data collection forms
The benefits of using existing data collection methods or
developing new methods
How to develop elements of a data collection plan for
your project
Summary of Section
41
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
End of Lesson: Measure – Data Collection
Lean Six Sigma Training
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Types of Variation
Understanding Variation
Measure – Describe and Display Data
Lean Six Sigma Training
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By the end of this section, you will be able to:
Understand what variation is and how to display and describe it
Develop a Histogram and use it to interpret variation
Understand normal and non-normal data
Utilize additional tools for categorical data
Overview – Objectives – Key Topics
2
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Reducing the process variability to meet customer requirements (CTQ’s) is
a central theme for Lean Six Sigma improvement. We must first document
this variability before we can understand the problems that drive it
(Analyze Phase) and how to improve it (Improve Phase).
The goal of Lean Six Sigma improvement is to center a process well
within customer requirements by reducing variation.
To determine whether this goal is achieved, Sigma requires that two
elements are measured:
Customer requirements (CTQ’s) – Define Phase
Process baseline performance (mean & standard deviation) –
Measure Phase
Variation and Sigma
3
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Variation Happens
All repetitive activities of a process have a certain amount of fluctuation
or variation
Variation is the “Voice of the Process”
When plotted, process variation becomes visible over time
Input, process, and output measures will have variation
Failure to understand variation could be costly
Time Frequency
What is Variation?
4
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PROCESS VARIATION INHIBITS OUR ABILITY TO
MEET CUSTOMER REQUIREMENTS
Variation
Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
A
Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
A
Why it’s Important to Understand Variation
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Histograms – a histogram is a bar graph that displays data in picture
form. Often times called a frequency distribution because it shows clearly
how frequently each separate value appears in the data.
A histogram reveals several factors about the data. Such as:
The central position of the data. For example, the mode or most
frequently appearing value shows one measure of central position.
(Another measure of central tendency is the average.)
The dispersion (spread or variation) of the data.
The shape (pattern) of the data.
Charting Variation – Histograms
6
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The first question to be answered in describing variation is “What is the
central tendency of the data?”
Central Tendency:
Refers to the “center” of the
frequency distribution
Represents where most of the
values (in this example cycle time)
tend to occur
Histograms – Central Tendency
7
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Descriptive Statistics:
Mean: 30.60 Days
Often referred to as the average, it is the
most likely or expected value. The
formula for mean is:
Median: 31 Days
The middle of the data set, where 50%
of the data is greater than the median,
and 50% of the data set is less than the
median
Mode: 31 Days
The most frequently occurring value.
Central Tendency can be estimated using the graphical display of the histogram, but
is more precisely measured by statistical measures of central tendency.
_
n
ΣxiX =
_
X is the value we are trying to solve (mean)
Σ is a mathematical notation for adding values (summation)
Xi is the I’th (where I runs from 1-n) data value of all the data
n is the number of data points
Statistics Overview:
Histograms – Central Tendency
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Example: Calculate Mean, Median and Mode from the following data set:
1, 2, 6, 6, 10, 11, 12, 13, 14, 28
Mean = 10.3; Median = 10.5; Mode = 6
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Many companies often use mean or average to describe their
process variation and performance.
Example:
A call center answers the phone on average within 30 seconds of the
customer call. The customer’s requirement of the speed of answer is <1
minute.
How well is this process performing at meeting the customer’s
requirement?
What additional information is missing to draw sound conclusions?
Mean = 30 Seconds CTQ = 1 Minute
time
Histograms – Central Tendency
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The second question to be answered in describing variation is “What is the
dispersion of the data?” Or, how much variation exists in the data?
Dispersion:
Often referred to as the spread or
variation in the measurements
Histograms – Dispersion
10
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Descriptive Statistics:
Range: 23 Days
The maximum value in the data set minus the
minimum value in the data set. The formula for
range is:
R = MAX - MIN
Standard Deviation: 4.67 Days
The most common measure of dispersion, the
standard deviation is the average distance, or
deviation, that a given point is away from the
mean. The formula is:
Dispersion can be estimated using the graphical display of the histogram, but is
more precisely measured by statistical measures of dispersion
S =
n - 1
Σ (xi – x)2
_
_
X is the average of all of the data
Σ is a mathematical notation for adding values (summation)
n is the number of data points
s is the value we are trying to solve (standard deviation)
Xi is the I’th (where I runs from 1-n) data value of all the data
Statistics Overview:
Histograms – Dispersion
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While the central tendency and dispersion of data provide valuable
information, they still are not sufficient in describing variation.
Example:
2 call centers have almost identical average and standard deviations.
Is one center performing better than the other?
What additional information is missing to draw sound conclusions?
Histograms – Central Tendency and Dispersion
N = 100, Mean = 30.42, StDev = 4.452
12
N = 100, Mean = 31.1, StDev = 4.462
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The final question to be answered in describing variation is “What is the
shape of the data?”
Histograms – Shape
13
Shape:
Refers to the pattern of the data
when plotted on a histogram
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These histogram examples above represent the 3 commonly encountered shapes. They are the normal distribution, bimodal distribution, and exponential distribution (which can be skewed either to the right-positive or left-negative).
Many processes do not follow a “normal” distribution and non-normal data should not be considered bad data. Some examples of non-normal processes would include:
Cycle time
Calls per hour
Customer waiting time
And many others
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The Normal Curve – a probability distribution where the most frequently occurring
values are centered around the middle (or center point) and the other values tail off
symmetrically in both directions.
In theory, the curve or distribution never ends
Equal proportions fall on either side of the most frequently occurring value
The center of the data is at the peak of the distribution
Almost 100% of the results are contained within 3 standard deviations on either side
of the average
Normal Curve
14
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The normal distribution is of special interest because it naturally arises from measurement data. In addition, many statistical tools assume a normal distribution:
Continuous Data Control Charts
Continuous Data Hypothesis Tests
Process Capability
Design of Experiments
We can use a “Normal Probability Plot” to test whether the data is normally distributed.
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The Normal Curve – can be divided into segments, mathematically called standard
deviations. Roughly 100% of the data falls within 3 standard deviations on either
side of the average .
Normal Curve and Standard Deviation
15
Number of Standard Deviations from the Mean
x
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6
Standard
Deviations (Sigma’s)
1
2
3
4
5
6
% of Data
Between Limits
68.26
95.46
99.73
99.9937
99.999943
99.9999998
68.26%
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Normal Probability Plot – Roughly Normal
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Normal Probability Plot – Bimodal Distribution
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Normal Probability Plot – Exponential Distribution
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After you have plotted data using the Normal Probability Plot, check the P-value.
Normality Test: P-value
Normal data will fall on a straight line within the probability confidence intervals (95% CI) and
have a P-value of >0.05. Normal: P-value >= 0.05, Not Normal: P-value < 0.05
Example: In the normal distribution probability plot (see previous pages):
Almost all of the data points fall within the limits
The P Value is 0.229
We would conclude that there is no serious departure from normality in this data.
Example: In the bimodal and exponential probability plots (see previous pages):
Many of the data points fall outside of the limits
The P Value is <0.05
We would conclude therefore that these data sets depart significantly from normal
distribution.
You can also perform the Anderson-Darling Normality Test to calculate the P-value (this test is
found in many statistical software applications).
There are several methods for handling non-normal data. These include stratifying differently,
sub-group averaging, using different distributions, and transforming data. Transforming data is
an advanced statistical technique that will not be covered in this course.
19
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As we have covered in displaying variation, histograms allow us
to answer the following questions:
What is the central position of the distribution?
What is the dispersion or spread of the distribution – is it wide or
narrow?
What is the shape of the distribution – symmetrical, twin peaked,
skewed to one side or the other, flat, etc?
Are there outliers or extreme data points?
Interpreting Histograms
20
After describing the data, we can use the histogram to
determine the appropriate strategy for improvement:
1. Reduce the process variation
2. Reduce the process mean
3. Reduce both the process variation and mean
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1. Reduce the process variation
Process A (dashed line)
Excessive variation
Defects are created when
process variation exceeds CTQ
(also known as USL – upper
spec limit)
Process B (solid line)
Reduced variation
Defects are eliminated or
reduced when process variation
stays within CTQ Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
A
B
Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
A
B
Interpreting Histograms
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2. Reduce the process mean
Process A
Mean > CTQ creates defects
Virtually all of the process
distribution is causing defects or is
“out-of-spec” for USL
Process B
Mean reduction* < CTQ
eliminates defects
Defects are eliminated or reduced
when process mean is shifted
within CTQ requirements Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
AB
*Remember that just measuring the mean
alone will not be sufficient to determine if
process is meeting CTQ’s
Interpreting Histograms
22
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3. Reduce the process variation then reduce the mean
Process A
Variation and mean exceed CTQ
requirements
Only shifting mean, the variation
would still cause defects
Reducing variation first will make
the process more stable
Process B
Mean > CTQ creates defects
Reduce process mean
Process C
Defects are eliminated or reduced
when process variation is reduced
and mean is shifted within CTQ
requirements
Product or Service Output
Critical to Quality (CTQ)
A
C B
Interpreting Histograms
23
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Reduce the Process
Variation
Process may be
stable with no outliers
present
Symmetric, bell
shaped
Revise measurement
process
Measurement may
not be sensitive
enough
No distinctive values
Investigate reason for
asymmetric
Process data may not
be normally
distributed
Asymmetric, long tail
(either positive or
negative)
Investigate reason for
bi-modal, try
segmentation
There may be 2 or
more processes or
segments
Bi-modal, two humps
Standardize
measurement
process
Inconsistent roundingMultiple dominant
observations
Investigate cause of
bias
Measurement may be
biased
One value dominant
ActionConcludeObservationShape
Common Histogram Shapes
24
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Objective
Practice interpreting histogram shapes.
Instructions
Interpret the shapes on the following page.
What can you gather from the shape?
What actions might you take on it?
Prepare your findings.
Histogram InterpretationEXERCISE
25
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Histogram InterpretationEXERCISE
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Please Do Not Proceed Forward
Histogram InterpretationEXERCISE
27
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When you see this symbol, please do not continue forward in the materials.
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Histogram Interpretation – ResultsEXERCISE
Symmetric
28
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Pie Chart – the pie chart is a tool that displays discrete variation by
breaking down the frequency of the data distribution into categories.
Pie Charts and Variation
29
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What you learned during this section:
What variation is and how to display and describe it
How to develop a Histogram and use it to interpret variation
What normal and non-normal data is and how to differentiate
between the two
Other variation tools that can be used for displaying categorical
data
Summary of Section
30
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Types of Variation
Understanding Variation
Measure – Describe and Display Data
Lean Six Sigma Training
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By the end of this section, you will be able to:
Understand what common cause and special cause variation are
Develop a Run Chart and Control Chart and use them to
distinguish common and special cause
Select the appropriate control chart based on the type of data
Overview – Objectives – Key Topics
32
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V
A
R
I
A
T
I
O
N
Machines
Materials
Methods
Measurement
Mother Nature
People
Describing and understanding the sources of variation is a first step in reducing it.
Sources of Variation
33
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Potential sources of variation:
Machines – The equipment used to transform inputs into outputs.
Materials – The outputs of the process. These may be tangible (i.e. documents) or not.
Methods – The procedures used to transform inputs into outputs. These may be as formal as standard operating procedures or not documented at all.
Measurement – Any tools that are used to monitor or track the performance of the process.
Mother Nature – Environmental elements within the process that have an impact on its performance.
People – The workers who perform the process.
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Variation
Common Cause
(natural/inherent)
Special Cause
(assignable/imposed)
Common Cause – natural inherent causes from the interaction of all of the sources
of variation.
Can only be reduced by changing the process
Special Cause – assignable cause from especially large influence by one of the
sources of variation.
Must be removed or reduced for a process to be considered stable or in control
Approximately 85 to 95 percent of variation within a process can be attributed to
the overall system in which the work is done rather than to the individuals
involved in the process
Two Types of Variation Defined
34
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Where does process variation come from in the first place? Given the same
input, shouldn’t the process produce the same output every time?
Dr. Walter Shewhart wrestled with this dilemma in the 1920s. He discovered that
process variation has two components: a stable, omnipresent variation inherent
in the process; and an unstable, intermittent variation attributable to assignable
causes.
Total Process Variation = VARSPECIAL + VARCOMMON
SPECIAL CAUSE COMMON CAUSE
Special Cause vs. Common Cause Variation
35
New procedure
implemented
Machinery failure
Power outage
Untrained operator
Employee strike
Improper setup
Different levels of
training
Inadequate
inspection/test
Lack of machinery
capability
Failure to understand
customer requirements
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Common
Cause
Special
Cause
Not significantly
influenced by one
of the sources
Significantly
influenced by one
of the sources
Expected
Predictable
Normal
Random
Chance
Unexpected
Unpredictable
Not Normal
Not Random
Chance
It is important to understand this distinction so the strategy for process
improvement and control can be determined.
Characteristics of the Two Types of Variation
36
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Common
Cause
Investigate to
determine the “vital
few” causes (X’s)
Develop solutions
for “vital few”
causes
The actions that will be taken are driven by the type of variation.
Analyze and Improve Phases
Special
Cause
Investigate the
specific causes from
the problem source
Develop solutions
and implement as
needed
Measure Phase
Improvement Strategies for Common and Special
Causes
37
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The first question most teams will ask is “How do we know whether we have
common cause or special cause variation?”
Distinguishing Common Cause vs. Special Cause
Variation
2 tools that
distinguish
Common and
Special
Cause
Run Chart
Control Chart
38
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Run Charts – time ordered plots of data that can be used to search for
special cause variation.
Run Charts and Variation
39
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Advantages
Most data collected over
time can be used
Provides baseline of
current process performance
Easy to create
No calculations needed
Easy to interpret
Disadvantages
Detecting special causes
takes time
Won’t detect:
Short duration shifts
Variation increases
Hard to assess process
capability
Run Chart Advantages and Disadvantages
40
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Run Charts should be used in conjunction with the Histogram to develop a full picture of process performance. A process may not have detectable patterns of special cause variation, but have considerable variation that can only be determined when using the Histogram.
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Control Charts – similar to the run chart, control charts are time-ordered plots
of data that can be used to search for special cause variation. The additional
benefit of control charts is that they also have “control limits”.
Upper Control
Limit
Lower Control
Limit
Control Charts and Variation
41
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Control limits are calculated at 3 standard deviations on either side of the mean (or center line).
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Control Limits – are a statistical calculation from the process data and define
the boundaries of common cause variation. Remember that a process is
considered out of control if it contains special cause variation.
Upper Control
Limit
Lower Control
Limit
Defined based on the performance of the process
Help to determine if your process in “in control”
(only common cause variation is present)
Plotted on control charts by statistical calculation
Can change based on changes to the process
“Control Limits”
Control Limits Defined
42
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Control limits (UCL and LCL) may be recalculated when the following
guidelines have been met.
No special cause variation exists in the process
Either the methods of collecting or operational definitions of the
data have changed in the process
When a change in the process has occurred that has fundamentally
changed the performance in the process
Recalculating Control Limits
43
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Defined by the customer
Help determine if the process is
producing defects
Not plotted on control charts
Change when customers
requirements change
Defined by the process
performance
Help determine if the process is in
control
Plotted on control charts
Change when the process changes
Upper Control
Limit
Lower Control
Limit
“Control Limits” Voice of
Process
Upper Spec
Limit
Lower Spec Limit
“Spec Limits”
Voice of
Customer
Control Limits vs. Specification Limits
44
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Only common cause variation is present
in the process
The process is predictable
The process is stable
A process that is “in control” may not be meeting
customer requirements
Definition of Control
45
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Look for patterns in the graph that indicate special cause. Patterns to look for are:
Shift – 8 or more consecutive points on the
same side of the center line
Outlier – 1 or more points that fall outside of
the control limits
Trend – 6 or more consecutive points
increasing or decreasing
Cycle – Data points that cycle up and down
Interpreting Control Charts
46
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We can conclude that special cause variation is present if one of these patterns is present in the data. Next steps would include:
Investigate the specific data points where the pattern occurs
Determine the source of the variation
Develop solutions and implement as needed
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In addition to the previous patterns, when the Control Chart is divided into zones, as shown
below, a process is out of control when any of the following is true:
2 points out of 3 consecutive points are on the same side of the average in Zone A or
beyond
4 points out of 5 consecutive points are on the same side of the average in Zone B or
beyond
There are 15 consecutive points within Zone C (above and below the average)
UCL
CL
LCL
Zone A
Zone B
Zone C
Zone B
Zone C
Zone A
Interpreting Control Charts
47
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By dividing the control chart into zones, we can better detect special cause variation. Each zone represents standard deviations from the mean:
Zone C represents +/- 1 standard deviations from the average (center line)
Zone B represents +/- 2 standard deviations from the average (center line)
Zone A represents +/- 3 standard deviations from the average (center line)
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2 points out of 3 consecutive
points are on the same side of
the average in Zone A or beyond
UCL
CL
LCL
A
B
C
C
B
A
UCL
CL
LCL
A
B
C
C
B
A
4 points out of 5 consecutive
points are on the same side of
the average in Zone B or beyond
There are 15 consecutive points
within Zone C (above and below
the average)
UCL
CL
LCL
A
B
C
C
B
A
Examples of Zone Variation Detection
48
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Use this chart to select the type of control chart to use.
Discrete
ImR Chart
Continuous
Type of Data
Subgroup Size
of 1
Rational Small
Subgroups (<8-
10)
Rational Large
Subgroups (>8-
10)
X and S
Chart
_
np Chart
Classification
(binomial data)
Sample Size is
Constant
Sample Size
Varies p chart
u Chart
Count
Opportunity
Varies
Opportunity is
Constant c chart
OR
OR
OR
OR
OR
X and R
Chart
_
Selecting a Control Chart
49
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For X-bar and R and X-bar and S you will need to collect data in sets of points called subgroups, or logical groupings of data.
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Overview of the different types of control charts
Discrete data control charts:
np Chart – used with classification data (i.e. pass/fail, good/bad) and charts the number of
defectives in each subgroup (sample size is constant).
p Chart – used with classification data (i.e. pass/fail, good/bad) and charts the proportion of
defectives in each subgroup (sample size varies).
u Chart – used with count data (e.g. number of defects) and charts the number of defects
per unit sampled in each subgroup (opportunity for defects varies).
c Chart – used with count data (e.g. number of defects) and charts the defect count per
sample (opportunity for defects is constant).
Continuous data control charts:
ImR Chart (Individuals) – for analyzing individual data points and rational subgroups can
not be formed from the data (data is assumed to be normally distributed).
X and R Chart – for analyzing the averages of small subgroups (<8-10) can be formed from
the data.
X and S Chart – for analyzing the averages of large subgroups (>8-10) can be formed from
the data.
Selecting a Control Chart
50
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What you learned during this section:
What common cause and special cause variation are
How to develop a Run Chart and Control Chart and use them
to distinguish common and special cause
How to select the appropriate control chart based on the type of
data
Summary of Section
51
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
End of Lesson: Measure – Describe and Display Data
Lean Six Sigma Training
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Yield
Sigma
Measure – Baseline Performance
Lean Six Sigma Training
Process Capability
1
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Understand the concept and benefits of sigma
Understand how sigma relates to process capability
Utilize the formula to calculate baseline performance
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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By now, you have gathered your data from Outputs (Y’s) and Process and Inputs
(X’s). You have displayed and described your data. The next question to solve is:
How well is my process performing against my
customer’s requirements?
Voice of Process
(variation)
Voice of
Customer
(CTQ’s)
I P O C
?
Measure Phase Review
3
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Sigma is a name given to indicate how much of the data falls within the
customers’ requirements. The higher the process sigma, the more
the process outputs, products and services, meet customers’
requirements – or, the fewer the defects.
Sigma is a Measurement scale which
compares the output (variation) of a
process to the customer’s requirements
(CTQ’s). Sigma shows how capable a
process is of meeting CTQ’s.
What is Sigma?
4
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Defects are defined as not meeting customer requirements. Put simply, sigma is the measure of how far a process is away from achieving near perfect customer satisfaction. Six, or 6 Sigma is measured at near perfect… meeting customer expectations 99.99966% of the time.
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If you were the VP of a company and these were current process performance
figures, how would you know which process is performing better?
Process Performance
Customer Service Speed of answer is 20
seconds
Systems
Loan Processing
Systems up time is 95%
Loans processed on
average 15 days
Why Having a Common Metric for
Comparison is Critical
5
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It’s difficult to compare processes with very different kinds of measures. There is no common metric between these processes.
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In this diagram, the number of occurrences that fall outside of the customer requirement
for Process A are considered defects. Process B represents the optimal performance
(most capable) with no occurrences (defects) outside of the requirement.
B
Product or Service Output
Critical to Quality (CTQ)
Defects: Service
unacceptable to
customer
A
Optimal Performance
Process Variation and CTQ’s
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Process A has considerable variability or spread and is not meeting the critical customer requirement (identified by the defects). By reducing the variation and mean of the process (B), the process is more capable of meeting customer requirements and will lead to higher sigma performance and greater customer satisfaction.
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The most capable process has variation and mean that are well within
customer requirements.
Product or Service Output
Critical to Quality
(CTQ)
Sigma is calculated by the variation against the CTQ’s, so
the smaller the variation the higher the Sigma.
Capable Process
7
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There are 2 ways a process can be non-capable.
Product or Service Output
Critical to Quality
(CTQ)
Defects:
Service
unacceptable to
customer
High Process Variation – the process
variation exceeds the customer
requirement (specification limits which
could have a lower or LSL and upper or
USL)
Process Mean Not Aligned – the
process mean exceeds the customer
requirement (specification limits which
could have a lower or LSL and upper or
USL)
Product or Service Output
Critical to Quality
(CTQ)
Defects:
Service
unacceptable
to customer
Product or Service Output
Critical to Quality
(CTQ)
Defects:
Service
unacceptable
to customer
Non-Capable Process
8
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The term “Six Sigma” refers to process capability equivalent to produce 3.4
defects per million opportunities (DPMO). A defect is considered any event which
fails to meet customer critical-to-quality (CTQ) requirements, while an opportunity
is any event where failure to meet CTQs is possible.
99% performance is generally considered quite good. Yet if many of the
processes we encounter in our daily lives functioned only at 99% effectiveness,
we would reconsider our definition of “good” performance:
20,000 lost articles of mail per hour
15 minutes worth of unsafe drinking
water each day
5000 incorrect surgical operations a
week
2 short or long landings at most major
airports every day
No electricity for 7 hours per month
99% Defect-Free 6σ (99.99966% Defect-Free)
7 lost articles of mail per hour
9 seconds worth of unsafe drinking
water each month
2 incorrect surgical operations a
week
1 short or long landing at most major
airports every 4 years
No electricity for 1 second per year
(Adapted from Mikel J. Harry, The Nature of Six Sigma Quality, 1987)
Which world would you rather live in?
Sigma Defined
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With performance at 2 Sigma:
69.146% of products and/or services meet customer requirements with
308,538 defects per million opportunities.
With performance at 4 Sigma:
99.379% of products and/or services meet customer requirements… but
there are still 6,210 defects per million opportunities.
With performance at 6 Sigma:
99.99966% – As close to flaw-free as a business can get, with just 3.4
defects per million opportunities (e.g., products, services or transactions).
Sigma Performance
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Most companies measured, prior to business performance improvement, perform around a 1 to 2 sigma, which equates to meeting customer expectations only 30.9% to 69.1% of the time.
These numbers are staggering and can be extremely detrimental to customer satisfaction with products and services. Although 6 Sigma is difficult to achieve in some industries, a 3.5 Sigma (meeting customer expectations 97.7% of the time) is realistic for most service related companies.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
A capable process is statistically defined as a process that has all of its
variation within 6 standard deviations (sigma’s) of the customer requirements.
Number of Standard Deviations from the Mean
x
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6
Standard
Deviations (Sigma’s)
1
2
3
4
5
6
% of Data
Between Limits
68.26
95.46
99.73
99.9937
99.999943
99.9999998
CTQ
(Upper Spec)
CTQ
(Lower Spec)
Capable Process and Sigma
11
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A measurement scale focused on improvement
Focuses on defects
Common metric for comparison
Why Sigma Measures?
12
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Yield exclusive of rework at a process stepFirst time yield
A unit with one or more defectsDefective
Any event which can be measured that provides a chance of not
meeting a customer requirement
Defect Opportunity
Any event that does not meet the specification of a CTQ. For
DPMO method, defects or non-defects must be at least 5*.
Defect:
The item produced or processed – either a product or service
transaction
Unit:
How these are operationally defined is critical to your
data collection effort
*Additional methods for calculating Six Sigma are utilized when defects and non-
defects are <5. These methods are an advanced statistical technique that will
not be covered in this course.
Six Sigma Calculation Definitions – DPMO Method
13
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There may be more than one defect opportunity per unit.
Ex. Fields on an invoice
The opportunity for the defect must be important to the customer
(relate directly to a CTQ).
Ex. Only count fields on an invoice that are requirements of
the customer
Don’t count every field, doing this can inflate the opportunities
and the sigma
Some defects may cause others. Only count the original defect
as the opportunity.
Guidelines for Determining Opportunity
14
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Unit Defect Opportunity
Invoice Incorrect fields
identified by
customer
The fields on
the invoice
Employee
Check
Customer
Phone Call
Check not
received on
date specified
Call not
answered
within 30
seconds
Each check
processed
Each customer
call
Six Sigma Calculation Definition Examples
15
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General Worksheet for Calculating
Process Sigma (DPMO)
1. Number of Units Processed (N) N = __________
2. Total Number of Defects Made (D)
(Include Defects Made and Later Fixed) D = __________
3. Number of Defect Opportunities
Per Unit (O) O = __________
4. Solve for Defects Per Million DPMO = 1,000,000 X
Opportunities
=1,000,000 X
= __________
5. Look up Process Sigma in an Abridged
Sigma Conversion Table = __________ Sigma
D
N•O
( )
( ) ( )
Sigma Calculator
16
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Unit Defect Opportunity
Employee
Check
Check not
received on
date specified
Each check
processed
Unit = Employee Processed Checks
Critical to Quality (CTQ) = 5th
of each month
Defects: Checks
received after 5th
Total Opportunities
Calculating Process Sigma (DPMO) Example
17
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Calculating Process Sigma (DPMO) Example
1. Number of Units Processed (employee checks) N = __________
2. Total Number of Defects Made
(checks received after the 5th) D = __________
3. Number of Defect Opportunities
Per Unit (each check) O = __________
4. Solve for Defects Per Million DPMO = 1,000,000 X
Opportunities
=1,000,000 X
= 356,000
1,000
356
1
D
N•O
( )
( ) ( )
356
1,000 1
A company that pays its employees on the 5th of the month, has collected data on
the number of checks that are received by the employee after the required date.
18
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Yield Sigma DPMO Yield Sigma DPMO
99.99966% 6.00 3.4 98.60966% 3.70 13,903
99.99946% 5.90 5.4 98.21356% 3.60 17,864
99.99915% 5.80 8.5 97.72499% 3.50 22,750
99.99867% 5.70 13 97.12834% 3.40 28,717
99.99793% 5.60 21 96.40697% 3.30 35,930
99.99683% 5.50 32 95.54345% 3.20 44,565
99.99519% 5.40 48 94.52007% 3.10 54,799
99.99277% 5.30 72 93.31928% 3.00 66,807
99.98922% 5.20 108 91.92433% 2.90 80,757
99.98409% 5.10 159 90.31995% 2.80 96,800
99.97674% 5.00 233 88.49303% 2.70 115,070
99.96631% 4.90 337 86.43339% 2.60 135,666
99.95166% 4.80 483 84.13447% 2.50 158,655
99.93129% 4.70 687 81.99519% 2.40 184,060
99.90323% 4.60 968 78.81446% 2.30 211,855
99.86501% 4.50 1,350 75.80363% 2.20 241,964
99.81342% 4.40 1,866 72.57469% 2.10 274,253
99.74449% 4.30 2,555 69.14625% 2.00 308,538
99.65330% 4.20 3,467 65.54217% 1.90 344,578
99.53388% 4.10 4,661 61.79114% 1.80 382,089
99.37903% 4.00 6,210 57.92597% 1.70 420,740
99.18025% 3.90 8,198 53.98278% 1.60 460,172
98.92759% 3.80 10,724 50.00000% 1.50 500,000
Abridged Sigma Table (For calculation of long-term sigma, subtract 1.5 sigma)
4. Solve for Defects Per Million Opportunities =
5. Look up Process Sigma in an Abridged
Sigma Conversion Table = __________ Sigma 1.90
356,000
Calculating Process Sigma (DPMO) Example
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Time
Co
nt
in
uo
us
D
at
a
Long-Term Data
Short-Term Data
The amount of variation in the process is influenced by whether the data is
long-term or short-term.
Long-Term Data
– Data that is collected over a long enough
period of time that it contains the diversity of
conditions within the process to contain large
process shifts and special causes.
Short-Term Data
– Data that is collected over a short enough
period of time that large shifts and special
causes are not likely to occur.
For the purposes of this training, all data (continuous and discrete) will be treated as
long-term data and contain short-term process sigma's that are automatically built into
the Abridged Sigma Table.
Long-Term vs. Short-Term Data
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What you learned during this section:
The concept and benefits of utilizing sigma
How sigma relates to process capability
How to calculate baseline performance with sigma
Summary of Section
21
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Yield
Sigma
Measure – Baseline Performance
Lean Six Sigma Training
Process Capability
22
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Understand the concept of process yield
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
23
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Buy
Seed
Sell
Corn
Plant
Seed
Gather
Corn
45,000 PPM
Wasted
95.5% Yield
Following Excess
Disposed and Lost Seed…
21,965 PPM
Wasted
97.7% Yield
Following Damaged
and Underdeveloped Corn…
46,652 PPM
Wasted
95.0% Yield
Available to Sell
After Packaging
113,617 Parts Per Million
Wasted Opportunities
Concept of Yield
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Yield and Defect Counts are related measures
Ex. 356,000Ex. 0.356Ex. 64%
= 1,000,000 ●== 1 -
The count of defects per
opportunity times 1 million
in products or services
The count of defects
per opportunity in
products or services
The % of good
products or
services
Defects per Million
Opportunity (DPMO)
Defects per
Opportunity
(DPO)
Yield
D
N•O
D
N•O
D
N•O
Yield and Defect Count
25
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If you were the VP of a company and these were current process
performance figures, how would you know which process is
performing better?
Customer Service Speed of answer is 20
seconds
Process Performance Sigma
Systems
Loan Processing
Systems up time is 95%
Loans processed on
average 15 days
4.8 Sigma
3.2 Sigma
2.1 Sigma
Why Having a Common Metric for
Comparison is Critical
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With sigma included, we have a common metric in order to gauge process performance. Loan Processing is not meeting customer requirements based on the low sigma.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
What you learned during this section:
The concept of process yield
Summary of Section
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
Yield
Sigma
Measure – Baseline Performance
Lean Six Sigma Training
Process Capability
28
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Overview – Objectives – Key Topics
Understand the concept of Process Capability
Understand the necessary data and calculations to
determine Process Capability
Calculate Process Capability
By the end of this section, you will be able to:
29
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What is Process Capability
Process Capability measures the Voice of Process against its ability to
meet Customer Requirements (Voice of the Customer).
Voice of the Customer
Voice of Process
U
pp
er
S
pe
ci
fic
at
io
n
Li
m
it
Lo
w
er
S
pe
ci
fic
at
io
n
Li
m
it
Is this process capable of meeting
customer requirements?
30
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Why Process Capability
Provides a single value to assess the capability of a
process in meeting customer expectations.
Evaluates the baseline of a process against customer
expectations.
Validates the capability of a process over time.
Validates the capability of a pilot against expected
results.
Capability indices are without a unit (i.e. does not have
a value like minutes, dollars, etc,) therefore you can
compare one process to another.
31
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Process Capability Assumptions
Data is normally* distributed
Data is continuous*
Process is in statistical control
Data is time ordered
*Process Capability can be calculated for non-normal data and discrete data. This
course will only cover calculating Process Capability for normal continuous data.
1019181716151413121111
30
15
0
In
di
vi
du
al
V
al
ue
_
X=15.42
UCL=29.74
LCL=1.10
1019181716151413121111
20
10
0
M
ov
in
g
R
an
ge
__
MR=5.38
UCL=17.59
LCL=0
I Chart
Moving Range Chart
Control Chart for Cycle Time
3020100
Normal Prob Plot
A D: 0.580, P: 0.128
32
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Capability Roadmap for Normal Continuous Data
Start
YES NO
LSL USL
Is Short
Term
Data
Available
?
Conduct Capability Analysis
& Specify Subgroup Size
for Short Term “Subgroup
Data Set”
Conduct Capability Analysis
in Long Term with
Subgroup Size of “1”
Note: Look at
Both Short Term
& Long Term
Data
Note: Only Look
at Long Term
Results
Conduct
Analysis
Calculate Sigma
Levels To Further
Understand Results
(not covered in this
course)
33
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Process Capability Definitions – Capability Indices
Cp (short term data) or Pp (long term data) = Potential capability of the process or the
ratio of the Specification Range (Voice of the Customer) to the natural range of the
process, it does not look at how well the process average is centered to the target value.
This value gives you an idea of whether the process could meet customer requirements.
Example: Let’s say you are driving your car into your garage, Cp tells you if you are
capable in the short term of fitting into the garage or not. It does not tell you if
the driver has driven in straight or centered the car properly. Pp tells you if
you are capable of fitting into the garage over the long term.
Cpk (short term data) or Ppk (long term data) = Actual capability of the process and takes
into account the location of the process average.
Example: Let’s say you are driving your car into your garage, Cpk tells you if you are
capable in the short term of fitting into the garage or not, and if the driver has
driven in straight or centered the car properly. Ppk tells you if you are capable
of fitting into the garage in the long term and if the driver has driven in straight
or centered the car properly.
Note: The problem with Cp or Pp is that it is a theoretical capability (entitlement) and you cannot
compare two processes that have the same Cp or Pp when one is off center (obviously creating
defects).
34
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Calculating Process Capability
Step 1: Identify/Calculate the following from your data:
a. Identify Specification Range
Upper Specification Limit: USL
and/or
Lower Specification Limit: LSL
b. Calculate the Process Range
Standard Deviation: “s”
c. Calculate the Location of the Process
Process Average: “X”
35
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Calculating Process Capability
Step 2: Determine if your data is Short Term or Long Term.
Data tends to vary over time due to many internal and
external factors. It is important to separate short term from
long term data in order to determine current process
capability.
Short Term data generally does not include special cause
variation.
Example: data collected only for: 1 day, 1 operator, or 1 call
center rep.
Long Term data includes the effects of special cause variation.
This means that you have collected enough data over a long
enough period of time to be confident that you have seen 80%
of the process variation. This is the variation that the customer
actually experiences over the long term.
Example: data collected for multiple: days, operators, or call
center reps.
Time
A
B
D
C
A + B +
C + D
The truth about process capability is Long Term. So you have to
determine what type of data you have and convert it from Short Term
to Long Term.
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Sigma values for Long Term data are generally lower than Sigma values for Short Term data. The difference between the two is called Sigma Shift. The Sigma Shift from Long Term to Short Term is 1.5 Sigma.
Example, to convert Short Term Sigma into Long Term Sigma you will need to subtract 1.5 Sigma from the Short Term Sigma value.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Calculating Process Capability
Interpreting Cp and Pp Values:
Above 1.33 is acceptable and capable of meeting customer
expectations
In general, the higher the Cp or Pp value, the more capable
your process is.
Cp or Pp Interpretation Example: A value of 1 would mean the Specification
range and the Process range are the same and that any variation would mean
the process could easily not meet the customer requirements therefore 1.3
and greater is acceptable.
Step 3: Calculate and Interpret Process Capability
Cp (short term data) or Pp (long term data) =
Voice of Customer
Voice of the Process
USL - LSL
6 * s
=
Requires both
USL and LSL
37
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Calculating Process Capability
Step 3: Calculate and Interpret Process Capability
Cpk (short term data) or Ppk (long term data)=
Interpreting Cpk and Ppk Values:
Below 1.0 is generally not acceptable for meeting customer
expectations
Above 1.33 is acceptable and capable of meeting customer
expectations
Min*: In the case that you have both USL and LSL, calculate both values and report the lower value.
Note: Cpk or Ppk divides the formula of Cp or Pp into 2 and takes into account where the process is situated.
38
Cpk or Ppk = Min*
USL - X
3 * s
X - LSL
3 * s
or
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Cpk or Ppk & Z score (Z score = the number of standard deviations that can fit between the mean and the nearest customer specification limit).
Something interesting that explains what range is acceptable and how short term, long term and Z score tie together.
Cpk = Z(short term) / 3 & Ppk = Z(long term) / 3
or 3 * Cpk = Z(short term)
So Z(short term) = 6 sigma then Cpk = 6/3 = Cpk of 2
Z (long term) = 6-1.5(shift for conversion to long term from short term) = Ppk 4.5/3 = 1.5
So a capability of 1 means the process is just capable and 2 is Six Sigma so the range has to depend on the requirements of the process. Some processes need to be closer to 2 and for others it is okay to be at 1.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Summary of Section
What you learned during this section:
The concept of Process Capability
The necessary data and calculations to determine
Process Capability
How to calculate Process Capability
39
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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove
End of Lesson: Measure – Baseline Performance
Lean Six Sigma Training
40
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Analyze Phase
Lean Six Sigma Training
1
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Analyze Phase Overview
Lean Six Sigma Training
2
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In Analyze, the questions of why the
organization is unable to meet customer
requirements is understood. Analyze utilizes
both process and data analysis techniques to
drill down to the root cause problems that will
ultimately lead to solutions.
Analyze also keeps the team from jumping to
premature solutions from Measure.
Analyze Phase Introduction
3
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Identify Potential Root Causes
Identify Value Added and Non-
Value Added Processes
Identify Cause and Effect
Relationships
Analyze the Data and Process to
Determine Root Causes
ANALYZE
CONTROL
IMPROVE
MEASURE
DEFINE
Why are
customer
hold times
so long?
Machinery
Methods
People
Inconsistent
processes
Too much rework
Systems do not
interact
Too much
review
Use different
technology platforms
Customer information
is not easy to access
Reps are not
well trained
International Products “As-Is” Process Map (Page 1)
R
ea
l
Es
ta
te
Ag
en
t
(R
A)
IP
M
or
tg
ag
e
Sa
le
s
As
so
ci
at
e
(M
SA
)
IP
L
oa
n
Pr
oc
es
so
r
(L
P)
IP
L
oa
n
O
ffi
ce
r
(L
O
)
H
om
e
Lo
an
C
us
to
m
er
Contact RA to
request loan
Mail loan
application to
customer
Complete loan
application
Mail loan
application to
RA
Forward
application to
MSA
Forward
application to
LP
Review
application
Request
additional info
from customer
Gather
additional
information
Mail additional
information to
LP
Go to Step 12
(Next Page)
Review
application
and additional
information
1
2
3 4
5
6
7 8
9 10
11
X = Non-Value Added Step
X
X
X
X
X
X
X
X
X
y = 15.213x + 0.7012
R2 = 0.5149
0
1
2
3
4
5
0.00 0.05 0.10 0.15 0.20 0.25
% of Defective Incoming Applications
# o
f F
in
al
De
te
rm
in
at
io
n
Pa
ck
ag
es
w
ith
E
rro
rs
Analyze Phase Overview
4
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Necessary to identify the “real” root causes of a problem
Ensures accurate focus on the real culprit so we avoid
jumping to the wrong conclusions and solutions
Enables understanding of the magnitude of the problem
Provides understanding of what is causing variation
Why Analyze is So Important
5
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Process Variables
(Xs)
Process
Input
Variables
(Xs)
Outputs
(Ys)
Analyze the Process to Identify the Critical X’s
6
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Definitions
Outputs
Product or service produced or delivered �by the process.
Process Variables (Xs)
Those variables that influence the output and are generally controllable by those who operate the process.
Input Variables (Xs)
Materials and information used by the process to create the outputs. Inputs are often outside the control of the internal operations group.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
For every process there is a dependent variable called Y that we are
attempting to influence. The independent variables which determine
what happens to our Y are called the process X’s. Thus, we can boil
down every process into a simple formula:
The goal of analyze is to understand
the relationship between our various
Xs and our Y, so we can manipulate the
Xs to modify Y as desired, then lock down
the process so that Y remains within the
proper range and is meeting customer
requirements.
The Focus of Process Analysis
Y = f(x1,x2,x3…xn)
7
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Process Variables
(Xs)
Process
Input
Variables
(Xs)
Outputs
(Ys)
Narrow down to the vital few process X’s
that will be useful in indicating the final
process output (measures conformance
to CTQ)
Identify which of these has the
greatest impact or affect on the
output and its performance
against the customer
requirements
The performance of the Y
indicates whether
customer requirements
have been met or not
Analyze Which are the Most Critical Process
Variables
Y = f(x1,x2,x3…xn)
8
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Process Door Data Door
0
2
4
6
8
10
12
In the analyze phase, improvement teams will go through both
the process “door” and the data “door” using both process tools
and data tools to identify and validate root causes.
Analyze Phase Overview
9
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It is recommended to go through both “doors” to make sure that potential causes and opportunities are not overlooked and true root causes are validated by statistical analysis.
Chart1
2 5 6 7 10 8 6 3 2
Sheet1
2 5 6 7 10 8 6 3 2
Sheet1
Sheet2
Sheet3
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Analyze the
Process
Develop
Theories
and
Formulate
Potential
Causes
Analyze the
Data
Understand
Cause and
Effect and
Verify Root
Causes
• Process Value
Analysis
• Lean
Measures
• Value Stream
Mapping
• Error Proofing
• 5s and Waste
• Fishbone
Diagram
• 5 Whys
• Histogram
• Pareto
• Box Plot
• Scatter
Diagram
• Regression
Analyze Tools
Analyze Approach
10
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Analyze Phase Deliverables
Define Measure Analyze Improve Control
Project Charter
Project Management
Project Plan
Process Definition
SIPOC
As-Is Process
Map
Quick Win
Identification
Stakeholder
Management
Stakeholder Map
Stakeholder
Management Plan
Communication
Plan
Voice of Customer
Customer
Identification
VOC Research
Plan
Kano Analysis
CTQ Identification
Root Cause Analysis
Affinity Diagram
Fishbone Diagram
and/or 5 Why’s
Lean Process
Analysis
Lean Tools and
Measures
Graphical Data
Analysis
Histogram
Pareto Chart
Box Plots
Correlation
Analysis
Statistical Data
Analysis
Linear Regression
Multiple
Regression
Root Causes
Identified
Quick Win
Identification
Identify Measures
X/Y Matrix
Data Collection
Operational
Definitions
Measurement
Systems Analysis
(MSA)
Data Collection
Plan
Describe and Display
Data
Histogram
Pareto Chart
Pie Chart
Run Chart
Control Charts
Baseline Performance
Sigma
Performance
Yield
Process
Capability
Quick Win
Identification
Identify and Select
Solutions
Generate Solutions
Benchmarking
Solutions
Prioritization Matrix
Solution Selection
Matrix
To-Be Process Map
Financial Impact of
Solutions
Cost/Benefit Analysis
Risk Planning and
Testing
Failure Modes and
Effects Analysis
(FMEA)
Pilot Plan
Implement Solutions
Multi-Generational
Product Plan (MGPP)
Implementation Plan
Stakeholder
Management
Project Storyboard
Process Control
Control Charts
Process
Monitoring Plan
Dashboard
Response Plan
Project
Documentation
Process
Procedures
Replication
Opportunities
Solution Transfer
Plan
11
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End of Lesson: Analyze Phase Overview
Lean Six Sigma Training
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Analyze – Root Cause Analysis
Lean Six Sigma Training
Root Cause
Analysis
1
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Understand how to use an affinity diagram to identify and
organize potential root causes
Learn how to develop and analyze a cause and effect
diagram
Understand how the “five why’s” technique can guide a
team to identify deeper root causes
By the end of this lesson, you will be able to:
Overview – Objectives – Key Topics
2
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Identifying Potential Causes – Where to Begin?
Add
res
s
Inac
cur
ate
Line
Item T
ota
l
Am
oun
t Ove
rch
arg
e
Oth
ers
42 32 14 9 3
42.0 32.0 14.0 9.0 3.0
42.0 74.0 88.0 97.0 100.0
0
50
100
0
20
40
60
80
100
Defect
Count
Percent
Cum %
Pe
rc
en
t
C
ou
nt
Pareto Chart for Statement Accuracy
9080706050403020100
60
50
40
30
20
10
0
Average Hold Time
#
of
C
al
ls
January Avg. Hold Time Distribution Plot
A good starting point for analysis is to go back to the data that was collected
and graphed during the Measure phase to begin to formulate possible causes
The data display tools that were conducted in Measure that described the
process and indicated information on variation, distribution, and defects can be
helpful in developing theories on potential causes
I-MR or Individuals Control Chart
3
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Identifying Potential Causes – Where to Begin?
Add
res
s
Inac
cur
ate
Line
Item T
ota
l
Am
oun
t Ove
rch
arg
e
Oth
ers
42 32 14 9 3
42.0 32.0 14.0 9.0 3.0
42.0 74.0 88.0 97.0 100.0
0
50
100
0
20
40
60
80
100
Defect
Count
Percent
Cum %
Pe
rc
en
t
C
ou
nt
Pareto Chart for Statement Accuracy
Pareto Chart
The largest defect/problem area(s) indicated on the Pareto point to the
section(s) of the process the team should focus on to formulate
potential causes
A Pareto can help prioritize analysis efforts
4
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Brainstorming
Affinity diagram (previously seen
in define)
Cause and Effect Diagram
(Fishbone)
The “Five Why’s”
There are several tools that a team can
employ to identify potential root causes.
Some of these tools include:
These tools can be used as stand alone
tools or in some cases in conjunction with
one another to drill deeper into potential
causes.
Lack of
staffing
Poor
Training
Missing
info
Cause
Cause
Cause
Cause
Cause
Cause
Cause
Cause
Cause
Cause
Cause
Cause
Identifying Potential Causes
EFFECT
Cause A
Cause D
Cause C
Cause B
5
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Purpose
Brainstorming is a method of generating lots of ideas
quickly
Encourage creativity
Involve everyone
Generate excitement and energy
Separate people from ideas they suggest
Uses in Analyze
Use brainstorming to generate a lot of potential causes
of the problem you defined in Measure
Key question is “why does that happen?”
Identifying Potential Causes – Brainstorming
6
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Brainstorming
1. Generation
2. Clarification
3. Evaluation
Brainstorming
The Generation phase is a free open forum for all
participants to generate ideas.
During the Clarification phase of brainstorming, the team
reviews the list to make sure everyone understands all
the items.
During the Evaluation phase of brainstorming, the team
reviews the list to eliminate duplicates or combine like
items.
Stages of Brainstorming
7
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Rules for Brainstorming:
Clearly state purpose of what you are brainstorming
Each person takes a turn, in sequence, around the group
Present one thought at a time
Do not criticize or discuss any idea
Build on ideas of others
Record ideas and make visible to the whole group (flipchart)
Brainstorming
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Problem: Why do 85% of claims take 37 days or longer to pay?
Lack of
staffing
Poor
Training Missing info
Process
Difficult
Cause
CauseCause
Cause A
Cause B
Cause C
Cause D
Cause E
Cause F
Cause
ResponseCause
ResponseCause
ResponseCause
ResponseCause G
Cause
ResponseCause
ResponseCause H
Cause I
Cause J
Cause K
Cause
ResponseCause L
Cause M
Cause N
Like or
similar
causes
Cause Category
An affinity diagram can help a team organize brainstormed
potential root causes
Good tool to use as pre-cursor to a fishbone diagram or 5 Why’s
Identify and Organize Potential Causes – Affinity
Diagram
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Instructions for Affinity Diagram:
Brainstorm potential causes of problem, write down the
feedback on sticky notes.
Post the stick notes to a white board or flip chart paper.
Once completed, sort issues into 4 – 8 related groups.
Create a summary issue category for each issue group. Make
sure everyone agrees to headings.
Identify and Organize Potential Causes – Affinity
Diagram
10
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Finds major themes out of large number of ideas
Groups items that are naturally related
Identifies one concept that ties each grouping
together
Creative, rather than logical
Good tool to facilitate consensus on major cause
categories
Affinity Diagram Summary
11
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Fishbone diagrams, also known as “cause-and-effect” diagrams, are employed to help teams
brainstorm possible causes of a problem (or effect) and rationally group potential causes
together. This diagram is called a fishbone as it resembles the skeletal structure of a fish once
completed.
Fishbone Diagram
Problem
Statement
Main Category A
Main Category C
Main Category B
Potential
Root Cause
Cause
Cause
Cause
Potential
Root Cause
Potential
Root Cause
Primary
Effect
Potential
Causes
Identify Potential Causes – Fishbone Diagram
12
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A Fishbone Diagram (also known as a Cause and Effect diagram is the starting point for analysis.
Based on the organizations experience, a problem is drilled down to potential causes by asking the question “Why”, thus showing the cause of each effect until the team is satisfied that they have reached the low-level cause (potential root cause). These low-level causes are then validated through data analysis.
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Fishbone diagrams link potential causes to effects
To brainstorm potential root causes to a problem (effect)
To identify reoccurring causes across multiple fishbone categories
To create a visual picture that identifies the link between cause and effect
To provide areas (potential causes) where data can be collected for root cause
validation
Fishbone…
...Get it?
Fishbone Diagram Uses
13
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STEP 1: Draw a box on the far right-hand side of the paper with a horizontal arrow to the
box and write the description of the problem in the box.
It is critical for the team to agree upon the problem under study. In most cases, the
problem will be identical to the definition of Y.
STEP 2: As a team, come to consensus on the 4-5 major cause categories to use on the
fishbone diagram. Write the names of the major cause categories above and below the
horizontal line. Connect them to the “back bone” of the fish.
EFFECT
Cause C Cause A
Cause BCause D
How to Construct a Fishbone Diagram
14
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STEP 3: Brainstorm a list of possible causes that could be driving the problem.
Brainstorming can be done by category or can be done prior to placing the potential
causes on the major bones. It is recommended that the entire list of possible causes be
generated first before attempting to place them on the major category bones. This keeps
the creative flow of ideas.
STEP 4: Place the brainstormed data causes in the appropriate category.
STEP 5: For each cause, drill down into “causes of the causes” by asking repeatedly, “why
does this happen?” Arrange contributing causes on the smaller bones.
STEP 6: Select 2-3 potential root causes from the fishbone diagram to verify with data.
Look for causes that appear repeatedly within or across major bones. Use multi-voting to
narrow down the list of potential causes and come to consensus on 2-3 potential root
causes from the fishbone diagram to drill down on further with additional analysis tools.
STEP 7: Select possible causes to verify with data.
How to Construct a Fishbone Diagram
15
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Machines (equipment)
Methods/procedures (how work is done/tasks and steps)
Materials (components or raw materials)
People (the human element)
Mother Nature (Environment)
Measurement (data collection)
Policies (higher level decision rules)
Typical categories utilized for the major bones of the fishbone are the
following:
Other possible categories are:
Utilize the major steps of the process in place of the major
cause categories listed above.
Note: The key is to select categories that are relevant to the problem that
the team is improving.
Fishbone Diagram Categories
16
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Why are
customer
hold times
so long?
Machinery
Methods
People
Inconsistent
processes
Too much rework
Systems do not
interact
Too much
review
Use different
technology platforms
Customer information
is not easy to access
Reps are not
well trained
Potential
Causes
Call Center Fishbone Diagram Example
17
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The call center team completed their cause and effect analysis utilizing a fishbone diagram and determined 3 potential root causes.
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The Five Why’s technique is a classic approach to root cause analysis of a problem
situation by asking the question “Why?” a number of times. While the name of the
approach contemplates 5 iterations, this is a recommendation only.
True root causes generally are deep, not as simple as first
suspected. In order to get long lasting and far reaching
corrective actions in place, the true root cause must be
found. If problems are identified before enough questions
are addressed, then the problems will diminish at first, but
will often resurface.
The “5 Why’s” technique digs deep into the root of the problem
The Five Why’s technique can be used in conjunction
with a fishbone diagram to identify potential root
causes or can be used as a stand alone tool to
formulate potential root causes.
Identify Potential Causes – The Five Why’s
5 Whys
18
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WHY?
Why do we have an increase in customer complaints?
Because of late orders.
Why don’t the orders leave the store in time?
Because the cooks receive the order 10 minutes after the call was
received, not instantly as they should.
Why do the cooks receive the orders 10 minutes after
the calls were received?
Because the new order entry method takes longer.
Why do we have late orders?
Because the orders don’t leave the restaurant in time.
Why does the new order-entry method take longer?
Because the employees were not properly trained.
WHY?
WHY?
WHY?
WHY?
The Potential Root Cause - Employee Order Entry Training Deficiency
The Five Why’s Example
19
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Helps assign a cause to the
correct sub-category
Guides team to deeper root
causes
Provides link from
effect to cause
Purpose of the Five Why’s
20
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What you learned during this lesson:
How to use an affinity diagram to identify and organize
potential root causes
How to develop and analyze a cause and effect diagram
How to use the “five why’s” technique to guide a team to
identify deeper root causes
Summary of Lesson
21
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
End of Lesson: Analyze – Root Cause Analysis
Lean Six Sigma Training
Root Cause
Analysis
22
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Lean Techniques
Lean Process Analysis and Measures
Analyze – Lean Process Analysis
Lean Six Sigma Training
Lean Process
Analysis
1
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Understand the purpose of process analysis
Understand how to calculate Lean measures of time
Understand how to analyze a process to identify potential
causes and effects
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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Process Door
To analyze and understand
current process flow
To identify process efficiency
problems and bottlenecks
To establish cause and effect
relationships
Detailed Process Maps
Value Added Analysis
Cycle Time Analysis
Process Door
3
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�
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To get results, we need to focus in on the X’s
Focus on the Process
Y
Dependent
Output
Effect
Symptom
Monitor
X1...XN
Independent
Input or Process
Cause
Problem
Control
Response Predictor
x
x
x
xx
x
x
x
4
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Understanding variation requires understanding the relationship between the process response (Y) and the process predictors (Xs).�� Y = f (X1, X2 , . . . , XN )�
The process predictors (Xs) affect (drive) the process outputs (Y).
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Process - Level 1
Step #1
Process - Level 2
Step #1 Step #2
Process - Level 3
Step #3
Step #1 Step #2 Step #3
Step #3
Step #2
Process analysis is
typically focused on
a level 3 process or
below
To highlight
process problems,
break out process
steps in detail
Selecting the Right Level for Process Analysis
5
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Drilling down into a detailed
process map can provide
clues for what is causing our
process to not meet CTQ’s
It can help a team begin to
identify and formulate what
the potential critical X’s are
which might be driving the
problem and process
variation.
Enables a team to identify
process streamlining
opportunities
1.
Activity
Yes
No
Yes
No
2.
Activity
3.
Activity
Process Analysis
6
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Review the Detailed Process Map and Identify “Points of Pain”
Examine steps that experience has shown are problem area or “points of pain”.
Example: Areas of rework, long delay, or errors
Examine steps that have long cycle times
Examine decision points and handoffs where the process moves from one process
customer to the next
X1 Inputs to the process
X2 “Rework” loops – rework points
X3 At the end of major process
steps
X4 Hand-offs between departments
5
m
in
10
m
in
Customer
Claims
Reviewer
Claims
Adjuster
Y
N
X1
X2
X4
X5
X3
X1
Y
?
Y Output (Measure of conformance to CTQ)
Drilling Down in the Process to
Identify Potential X’s
7
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Analysis Techniques – Lean and Six Sigma
Six SigmaLean
Effect
Cause A
Cause D
Cause C
Cause B
Quality and Efficiency
Improvement
Efficiency
Improvement
Combining Lean and Six Sigma is Best in Class
8
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What is Lean?
Lean is utilized for the following purposes:
To reduce or eliminate capacity constraints of the
process
To reduce the lead time of the process
Inputs Step 1 Step 2 Step 3 Step 4
Bottleneck
Outputs
2 Days 10 Days 4 Days 6 DaysInputs Outputs
=22 Days
9
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Lean Definition
The AIM of Lean is to eliminate waste in every area including:
Customer relations
Product design
Supplier networks
And office management
Its GOAL is to incorporate:
Less human effort
Less inventory
Less time to develop products
And less space to become highly responsive to customer demand
while producing top quality services in the most efficient and
economical manner possible
10
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Lean Concepts – Measures of Time
Lead Time: Amount of Time a unit spends in the process
Lead Time (T) = Cycle time (Value Add) and Inactive Time (Non Value Add)
Advantages of Short Lead Times
Customer satisfaction through increased responsiveness
Reduced inventory at constant throughput
Reduced working capital
Increased throughput at constant inventory levels
Increases accuracy
Lead Time
Non Value Add
Value Add
11
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Lean Concepts – Measures of Time
Cycle Time: Total time that elapses from the beginning of a
process step until its completion. It is the time a unit is being
worked on.
12
min
1
min
15
min
Cycle
Time
Start Finish
Cycle
Time
Cycle
Time
Reference: Value Stream Management for the Lean Office: Don Tapping and Tom Shuker
Total Process Cycle Time = 28 minutes
12
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Elements of Cycle Time
Cycle Time
Value
Added
Value
Activities Decisions
Non Value
Added
Transport Inspection Over Processing
Defects /
Rework
Over
Processing
Lead Time can be
reduced by
eliminating Non-
Value Added
Activities
Lead Time can be
reduced by
reducing the cycle
time of value
added activities
13
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Lean Efficiency Metrics:
Measure need to reflect how efficiently you
are utilizing time and resources
Look at what happens to time and how
efficiently we use it.
Here we will learn the Lean Efficiency
Metrics of:
Applying Lean Can Improve Efficiency
Lean Efficiency Metrics
14
- Utilization
- Efficiency
- Quality
- Overall Resource Effectiveness
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What Happens to Time
*Service Time = Standard Service Time multiplied by the Quantity Serviced
15
Total Time = Total time in the shift
Target Time = Total Time less planned breaks & shutdowns
Available Time = Target Time less lost time
Effective Time Serviced**
Service Time*
450 min.
210 min.
120 min.
1
2
3
4
5
480 min.
540 min.
Example:
**Effective Time Serviced = Standard Service Time multiplied by the number of good units
produced.
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Lean Efficiency Metrics
Utilization, the % of time made available for service
Efficiency, how well did we work while we
were working
Quality, the % Good units we serviced out of the total units serviced
ORE (Overall Resource Effectiveness), the % of time that we spent and
got back in good units
16
Utilization = Available Time/Target Time
Efficiency = Service Time/Available Time
Quality = Effective Time Serviced/Service Time
ORE = Effective Time Serviced/Target Time
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Lean Process Analysis Tool – Process Value
Analysis
Non Value-Added Work
• Customer does not recognize value in the step
• Step is not done right the first time
• Step does not change the process
Value-Added Work
• Customer recognizes the value in the step
• Step is done right the first time
• Step changes the process
Examples of Non Value-Added Work
Delay Steps “Re” Steps (ex. Re-Work)
“Checker Checking the Checker”
Approvals
Back Office
Internal Failure
External Failures
Hand-offs
17
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Any steps in the process not meeting value-added criteria is considered non value-added work.
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Lean Analysis – Process Value Analysis
Process Value
Analysis
Process Step 1 2 3 4 5 6 7 8 9 Total % Total
Time (Hours) 100%
Value-Added
Non Value-Added
Delay
Set-up
Inspection
Transporting
Rework
Total
To better understand the process
Review detailed process map (deployment flow chart)
Identify which of the process steps are value-added and which are non value-added
Determine cycle time and identify bottlenecks
Look for errors or inefficiencies that contribute to defects
Value-Added Questions:
1.Change the process?
2.Customer recognizes the value?
3.Done right the first time?
4.Required by law or regulation?
Non Value-Added Examples:
- Waiting - Storing - Counting
- Inspecting - Recording - Obtaining
- Approvals - Reviewing - Copying
- Reworking - Filing - Tracking
18
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Lean Analysis – Process Value Analysis
To easily identify non value-add steps in the process, the following symbols can
be used to label non value-added activity on the process map:
D = Delay
S = Set-up
I = Inspection
T = Transporting
R = Rework
Lean Six Sigma teams can develop and customize symbols as necessary
19
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Lean Process Analysis
Analyzing a process is a valuable tool for identifying process disconnects
such as:
By linking the cycle time (hours/minutes) with the process analysis, we
can begin to develop a complete picture of the need for change and
where this change should occur.
Process gaps
Redundant work
Implicit or unclear requirements
Tricky hand-offs
Conflicting objectives
Common problem areas
20
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What you learned during this section:
Summary of Section
The purpose of process analysis
How to calculate Lean measures of time
How to analyze a process to identify potential causes and
effects
21
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Lean Techniques
Lean Process Analysis and Measures
Analyze – Lean Process Analysis
Lean Six Sigma Training
Lean Process
Analysis
22
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Understand how to identify the process value stream
Understand how to indentify opportunities to implement
error proofing techniques
Determine how to identify waste in your process
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
23
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Lean Analysis Techniques
5s & WasteError ProofingValue Stream
Identify the Process
Value Stream
Implement Process
Checks to Identify
and Fix Incoming /
Outgoing Errors
Clean Up the Work
Environment and
Standardize
Processes
I P O
Inputs Process Outputs
24
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Lean Analysis Techniques – Value Stream
Successful companies are sustainable in the long term because they define
value from the Customer’s perspective
The Flow of Units through a process that produce value to the customer
is a Value Stream
Identifying the Value Streams and what value the Customer is prepared to
pay for in the Value Stream is the first step in creating a better flow.
For each Value Stream, identify the customer’s needs and their demand
25
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What is Value?
Value is defined in terms of specific
products and services having specific
capabilities, offered at specific prices to
specific customers, to be delivered defect-
free at specific times
Value must be viewed in terms of the entire
Customer Experience
Any action or resource expenditure that
does not contribute directly to the goal of
creating value is Waste (Muda) and should
be eliminated to the greatest extent
possible
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Difference Between Waste and Value
In assessing a process, it is important to understand what activities in the
process actually add value to the end result, all other activities are wasteful
CVA (Customer Value-Added - or just VA for Value-Added): an activity
that the customer would be willing to pay for in isolation if they knew it was
being done
– e.g. Implementing functionality to a product/process
BVA (Business Value-Added - non-negotiable waste): an activity that is
required to operate the business but the customer is unwilling to pay for
– e.g. Budget tracking, code documentation
NVA (Non Value-Added): an activity that is not required by the business nor
is the customer willing to pay for
– e.g. Waiting for resource allocation, requirements documents
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The Value Stream
Suppliers Your Company Customer
TOTAL VALUE STREAM
The flow of activity required
to turn raw materials into
finished products
Fit for purpose, for use by
the end customer
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Implement Flow in the Value Stream
Standardize work
Mistake proof processes
Achieve process control
Implement self inspection
Cross train workforce
Reduce set up times
Implement visual controls
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Value Stream Mapping
Value Stream Mapping is a pencil and paper tool that helps you to see
and understand the flow of material and information as an order makes
its way through your transactional process.
Value stream mapping is a way to evaluate the current transactional
process, identify the value-added steps, and envision the improved
(future) transactional process.
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General Icons used in Value Stream Mapping
Dedicated
Process Box
Customer or
Supplier
Mail Delivery Database
(Excel, Access, etc)
Queue Time
Schedule
Box
Schedule
Worker
Shared
Process Box
31
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General Icons used in Value Stream Mapping
Push Arrow
Manual Information
Flow
Exceptions or
Disruptions
Electronic
Information Flow
F I F O
Max. 5 pieces
First In First Out
Sequence Flow
Kaizen Focus
Physical
Material
Pull
Non Value-Added Time
Value-Added Time
hrs/min hrs/min
hrs/min
32
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Value Stream Mapping Example
Customers
Orders processed
within 1 day
Central
Mail Sort
Joe
Sort orders
To depts/5s
Place in out
Box/5s
Sales
Mail Sort
Debbie
Sort orders
By customer
Date stamp/
2s
Place for
CSR/10s
Initiate
Order
CSR 1 -
Susan/Cathy
Initiate Order
/45s Per line
Check Parts
Numbers
CSR 2 -
John/Jane
Check part#
10s per line
Attach
Revisions/ 10s
Assign part#
15s per line
Assign
Delivery Date
CSR 1 -
Susan/Cathy
Assign Delivery
date/30s line
File hard copy
/90s
Verify
Order
CSR 2 -
John/Jane
Review/15s per
line
Sales
Mail Sort
Debbie
Sort/30s
Central
Mail Sort
Joe
Post order/30s
8 Hrs 4 Hrs 4 Hrs 2 Hrs 1 Hr 4 Hrs 4 Hrs 8 Hrs
Schedule
8:00, 2:00
& 3:00
3 x Daily
Mail
Orders
Order
Acknowledgements
1 x Daily
Phone Orders
(Expedited)
Faxed
Orders
.16
480
.28
240
11.25
240 120 60 240 240 480
23.75 9 3.75 5 5
NVA / VA
Minutes
Lead Time
33
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Background to this VSM example: A Lean Six Sigma team chose to focus on the Value Stream Map for orders for its customers.
The main processes were determined and are as follows: Central mail sort – Joe; Sales mail sort – Debbie; Initiate Order – Customer sales rep 1 – Susan/Cathy; Check parts numbers – Customer sales rep 2 – Jane/John; Assign delivery date - Customer sales rep 1 – Susan/Cathy; Verify order - Customer sales rep 2 – Jane/John; Sales mail sort – Debbie; Central mail sort – Joe
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Tips for Value Stream Mapping
DO’s DON’T
• Do begin at the end and work your way
upstream
• Don’t sit at the computer (Get up, walk
around, and collect the required information)
• Do map things as they are, and not the way
they are supposed to be
• Don’t try to map all of your process flows in
one map (Its too confusing)
• Do map the value stream yourself and
refrain from using the committee approach
• Don’t rely on standard times/information that
you did not collect (Get a stopwatch and
collect the data yourself)
• Do use a customer focus approach • Don’t try to map all the parts (Just flow a few of the main raw materials)
• Do walk the process, documenting as you
go, and gathering information
• Don’t‘ be hasty, take your time as this is a
very important exercise
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Lean Analysis Techniques – Error Proofing
Implementing process checks may be necessary to ensure quality and
timely input and outputs. Examples include:
Inspecting inputs from suppliers and not accepting defective inputs
Introducing required information on inputs
Implementing auto correcting techniques
Training employees on the process
Inspecting outputs to ensure quality and timeliness before the customer is
affected
I P O
Inputs Process Outputs
Error Proofing Checks
*Additional information on Error Proofing will be covered in the Improve Phase
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Lean Analysis Techniques – 5s
Cleaning up the work environment will make it
easier for employees to get to needed information.
Sort – Sort through the contents of a work area and
remove unnecessary items.
Set – Set necessary items for easy and efficient
access in demarcated areas.
Shine – Clean everything to ensure that your
workplace and equipment are properly maintained.
Standardize – Create guidelines to keep the area
organized, orderly and clean. You may also
standardize the way you work by determining that
work will flow using the FIFO principle (First-In, First-
Out) – This means that first work in, is the first work
to be processed (first out).
Sustain – Educate and communicate to ensure that
5S standards are followed.
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Lean Analysis Techniques – Waste
WASTE IS...
Any human activity which absorbs resource but creates NO VALUE –
This is the direct translation of “Muda” the Japanese term for waste
Use of resources over and above what is actually required to produce
the product/service as defined by the customer
If the customer does not need it or will not pay for it then it is waste
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Two Major Categories of Waste
1. Obvious Waste
2. Hidden Waste
Obvious waste is easily recognizable
Examples: Undisciplined meetings, excessive paperwork systems,
working ahead of schedule, and doing more than is actually required
Hidden waste refers to work which is necessary under current methods of
operation, but could be eliminated if improved methods were adopted
Examples: Poor office layout, excess overtime, excess labor
We must always strive to minimize the amount of resources utilized to create
products and services. Identification and Elimination of all types of waste
is imperative to succeed.
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8 Types Of Waste
There are 8 basic categories of waste:
MotionTransportation
Over-Processing
Waiting
Over-ProductionDefects / Rework
Inventory
SkillsHey Tim
Woods!!
39
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“WHEN LOOKING FOR WASTE, BE LOOKING FOR “TIMWOODS”
http://images.google.co.za/imgres?imgurl=http://digital-photography-school.com/blog/wp-content/uploads/2007/08/motion-blur-1 &imgrefurl=http://digital-photography-school.com/blog/how-to-capture-motion-blur-in-photography/&h=350&w=350&sz=103&hl=en&start=10&tbnid=3e6F_dkgCMqI-M:&tbnh=120&tbnw=120&prev=/images?q=motion&gbv=2&hl=en
http://images.google.co.za/imgres?imgurl=http://digital-photography-school.com/blog/wp-content/uploads/2007/08/motion-blur-1 &imgrefurl=http://digital-photography-school.com/blog/how-to-capture-motion-blur-in-photography/&h=350&w=350&sz=103&hl=en&start=10&tbnid=3e6F_dkgCMqI-M:&tbnh=120&tbnw=120&prev=/images?q=motion&gbv=2&hl=en
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8 Types of Waste – Definitions
TYPES OF WASTE DEFINITION
TRANSPORTATION
Back and forth work - handling documents more than once,
unnecessary moving or handling of work between
departments
INVENTORY Any amount of work greater than single-piece flow. Excessive work in process (WIP), calls on hold, people waiting in line.
MOTION Movement of people that adds no value (searching for paperwork, quotes, supplies etc)
WAITING
When work is sent from one department to another then waits
for the next processing to occur (queues, time when no value
is added to the product/service)
OVER-PRODUCTION Producing more than the next operation can handle.
OVER-PROCESSING
Over-processing, unnecessary processing, or procedures
(work carried out on the product/service which adds no value)
often caused by bureaucracy
DEFECTS / REWORK
Ineffective work practices that result in poor data collection
and poor data entry – result in data integrity issues; wrong
customer details
SKILLS Not listening to employees ideas or not asking them to use their brain and help solve problems
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The idea of 8 wastes is useful because it allows a company to categorize problems and then focus attention in the appropriate areas once they have been identified. There are many tools and techniques in the Lean tool box which can be applied to many areas of service in order to tackle any one of these wastes.
Reference: http://www.swmas.co.uk/Lean_Tools/The_7_Wastes.php
http://images.google.co.za/imgres?imgurl=http://digital-photography-school.com/blog/wp-content/uploads/2007/08/motion-blur-1 &imgrefurl=http://digital-photography-school.com/blog/how-to-capture-motion-blur-in-photography/&h=350&w=350&sz=103&hl=en&start=10&tbnid=3e6F_dkgCMqI-M:&tbnh=120&tbnw=120&prev=/images?q=motion&gbv=2&hl=en
http://images.google.co.za/imgres?imgurl=http://digital-photography-school.com/blog/wp-content/uploads/2007/08/motion-blur-1 &imgrefurl=http://digital-photography-school.com/blog/how-to-capture-motion-blur-in-photography/&h=350&w=350&sz=103&hl=en&start=10&tbnid=3e6F_dkgCMqI-M:&tbnh=120&tbnw=120&prev=/images?q=motion&gbv=2&hl=en
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What you learned during this section:
Summary of Section
How to identify the process value stream
How to indentify opportunities to implement error proofing
techniques
How to identify waste in your process
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
End of Lesson: Analyze – Lean Process Analysis
Lean Six Sigma Training
Lean Process
Analysis
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Analyzing Data Graphically
Stratification
Data Analysis Overview
Analyze – Graphical Data Analysis
Lean Six Sigma Training
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To understand the drivers of variation in
the process
To validate cause and effect relationships
To understand the root cause of
differences between inputs, process, and
outputs
Stratification
Graphical Analysis
Hypothesis Testing
Regression
Experimentation
Data Door
0
2
4
6
8
10
12
Data Door
2
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Chart1
2 5 6 7 10 8 6 3 2
Sheet1
2 5 6 7 10 8 6 3 2
Sheet1
Sheet2
Sheet3
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0
2
4
6
8
10
12
0
2
4
6
8
10
12
The data door for Analyze functions more as a toolbox of tools and
techniques than a step by step linear process. Depending on the problem
that is being addressed and what the suspected causes are, the set of tools
and the order of tools will vary according to the specific needs of each
individual project.
Depending on the problem being addressed, some teams will pass through
all doors and some teams may only go through 1 door to identify root
causes.
Graphical Data
Analysis
Statistical Data
Analysis
Within the data door there are
many different “doors” a team
can pass through to analyze for
root causes.
Data Door
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Chart1
2 5 6 7 10 8 6 3 2
Sheet1
2 5 6 7 10 8 6 3 2
Sheet1
Sheet2
Sheet3
Chart1
2 5 6 7 10 8 6 3 2
Sheet1
2 5 6 7 10 8 6 3 2
Sheet1
Sheet2
Sheet3
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Analyzing Data Graphically
Stratification
Data Analysis Overview
Analyze – Graphical Data Analysis
Lean Six Sigma Training
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Know what stratification is and how it’s used in analysis
Understand the importance of stratification
Know common stratification factors
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
5
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DATA
Process
Subset
1
Subset
2
Subset
3
A data analysis technique by which
data is sorted into various
categories by specific factors
Divides data into several
subgroups with common themes
that may be the cause of observed
variation
Enables suspicious patterns to
surface
Unveils differences in processes
Allows for more accurate focus
and prioritization of analysis efforts
Stratification – What it is and What it’s Used for
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-Region
-City
-Office site
Where
-Business Unit
-Department
-Individual
Who
-Year
-Month
-Week
-Day
When
-Defect type
-Problem type
-Complaint type
Type of Category
ExampleFactor
Common Stratification Factors
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Stratification is critical to getting down to the deeper root cause level. However stratification should be balanced with the time it takes to analyze each factor.
It is recommended that a team narrows their list of stratification factors down to 3-4 key categories of possible causes of variation.
The most efficient way to stratify data is to identify what stratification factors you want to analyze prior to collecting data in the measure phase. Otherwise it may be necessary to collect more data.
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Example of “delivery time” data stratified by “day of week”
Monday Tuesday Wednesday Thursday Friday
D
el
iv
er
y
Ti
m
e
Since Tuesdays are consistently later than other days - the
next step would be to look into Tuesday and analyze why
Examples of Stratification
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Example of trend data on complaints broken out by product type
Total Complaints
Month
Pr
ob
le
m
s
2000
2200
2400
2600
2800
3000
3200
1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23 24
Month
Product B Complaints
Pr
ob
le
m
s
300
500
700
900
1100
1300
1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23
Product A Complaints
Pr
ob
le
m
s
300
500
700
900
1100
1300
1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23
Month
Product C Complaints
Month
Pr
ob
le
m
s
300
500
700
900
1100
1300
1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23 24
Examples of Stratification
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What you learned during this section:
What stratification is and how it’s used in analysis
The importance of stratification
Common stratification factors
Summary of Section
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Analyzing Data Graphically
Stratification
Data Analysis Overview
Analyze – Graphical Data Analysis
Lean Six Sigma Training
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Know how, why and when to use pareto charts, stratified
histograms, box plots, and scatter diagrams (correlation
analysis).
Understand what type of data is required to use various
analysis tools.
Learn how to interpret pareto charts, histograms, box plots,
and scatter diagrams.
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
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You most likely identified many potential causes through your fishbone
diagram and process value analysis
The potential cause is really a theory that two factors—a cause and an
effect—are related
You need data to verify whether the cause-and-effect relationship truly
exists
You can analyze historical data to test that theory, or collect new data
It’s possible the data you collected in the Measure phase can be
analyzed in new ways to answer your questions about cause-effect
relationships
Use other existing data only if you have confidence in its reliability and
accuracy (presuming it is appropriate for your needs)
If historical or existing data will not answer the questions you are now
trying to answer or if the existing data is unreliable, then you must
collect new data
Analyzing Data
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Remember we are trying to identify which X’s (input/process variables) have the greatest
impact on the process Y (output).
There are a variety of graphical tools that can be used to examine the relationship
between X’s and Y’s, the key is selecting the right tool.
Selecting the right tool depends on the type of data for both X and Y.
Some of the analysis tools have already been presented in the Measure phase, in this
section we will summarize new tools that have not yet been fully presented.
9080706050403020100
60
50
40
30
20
10
0
Average Hold Time
#
of
C
al
ls
January Avg. Hold Time Distribution Plot
Potential Root Potential Root
CausesCauses
Potential Root Potential Root
CausesCauses
Tools for Analyzing Data Graphically
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A Pareto chart is a graphical tool that assists in segmenting a large problem into
multiple components and identifying which components are the most important
Pareto charts rely on the Pareto Principle, postulated in the 19th century by Vilfredo
Pareto, who found that 80 percent of Italy’s wealth was held by 20 percent of the Italian
population.
This 80/20 Rule applied to Lean Six Sigma says that 80% of the process defects are
caused by 20% of the problems.
Pareto Chart
A B C D
50 10 6 5
70.4 14.1 8.5 7.0
70.4 84.5 93.0 100.0
0
10
20
30
40
50
60
70
0
20
40
60
80
100
Defect
Count
Percent
Cum %
Pe
rc
en
t
C
ou
nt
Defects
Pareto charts are one of the
most widely used Lean Six
Sigma tools
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To analyze categorical or discrete data
Aids in understanding the pattern of occurrence for a
problem
To identify the relative impact of various parts of a
problem (quantifying the problem)
To identify the biggest contributors to a problem
Prioritizes where to focus analysis and improvement
efforts
Helps prevent “shifting the problem” where the
solution removes some causes, but worsens others
Why Use a Pareto Chart
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You can use a Pareto Chart when:
The problem under study can be broken down into
categories
You want to identify the “vital few” categories—focus
your improvement effort
When to Use a Pareto Chart
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Understanding How to Read a Pareto
Add
res
s
Inac
cura
te
Line
I te
m Tota
l
Am
oun
t Ove
rcha
rge
Oth
ers
0
50
100
0
20
40
60
80
100
Defect
Pe
rc
en
t
Co
un
t
Pareto Chart for Statement Accuracy
Height of vertical
axis represents
all occurrences
Bar height
arranged in
descending order
with tallest bar on
left, shows
relative
importance
“Other”
category
is always
last
Cumulative
count line
Potential
X’s
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Pareto Charts are used to graphically summarize and display the relative importance of the differences between groups of data. Further, it is used to identify and prioritize problems or causes of problems.
What Questions Does The Pareto Chart Answer:
- What are the largest issues facing our team or business?
- What 20% of sources are causing 80% of the problems (80/20 Rule)?
- Where should we focus our efforts to achieve the greatest improvements?
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1. Decide which problem you want to know more about
2. Choose the causes or problems that will be monitored, compared, and rank ordered
3. Choose the time period for study (pareto charts show variation for a period of time)
Tip: Select a time period that is long enough to represent the situation, consider
volume and variety within the data.
4. Gather the appropriate data (either historical or new)
5. Compare the relative frequency of each problem category (see example below)
6. List the problem categories (sorted by frequency, in descending order) on the horizontal line
and frequencies on the vertical line
7. Draw the cumulative percentage line showing the portion of the total that each problem
category represents
Tip: Always include the source of data and time period covered on the chart.
8. Interpret the results
(This tool can and should be done using statistical software)
Problem Category Frequency
Printing problems 15
Erroneous configuration 30
Filing problems 10
Network problems 6
How to Construct a Pareto Chart
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Indicates Pareto Principle holds true:
one or a few categories account for the
majority of the problem
Focus analysis/improvement efforts
on top one or two bars
If the Pareto looks like this…
Indicates Pareto Principle does not
hold (bars are all close to equal in
height)
Look for other ways to categorize data
or stratify data
Interpretation:
Response:
Interpretation:
Response:
How to Interpret and Respond to a Pareto Chart
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Check the Pareto chart to evaluate whether the Pareto principle holds true. A few of the categories should account for the majority of the problem.
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Data has been correctly distributed
among categories, with the “other”
category consisting only of issues that
have a relatively low frequency of
occurrence
Continue with analysis efforts on
top one or two bars
If the Pareto looks like this…
“Other” category has categories
included in it that should be broken out
into other separate categories
Evaluate whether “other” items should
be redistributed to existing categories
or to newly created categories
Interpretation:
“Other” bar
is relatively
small
“Other” bar is
relatively tall
Response:
Interpretation:
Response:
How to Interpret and Respond to a Pareto Chart
21
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If Pareto principle holds true, the largest bar on the pareto should be
further broken into sub-causes to identify potential X’s.
Defects
A
0
5000
10000
15000
20000
25000
D
ef
ec
ts
Defect Type
B C D E
0
2500
5000
7500
10000
12500
Am
ou
nt
M
on
Day of Week
For Defect A
Tu
es
W
ed
Th
ur
s Fr
iTeam focus for further analysis:
defects on Monday
Pareto Chart Drill Down
22
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3020100
150
100
50
0
Location 1
Fr
eq
ue
nc
y
Days
CTQ = 15 Days
Av erage = 12.29 Day s
5040302010
100
50
0
Location 3
Fr
eq
ue
nc
y CTQ = 15 Days
Days
Av erage = 30.02 Day s
3020100
100
50
0
Days
Fr
eq
ue
nc
y
Location 2
CTQ = 15 Days Av erage = 15.88 Day s
Remember this? Going back to the histograms we learned in previous lessons…..
In Analyze a Stratified Histogram enables you to compare distributions by providing one
graph for each group, which aids in formulating potential causes.
0 10 20 30 40 50
0
100
200
Days
Fr
eq
ue
nc
y
15 Days
CTQ =
Average = 19.39 Days
N = 4266
Example of Stratified Histogram
23
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0 10 20 30 40 50
0
100
200
Days
Fr
eq
ue
nc
y
15 Days
CTQ =
Average = 19.39 Days
N = 4266
3020100
150
100
50
0
Location 1
Fr
eq
ue
nc
y
Days
CTQ = 15 Days
Av erage = 12.29 Day s
5040302010
100
50
0
Location 3
Fr
eq
ue
nc
y CTQ = 15 Days
Days
Av erage = 30.02 Day s
3020100
100
50
0
Days
Fr
eq
ue
nc
y
Location 2
CTQ = 15 Days Av erage = 15.88 Day s
Sample
Size
Guideline:
n > 50 for
each
group
Team’s Theory: The total variation in how long it takes to pay claims at all locations combined
is caused by variation in training and procedures at different locations.
What conclusions would the team have drawn from the results of the stratified histograms
below?
Example of Stratified Histogram
24
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When to Use:
To analyze results when one variable has continuous data and another has
attribute or discrete data
Why use it:
To compare distributions and measures of central tendency
To look for patterns
How to create:
Gather appropriate continuous data for each of the attribute types or
categories you want to investigate
Create a histogram for each category (use the same numeric scale and plot
size for each individual histogram so you can easily compare distributions)
Sample size for each group should be greater than 50 data points
Stratified Histograms
25
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A box plot is a tool used to draw comparisons between different
distributions based on quartiles
Box plots take key statistics from the data and summarize them in
a box format
Box plots of shift A and shift B
BA
1020
1010
1000
990
(means are indicated by solid circles)
*
Box Plots
26
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Why Use it:
To compare several distributions against each other
To identify variability and centering of two or more distributions
When To Use It:
When you want to identify differences in distributions between
groups
When you want to identify variability and centering in a variable
output (y) vs. an attribute input (x)
An excellent tool to provide visibility to outliers
Box Plots – Why and When to use them
27
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Box Plots measure variation (spread) by dividing data into four equal groups to see how far
apart the extreme groups are. It is based off of the Inter-quartile range (IQR).
The IQR is the distance between the first quartile (Q1) and the third quartile (Q3). The IQR
= Q3 – Q1.
A box plot indicates:
Where the median of the dataset lies (represented by the middle line)
A view of the size of each quartile of the data set
Easy identification of data points that might be deemed extreme values or outliers (here an outlier is
defined as a point that is more than 1.5 IQR from an end of the box.)
The dispersion or spread of the data (the whiskers)
Fourth Quartile
First Quartile
Second Quartile Third Quartile
Median
Outlier
Whisker
Mean
Understanding How to Read a Box Plot
28
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1. Gather appropriate continuous data for each of the attribute types you want
to investigate.
2. Draw a box between the first and third quartiles of data, this represents 50%
of the data values.
3. Draw horizontal lines from the middle of the sides of the box to the minimum
and maximum values. (These represent the whiskers).
4. Draw a vertical line inside the box to represent the median value.
5. Indicate any outliers with a dot or an asterisk.
6. Sample size for each subgroup should not have less than 25 data points.
7. Box plots can be constructed vertically or horizontally.
(Of course this can and should be done using statistical software)
How to Construct a Box Plot
29
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*
80
70
60
50
40
30
20
10
0
Phone Queue A Phone Queue B
Box Plot of Hold Time of Queue A and Queue B
H
ol
d
Ti
m
e
Stratified Box Plot Example
30
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Symmetrical
(based off of median)
If the median is close to the
center of the box, the
distribution of the data will
be symmetrical.
Negatively Skewed
(based off of median)
If the median is in the upper
half of the box, the
distribution of the data
values will be negatively
skewed.
Positively Skewed
(based off of median)
If the median is in the lower
half of the box, the
distribution of the data
values will be positively
skewed.
Symmetrical
(based off of whisker)
If the whiskers are
approximately the same
length, the distribution of the
data values will be
symmetrical.
Positively Skewed
(based off of whisker)
If the upper whisker is longer
than the lower whisker then
the distribution of the data
values will be positively
skewed.
Negatively Skewed
(based off of whisker)
If the lower whisker is longer
than the upper whisker then
the distribution of the data
values will be negatively
skewed.
How to Interpret a Box Plot
31
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A Scatter Diagram assists in studying the relationship between 2 variables
Output
Variable
(Y)
Process Variable (X)
A Scatter Diagram is a graph that helps you visualize the relationship
between two variables. It can be used to check whether one variable is
related to another
Scatter Diagram or Correlation Analysis
32
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One tool that can be used for identifying the relationship between input and process variables (X’s) and the process output (Y) is a scatter diagram.
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Tests and verifies cause and effect
relationship between input/process
variable (X’s) and output variable (Ys)
Analyzes the strength of relationship or
correlation between potential cause and
effect
Provides indication of a root cause
Scatter Diagram – Why Use it?
33
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To discover whether two variables are related
To find out if changes in one variable are associated with changes in
the other
To test for a cause and effect relationship (but finding a relationship
does not always imply causation)
Scatter Diagram – When to Use it
34
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Each data point
represents a pair of
measurements (ex. 10
defects for 5 min
process time)
Cause on the
X axis
High
# Defects
(Y)
Low
Low
Speed (X)
High
The pattern
Effect on
the Y axis
Both axis need
to be roughly
equal in length,
so the plot is
square
The pattern
indicates how
the variables are
related
Understanding How to Read a Scatter Diagram
35
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Both axes need to be about the same length so the plot is square. If you make one axis is longer or shorter than the other, the pattern formed by the scatter can be distorted.
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1. Gather appropriate data
2. Determine which variable will be on the horizontal axis (X) and
which will be on the vertical axis (Y)
3. Find the minimum and maximum value of X and Y
4. Set up the axes (ensure they are the same length)
5. Plot all the X & Y pairs on the graph (need 30 -100 pairs of data)
(This can and should be done using statistical software)
How to Construct a Scatter Diagram
36
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High
# Defects
(Y)
Low
Low
Speed (X)
High
Scatter Diagram Example
37
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In this scatter diagram, there appears to be a positive relationship between speed of the process and the number of process defects.
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Scatter Diagram Example: Printers Installed –
Printer Calls
Printer Calls
Pr
in
te
rs
In
st
al
le
d
420400380360340320
475
450
425
400
375
350
Scatterplot of Printers Installed vs Printer Calls
38
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This scatter diagram indicates that there appears to be a positive correlation between increased printer installation and printer calls to the Helpdesk.
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Common Mistakes Constructing Scatter Diagrams
Mixing up the “X” and the “Y” variables
Data is not paired correctly
Improper scaling – scatter diagram not square
Incorrect increment spacing between tick
marks
39
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Mixing Up The “X” And The “Y” Variables
In analyzing variables for potential cause and effect, the process variable as the predictor is on the “X” axis and the output or process performance variable as the response is on the “Y” axis.
Data Is Not Paired Correctly
Scatter Diagrams require that the “X” and “Y” variables be paired. It means that there has to be a logical correspondence between the data to appropriately study the correlation. For example, if one examines the relationship between length of time to approve loans and number of telephone calls to the applicant, the paired data would be based on a specific loan application. Taking a sample of loan applications, it will be necessary to know the length of the time to approve and the number of telephone calls for each loan.
Improper Scaling – Scatter Diagram Not Square
To ensure proper interpretation, it is necessary to use the fullest possible extent of both the “X” and “Y” axis to cover the range of the data collected. Improper scaling can result in the pattern being obscured.
Incorrect Increment Spacing Between Tick Marks
The increment, or the space width between tick marks on the Scatter Diagram, should be a value that makes it easy to plot the data and easy to read. A general guideline is to have between 5 to 15 increments of equal width along the full length of each axis.
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No Correlation
Possible Positive
Correlation
Strong Positive Correlation
Other PatternPossible Negative
Correlation
Strong Negative Correlation
Look For Patterns
Interpreting a Scatter Diagram
40
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In examining Scatter Diagrams, it is helpful to look for patterns. First, is there a pattern or correlation between the X and Y variables?
Second, the direction of the pattern, either positive or negative. For example, a strong positive correlation indicates an increase in the process variable (X) and increases the process performance (Y).�
Examples of positive correlation include:�- Hours worked and amount of production
– Age and height of school children
– Advertising costs and sales receipts
If a relationship is such that as one quantity increases the other quantity decreases, we call the relationship a negative correlation. ��Examples of negative correlation include:�- Time spent designing a piece of equipment and the time spent maintaining it
– Hours spent on training new employees and hours spent correcting errors
– Speed of a vehicle and time required to complete a trip
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Common patterns in the data
Range of the predictor variable (X’s)
Irregularities in the data pattern (investigate
outliers)
Look for:
Interpretation of a Scatter Diagram
41
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Correlation Between Butterflies and Hurricanes
It is important to understand that correlation, no matter how strong, does not imply causation. As tempting as
it may be for us to leap to causation, we must understand that two variables may be strongly correlated with
no causal link whatsoever.
Just because the correlation between number of butterflies and number of hurricanes in a given year is
very strong does not mean that hurricanes are caused by butterflies flapping their wings.
50
80
70
60
50
80
70
60
100 200 300
H
ur
ric
an
es
Butterflies (Billions)
Be Careful – Correlation Does Not Imply Causation
42
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Summary of Data Tools
Tool Purpose
Box Plot Used to identify variability and centering of two or more groups
of data
Control Chart
(Measure Phase)
Used to help understand variation and to control and improve a
process
Histogram
(Measure Phase)
Used to determine shape, center and range of numeric data,
also used to prepare Pareto charts
Pareto Chart Used to identify and prioritize problems or causes of problems
Pie Chart Used to depict percentages of total in a circular diagram
Run Chart
(Measure Phase)
Type of chart used to display data related to a process variable
in sequence over time to identify changes
Scatter Diagram Used to confirm relationship between two variables
43
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What you learned during this section:
How, why and when to use Pareto charts, stratified
histograms, box plots, and scatter diagrams (correlation
analysis).
What type of data is required to use various analysis tools.
How to Interpret pareto charts, histograms, box plots, and
scatter diagrams.
Summary of Section
44
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
End of Lesson: Analyze – Graphical Data Analysis
Lean Six Sigma Training
45
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Hypothesis Testing Tools
Hypothesis Testing Overview
Statistical Data Analysis Overview
Analyze – Statistical Data Analysis
Lean Six Sigma Training
1
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At this point, the vital few potential root causes have been identified.
Now we need to validate the root causes with 95% confidence in the
results. Statistical data enables us to do this.
Allows us to draw meaningful conclusions from data samples
So we can have a greater level of certainty in our identified vital few X’s
Enables us to pinpoint the root cause so we can select the best fit
solutions to improve our process problems
Helps to make the case for change with solid data to back up our plan
for change
Why do we Need to Use Statistical Data?
2
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Statistical Problem
Understand the process
• Only two issues can exist:
• Is the mean not centered properly
• Is the variability (spread) to large?
2
Practical Solution
• Once root causes are validated,
implement focused solutions
43 Statistical Solution
• Understand what drives the process
output
• Measure the influence of the vital few
X’s on the mean and the variability
1 Practical Problem
Problem Statement
• Magnitude
• Impact to business
Translate the Practical Problem into a Statistical Problem. Solve the
Statistical Problem and translate into practical terms and implement a
solution.
Statistical Thought Process
3
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Just like graphical analysis tools, there are several statistical tools to help you
identify which X’s (input/process variables) affect the process output (Y).
Again, in order to select the right tool to examine the relationship between X’s
and Y’s it depends on the type of data you are testing for both X and Y.
The tools this course will cover are:
Simple Linear &
Multiple Regression
5040302010 0
65
55
45
35
25
15
5
Cycle Time Sending Information
To
ta
l C
yc
le
T
im
e
Correlation Plot of Cycle Time
Statistical Analysis Tools
4
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Hypothesis Testing Tools
Hypothesis Testing Overview
Statistical Data Analysis Overview
Analyze – Statistical Data Analysis
Lean Six Sigma Training
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Understand what a hypothesis test is
Know how to properly state a null and alternative
hypothesis
Understand the significance of a p-value
Know when to reject the null hypothesis
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
6
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A hypothesis test is used to detect
differences between two or more groups
that may be important to the business
Because of variation, no two things
will be exactly alike
The question is whether differences
you see between samples, groups,
processes, etc., are due to random,
common cause variation, or if there
is a real difference.
Hypothesis testing answers this
question for us.
Are A and B
really different?
Statistically
speaking?
10
20
30
40
A B
What is a Hypothesis Test?
7
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To determine whether
making a change to an input
or process (X) significantly
changes the output (Y) of
the overall process.
Statistically determine if
there are differences
between two or more
process outputs.
Bottom Line: To determine
which process factors are
the cause of the variation in
our output that is causing
defects.
Y = f(X1, X2, X3…, Xn)
mmm….is it X1 or
X2 that’s causing
the problem?
Why Use a Hypothesis Test?
8
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Hypothesis testing consists of a set of tools that can tell us how certain we can be
in the observations and formulated causes we made from our process analysis
and graphical analysis.
There are different hypothesis testing methods to use for each situation
Type of Data
What You
Can Compare Example
Continuous
Proportions Is the % of on-time application completions
the same for group 1 as for group 2
Discrete
Averages
Variation
Shapes or
Distributions
Is the average productivity the same
for multiple regions?
Do results from the department using
the improved process have less
variation than the results from the
department using the old process?
How does the cycle time
distribution compare for various
processes?
Hypothesis Testing
9
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The goal of a Hypothesis test is to either reject or not reject
the Null Hypothesis.
The way it works:
Test the null hypothesis
H0: no difference between groups
Against the alternative hypothesis (represents the
theory you are trying test or prove)
Ha: groups are different
…to determine if we can reject the null hypothesis or not
Overview of Hypothesis
10
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There is a difference in the
waiting time across the
different regions
There is no difference in
the waiting time across the
different regions
Process waiting times
across different regions
There is a difference in the
variation of the dimension
from the different machines
There is no difference in
the variation of the
dimension from the
different machines
The variation in a product
dimension from different
machines
There is a difference in
customer satisfaction levels
between product A and
Product B
There is no difference in
customer satisfaction
levels between product A
and Product B
Customer satisfaction levels
for different products
There is a difference in
average wait times between
call centers
There is no difference in
average wait times
between call centers
Average call answer times
between call centers
The Alternative
Hypothesis
The Null HypothesisWhat you are looking at
Your aim is to disprove or reject the null hypothesis
Examples of Determining the Correct Null
Hypothesis
11
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Example: What is the p-value?
The p-value is the probability that the observed difference between the
means is caused by sampling variation, OR
The p-value is the probability that these two samples came from the
same population.
P-values range from 0.0 to 1.0 (0% chance to 100% chance)
By convention, usually treat P < 0.05 as indicative that the difference is
significant.
How do I Interpret the p-value?
If p < 0.05, we declare a significant difference exists and therefore we
should reject the null hypothesis. (In other terms, if P < 0.05, reject the H0
and conclude the Ha)
When performing a Hypothesis test, an output of the test will be a calculated p-
value. Identifying the p-value will tell us whether a significant difference exists.
How do we Know When to Reject the Null
Hypothesis?
12
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P-values are probabilities for values of interest
P-value =
Tail area
Area beyond value-of-interest
Probability of being at the value-of-interest or beyond
A small P-value (0 to 0.05) means:
The probability is small that the value-of-interest did, indeed,
come from that distribution. . . . It is likely to have come from
some other distribution
A practical definition of the p-value is: The p-value is your confidence in
the null hypothesis, so when it’s low you reject the null.
Value of interest
0 0.05 p 1.0
Understanding P-values
13
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“If p falls below, H0 must go.”
Simple Method to Remember How to Interpret the
Hypothesis
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Hypothesis Terminology:
So…..If the “null hypothesis” (H0) is that there is no difference
between the two groups.
Then…..If we are able to reject the “null hypothesis” then we will
be able to say that the two groups are statistically different with
95% confidence.
If p < 0.05, we declare a significant difference exists.
The p-value is the probability that the observed difference between
the means is caused by sampling variation, OR
The p-value is the probability that these two samples came from
the same population.
Hypothesis Overview Summary
15
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What you learned during this section:
What a hypothesis test is
How to properly state a null and alternative hypothesis
The significance of a p-value
When it is appropriate to reject the null hypothesis
Summary of Section
16
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Hypothesis Testing Tools
Hypothesis Testing Overview
Statistical Data Analysis Overview
Analyze – Statistical Data Analysis
Lean Six Sigma Training
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Know how to perform linear regression analysis
Understand how to perform multiple regression
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
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Note: This is not an exhaustive list and in this course we will only
introduce Regression Analysis
Hypothesis testing consists of a set of tools that can tell us how certain we
can be in the observations and formulated causes we made from our
process analysis and graphical analysis.
There are different hypothesis testing methods to use for each situation
Overview of Hypothesis Testing Tools
Hypothesis Test Purpose
Regression Identify if two variables are correlated
t-test Compare two group averages
ANOVA (Analysis Of Variance) Compare two or more group
averages
Chi-Square Compare two or more group
proportions
Design of Experiments (DOE) Identify the cause and effect
relationships between Xs and a Y
19
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Hypothesis tests rely on the following assumptions:
Data is normally distributed (If continuous data).
When comparing groups from different populations, we assume samples are
independent samples, were randomly selected, and representative of the
population.
When comparing groups from different populations, we assume variances are
not dramatically different.
When comparing groups from different processes, each process is stable (no
special cause variation exists in the process.)
CAUTION: Bear in mind that many processes are not stable, hypothesis testing
should not be applied until the process is in control.
For the purposes of learning and discussing hypothesis testing in this
course, we will assume the above conditions have been met.
Hypothesis Testing Assumptions
20
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Regression
Takes correlation one step further by
developing a mathematical model that
represents the relationship between the
X (input) and Y (output).
Y
X
Correlation
is used to determine the strength of a
linear relationship between two
continuous process variables. If two
variables have a strong relationship,
they are said to be correlated.
R= +0.82
Y
X
Correlation and Regression Analysis – What is it?
21
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Correlation
To validate root causes by quantifying the magnitude
of the relationship between variables.
This relationship of variables may be between:
• A potential root cause (X) and the problem or
output (Y).
• Two potential causes, inputs, or factors (X1 and
X2 ).
Regression
To define the mathematical relationship between 2 or
more variables so we can:
• Make predictions of process performance, Y,
based on a given value of the process variable,
X.
• Improve process performance (Y) based on
controlling or manipulating process conditions (X)
to generate desired results.
Y
X
R= +0.82
Y
X
Correlation and Regression Analysis – Why use it?
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Correlation and regression are intended to be used in conjunction with one another.
Conducting regression analysis involves several steps and uses multiple tools.
We can break down regression analysis into a 3 step process:
Step 1:
Graph the
data
Step 2:
Measure
strength of
correlation
Step 3:
Run
regression
Y
X
Using a
scatter
diagram
Y
X
By developing
fitted line plot
R= +0.82
By obtaining
correlation
coefficient
The Process of Regression Analysis Overview
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X Variable
Is an input or process variable (sometimes
called a predictor) which we are hoping to be
able to manipulate to influence our project Y.
If not, it can be used to predict Y
Y Variable
Is an output variable or a
measure of process
performance which we are
hoping to positively affect by
managing or manipulating X. If
not, at least it can be predicted
from X
The scatter diagram indicates
how a change in an input or
process (X) can affect a change
in output (Y) based on the
strength of the relationship.
Scatter Diagram – Identifying Possible Correlations
Speed (X)
# Defects
(Y)
Scatter Diagram
24
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A correlation coefficient is used to measure the degree of linear association (correlation)
between continuous sets of data.
The correlation coefficient is referred to as “r.”
The possible range of “r” is: +1 to -1
r = +1 Perfect positive relationship
r = 0 No linear relationship
r = -1 Perfect negative relationship
(the higher the absolute value of r, the stronger the correlation)
The correlation coefficient (r):
Reflects the degree to which the data points are tightly clustered
Is sometimes referred to as the Pearson Coefficient
Once scatter diagrams have been used to look for correlations, a correlation coefficient can be
used to measure the strength of any correlations found.
Correlation analysis places a quantifiable magnitude on the graphical scatter diagram relationship.
Correlation Coefficient
25
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Examples of scatter diagrams and their associated correlation
coefficients:
Indicates a strong negative
correlation, so the r value is very
high. The r is a negative number
to represent the downhill slope.
Interpretation: the more call
center reps available, the faster
the speed of answer.
Indicates a strong positive
correlation, so the r value is very
high. The r is a positive number
to represent the upward slope.
Interpretation: the more call
center reps, the longer the talk
time.
No. of call center reps
Sp
ee
d
of
a
ns
w
er
r = - 0.98
100 110
10
120
30
50
Indicates no correlation exists,
so the r value is very low.
Interpretation: there is no
relationship between the number
of call center reps, and the claims
payment cycle time.
No. of call center reps
r = +0.06
Pa
ym
en
t c
yc
le
ti
m
e
120110100
30
Ta
lk
T
im
e
No. of call center reps
r = +0.96
120110100
10
50
Interpreting Correlation Coefficient
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Before you can use the correlation coefficient the
statistical significance of the correlation coefficient
should be assessed.
Because of the random nature of data, it is possible
for a scatter diagram to suggest a correlation
between variables when in reality, none exists.
There is a greater risk of this occurring if a
scatter diagram is based on a small sample size
To solve for this issue, look at the correlation
coefficient’s corresponding p-value
Just like hypothesis testing, a p-value is
generated for a correlation coefficient using
statistical software.
If the p-value < 0.05, you can be 95% confident
that a correlation exists. r = - 0.98
p-value 0.000
y-
ef
fe
ct
r = - 0.98
Interpreting Correlation Coefficient
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Linear regression develops a mathematical model to represent the data in a
scatter diagram
It defines the mathematical relationship between two variables
It generates a fitted line that quantifies the relationship between X and Y
Enables us to predict the value of Y given a certain value of X
The line or regression equation is represented
as:
y = b0 + b1 “multiplied by” x1, where
y = output
x1 = an input
b1 = the slope of the line (rise over run, or
change in Y per unit increase in X)
b0 = the predicted value of y when x1 = 0
Linear Regression Analysis
X1
Y
Residuals
Fitted Line
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Residuals are the difference between the fitted line (in the model) and the actual data point. Residuals can be analyzed to validate if the fitted line models the shape of the relationship intended.
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Regression analysis has its own measure for the
strength of the relationship. This measure is the
square of the correlation coefficient, and is simply
referred to as “r-squared” (R-sq).
r-squared is the measure of how much variation in the
process output is accounted for by the model. Another
way to look at it is, it’s the measure of how well the
regression line describes the data. (Therefore, the
closer to 100% the better).
Since it is a squared value, it can range from 0 to
positive 1.
It is defined as the proportion of the variability in
Y (the output) that is explained by X (the input
and/or process).
The regression process creates a line that
best resembles the relationship between the
process or input (X) and output (Y).
Y
X
Linear Regression – How it Works
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There are two values that are generated from regression analysis that serve as
indicators for how to interpret regression results:
P-value
R-sq value
Interpreting P-value:
Null Hypothesis
H0: slope = 0 (or no difference in Y when X changes)
Alternative Hypothesis
Ha: slope = 0 (or Y changes as X changes)
Interpreting R-sq value:
Represents how much of the variation in the process
output is accounted for by the model so the closer to
100% the more confident we can be in our results.
Linear Regression Interpretation
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Theory:
A Lean Six Sigma team wanted to see if the
number of call center representatives had
an affect on the speed of answer.
Steps Used:
They took their data and first developed a
scatter diagram and obtained their r- value.
Next, they ran regression analysis in a
statistical software program to create the
fitted line.
Finally they obtained, the R-sq value and
the P value
The results:
R-sq = 95.4%
P-value = 0.0
# of Call Center Representatives
Sp
ee
d
of
A
ns
w
er
X1
Y
Interpretation:
The number of call center reps has a large affect on the
speed of answer (95.4% of the variation in speed of
answer is explained by the number of call center reps.)
This is a critical X (since p < 0.05, we rejected H0, and
determined Y changes as X changes)
Linear Regression Interpretation Example
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0.055
0.045
0.035
0.025
0.015
0.005
Speed of Answer
Ab
an
do
n
R
at
e
10 20 30
The range of data ends here
Do not attempt to make predictions beyond the range of your data!
Regression Tips and Traps
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As tempting as it might be to extrapolate beyond the range of data, don’t attempt to do this because it’s risky. Predictions using regression equations are more reliable for X’s that are within the range of the data set collected.
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Y= f (X1, X2, X3, etc.)
Multiple regression is the same concept as linear regression, but it is an equation to
show the mathematical relationship between several X’s and one Y.
Multiple regression is used to sift through many X’s (input and process variables) at the
same time to find the most critical variables that affect the Y (the output variable). This
enables us to select the best improvement solution.
Multiple Regression equation:
Y= b0 + b1 X1 + b2 X2 + b3 X3 + …etc.
Where…
Y = output variable
XS = predictor variables (input or process variables)
b0 = intercept (predicted value of Y when each X = 0)
b1 = slope of the linear relationship between Y and X1,
or the change in Y per unit increase in X1 holding
all other XS constant
b2 = slope for X2
b3 = slope for X3
etc….
Multiple Regression
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Scenario:
A Lean Six Sigma team working in a
call center focused on improving
speed of answer wanted to see if
the number of customer service
calls and the number of inquiries on
active accounts were correlated to
the speed of answer.
For this scenario predictor
and response variables were:
Y = Speed of Answer
X1 = number of calls
X2 = number of inquiries
Speed of Answer
(seconds)
Number of Calls
(per hour)
Number of
Inquiries
(per hour)
21 503 45
24 654 52
30 709 22
16 598 16
Data Sheet:
Multiple Regression Example
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Results:
R-Sq = 94.3%
P-value for number of calls = 0.0
P-value for number of inquiries = 0.785
Interpretation:
The R-sq value indicates that the input variables in the regression account for
94.3% of the variation in speed of answer, however…
Since the p-value of number of inquiries is greater than 0.05 it does not
influence the speed of answer
Since the p-value for number of calls is less than 0.05, it does influence the
speed of answer and therefore is a critical X.
Conclusion:
It must be the number of calls that is creating all the variation in speed of answer.
The number of calls
is causing the
variation in the
speed of answer
Multiple Regression Example Continued
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Determine the type of test suited to your data and
question
Arrange the data appropriately in the statistical
software program of your choice.
Perform the statistical test
Obtain the p-value from statistical software output;
declare a statistically significant difference if the p <
0.05
How to Perform a Hypothesis Test Summary
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What you learned during this section:
How to perform linear regression analysis
How to perform multiple regression
Summary of Section
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
End of Lesson: Analyze – Statistical Data Analysis
Lean Six Sigma Training
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
Analyze – Identify Root Causes
Lean Six Sigma Training
Identify
Root Causes
Validated Root Causes
1
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Validated Root Causes
The Process of Identifying Root Causes
Pareto
Regression
Stratification Process Value Analysis
Fishbone
5 Whys
Potential Root Causes
Value Stream
Map
Root Cause Analysis
Lean Process Analysis
Graphical Data Analysis
Statistical Data Analysis
2
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The process of identifying root causes is similar to a funnel. It begins at a macro level with a multitude of possible root causes. Through root cause analysis, lean process analysis, graphical data analysis and statistical data analysis, the list of potential root causes gets narrowed down to the vital few process and input variables that affect CTQ process output performance.
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Root Cause Analysis
Graphical Data Analysis
Statistical Data Analysis
Potential causes identified (fishbone, 5 whys)
Statistical tests conducted to validate differences in data groups
Testing method utilized is appropriate for the data
P-value determined
Root causes identified to target for improvement
Data graphically analyzed to identify the Xs that account for variation in the process
Data sample is random and independent
Data stratifications conducted to identify variation
Analyze Completion Checklist
Lean Process Analysis
Process value analysis and Lean measures
Value Stream
Waste identification
3
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Identify potential root
causes
Statistical Data
Analysis
X1
Y
Validate root causes
through statistical
tools
Investigate potential
root causes through
graphical tools
Graphical Data
Analysis
10
20
30
40
A B
Next Steps……
Move to Improve Phase
to Identify Solutions
Identify Root Cause Summary
Root Cause Analysis &
Lean Process Analysis
Cause A
Cause D
Cause C
Cause B
Effect
4
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Once the Lean Six Sigma improvement team has analyzed which of the process variables (X’s) have the have the strongest relationship to the output measures (Y), they can confidently select the best solution.
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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve
End of Lesson: Analyze – Identify Root Causes
Lean Six Sigma Training
Identify
Root Causes
Validated Root Causes
5
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Improve Phase
Lean Six Sigma Training
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Improve Phase Overview
Lean Six Sigma Training
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Once root causes are understood, the
team can begin to develop solutions for
the process. Generating both obvious and
creative solutions requires innovation,
technology, and discipline.
Improve Phase Introduction
3
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ANALYZE
CONTROL
IMPROVE
MEASURE
DEFINE
Generate Solutions
Prioritize and Document Improved
Process
Document Solution Impacts and
Cost/Benefits
Pilot Solutions and Identify Potential
Problem Analysis
Develop Implementation Plan
Best Practices
Root Causes
Project Goals
“Discoveries”
During Analysis
Benchmark
Ideas
Ideas from Other
Projects
Brainstorming
Performance
Targets
Generate
Solution
Ideas
Generate
Solution
Ideas
Implement Solution
ID
1
2
3
4
5
6
7
8
9
Install new hardware
Revalidate System
Install new software
Train
Processing Staff
Update documentation
Develop Training Plan
Train Staff
Test
Task Name 5/31 6/7 6/14 6/21
MAY JUNE
6/28
Jen, Kris, Sue
Conroy
Conroy
Gwen
Team, TBD
Team, TBD
Improve Phase Overview
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Identify and
Select
Solutions
Financial
Impact of
Solutions
Risk
Planning
and Testing
Implement
Solution
Benchmarking
Brainstorming
Solution
Selection
Matrix
Deployment
Flowchart
Quantify
Benefits
Quantify
Costs
CBA
Improve Tools
FMEA
Error
Proofing
Pilot
Planning
MGPP
Change
Management
Strategy
Implementation
Plan
Improve Approach
5
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Improve Phase Deliverables
Define Measure Analyze Improve Control
Project Charter
Project Management
Project Plan
Process Definition
SIPOC
As-Is Process
Map
Quick Win
Identification
Stakeholder
Management
Stakeholder Map
Stakeholder
Management Plan
Communication
Plan
Voice of Customer
Customer
Identification
VOC Research
Plan
Kano Analysis
CTQ Identification
Root Cause Analysis
Affinity Diagram
Fishbone Diagram
and/or 5 Why’s
Lean Process
Analysis
Lean Tools and
Measures
Graphical Data
Analysis
Histogram
Pareto Chart
Box Plots
Correlation
Analysis
Statistical Data
Analysis
Linear Regression
Multiple
Regression
Root Causes
Identified
Quick Win
Identification
Identify Measures
X/Y Matrix
Data Collection
Operational
Definitions
Measurement
Systems Analysis
(MSA)
Data Collection
Plan
Describe and Display
Data
Histogram
Pareto Chart
Pie Chart
Run Chart
Control Charts
Baseline Performance
Sigma
Performance
Yield
Process
Capability
Quick Win
Identification
Identify and Select
Solutions
Generate Solutions
Benchmarking
Solutions
Prioritization Matrix
Solution Selection
Matrix
To-Be Process Map
Financial Impact of
Solutions
Cost/Benefit Analysis
Risk Planning and
Testing
Failure Modes and
Effects Analysis
(FMEA)
Pilot Plan
Implement Solutions
Multi-Generational
Product Plan (MGPP)
Implementation Plan
Stakeholder
Management
Project Storyboard
Process Control
Control Charts
Process
Monitoring Plan
Dashboard
Response Plan
Project
Documentation
Process
Procedures
Replication
Opportunities
Solution Transfer
Plan
6
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End of Lesson: Improve Phase Overview
Lean Six Sigma Training
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Document/Design Solution
Select Solutions
Identify Potential Solutions
Improve – Identify and Select Solutions
Lean Sigma Training
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Understand how to conduct a gap analysis
Understand the difference between an incremental
improvement strategy vs. an exponential improvement
strategy
Understand various methods and techniques to generate
solution ideas
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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ANALYZE→ Identify the vital few root causes
IMPROVE→ Generate solution ideas using both logical and creative thinking
Look outside of the box for
innovative solution ideas
Obvious remedies to root
causes of problem
Project goals and targets
Benchmarking
+
Review process and data
analysis results
Select “best fit” solution
Filter ideas
against criteria
Process to Identify and Select Improvement
Solutions
3
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Things to consider before generating solution ideas:
Assess gap between current performance and required
performance
Determine if incremental or exponential process
improvement is required to meet project goals
Key Considerations to Generating & Developing
Solutions
4
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To comprehend the gap between current and desired performance, a Gap
Analysis can be utilized to provide a structured approach to understanding this
difference.
After the root causes (critical Xs) have been identified, the
project team can evaluate each root cause and assess what
level of improvement the team needs for each critical X. The
larger the gap, the more effort and risk associated with
crossing it.
An example of a gap analysis is below (some teams may
only have one root cause):
Gap Analysis Defines Delta Between Current & Desired Performance
Root Cause Current Performance Desired Performance Gap
Key Considerations to Generating & Developing
Solutions
5
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Incremental
Improvement
Is the gap
large?
Customer
Requirements
Process
Capability
YesNo
Design for Six Sigma
(DFSS or DMADV)
DMAIC
Example: Modify the existing
process
Exponential
Improvement
Example: Completely re-design
the existing process and/or build a
new process
Define
Measure
Analyze
Improve
Control
Define
Measure
Analyze
Design
Verify
Improvement Strategies
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Process entirely broken: the existing process is unable to meet
many CTQs, too many successive DMAIC projects required
Technology development: new technology solution enables all
customer requirements to be met at lower cost or gain a
competitive advantage
Process has reached entitlement
When to Utilize Design for Six Sigma Methodology
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Best Practices
Root Causes
Project Goals
“Discoveries”
During Analysis
Benchmark
Ideas
Ideas from Other
Projects
Brainstorming
Performance
Targets
Generate
Solution
Ideas
Improve: Sources of Solution Ideas
8
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Generating solution ideas should be based on all of the analysis and conclusions the team has developed through the project.
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These techniques allow a team to think
outside of the box which can lead a team
to build upon or discover a new idea
which can lead to a better, more
improved solution than the obvious or
conventional solution.
Brainstorming
Benchmarking
The following techniques enable creative thinking beyond the
obvious solutions.
Creative Solution Generation Techniques
9
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Traditional Brainstorming Review
1. Generation
2. Clarification
3. Evaluation
Brainstorming
The Generation phase is a free open forum for all
participants to generate solution ideas.
During the Clarification phase of brainstorming, the team
reviews the list to make sure everyone understands all the
items.
During the Evaluation phase of brainstorming, the team
reviews the list to eliminate duplicates or combine like items.
Stages of Brainstorming
In preparation for brainstorming, the team should begin by reviewing the “as is”
process, the gap analysis and the verified root causes.
10
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Rules for Brainstorming:
Clearly state the purpose of what you are brainstorming
Each person takes a turn, in sequence, around the group
Present one thought at a time
Do not criticize or discuss any idea
Build on ideas of others
Record ideas and make visible to the whole group (flipchart)
Traditional Brainstorming Review
11
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dopt-
Other Companies’
Best Practices
A
dapt-
Best Practices to our
Business Processes
A
dvance-
Our Business
Performance
A
So We Can . . .
What is Benchmarking?
Benchmarking
A Continuous, systematic approach to
improving processes by identifying,
evaluating and implementing World-Class
processes, practices, products and
services of highly successful
organizations.
12
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Benchmarking is an improvement methodology that an organization can use to assist in identifying solutions. By identifying best practices in other organizations and companies and determining the reasons for success, an organization can integrate valuable knowledge into its processes, practices, products and services.
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…And not reinvent the wheel?
Benchmarking
Benchmarking promotes the discovery of best practices and
processes of successful external organizations or internal teams,
units or segments.
The Benchmarking methodology focuses on adapting and building
on these innovations to improve them even further.
Benchmarking is an excellent tool for identifying potential
solutions during the improve phase.
How do you Develop Innovative Solution Ideas for
Breakthrough Change?
13
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A continuous process
A process of investigation that
provides valuable information
A process of learning from others; a
pragmatic search for ideas
A time consuming, labor-intensive
process requiring discipline
A viable tool that provides useful
information for improving virtually any
business process
Benchmarking Is . . .
A one-time event
A process of investigation that provides
simple answers
Copying; imitating
Quick and easy
A buzzword, a fad
Benchmarking Isn’t . . .
Benchmarking Defined
14
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Internal Benchmarking
Work processes are compared between departments, divisions or
internal company segments
Competitive Benchmarking
Measuring process performance against peers or competitors
Functional/Industry Benchmarking
Comparing similar process performance of the same function at
companies outside your industry
Generic Process/Best In Class Benchmarking
Internal processes are compared against truly innovative practices
and world class performance levels, regardless of industry
Types of Benchmarking
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Determining who to benchmark is a critical step. Research and analysis to decide which organizations have best in class processes have to be carefully conducted. This is particularly important when benchmarking a competitor. Collection of data is best performed by site visits to benchmarking partners. Telephone and written surveys are often satisfactory for preliminary screening or supplemental data. Site visits and surveys should be carefully planned to ensure good data is obtained.
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Benchmarking Evaluation Example
XXFunctional leaders
XXGeneric processes
XDirect competitors
XXInternal operations
Innovative PracticesData Collection EaseRelevanceBenchmarking Operation
To determine which type of Benchmarking might be the best approach for your
team to generate solution ideas, consider the relevance to your process, the
level of effort required to collect the benchmarking information, and the level of
creativity.
Evaluation by Type of Benchmarking
16
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To help determine who are the best benchmarking partners to focus efforts on, above is an example of a matrix of criteria used to flush out which type of benchmarking might provide the most best practice information with the least effort and time.
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Thinking “out-of-the-box” produces the best results when selecting
benchmark partners and analyzing their processes
Company: Remington Rifle Co.
Issue: Surveys revealed Remington’s customers’
prefer shiny rifle shells
Benchmark Maybelline Cosmetics
Partner:
Results: Remington adopted Maybelline’s practice
of making shiny tubes of lipstick to
improve the shininess of their rifle shells
Company: Southwest Airlines
Issue: Southwest was interested in reducing
aircraft maintenance and turnaround time
Benchmark Indy 500 Pit Crews
Partner:
Results: Southwest adopted some of the crews’
ideas to develop an action plan and
incorporate these Best Practices into
it’s own organization
Southwest Airlines Indy 500
Maybelline CosmeticsRemington Rifle Company
Innovative Benchmarking Examples
(Different Process and Industry)
17
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To contribute to efficient, effective and ethical benchmarking, individuals agree
for themselves and their organization to abide by the following principles:
Keep it legal
Be willing to give what you get
Respect confidentiality
Keep information internal
Use benchmarking contacts
Don’t refer without permission
Be prepared at initial contact
Benchmarking Code of Conduct
18
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What you learned during this section:
How to conduct a gap analysis
The difference between an incremental improvement
strategy vs. an exponential improvement strategy
Various methods and techniques to generate solution ideas
Summary of Section
19
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Document/Design Solution
Select Solutions
Identify Potential Solutions
Improve – Identify and Select Solutions
Lean Six Sigma Training
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Understand how to organize solutions
Know how to use various methods and tools to prioritize
solutions
Know how to use various methods and tools to select
solutions
Understand how to select solutions in the event that no
clear solution option emerges
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
21
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After solution ideas have been generated, duplicates need to be
removed and they need to be organized into like categories.
One of the best tools for categorizing the solutions is a familiar tool - the
Affinity Diagram.
Solution
1
Solution
2
Solution
3
Affinity Diagram
Organize Solutions
22
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Develop the Evaluation Criteria
Remove Show Stoppers
Consider Organization Fit
Determine Sigma Impact
Evaluate Time Impact
Evaluate Cost Benefit Impact
Evaluate Other Impacts
Narrow the List
Narrowing List Select Solutions
Solution Evaluation and Selection Process
Po
te
nt
ia
l S
ol
ut
io
ns
23
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Once solution ideas have been generated, the next step is to select the best solutions. Developing evaluation criteria helps identify those solutions that meet specific requirements. These requirements should be based on the needs of the customers and the organization.
Eliminating ideas that do not meet certain criteria will save time and energy discussing unacceptable solutions.
Criteria examples:
- Show Stoppers contain minimum requirements that must be met for a solution to be considered.
- Solutions may not fit into the current organization structure and should be eliminated or considered for later implementation.
- Any solution selected should have a favorable impact to the process Sigma.
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Payoff Matrix
In this example, solution C and
solution D would be eliminated
from the list because of the
relatively high level of effort and
low benefit.
Estimated
Financial
Benefit
Implementation
Level of Effort
Solution A
Solution B
Solution C
L
H
L
Solution D
H
Narrow the List By Removing the Low Payoff
Solutions
24
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The Payoff Matrix is an effective tool used to narrow down the list of solutions by eliminating those solutions that are low “pay-offs” for the organization in terms of estimated cost benefit. Although we have not yet completed a detailed cost benefit analysis, at this stage of the project, the team should have enough information from quantifying the cost associated with the problem during the Define phase and a sense of the level of effort to be able to estimate the Level of Effort and Financial Benefit to use this tool.
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A tool used to narrow and prioritize those solutions that have the
greatest impact to key criteria. Example of criteria include:
Root cause identified in the Analyze Phase
that will be impacted by the solution
The description of the solution that was
generated from the brainstorming session
Customer / CTQ Impact (H, M, L)
The impact the solution will have on the CTQ,
measured by High Impact, Medium Impact, or
Low Impact
The costs required to implement the solution
suggested, measured by High, Medium, or
Low
The solution represents a quick win and can
be implemented immediately
Technology is required to implement the
solution
Root Cause Addressed
Solution Description
Implementation Cost (H,M,L)
Quick Win (Yes, No)
Technology Required (Yes, No)
Solution Prioritization Matrix
Solution
Prioritization
Matrix
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Choosing the right solutions can be challenging. The Solution Prioritization Matrix is another tool that will help drill down to a list of the best potential solutions. By comparing each idea against the criteria listed above, the project team can narrow down the list of solutions based on key requirements and not on gut feeling or popularity.
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Criteria
Develop 1 platform
for systems to
interact
Increase approval
levels of reps
4 2 1
Imp costs Quick-Win Tech. Rqd.CTQ Impact
SUM
3Weight
Standardize training
materials/program
Standardize &
document resolution
process
9
3
9
3
36
12
36
12
1
9
3
9
3
27
9
27
1
9
3
3
2
18
6
6
1
9
9
9
1
9
9
9
42
66
60
54
Weight
(based on
rank ordering
Score against
criteria 1(L),
3(M), 9(H)
Score multiplied
against weight
To quantitatively select the final “best fit” solutions for your organization based on
criteria, a Solution Selection Matrix can be used. See example and explanation below:
Note: the implementation costs for this solution are high, but we give
it a 1 instead of a 9 because increased cost is a negative.
The sum of
the multiplied
scores
Selected
Solution
Selected
Solution
Highest score
solutions are
selected
Solution Selection Matrix
Solution
Selection Matrix
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Steps to Developing Solution Selection Matrix:
1. Record a list of final solutions
2. Create a list of criteria
This criteria should include the common criteria (root cause addressed,
customer impact, implementation effort, etc. as seen on the previous page)
as well as criteria that is specific and most important to the organization.
3. Weight the criteria
To identify the appropriate weighting of each criterion the individual criterion
should be either rank ordered or weighted on a scale of 1-10. Criterion that
are the most important are weighted a 10; lower weighted criterion are
weighted a 2 or 1.
One method of determining the weight of each criterion is to have the team
multi-vote .
4. Evaluate the list of solutions against the weighted criteria using a 1 for low, 3 for
medium and 9 for high.
5. Tally the scores for each solution, discuss, and select those solutions that had the
highest score.
Developing a Solution Selection Matrix
27
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On rare occasions, the choice may be obvious given your
knowledge of the process and problem
More often, you need to carefully weigh pros and cons utilizing tools
such as, the pay-off matrix, solution prioritization matrix, and
solution selection matrix
If the solution selection matrix does not result in a clear choice—and
perhaps even if it does—you can get more information about a
solution by…
Modeling or simulating the solutions
Doing trial implementations (small scale tests)
Observation (find a person or organization who is doing
something similar and observe)
Selecting Solutions
28
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Since a solution selection decision is typically high impact, emotionally charged, and
sometimes offers a wide diversity of opinion, consensus is generally the best
decision making method to use when using a fall back solution selection method like
decision making is required.
Gathers upon every
team members
opinion
Increased
participation and
buy-in
Provides a structured
process to arrive at
decision
Ensure you have
allocated enough time
Take thorough notes
The Benefits of Using
Consensus
Tips to Using Consensus
Decision Making
Balance Power
Listen carefully and
check for understanding
Decision Making Method – Consensus
29
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To aid in the selection of solutions and aid in evaluating solutions against criteria,
often more information must be gathered on each solution idea. Below are some
effective and recommended methods:
Visit an organization that uses the particular solution option you are evaluating to see how
effective it is.
Hopefully, you have already done this through benchmarking during the solution
generation phase. If not, make a site visit to benchmark the solution at this stage.
Making a site visit to an organization who has a particular solution option can also
provide valuable information about lessons learned through implementation and
estimated costs to implement.
If evaluating potential solutions that involve a level of automation or technology:
Ask for a demonstration.
Compare different vendors (if applicable).
Visit an organization that uses this particular solution.
Prepare a list of questions.
Obtaining More Information to Aid in Selecting
Solutions
30
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Consensus
Delegate with Constraints
Gather Input from Others
(influencers) and Decide
Gather Input from the
Team and Decide
Decide and Announce
High Level of
Involvement/Time
Required to Make a
Decision
Medium Level of
Involvement/Time
Required to Make a
Decision
Low Level of
Involvement/Time
Required to Make a
Decision
What to Do if No Clear Solution Option Emerges
31
If the criteria-based comparison tools, and methods to gather additional information
on solutions as discussed on previous pages still does not result in a clear solution
choice or if many solutions are equally scored, a fallback method is using decision
making methods. See below….
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What you learned during this section:
How to organize solutions
How to use various methods and tools to prioritize solutions
How to use various methods and tools to select solutions
How to select solutions in the event that no clear solution
option emerges
Summary of Section
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Document/Design Solution
Select Solutions
Identify Potential Solutions
Improve – Identify and Select Solutions
Lean Six Sigma Training
33
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Understand the importance of documenting the new
process
Understand tools to document the new solution
Understand how to document the new process solution by
creating a “to-be” process map
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
34
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Documenting the newly selected solution is critical to understanding costs
and risks, training associates, and achieving desired improvement results.
The tools for documenting the improved process solution design can include
the following:
Process maps/flowcharts
Functional requirements document (for solutions that involve
technology)
Drawings
Documenting the New “To-Be” Process Solution
35
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Once the solution has been selected we need to go back to the
baseline “as-is” process and identify and document how the process will
change as a result of implementing the new solution.
The new “to-be” process map will also be a valuable tool for training the
organization before implementation.
S I P O C
Suppliers Inputs Process Outputs Customers
Process Map
Documenting the New “To-Be” Process
36
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It is helpful in documenting the new “to-be” process, to go back to the SIPOC first and identify what will change. In addition to the process steps, often suppliers and inputs will change as a result of the selected solution.
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Deployment flowchart (“swim lanes”)
Processing Administration Adjusters Payables
Since both “who” conducts each process step and “how” work gets
accomplished in a process changes after the improvement solution is
applied, the best process mapping tool to document these changes is a
Deployment flowchart.
Deployment flowcharts clearly indicate both who handles each process
step and how it gets done.
Documenting the New “To-Be” Process
37
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Requirement documents for IT solutions can include items such as:
Business requirements
Data requirements
Functional requirements of product or service
Historic data specs
Production data specs
Functionality of product or service
User access/security
If the solutions selected involves technology or automation, a detailed
requirements and design document would also need to be developed with
the support of an IT SME (information technology subject matter expert)
that is assigned by the organization to be on the implementation team.
Documenting Solution which Involves Technology
38
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What you learned during this section:
Understand the importance of documenting the new
process solution
Understand tools to document the new solution
Understand how to document the new process solution by
creating a “to-be” process map
Summary of Section
39
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
End of Lesson: Improve – Identify and Select Solutions
Lean Six Sigma Training
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Cost/Benefit Analysis
Costs of the “As-Is” Process
Improve – Financial Impact of Solutions
Lean Six Sigma Training
1
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Understand the costs of poor quality and defects
Understand how to quantify the costs and inefficiencies
of the “As-Is” process
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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For many companies, performance depends on meeting shareholder expectations.
Given limited resources, an executive is unlikely to support quality for quality’s sake---
the business environment requires getting the most “bang for the buck” by increasing
revenue and reducing cost.
The focus of Lean Six Sigma projects is to reduce defects and inefficiency to increase
earnings and value for the shareholder.
Overview of the Financial Side of Poor Quality and
Defects
generating
gross revenue
which
minus costs
results in
profits
some of which
is reinvested
the remainder
reported as
earnings
thus meeting
financial
expectations
Organizations produce products/services
to the marketplace, thereby (which gets reduced by poor quality)
(increased by
inefficiency)
3
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To identify the costs of the “As-Is” process, we need to identify the labor, material,
and equipment costs to operate the process, plus the cost effect of the non value-
added activities in the process.
To do this assessment, go back to the process map analysis conducted earlier in
the project where the percentage of value-added activity vs. non value-added
activity was identified and calculate the cost of the non value-added activities.
Method to Quantify the Cost of the “As-Is” Process
Examples of Cost Categories
Material Costs:
Postage
Paper
Ink
Forms
Equipment Costs:
Computers
Phones
Office Furniture
Office Space
Labor Costs:
Salary
Benefits
4
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Collect data on how many times the problem/defect occurs per unit
of time (example: 12 occurrences/week)
Work with process owners and finance to collect data on the cost per
occurrence in terms of labor, materials and equipment costs.
(example, $200 per occurrence)
Identify time involved (example: 52 weeks)
Calculate total annual cost by multiplying the above three factors
(example: 12 X $200 X52 = $124,800)
Quantifying the Cost of the “As-Is” Process
5
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The Cost of Conformance
The money and time spent to ensure valid customer requirements are being met.
Includes money and time spent on both prevention (finding mistakes before they happen) and inspection
(finding defects after they happen but before they touch the customer).
The Cost of Lost Opportunity
The profit impact of lost revenues that result from failure to meet customer requirements . If a company
loses business because it has a reputation for poor quality, it loses revenue. The profit the company
could have made on that revenue is the cost of lost opportunity.
The Cost of Non-conformance
The money spent to fix products and services that do not meet valid customer requirements.
This cost includes money spent on warranties, credits, and other customer concessions paid as a result
of poor product and service performance.
These are considered external failures and are the worst type of cost because they touch the customer.
Remember non-value added activities, such as, rework and defects cost money, this is considered the cost
of poor quality. The cost of poor quality generally breaks down into three major categories:
Considerations for Capturing the Costs of Non-
Value Added Activities
6
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Once the team has collected data around the costs associated with the
inefficiencies of the “As-Is” process, and has selected the solution to
target these inefficiencies, the team now has enough information to
perform a Cost/Benefit Analysis.
Selected Solution“As Is” Costs
Cost/Benefit Analysis
Inputs to the Cost/Benefit Analysis
7
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What you learned during this section:
The costs of poor quality and defects (poor effectiveness)
How to quantify the costs and inefficiencies of the “As-Is”
process (poor efficiency)
Summary of Section
8
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Cost/Benefit Analysis
Costs of the “As-Is” Process
Improve – Financial Impact of Solutions
Lean Six Sigma Training
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Understand the elements of capturing the financial impact
of the selected solutions
Understand why performing a cost/benefit analysis on
selected solutions is necessary
Know how to develop a cost/benefit analysis
Understand examples of various cost/benefit analysis
formats
Understand key considerations and lessons learned around
capturing financial benefits of improvement projects
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
10
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An analysis which quantifies the benefits of your
project and compares them to the cost of pursuing
the project.
A document which communicates in financial terms
why the organization should implement your
selected improvement solution(s).
A cost/benefit analysis includes calculations and
financial measurements that fit your particular
project and are important to the organization. These
vary from project to project and might include
measurements such as:
Return on investment
Return on equity
Return on capital
Cash flow
Net present value
Pay back period
What is a Cost/Benefit Analysis?
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It identifies the criteria against which we can measure the
project success. Remember the key reason for conducting
Lean Six Sigma improvement projects is to have a positive
financial impact and increase value to the shareholder.
Before implementing the solution that has been selected
we need to ensure that it meets the financial requirements
of the business.
Allows us to determine if implementing improvement
solutions will have clear financial payback.
The business case for implementing the selected solution
might not be apparent to those stakeholders outside of the
project team.
Data that indicates implementing the selected solution will
result in a positive impact to the bottom line by creating
buy-in and mobilize the organization’s commitment and
support for the project.
Why Perform a Cost/Benefit Analysis?
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Ties process defects to dollar impact
Translates “Quality Lingo” into common financial terms
Eliminates perception of Quality improvements as being “pie in the sky”
Enables Lean Six Sigma projects to compete effectively with other business
initiatives for human and financial resources
Makes Lean Six Sigma project savings auditable
Increases credibility and support of Lean Six Sigma philosophy with business
and finance leaders
Greatly enhances project success
The Benefits of Quantifying Project Costs and
Benefits
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Benefits generally fall into 2 categories:
Hard Benefits
Soft Benefits
Cost categories:
Direct Project Costs
Indirect Project/Process Costs
Benefits
Costs
When performing a cost/benefit analysis we are evaluating
whether the benefits to be gained with the new improved
process outweigh the costs of implementing the improvement
solution, and to what degree.
It is important to understand that every organization has its own guidelines and
methodology to justify cost/benefit analysis. It is critical to work with the organization’s
Quality/Financial Analyst to gain agreement and approval on the Cost/Benefit
methodology used.
Developing a Cost/Benefit Analysis
Solutions
Benefits and
Implications
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Hard Benefits - Improvements that result in real and measurable cost
or asset reductions.
Examples of Hard Benefits:
– Incremental revenues
– Cost reductions such as fewer headcount
Soft Benefits - Improvements that do not immediately reduce cost or
assets but provide benefits through improved process efficiency,
employee productivity, improved customer satisfaction, improved
competitiveness, etc.
Examples of Soft Benefits:
– Avoidance of lost sales
– Cost avoidance such as the need to hire 5 instead of 10*
*Note: in some organizations cost avoidance is considered a hard dollar benefit
The Two Categories of Project Benefits ($$)
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Additional Examples of Hard Benefits (typically tracked by the company accounting system).
Reduction in unit cost of operations
Reduction in unit cost of production
Reduction in transaction cost
Reduction in overhead cost
Reduction in transportation cost
Reduction in manpower
Increased throughput, resulting in increased sales or revenue
Additional Examples of Soft Benefits (less tangible, typically not tracked by accounting system).
Reduced cycle time
Improved on-time delivery
Increased flexibility
Faster response
Reduced effort
Increased availability
Fewer defects
Higher scores on customer satisfaction scores
Additional Examples of Project Benefits ($$)
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Direct Project Costs – Costs that can be tied directly to a particular process
or project. These include incremental costs (costs which are only being
incurred as a result of deciding to implement the selected Improvement
solution). Incremental costs are the costs above the current cost to operate
the process.
Example of Incremental Costs:
̶ If recommended improvement solution was to implement a new
computer system to improve the processing of loans, the purchase
cost of the computer would be an incremental cost of the project.
Indirect Project/Process Costs – Costs associated with running the
enterprise or organization (often called facilities and administrative costs.)
Examples of Indirect Costs:
̶ Utilities and rent
̶ Cost of Quality resources working on the project prior to
implementation of solution.
Note: in most organizations only incremental costs should be considered in the cost/benefit analysis.
Implementation Costs ($$)
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Gross Hard Project Benefits
+
Gross Soft Project Benefits
Less: Project Implementation Costs
= Net Project Benefits
Net Project
Benefits
Method to Calculate Estimated Project Benefits ($$)
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Hard benefits…such as:
Incremental Revenues…less Cost of
Goods Sold (COGS)
Cost Reductions
Soft benefits…such as:
Avoidance of lost sales…less COGS
Cost avoidance
Implementation costs include...
Full-time resources assigned to the
implementation
Consultants, contractors and temps
Other considerations for running the project
Implementation costs exclude…
Costs of Quality resources assigned to the
project prior to implementation
Gross Project Benefits
Gross Hard Project Benefits
+
Gross Soft Project Benefits
Less: Project Implementation Costs
Net Project
Benefits
Project Implementation
Costs
Method to Calculate Estimated Project Benefits ($$)
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Time
Fi
na
nc
ia
l &
p
ro
ce
ss
p
er
fo
rm
an
ce
Before
improvement
Minimize
this effect
After
improvement
In the initial stages of the solution being implemented, there is often a period of time when
process participants are adjusting to the new process which causes a degradation to both the
process and financial performance. After the adjustment period, performance will gradually
improve to the new desired level.
Implementing the solution quickly
and minimizing this adjustment
period will result in realizing
improved process performance
and therefore improved financial
benefits faster.
Key Considerations
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Start with the “As-Is” process analyzed earlier in the life of the project
Use the data generated in the previous project phases to illustrate the difference
between the “as-is” state and your solution.
Cost out the various “Should-Be” alternatives
Use the process map and personnel in associated departments to identify cost and
benefit information.
“As-Is” minus “Should-Be” represents the cost savings associated with the proposed
solution
Determine cost of implementing the proposed solution
Concentrate on direct costs and direct benefits. Use indirect costs that are generally
acceptable to all stakeholders
Use standard methods and rates in your calculations
Document your assumptions
How to Perform a Cost/Benefit Analysis
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Project Name: Improve credit card billing process
Problem Statement: The credit card billing process is inaccurate resulting in incorrect bills being sent to card holders.
Proposed Solution: Improve credit card billing process by implementing new software.
Implementation Costs: Measurement Variable Cost Estimate Total Notes
Software 1 site license $50,000 $50,000
Training 2 contractors @ 40hrs each/week
for 1 week
$50/hr/each $4,000
Implementation team personnel time 4 people @10 hrs./wk. for 5 weeks $50/hr. $10,000
Hard Benefits: Measurement Variable Cost Estimate Total Notes
Reduce billing inquiries 1 staff eliminated @ $9.50/hr. $20,000/yr. $20,000
Hard Benefits:
Cardholder receives more accurate and
understandable statement
5 day reduction in receivables days
outstanding per quarter
Avg. receivables
balance = $1.5M @15%
cost of capital
$123,000 Time value of money
indicates because of
interest costs, a dollar
received today is
worth more than a
dollar in the future so
collecting receivables
sooner is a benefit
Net Benefit (equals total benefits, less costs): $79,000
Example of Cost/Benefit Analysis
*A cost/benefit analysis can be done in many different formats. If a standardized cost/benefit analysis template
does not exist within your organization, then propose one to the organization.
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Company: Auto Insurance provider
Problem: Extended claims payment cycle time due to manual claims payment process with multiple handoffs.
Process Solution: Implement an automated workflow system with built in automated payment system to
reduce process cycle time to pay auto claims.
Cost/Benefit Summary:
Implementation Costs: $58,000
Hard Benefits:
Head Count Reductions $398,261
Overtime Elimination $56,799
Reduction in check writing costs $69,176
Soft Benefits:
Productivity Increases $121,750
Total Project Benefit: $645,986
Net Benefit: (Benefits less costs) $587,986
See back up data on following pages
Example of Cost/Benefit Analysis with Back Up
Data Detail
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In this example, an auto insurance provider’s auto repair claims payment process was incapable of meeting its cycle time CTQ of paying claims within 7 days. The “as-is” process was completely manual and they paid the majority of their claims via checks. Due to the manual nature of the process, it required a lot of labor to complete the process effectively. To improve the process, the improvement team recommended implementing an automated workflow system with a built in automated payment process. This solution enabled the auto insurance provider to reduce the staff required to process claims manually, expand their payment capabilities, reduce check writing costs, and improve cycle time.
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Automated Workflow System with Build in the payment system:
$58,000Total Costs:
$3,000 User Training on new system (10 @ $300 each)
Training:
$50,000Software program (1 site license @ $50,000)
$5,000Hardware (10 computers @ $500 each)
Implementation Costs:
Example of Cost/Benefit Analysis with Back Up
Data Detail
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The back up data to the CBA shows the comparison of the “As-Is” process to the new “To-Be” process
Old Process Department Makeup:
Count Job Title Gross Annual Pay*
(avg. annual pay for 1 x total count)
1 Supervisor $33,141 (1 @ $33,141)
3 Fax People $55,029 (3 @ $18,343)
3 Filers $63,426 (3 @ $21,142)
5 Mail Openers $91,615 (5 @ $18,323)
3 Researchers $67,476 (3 @ $22,492)
Total= $310,687
New Process Department Makeup:
Clerical: Clerical:
Count Job Title Gross Annual Pay*
1 Manager $37,343 (1 @ $37,343)
9 Payment Reps $225,000 (9 @ $25,000)
3 Exceptions $66,669 (3 @ $22,223)
Total= $329,012
Count Job Title Gross Annual Pay*
1 Manager $37,343 (1 @ $37,343)
4 Payment Reps $100,000 (4 @ $25,000)
0 Exceptions $0
2 Master Card Reps $49,066 (2 @ $24,533)
Total= $186,409
Accounts Payable: Accounts Payable:
Expected Annual Savings from headcount reduction:
Old process $639,699
New Process $241,438
Total head count savings = $398,261
Count Job Title Gross Annual Pay*
(avg. annual pay for 1 x total count)
0 Supervisor $0
3 Fax People $55,029 (3 @ $18,343)
0 Filers $0
0 Mail Openers $0
0 Researchers $0
Total= $55,029
*Reflects salary with benefits, exclusive of overtime
Example of Cost/Benefit Analysis with Back Up
Data Detail
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Savings From Elimination of Overtime:
Overtime paid from week 9-43 4,863
Avg. hourly pay, non exempt employees* $ 11.68
Total Over time elimination savings $ 56,799
*fully loaded labor rate based on average of the time periods studied
FINANCIAL WEEK
HEAD
COUNT TOTAL HOURS
TOTAL OT
HOURS Loaded Labor Rate
9 62 5,336.00 721.28 11.25
PRIOR TO 11 68 6,904.57 796.28 11.31
IMPROVE- 13 67 5,990.67 667.80 11.45
MENT 15 67 5,956.65 641.63 11.19
17 62 5,169.00 114.02 11.42
19 63 5,074.25 2.25 11.24
21 61 4,768.00 - 12.01
I 23 60 4,879.27 115.95 11.23
M 25 59 4,688.00 - 11.42
P 27 58 4,625.25 17.25 12.26
R 29 57 4,541.70 16.50 12.24
O 31 58 4,705.87 97.88 11.34
V 33 56 4,487.75 39.75 12.26
E 35 56 4,403.45 54.75 12.11
M 37 56 4,652.43 369.38 12.61
E 39 55 4,918.54 631.95 11.44
N 41 55 4,918.02 563.33 12.23
T 43 55 4,381.12 13.13 11.23
90, 400.54 4,863.13
Example of Cost/Benefit Analysis with Back Up
Data Detail
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Elimination of Check Writing Costs:
Old Process: New Process:
Check printing and postage costs $120,000 $50,824
Check processing volume (percent of total volume) 85% 36%
Check Printing and Postage Cost
Check printing and postage after improvement
$120,000
$ 50,824
Total Cost Savings from reduction in check writing as a result of automation: $69,176
Productivity Increases:
Old Process: New process:
Avg. number of transactions per payment rep./day (based on time studies) 31.8 49.0
Expected annual savings from productivity increases:
Productivity Improvement as a result of new process = (49.0 -31.8)/31.8 54%
Required additional payment reps, old process, to achieve new process productivity level
(% change * 9 people) = 4.87 additional people
Avg. annual salary, net of overtime
4.87
$25,000
Productivity Increase Savings: $121,750
Example of Cost/Benefit Analysis with Back Up
Data Detail
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When analyzing the costs it is important to distinguish between the
design/implementation and the operational impacts
Cost associated with design and implementation
Training Cost
System Cost
Design and Development Cost
Cost of Change
Costs associated with operational impacts
Resource Consumption
Rework Cost
Cost of Capital
Maintenance Cost
Considerations for Analyzing Costs
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Lean Six Sigma focuses on tying process improvement to the company bottom line. The
Finance function is responsible for reporting this bottom line---the effectiveness of any Lean Six
Sigma implementation is therefore dependent on building credibility with Finance. This can be
accomplished through either a separate Finance tollgate or a Finance representative being
present at the regularly scheduled tollgates at the end of each phase.
AnalyzeDefine Measure Improve Control
PHASE
TOLLGATE
PHASE
TOLLGATE
PHASE
TOLLGATE
PHASE
TOLLGATE
PHASE
TOLLGATE
FINANCE
TOLLGATE
FINANCE
TOLLGATE
Phase Tollgates are reviews with Lean Six Sigma Mentors and Sponsors after every phase to
ensure that all phase deliverables have been met and sufficient rigor maintained to move on
to the next phase. Finance Tollgates occur during or after Improve (when one knows enough
about the process to develop a cost/benefit analysis) and Control phases (when project
savings are to be booked).
The Importance of Finance Review at Tollgates
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A lot can change during the course of a Lean Six Sigma project: key business
assumptions, strategy, execution, processes, etc. This change can have
dramatic impact upon a project’s cost/benefit analysis model. As a result, most
companies set up periodic audits of Lean Six Sigma projects after
implementation to review and update cost models and savings.
Auditing and Updating Cost/Benefit Analysis
PROJECT
COMPLETE
SAVINGS
START
PROJECT
AUDIT
COST
MODEL
OK?
UPDATE
MODEL
UPDATE
SAVINGS
END
START
Y
N
30
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When presenting CBA, consider focusing on the following:
Keep it simple
Focus on the summary benefits and costs; have back up data and be prepared to go into
detail if necessary, but be careful not to go “into the weeds” in terms of detail
Discuss benefits, be clear on what are soft vs. hard benefits
Speak frankly about the costs
Speak the language of the business: use standard methods and techniques
Ask for input
Confirm go/no go decision
Gaining Approval on Cost/Benefit Analysis
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What you learned during this section:
The elements of capturing the financial impact of selected
solutions
Why performing a cost/benefit analysis on selected
solutions is necessary
How to develop a cost/benefit analysis
Examples of various cost/benefit analysis formats
Key considerations and lessons learned around capturing
financial benefits of improvement projects
Summary of Section
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
End of Lesson: Improve – Financial Impact of Solutions
Lean Six Sigma Training
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Test Solution
Plan for Risks
Improve – Risk Planning and Testing
Lean Six Sigma Training
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Understand the importance of assessing and managing
risks
Learn how to conduct a Failure Mode and Effects Analysis
(FMEA)
Understand the concept of Errorproofing
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
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Every process change carries risk. Unintended consequences can strike even
the best-planned implementation. While we cannot eliminate risk, we can
certainly mitigate it.
In the following pages, we will examine some tools that allow us to anticipate
potential problems with the new “to-be” process and therefore reduce the risks.
RED
YELLOW
GREEN Minimal risk to implementation
Moderate risk to implementation
Severe risk to implementation
Risk Assessment and Mitigation
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Common tools for risk assessment and mitigation:
Failure Mode and Effects Analysis (FMEA)
Errorproofing
Risk Assessment and Management Tools
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Is a structured approach to evaluating and prioritizing
risks in a process and/or product
Can be used to identify and mitigate risks prior to making
changes to a process and/or product
Can be used to prevent failures in a process and/or
product
Failure Mode and Effects Analysis (FMEA)
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To identify specific parts of the product or process that
need improvement
To improve the quality, reliability, and safety of products
and services
To increase customer satisfaction
To document and track actions taken to reduce risk
Why Use an FMEA
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1. Review the product, service or process (use process map)
2. Brainstorm to identify potential failure modes. These are ways
in which the product, service, or process might fail (ask the
question, if the failure occurs, what are the consequences?)
3. Identify 1 or more potential effects of each failure
(consequences of that failure) and rate its severity
4. Identify causes of the potential failures and rate their likelihood of
occurrence (frequency)
5. Rate your ability to detect each failure mode
6. Multiply the three numbers (severity, occurrence, detection)
together to determine the risk of each failure mode (RPN = Risk
Priority Number)
7. Identify ways to reduce or eliminate risk associated with high
RPNs
How to Conduct an FMEA
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FMEA Worksheet
FMEA
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Severity = likely impact of the failure
Rating Criteria: A failure could…
10 Customer leaves you because of poor customer service
5 Poor customer service likely to result in a complaint from the customer
1 Be unnoticed and not affect customer service
Bad
Good
Sample Severity Rating Scale
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This scale is just one example; you can develop your own scale customized to your specific product, service, or process. For example, you can have more rating levels, and use other criteria.
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Occurrence = frequency of occurrence
Rating Time Period
Sample Occurrence Rating Scale
10 Once an hour
5 Once a week
1 Once a quarter
Bad
Good
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This scale is just one example; you can develop your own scale customized to your specific product, service, or process. For example, you can have more rating levels, and use other criteria.
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Detection = how easily the failure can be detected
Rating Definition
Defect caused by failure is not detectable
Process is monitored and manually inspected
Defect is obvious and can be kept from affecting customer
Sample Detection Rating Scale
10
5
1
Bad
Good
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RPN = (severity) x (frequency of occurrence) x (likelihood of detection)
The idea is to focus action/improvement efforts on the failures that have the
biggest impact on customers. The highest scoring failure modes are those that
happen a lot, that are bad when they happen, and/or that are unlikely to be
detected. Difficult-to-detect errors obviously are more likely to get through to
customers.
The RPN number identifies those items or process steps in the new “to-be”
process that pose the greatest risk. Anticipating these risks ahead of time will
allow the team to put countermeasures in place to mitigate the risks associated
with the new process, thereby increasing the chances of success.
Calculating the Risk Priority Number (RPN)
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Copyright © 2016 Acuity Institute LLC. All rights reserved.
Item or Process
Step
Potential Failure
Mode
Potential
Effect(s) of
Failure
S
E
V
E
R
I
T
Y
Potential
Cause(s)
O
C
C
U
R
R
E
N
C
E
Current
Controls
D
E
T
E
C
T
I
O
N
R
P
N
Recommended
Action Responsible
Computers Viruses Loss of data,
corrupted
files, network
invasion
4 Virus software
isn’t up to
date or gets
disabled
8 Virus
protection
software
2 64 Ensure that
virus protection
software is up
to date
Susan K.
Files not
backed up
Data loss,
rework
4 Staff forgets,
low priority
6 None 9 216 Keep files on
LAN, notify IT
of remote files
for automatic
backup
Sam T.
Stolen Lost data,
rework
8 Not locked up
at night
7 None 10 560 IT Security
awareness
training and
communication
Bob J.
Example of FMEA – IT Security
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Focus taking action on those process steps which have the highest RPN.
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Before you use the standard scales, make sure they are in line with
your process or product
Make the tool work for you and your particular process
The scales for severity, occurrence, and detection can be adjusted
if necessary
If standard scales don’t apply, brainstorm the appropriate FMEA
scales that best fit your particular process
Adjusting FMEA Scales
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No matter how good people’s intentions are, if a process allows for the generation
of defects, the process will generate defects.
A common tendency to eliminate errors is to add inspection steps. Inspection
does not prevent errors, it just detects them. Inspection requires time and
resources and is not an efficient method to reduce errors.
Another technique to combat this propensity toward defect generation is
Errorproofing. Errorproofing is an alternative to inspection.
Error-proofing a process is a technique to
help prevent errors and increase the
chances of detection so that failure mode
occurrences are eliminated.
Similar to FMEA, teams can use this tool
to identify many possible actions to
prevent errors or mitigate their effects.
Errorproofing
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What is considered an error?
Errors are inadvertent, unintentional, accidental
mistakes made by people because of the human
sensitivity designed into processes.
Errors result in those once in a while defects that we
always find difficult to control.
Errorproofing
16
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It’s Origins:
Errorproofing (also known as Poka-Yoke technique) was developed to mistake-proof
processes.
Poka-Yoke translates into English as to avoid (yokeru) inadvertent errors (poka). The result
is a business that wastes less energy, time and resources doing things wrong in the future.
How it works:
Errorproofing involves physical process modifications to eliminate the opportunity for
defects. Errorproofing measures or techniques should be an integral part of the process.
The technique or device to eliminate or reduce the error is placed sufficiently close to where
mistakes occur, providing fast feedback to the process operator of mistakes occurring.
The selected errorproofing technique should qualify the following criteria:
Inexpensive.
Based upon common sense, preferably of the operator or the 1st line employee.
It MUST eliminate or reduce occurrence and/or provide detection of the problem at the
source itself.
Errorproofing
17
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Eliminates errors in counting out change owed
back to the customer
Cash register is programmed to calculate correct
change
Eliminates safety hazardChild locks on car doors
Error reduced or prevented as a result
of errorproofing
Errorproofing Technique
Examples of Errorproofing
18
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This prevents the processing department from
reviewing an incomplete document, sending it
back to the loan department, delaying the
processing of paperwork
The online banking form requires all fields to be
filled in for a loan (including the loaner signature)
before allowing the form to be sent to processing
Reduces spelling errorsSpell check function and auto correct function in
a word processor
Error reduced or prevented as a result
of errorproofing
Errorproofing Technique
Examples of Errorproofing
19
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Prevents surgery from being conducted on the
wrong limb or side of the body
Before surgery patient’s incision site is marked
with a marker
Reduces plane collisionsCollision avoidance radar in planes
Error reduced or prevented as a result
of errorproofing
Errorproofing Technique
Examples of Errorproofing
20
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What you learned during this section:
Understand the importance of assessing and managing
risks
Learn how to conduct a Failure Mode and Effects Analysis
(FMEA)
Understand the concept of errorproofing
Summary of Section
21
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Test Solution
Plan for Risks
Improve – Risk Planning and Testing
Lean Six Sigma Training
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Understand the importance of testing the new solution
Learn what a pilot is and the benefits of conducting one
Learn the elements of an effective pilot plan and the key
considerations for making the pilot successful
Learn how to evaluate and confirm pilot results
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
23
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Before we can implement our solution, we need to test our solution to confirm
the expected impact on our process performance. The Shewhart Cycle of Plan-
Do-Check-Act (PDCA) applies to this effort:
PLAN DO
CHECKACT
Develop a plan of
how we will test the
solution
Conduct a pilot test
Check the plan and
the results
Compare estimated
improved process
performance (Y) to
goals for project
Revise action plan if
improved process
performance (Y) would
not be sufficient
Implement action plan
if improved Y is
sufficient
Testing Our Solution
24
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Definition of a Pilot:
A test of all or part of a proposed solution on a small scale in order
to better understand its effects and to learn about how to make the
full scale implementation more effective and successful.
It is important to test your solution to identify any problems and
manage risks prior to implementing the solution across the
organization.
One method we use to test our solution is a Pilot.
Testing Your Solution
25
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Make further improvements to the solution
Gain additional understanding of the risks
Identify opportunities to reduce risks
Validate assumptions
Validate solution cost/benefit
Practice run prior to full implementation
Facilitate stakeholder buy-in
Reasons to Pilot
26
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The scope of the implementation is large
The scope of the implementation is complex
Confirmation of the desired results is required
Validation of the selected solutions is required
Additional stakeholder commitment is needed
When to Pilot
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Test product/process:
With a specific market or customer segment
Within a particular business unit or location
With a single row of employees or shift (morning shift
employees, afternoon shift employees, etc.)
With a focus group
When processing a subset of items
Pilot Strategy
28
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Defined
Roles/Responsibilities
Pilot steering
committee/team (select
those who will be
supportive)
Pilot participants
Liaison between pilot area
and core pilot team
Workplan
Have a detailed project
plan
Identify tasks and owners
Identify dates of
completion
Pilot plan outline
Communication Plan
Inform and motivate
steering committee and
pilot participants
Inform and motivate all
associates
Conduct daily briefings
with steering committee
Training Plan
Train all employees which
are affected by the pilot
Review pilot plan with
trainees
Goals/Targets
Identify success measure
Make continuous, small
improvements towards the
CTQ and specifications
Evaluation Process
Record observations
Set up a feedback loop
Compare actuals to goal
Elements of an Effective Pilot Plan
Pilot Plan
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Step 1. Select pilot oversight committee
Step 2. Identify pilot participants
Step 3. Develop pilot plan
Step 4. Communicate to the organization about the pilot
Step 5. Train pilot participants
Step 6. Execute pilot
Step 7. Evaluate pilot results
Step 8. Debrief on lessons learned from the pilot
Step 9. Adjust process where necessary based on pilot results
Step 10. Prepare for full scale implementation or increase scope of
pilot to a second area prior to implementation if necessary
Steps to Piloting
30
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Product/Service: Insurance Services
Function/Process Tested: Claims Payment process
Pilot Plan Objectives: 1. Test new “to-be” process
2. Validate expected results
3. Identify risks
Pilot Strategy: Pilot within claims department in location A
Pilot Duration: 30 days
Plan Pilot Actuals
Measure Target Tolerance Average Sigma
CTQ 5 day cycle time + 1 day
Measurement Plan:
Pilot Observations:
Gaps:
Follow-up Actions:
Pilot Plan Outline Example
31
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Where to pilot? What location, department or segment of the
organizational process?
How do we ensure that the full range of process conditions are
tested during the pilot (i.e. cyclical business cycles)?
How long do we need to pilot or how many samples do we need to
statistically be sure that the process is capable to produce the
desired outcome?
What needs to be measured? How? When? Where?
How do we ensure that pilot process is contained (i.e. not
influenced by other processes or departments)?
How to minimize service or production disruptions that the pilot
may cause to the business?
Key Considerations when Planning the Pilot
32
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PLAN DO
CHECKACT
Check
the Plan
Check
the
Results
Date
Completed
Develop Form 4/28
Test Form 5/03
Revise Form 5/10
Roll-Out 5/12
Check Results:
Compare graphs such as
paretos, histograms, etc.
before pilot to the same
graphs post pilot
Confirm the results via
hypothesis testing tools
Check Plan and Results
33
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Add more data to an existing run
chart or control chart
Prepare new Pareto charts for
those you created in
Measure/Analyze. Make the
scale and dimensions the same
so you can more accurately
judge degree of improvement
Draw new histograms on the
same scale as the original
graphs
Before After
}Improvement
Target
}Remaining Gap
Good
Step 4 changes
implemented
} Improvement
Before After
A1 A2 A3 A4 A2 A1 A3 A4
151050
8
7
6
5
4
3
2
1
0
Fr
eq
ue
nc
y
654321
8
7
6
5
4
3
2
1
0
Fr
eq
ue
nc
y
Before After
Evaluating Before and After Data
34
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Total Opportunities Total Defects Before Pilot Total Defects After Pilot
960 846 86
Sigma = 0.3
Yield = 1 –
= 1 – .88
= 12%
960
846
BEFORE
Sigma = 2.8
Yield = 1 –
= 1 – .09
= 91%
960
86
AFTER
Assessing Pilot Results – Recalculate Process
Sigma
35
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Results
How much was the gap between desired and actual reduced?
What targets were missed and why?
Were the plans effective in addressing the root causes you targeted?
What do customers tell you now that the changes are in place?
Has enough progress been made or do you need to go back and try other solutions?
Were there unintended benefits or negative side effects?
Methods
Did you follow your plan? Did the pilot represent the conditions of what the actual
implementation will be like?
Do you need to modify the plan/solution prior to implementation?
In what ways do you need to modify the process/solution before implementation?
When evaluating pilot results, both the results and the methods need to be
considered
What to Consider when Evaluating Pilot Results
36
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Confirm that you followed the plan
and didn’t deviate from it, causing
poor results
Retrace your steps and look for
flaws or gaps in your analysis
Pick up with that step and start
again if necessary
Go back and select another solution
if necessary
What to do if Desired Results aren’t Achieved After
Pilot
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What you learned during this section:
The importance of testing the new solution
What a pilot is and the benefits of conducting one
The elements of an effective pilot plan and the key
considerations for making the pilot successful
How to evaluate and confirm pilot results
Summary of Section
38
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
End of Lesson: Improve – Risk Planning and Testing
Lean Six Sigma Training
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Implementation of Solutions
Implementation Planning - Cultural
Implementation Planning - Technical
Improve – Implement Solution
Lean Six Sigma Training
1
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Understand the two sides to implementation planning
Learn the elements of the technical implementation plan
Understand how to use an MGPP
Learn various work planning tools
Know what a Gantt Chart is and how to use it
Gain experience developing an implementation plan
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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Planning for Implementation
The project team has selected the solution, analyzed the potential risks and
conducted a pilot test of the solution and is now ready to implement it. You
must now translate the drawing board solution design into a working, breathing
implementation plan.
Implementation Planning
Implementation
Plan – High
Level or
Implementation
Plan - Detailed
3
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There are two sides to Implementation:
The technical side The people/cultural side
To successfully implement the solution we must plan for both!
We will begin by learning about the technical plan….
And
The Two Sides to Implementation Planning
4
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Elements of the
technical plan include:
Project definition and objective
A plan for the work involved to
implement the solution
Tasks and subtasks to complete
the work
Time and schedule to complete
the tasks
People and resources (money,
equipment, etc.) needed to fulfill
the plan
The Technical Plan
5
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The source of this information should come from your project
charter.
Just like the purpose of the charter, the purpose of the project
definition is to keep the implementation team on track.
It also serves as the foundation of the implementation plan.
Project Definition should include:
Purpose/goal
Objectives
Specifications
Constraints
Scope
The project definition is a statement of the project objective, purpose,
goal and scope.
Develop Project Definition and Goals of the
Implementation
6
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Purpose/Goal:
Why are we doing this project?
(Ex. To improve productivity? Increase Sales? Reduce lost customers?)
Objectives:
What specific outcomes are desired? What is the definition of success?
(Ex. To implement the new MasterCard payment process with as little impact on the
business as possible.)
Specifications:
What are the targets and specifications for the improved process?
(Ex. 5 day cycle time)
Constraints:
What parameters must the implementation be completed under?
(Ex. Time to implement solution must not exceed 3 weeks)
Scope:
Are there any processes or locations that the solution will not be implemented in?
(Ex. Excluded: Tokyo office)
Develop Project Definition
7
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When implementing solutions that are very large in scope or large in the
magnitude of change from the “as-is” process, a Multi-Generational
Product Plan (MGPP) can be a useful tool to scope the implementation
effort into three separate phases.
The Multi-Generational Product Plan (MGPP) is a tool used to
define the scope of a new product or new service process as well
as to plan the long-term direction of future product/service
generations.
It is built around core technologies, competencies or platforms (this
can be an excellent tool for solutions that involve technology)
Definition of MGPP:
Project Definition – Scoping Large Implementation
Efforts
8
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Not all teams will use this tool. Many DMAIC solutions are scoped to only require 1 generation. However even for those teams with a small to medium scope, it can still be an effective tool for long term planning and future enhancements to the product/process.
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Product/
Process
Generations
Platforms
and
Technology
Vision
Long Term direction for each key product/service
process based on anticipated evolution of the market
and competitor products/services beyond current
applications
Series of releases; each release characterized by
distinct combinations of features or technology
Product/service/process competencies which can be
leveraged to introduce a number of product generations
quickly and to reduce the cost of new product/process
development
Elements of an MGPP
9
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Generation 1
Generation II
Generation III
Stop the Bleeding
Fill selected
product/process voids
Take the offensive
Fill new target markets
Attain technical leadership
Deliver productivity
breakthroughs
Step
Stretch
Leap
Generations of an MGPP
10
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Most DMAIC project are focused on achieving generation 1.
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MGPP’s uses in the Improve phase:
To break large scoped improvement solutions into manageable
phases
To help the organization focus on long term planning around the
solution
To plan future releases or enhancements to improvement solution
If some part of the solution is going to have a very unfavorable
impact, you can look to the MGPP to see whether it might make
sense to move that capability to a later generation
MGPP can control scope additions/changes to current improvement
solution design
MGPP can prevent products/services/processes from stagnating
while the market changes around them
MGPP
11
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Create Work Plan
The work plan will be the specific set of tasks and objectives, aligned with
identified resources and a defined schedule. It will define the integrated
activities and their sequence that the team will use to implement the
improvement solution.
Tasks & Timeline
Aug. Sept. Oct. Nov. Dec. Jan. Feb.Step
Budget & Resources
Expenses
Staff time
xxxxx 00.00
xxxxx 00.00
xxxxx 00.00
Bob 5 hrs
Develop the Work Plan for Implementing the
Solution
12
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When listing the tasks and activities that must be completed for the
solution to be implemented successfully, consider these major
activities/elements the plan should include:
Tasks & Timeline
Aug. Sept. Oct. Nov. Dec. Jan. Feb.Step
Training Plan
Communication Plan
Rollout Schedule
Implementation of Equipment, and
Materials (if applicable)
Evaluation Process
Change Management Plan
Develop the Work Plan for Implementing the
Solution
13
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Project Plans
April. May. June July Aug. Sept OctStep
Gantt Charts
Flowcharts
Processing Administration Adjusters Payables
Work Planning Tools
14
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Now we want to put all of the tasks associated with the elements of the Implementation plan into a work plan which indicates the dates and owners of each of the tasks and activities. Project plans, Gantt charts and flowcharts are all excellent work planning tools.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
A Gantt chart is a project management tool that shows the
timing, duration, and interrelationship of steps in a process.
Implement New Claim’s Processing System
Implement Solution
ID
1
2
3
4
5
6
7
8
9
Install new hardware
Revalidate System
Install new software
Train
Processing Staff
Update documentation
Develop Training Plan
Train Staff
Test
Task Name 5/31 6/7 6/14 6/21
MAY JUNE
6/28
Jen, Kris, Sue
Conroy
Conroy
Gwen
Team, TBD
Team, TBD
Gantt Chart
15
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Tasks
(level of detail
will vary)
Tasks
ID # Length of bar indicates duration
of task. Also indicates start and
end point in relationship to other
tasks
Implement New Claim’s Processing System
Implement Solution
ID
1
2
3
4
5
6
7
8
9
Install new hardware
Revalidate System
Install new software
Train
Processing Staff
Update documentation
Develop Training Plan
Train Staff
Test
Task Name 5/31 6/7 6/14 6/21
MAY JUNE
6/28
Jen, Kris, Sue
Conroy
Conroy
Gwen
Team, TBD
Team, TBD
Indicates
owner of
task
Illustrates
duration of
main task
Gantt Chart Elements
16
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There are generally five kinds of relationships between steps in a Gantt chart:
1. No relationship (the tasks are independent)
2. Start-to-end (one task can’t start until another ends)
3. End-to-start (one task can’t end until another starts)
4. Parallel start (both tasks need to start at the same time)
5. Parallel stop (both tasks need to end at the same time)
Copyright © 2016 Acuity Institute LLC. All rights reserved.
What you learned during this section:
The two sides to implementation planning
The elements of the implementation plan
How to use an MGPP
Various work planning tools
What a Gantt Chart is and how to use it
How to develop an implementation plan
Summary of Section
17
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Implementation of Solutions
Implementation Planning - Cultural
Implementation Planning - Technical
Improve – Implement Solution
Lean Six Sigma Training
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Understand the importance of developing a plan to
prepare the organization to successfully accept and
transition through to using the new improvement process
Learn the key elements of a change management plan
Learn tools and techniques to effectively manage
stakeholder support for your selected solution
Understand the critical role communication planning plays
in a successful implementation
Learn how to develop a project storyboard
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
19
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To enable a smooth implementation of the improvement solution
To identify sources of resistance, uncover the reasons, and convert
resistors
To build commitment and support for the improvement solution
across the organization
For the critical stakeholders to fully support or even embrace the
change
To help the team develop a comprehensive change management plan and
keep the efforts focused, you should clearly define the goals and objectives
of the change management effort.
Change Management Goals
Change Management Plan – Objectives and Goals
20
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Early on in the project we identified the importance of stakeholder influence on
the projects success. The implementation of the solution is one of the most critical
junctures in the life of the project where stakeholder influence can either make or
break the project’s success.
Because positive stakeholder influence is so essential to a smooth and
successful implementation, it is important to review and re-evaluate our
stakeholder analysis specifically for the implementation effort.
Project Sponsor
Process Owner
Middle Management
Executive Leadership
Front Line Employees
Enabling Functions Supplier
Team Members
Stakeholder Influence During the Implementation
Phase
21
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Once the actual solution has been selected to address the process problem, often
times stakeholder support can shift either positively or negatively.
Therefore it is important to revisit the process for managing stakeholders.
In
flu
en
ce
o
n
Pr
oj
ec
t
Impact of Change (from the Solution)
After Solution Selected
Low Medium High
Lo
w
M
ed
iu
m
H
ig
h
9
4
5
6
8
3
9
6
1
2
In
flu
en
ce
o
n
Pr
oj
ec
t
Before Solution Selected
Impact of Change (from the Solution)
Low Medium High
Lo
w
M
ed
iu
m
H
ig
h
9
4
5
6
8
3
9
6
1
2
Stakeholder Shift
22
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Often times a stakeholder who is supportive of the project during the earlier phases of the DMAIC project lifecycle can shift once the solution is selected for the following reasons:
- The selected solution is perceived as a threat to the stakeholder’s position of power
- The stakeholder wanted a different solution to be selected
- The selected solution is perceived by the stakeholder as being too risky or not likely to succeed
The selected solution is perceived by the stakeholder as adding too much to daily workload.
Stakeholder Map Legend: Triangle = Enthusiast, Square/Rectangle = Neutral, Circle/Oval = Opponent
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Identify
Stakeholders
Develop
Stakeholder Map
Develop
Stakeholder
Management Plan
Step 1 Step 2 Step 3
Re-examine the list
of stakeholders
Are there any new
stakeholders that
should be added
when considering
the newly selected
solution and
implementation
effort?
Re-evaluate the
stakeholder map and
identify positive and
negative stakeholder
shifts in support,
based on the
selected solution
Identify where key
stakeholders need to
be for successful
implementation
To meet the objective of a successful implementation and effectively manage
stakeholder shift, we must re-tool the process for managing stakeholders with a
focus on the newly selected solution.
Identify source of
concern and develop
action plan to convert
resistors who are
critical stakeholders
to the successful
implementation of the
solution.
Readdress the Process for Managing Stakeholders
23
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Benefits and Barriers:
Assume that it is now two years in the future
and we have been successful in implementing
the process. What benefits do you see for
yourself as an individual, for your dept., and for
the company as a whole?
Benefits
What are the barriers that we as an
organization are going to have to overcome in
order to make the implemented change a
success and thereby achieve the benefits?
Barriers
Brainstorm the benefits and barriers to implementation with
stakeholders, identify top three, and develop action plans
Force Field Analysis:
Additional Tools to Manage Stakeholders
Forcefield
Diagram
24
Driving Forces Restraining Forces
Goal
Brainstorm the driving forces and restraining forces with stakeholders,
identify top three, and develop action plans
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Teams can impede their own success when they don’t
consider the following when managing stakeholder
support:
The importance of political sensitivity
Failing to recognize the need to “share the glory”
Assume technical solution is sufficient
Don’t involve others due to time constraints
Use only one or two conflict resolution styles
Fail to appreciate the human side of implementing
solutions
Tips and Traps for Managing Stakeholders
25
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Another component to building and maintaining support for the implementation of
the improvement solution is aligning systems and structures with the new process
solution.
When we are expecting stakeholders to be supportive and enthusiastic about the
new solution, it is important to make sure the way we organize, train, reward,
compensate, and promote aligns with the behavior we are expecting.
If organizational measures and rewards don’t link to the desired behavior and the
new process solution, we run the risk of the change not being effective or not
lasting long term.
Aligning Systems and Structures
26
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Do any measurements exist around achieving sigma goals and
service quality?
Do any rewards exist around rewarding sigma goals and service
quality?
What type of behavior do we want to reward?
What types of behaviors do we want to eliminate?
Are there measurements in place today that actually promote the
wrong behavior or are in conflict with what we are trying to achieve
with the new “to-be” process?
Aligning Systems and Structures
Key considerations for aligning systems and structures with the
new process goals:
27
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One of the most important elements to facilitate change is communication to those
affected by the change.
Consistent and effective communication also fosters cooperation and collaboration
which are key elements to an efficient transition to the “to-be” process.
Communication
Collaboration
Change
Communication Planning
28
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Below is a review of some key considerations when developing your communication plan for the
implementation of the solution.
Organizational communication is a change agent
The purpose of communication is not just to convey information, but to change behavior.
Project communication should change behavior by building support of and buy-in toward the
project's objectives.
Communication is a two way process
Listening and encouragement of feedback is critical to understanding whether project
communication has been effective and to evaluate whether the project is being supported or
not; and if not why.
Craft communication in the interests and language of the target audience
To be effective, the message should be focused on the receiver of the communication’s
interests in both content and context.
Communication must be compelling and continuous
To be compelling consider creative ways to deliver your message. To be remembered and
internalized, communication needs to be continuous and consistent.
Communication Planning Considerations
29
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A communication plan for the project was developed back in the Define phase.
That plan should be revisited at this stage in the project to identify specific
messages that need to be delivered regarding the implementation of the solution.
Communication regarding the solution and why that particular solution was
selected
Communication to key stakeholders to prevent resistance and gain support
for the solution
Communication around the implementation schedule and timeline
Selling the project story and its benefits to the organization
The key communication messages that should be disseminated regarding
the implementation fall into the following major categories:
Communication Plan for Implementation of the
Solution
30
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All
employees
All
employees
Audience
SurveySponsorDMAIC
Team
Gallery Walk
to present
project story
board
August 30Selling the
project story
and benefits
Check in with
key
stakeholders
for feedback
SponsorBlack Belt /
Green Belt
Mass e-mail
campaign to
the
organization
August 5Selling the
project story
and benefits
Feedback
Loop
Required
Approval
OwnerMethodWhenWhat
Implementation Communication Plan Example
Communication
Plan
31
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When looking at the core categories of communication that should be considered for the
implementation plan, we have looked at all the categories but the last.
Communicating the “project story” and its benefits to the organization is an important
part of facilitating change and building support for the project across the organization.
Communication regarding the solution and why that particular solution was
selected
Communication to key stakeholders to prevent resistance and gain support for
the solution
Communication around the implementation schedule and timeline
Selling the project story and its benefits to the organization as a whole
Communication Planning
32
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What is a Project Story?
A presentation and visual depiction of the steps the team took during each phase of the
DMAIC process.
It communicates key deliverables and accomplishments that were completed by the team
during each phase of the improvement process.
A project story brings all the work and effort the team put into their DMAIC project to life
through a storyboard presentation.
Why Communicate your Project Story?
Provides the organization with a full understanding and appreciation of the rigor that went
into selecting the solution.
It provides a standard way to communicate the team’s progress.
Builds enthusiasm and support for the project.
Educates the organization on the Lean Six Sigma DMAIC process and the DMAIC project
lifecycle.
“Selling the project story” and its benefits to the organization is crucial in developing a
critical mass of support for the Quality initiative.
The Project Story
33
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The most effective way to tell and “sell” the project story is by developing and
presenting a storyboard.
What’s a Storyboard?
A visual illustration of the project story (steps, tasks, key deliverables, and
results from each phase of the project) typically displayed on a large board
so it can be easily read and viewed.
How to Communicate the Project Story
34
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Team Information DEFINE MEASURE
Project
Overview
ANALYZE IMPROVE CONTROL
9080706050403020100
60
50
40
30
20
10
0
Average Hold Time
#
of
C
al
ls
January Avg. Hold Time Distribution Plot
Add
res
s
Inac
cur
ate
Line
Item T
ota
l
Am
oun
t Ove
rch
arg
e
Oth
ers
42 32 14 9 3
42.0 32.0 14.0 9.0 3.0
42.0 74.0 88.0 97.0 100.0
0
50
100
0
20
40
60
80
100
Defect
Count
Percent
Cum %
Pe
rc
en
t
C
ou
nt
Pareto Chart for Statement Accuracy
0Subgroup 5 10
0.000
0.001
0.002
0.003
0.004
0.005
0.006
0.007
Pr
op
or
tio
n
IncreasedOpportunities per
Unit
Charter
CTQ’s
Process Map
Data Coll.
Sigma
Capability
Root Causes Solution Selected
FMEA
Pilot
Monitoring
Response plan
A 12 22 145
B 52 43 130
C 48 43 180
“1 Page” Project Storyboard Example
Project Storyboard
35
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The Gallery walk also provides an opportunity for the
members of the organization to ask questions of the
project team about the project.
Gallery walks are a very effective communication
method to use before the solution is implemented, as
well as, throughout the life of the project to
communicate project progress and generate
enthusiasm for the project.
Project Storyboards are typically presented at a Gallery Walk.
What’s a Gallery Walk?
Gallery walks are scheduled coordinated meetings
where members of the organization are invited to
attend the meeting to hear about each of the Lean
Six Sigma projects that are being worked on by
DMAIC teams throughout the organization.
How to Communicate the Project Story at a Gallery
Walk
36
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1. Communicate the focus of your project and the phase of DMAIC the
team is currently in
2. When presenting the storyboard, consider your audience
3. Identify the story you want to tell them. What do you really want the
organization to know and understand about your project?
4. Emphasize the benefits of your project
5. Use strong visual aids to tell your story (graphs and charts)
6. Communicate the key deliverable, lessons learned and output of each
DMAIC phase of the project
7. Have the entire team participate in the gallery walk presentation, this is a
great team builder
Storyboard and Gallery Walk Tips and Traps
37
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8. Keep your storyboard to no more than 10 slides (for a gallery walk)
9. Slides can have a lot packed in, but be careful not to make too busy
10. When developing the gallery walk presentation for the storyboard, draw
it out on paper first before you create your final presentation
11. Developing a presentation script makes the presentation more effective
and can be a good exercise for the team, particularly if the team has
inexperienced presenters
12. Be creative!
13. Be sure to conduct a survey after the gallery walk to determine if your
communication was effective
14. Allow sufficient time to develop your project storyboard and practice the
gallery walk presentation
Storyboard and Gallery Walk Tips and Traps
38
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What you learned during this section:
The importance of developing a plan to prepare the
organization to successfully accept and transition
through to using the new improvement process
The key elements of a change management plan
Tools and techniques to effectively manage stakeholder
support for your selected solution
The critical role communication planning plays in a
successful implementation
How to develop a project storyboard
Summary of Section
39
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
Implementation of Solutions
Implementation Planning - Cultural
Implementation Planning - Technical
Improve – Implement Solution
Lean Six Sigma Training
40
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Know the steps to implementing the solution
Understand the key questions that need to be answered
to complete the Improve phase
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
41
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Now that the planning process is complete it is time to
execute the plans
If the appropriate amount of time and attention to detail
was put into the planning of the implementation, the rollout
of the solution should be successful
Implementing the Plans
42
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1. Update “to-be” process maps to reflect any changes that came out
of the pilot
2. Prepare data collection forms
3. Conduct training
4. Rollout process on a small scale first if possible, then move to full
scale rollout
5. Monitor implementation and evaluate results
Steps to Implementing the Solution
43
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Use the same methods and procedures used during the
pilot to monitor and evaluate results
PLAN ACTUALS
Conduct daily “book end” meetings with the implementation team
Meet at the beginning of each morning to discuss any key
information points or plans
Meet at the end of each day to debrief on the outcome and
results of process performance for that day
Before implementation
151050
8
7
6
5
4
3
2
1
0
Fr
eq
ue
nc
y
654321
8
7
6
5
4
3
2
1
0
Fr
eq
ue
nc
y
After Implementation
Monitoring the Implementation and Establishing
Check Points
44
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Solution Selection:
What other potential solutions did the team consider?
What were the primary criteria for selecting the solution(s)?
Cost/Benefit:
What is the net project benefit?
What are the assumptions of the cost/benefit analysis?
Risk Assessment:
How did the team analyze process risks?
What risks were identified? What was done to mitigate the risks?
In what ways has the solution been modified based on pilot results?
Yes No
Yes No
Yes No
Tollgate Questions and Check list Items:
Improvement Completion Checklist
45
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Tollgate Questions and Check list Items:
Solutions Pilot:
Was the solution tested? Did the pilot represent the conditions of the actual
implementation?
What measures were established for pilot results? What target performance levels were
set for those measures? What targets were missed, and why?
In what ways has the solution been modified based on pilot results?
Implementation Planning:
What is the implementation schedule and timeline?
What new stakeholders were added as a result of the selected solution? Did any of the
stakeholders negatively shift their position after solution selection?
What were the survey results from the gallery walk?
Yes No
Yes No
Improvement Completion Checklist
46
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What you learned during this section:
Know the steps to implementing the solution
Understand the key questions that need to be answered
to complete the Improve phase.
Summary of Section
47
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control
End of Lesson: Improve – Implement Solution
Lean Six Sigma Training
48
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Control Phase
Lean Six Sigma Training
1
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Control Phase Overview
Lean Six Sigma Training
2
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Control develops the monitoring plan that will be
used to ensure the process gains are maintained,
develops the response plans should a problem with
the process develop, documents all processes and
procedures for the organization, reviews any
replication opportunities from the project, and
celebrates the projects success.
Control Phase Introduction
3
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ANALYZE
CONTROL
IMPROVE
MEASURE
DEFINE
Develop Process Control Monitoring Plan
Standardize Processes and Develop Change
Implementation Plans
Create Storyboards of Improvement
Identify Replication Opportunities
Complete Project Closure and Celebrate
Success
Processing Administration Adjusters PayablesProcessing Administration Adjusters Payables
Control Phase Overview
4
Loan Processing Cycle Time Sigma = >6
Mean CL: 8.86
1.91
15.81
1.31
3.31
5.31
7.31
9.31
11.31
13.31
15.31
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
In
di
vi
du
al
s
– C
hi
ca
go
L
oa
n
P
ro
ce
ss
in
g
C
yc
le
T
im
e
Mean CL: 1.52
-0.11
3.15
-0.11
0.39
0.89
1.39
1.89
2.39
2.89
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
In
di
vi
du
al
s
– C
hi
ca
go
L
P
L
oa
n
R
ev
ie
w
in
g
Ti
m
e
Chicago Loan Processing Cycle Time
Chicago LP Reviewing Time Chicago Package Accuracy – Error Type
Final Package Accuracy Sigma = 3.5 LP Reviewing Time Sigma = 3.1
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Develop
Process
Control Plan
Develop
Response
Plan
Document
Solutions
Control Chart
Dashboard
Measurement
Plan Matrix
Dashboard
Benefits
Realization
Response
Plan
Process
Management
Chart
Process
Reviews
Process and
Procedures
Communication
Plan
Control Tools
Control Approach
5
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Control Phase Deliverables
Define Measure Analyze Improve Control
Project Charter
Project Management
Project Plan
Process Definition
SIPOC
As-Is Process
Map
Quick Win
Identification
Stakeholder
Management
Stakeholder Map
Stakeholder
Management Plan
Communication
Plan
Voice of Customer
Customer
Identification
VOC Research
Plan
Kano Analysis
CTQ Identification
Root Cause Analysis
Affinity Diagram
Fishbone Diagram
and/or 5 Why’s
Lean Process
Analysis
Lean Tools and
Measures
Graphical Data
Analysis
Histogram
Pareto Chart
Box Plots
Correlation
Analysis
Statistical Data
Analysis
Linear Regression
Multiple
Regression
Root Causes
Identified
Quick Win
Identification
Identify Measures
X/Y Matrix
Data Collection
Operational
Definitions
Measurement
Systems Analysis
(MSA)
Data Collection
Plan
Describe and Display
Data
Histogram
Pareto Chart
Pie Chart
Run Chart
Control Charts
Baseline Performance
Sigma
Performance
Yield
Process
Capability
Quick Win
Identification
Identify and Select
Solutions
Generate Solutions
Benchmarking
Solutions
Prioritization Matrix
Solution Selection
Matrix
To-Be Process Map
Financial Impact of
Solutions
Cost/Benefit Analysis
Risk Planning and
Testing
Failure Modes and
Effects Analysis
(FMEA)
Pilot Plan
Implement Solutions
Multi-Generational
Product Plan (MGPP)
Implementation Plan
Stakeholder
Management
Project Storyboard
Process Control
Control Charts
Process
Monitoring Plan
Dashboard
Response Plan
Project
Documentation
Process
Procedures
Replication
Opportunities
Solution Transfer
Plan
6
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End of Lesson: Control Phase Overview
Lean Six Sigma Training
7
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Control – Process Control
Dashboards
Process Monitoring
Introduction to Process Management
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
1
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Define Process Management
Understand the benefits of an organization using Process
Management vs. Functional Management
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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A Process Management System is a
measurement system used to ensure the outputs
of processes are predictable (stable) and meet
customer requirements (capable).
Definition of Process Management System
3
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Why Process Management?
Provides a framework that will facilitate process improvement and
process design activity that ultimately drives the fulfillment of
important organizational goals.
Process Management enables an organization to:
Understand operations – process metrics
Select the right processes for improvements
Enable clear links between customer requirements and
internal operational activities
Drive process ownership and accountability
4
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What are the
functional
objectives
of these
departments?
What are their
real priorities?
Functional Management
FUNCTIONAL OBJECTIVES
Sales Under-
writing Processing Claims
Info.
Technology
5
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Many organizations have been based on functional differentiation or specialization.
This has resulted in the traditional vertical/hierarchical organizations. Management
direction, goals, and measurements have been deployed or cascaded down the existing
organizational structure.
In a traditional functional organization, the dominant focus of people is:
Please the boss…
The department’s specialized knowledge or skill.
The functional goals which may not have been stated in terms that the external
customer would recognize.
The people in your silo.
Successful performance is defined as winning for the function. Things often fall through
the cracks in this model causing fragmented efforts at satisfying external customers’
needs.
Functional Management System
6
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What are
employees’
REAL
priorities?
Process G
oals
Sales Under-
writing Processing Claims
Info.
Technology
Sell
Products
& Services
Process
Contracts
FUNCTIONAL OBJECTIVES
Process
Claims
Process Performance
What We Sell…
Process Performance
How We Sell…
Process Performance
The Service We Provide…
Process Performance
The Service We Provide…
Process Management
7
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The need to manage process quality with a link to strategic objectives
What are
employees’
REAL
priorities?
Functional Management vs. Process Management
8
What are
employees’
REAL
priorities?
CustomerDevelop
Products &
Services
Sales Process Claims Info.
Tech
Process
Contracts
FUNCTIONAL OBJECTIVES
Process G
oalsProcess
Claims
Process Performance
Process Performance
Process Performance
Process Performance
Under-
writing
Customer
Customer
Customer
STRATEGIC
OBJECTIVES
What are
employees’
REAL
priorities?
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Functional And Process Management Systems
From the figure above, we see the connection of core processes with Strategic Objectives, the linkage of process deliverables with customers, and the ongoing interest that Shareholders and Upper Management will have in functional contributions to traditional business indicators such as revenue, market share, profit, ROI, etc. To meet customer needs, Functional and Process Management systems must be integrated and harmonized so that both support Strategic Objectives.
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Provides a system of processes and indicators to help manage objectively
Focuses on the customer
Provides a common language within or across departments
Internally you know how well you are doing in the eyes of the customer
Provides accurate focus for improvement teams
Provides learnings supported by data that can be applied to other
processes
Benefits to Process Management
9
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From To
Function-Oriented
Somewhat Flexible, Efficient,
Effective Processes
High Walls between Functions
Uneven Cycle Time
Focus on the Function/Project
Value Stream is in the middle
Quality is added on
Cross-Functional
Process Focus
Increased Flexibility, Better
Efficiency, Greater Effectiveness
Walls between Functions
broken down
Improved Cycle Time
Focus on the Customer
Value Stream is end-to-end
Quality is built in
Sub-Optimization Integrated System
What will Change as a Result of Process
Management?
10
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Eliminating departmental barriers and becoming process focused takes time. As the shift occurs from well-defended functional-silos to cross-functional processes, the process becomes more flexible, efficient and effective at delivering quality to its customers. Department walls become less visible as the process and its outputs become more visible and dominant.
Process improvement results in processes that take less time, have steps that only add value to the customer, have fewer hand-offs, and fewer defects and errors.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
What does a Process Management System Look
Like?
There will be as much focus to processes as to individual functions
Everyone will be able to more efficiently utilize resources
Employees will know all of the process steps and how they add value
Employees will understand how the process is performing
Customers’ requirements will become known and everyone in the
organization will strive to meet or exceed them
Employees will help manage each other instead of escalating conflicts
Hand-offs between employees are smooth and boundaryless
Processes will be objectively and frequently measured and reviewed
11
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1. How are these different from traditional management approaches?
2. When your Process Management System is in place, what will be different for your organization compared to the past?
Copyright © 2016 Acuity Institute LLC. All rights reserved.
What you learned during this section:
The definition of Process Management
The benefits of an organization using Process Management
vs. Functional Management
Summary of Section
12
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Control – Process Control
Dashboards
Process Monitoring
Introduction to Process Management
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
13
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Understand what is meant by process control
Understand the types of control charts
Determine how to develop a monitoring plan
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
14
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Document and Standardize
(covered later in Project Documentation
section)
4. How can I assure that things will
continue?
Response Planning3. What do I do if I detect a change in
the process?
Process Monitoring2. How can I detect changes in my
process?
Earliest possible detection
Acceptable false alarm
Process Monitoring1. What should I monitor?
TopicQuestion
Four Key Questions for Managing and Controlling
Processes
15
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Process Control is:
The activities necessary to help to maintain the
gains the project team has accomplished through
their improvements.
What is Process Control?
16
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Using Control Charts to Monitor for Process
Control
The more we know about our process,
the more likely we will be able to predict
process performance
Using Control Charts to track and
monitor our process indicators is
critical to being able to Control and
manipulate the process outcome
(output)
17
therefore……
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Monitoring a Process for Control
Ongoing monitoring of the process is important for two reasons:
Ensure that the process is in control
Maintain process in its stable state
Compare with standards or control limits
If not within standard or out of control,
seek to identify special cause, eliminate
it and prevent recurrence
Identify opportunities for future improvements
18
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Monitoring a process helps us answer 5 key questions:
What is the current performance level?
Has the performance changed?
Do we need to adjust the process?
Do we need to improve the process?
How will the process perform in the future?
Adjust &
Improve
Compare
Current
Status
Predict
Future
Performance
Past
Performance
Present
Performance
For comparison with baseline
performance in Measure
Monitoring a Process
19
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X
X
X
X X X X
Y
Y
Y
Process Flow
Key input and
process
measures (X)
that track
variables
identified in your
project as Key
drivers of Project
Y variables
Key output
measures (Y) from
the customers’
perspective
Process Variables
(Xs)
Input
Variables
(Xs)
Outputs
(Ys)
NOTE: Whether or not improvements were
made to inputs, process, or outputs –
Monitoring should still be developed for all
critical measures
What Should We Monitor
20
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The measures that you choose to monitor in the control plan are the critical measures for your process. These are the process management measures that the Process Owner will rely on to track process performance over time.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Special Cause Variation
Sporadic, isolated events
that affect a Process
Management Role: Eliminate
Common Cause Variation
Expected, normal, random
fluctuations in Process
Management role: Reduce
Categorizing Variation on a Control Chart
21
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By observing how variation in the process causes results to fluctuate, we can
make some objective decisions about when to take action.
We do not always Want to take action.
When a process has special or assignable causes (i.e. out of control points) the
action necessary to improve the process is investigation and removal of those
special causes.
Processes that vary only from common causes will perform within the upper
and lower control limits. If a process has only normal or common causes of
variation, the focus should be on improving the process itself.
If process variation is not understood, time and money may be wasted reacting to a
variation that is normal. Fixing something that does not need to be fixed can
introduce more variation to the process and reduce the ability to meet
customer’s needs.
Key Point:
Using Control Charts to Make Decisions
22
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Out of Control
Upper Control Limit
Lower Control Limit
#1
fre
qu
en
cy
LSL USL
Not Capable of
Meeting Specification
fre
qu
en
cy
LSL USL
Not Capable of
Meeting Specification
In Control
Upper Control Limit
Lower Control Limit
#2
Four Possible States of the Process
23
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– Out of control and out of specification
This situation is the least optimal because you have two types of variation problems to consider and the process clearly isn’t meeting customer expectations.
– In control and not meeting customer specifications
Getting the process in control/stable is the first step in improving the process, however it is still not meeting customer expectations.
Note: It’s possible to be inside the control limits, yet still out of control as a result of shifts, patterns or trends in the data.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Capable of Meeting
Specification
fre
qu
en
cy
LSL USL
Out of Control
Upper Control Limit
Lower Control Limit
#3
In Control
Upper Control Limit
Lower Control Limit
#4
Capable of Meeting
Specification
fre
qu
en
cy
LSL USL
Four Possible States of the Process – Continued
24
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– Not in control but meeting customer specifications
In this scenario, the customer specifications are broad enough to accommodate the instability in the process but the customer is being satisfied purely by chance. Because the process is not predictable, we cannot guarantee the customers specifications will continue to be met.
– In control and meeting customer specifications
This is the most optimal state of the process. The process is both stable and capable. The goal is to have all processes in this state.
Note: It’s possible to be inside the control limits, yet still out of control as a result of shifts, patterns or trends in the data.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
It is inaccurate to put specification limits on a Control Chart.
Upper Control
Limit
Lower Control
Limit
“Control Limits”
Upper Spec
Limit
Lower Spec Limit
“Spec Limits”
Defined by the customer
Help determine if the process is
producing defects
Not plotted on control charts
Change when customer
requirements change
Defined by the process
performance
Help determine if the process is in
control
Plotted on control charts
Change when the process changes
Voice of
Process
Voice of
Customer
Key Concept – Control Limits vs. Specification
Limits
25
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Common Errors in Using Control Charts
Management/Process Owners do not buy into the concept
Special cause variation goes unnoticed
Non-random patterns are not studied for special causes
Poor or erroneous measurements are used
Data on charts is not current
Specifications are plotted on charts
26
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Use this chart to select the type of control chart to use.
Discrete
ImR Chart
Continuous
Type of Data
Subgroup Size
of 1
Rational Small
Subgroups (<8-
10)
Rational Large
Subgroups (>8-
10)
X and S
Chart
_
np Chart
Classification
(binomial data)
Sample Size is
Constant
Sample Size
Varies p chart
u Chart
Count
Opportunity
Varies
Opportunity is
Constant c chart
OR
OR
OR
OR
OR
X and R
Chart
_
Control Chart Types
27
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For X-bar and R and X-bar and S you will need to collect data in sets of points called subgroups, or logical groupings of data.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Overview of the different types of control charts
Discrete data control charts:
np Chart – used with classification data (i.e. pass/fail, good/bad) and charts the number of
defectives in each subgroup (sample size is constant).
p Chart – used with classification data (i.e. pass/fail, good/bad) and charts the proportion of
defectives in each subgroup (sample size varies).
u Chart – used with count data (e.g. number of defects) and charts the number of defects
per unit sampled in each subgroup (opportunity for defects varies).
c Chart – used with count data (e.g. number of defects) and charts the defect count per
sample (opportunity for defects is constant).
Continuous data control charts:
ImR Chart (Individuals) – for analyzing individual data points and rational subgroups can
not be formed from the data (data is assumed to be normally distributed).
X and R Chart – for analyzing the averages of small subgroups (<8-10) can be formed from
the data.
X and S Chart – for analyzing the averages of large subgroups (>8-10) can be formed from
the data.
Selecting a Control Chart
28
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Number of defects,
accidents or flaws
# of accidents/month
# of times the phone is
not answered within
three ring
# of breakdowns/week
# of flaws on an
automobile
Fraction of
“defectives”
fraction of requests not
processed within 15
minutes; fraction of
orders not processed
perfectly the first time
through (first-pass
quality)
Situation Chart Used
c Chart
u Chart
p Chart
np Chart
Variables data, one
figure at a time
sales, cost variances,
customer satisfaction
score, total cycle time
per order, average
cycle time per month
Variables data, sets of
measurements
Situation Chart Used
ImR Chart
(Individuals)
X and R
Chart
X and S
Chart
_
_
Examples of which Control Chart to Use
29
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X Chart
0
5
10
15
20
25
30
35
40
45
50
1/1
/20
04
1/8
/20
04
1/1
5/2
004
1/2
2/2
004
1/2
9/2
004
2/5
/20
04
2/1
2/2
004
2/1
9/2
004
2/2
6/2
004
3/4
/20
04
3/1
1/2
004
3/1
8/2
004
3/2
5/2
004
Date
Ch
ica
go
Lo
an
P
ro
ce
ss
ing
Cy
cle
Ti
me
Range Chart
0
5
10
15
20
25
1/1
/20
04
1/8
/20
04
1/1
5/2
004
1/2
2/2
004
1/2
9/2
004
2/5
/20
04
2/1
2/2
004
2/1
9/2
004
2/2
6/2
004
3/4
/20
04
3/1
1/2
004
3/1
8/2
004
3/2
5/2
004
Date
Ra
ng
e
The first control chart (X Chart) is
designed to monitor the variation
from data point to data point or
subgroup to subgroup (depending
on the control chart used).
The second control chart (Range
Chart) is designed to monitor
variation within a sample of data
points. The range of a process is a
reflection of the amount of variation
in the process and can be useful to
detect changes in variation.
It is possible that the averages could remain fairly consistent, but the spread within the
samples could fluctuate wildly. By monitoring both the variation between data points and
variation within data points, we can detect special cause variation more effectively.
Why Two Charts with Continuous Data?
30
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Chart3
39 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
45 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
20 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
14 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
39 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
41 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
38 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
15 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
Data1
Average
UCL
LCL
Date
Chicago Loan Processing Cycle Time
X Chart
Case Study Histogram
Chicago Loan Processing Cycle Time
45
20
24
31
24
29
28
34
33
25
25
25
24
30
30
32
31
27
21
36
28
35
35
26
42
35
29
22
29
26
32
27
28
28
26
30
32
36
28
39
22
30
32
24
31
31
45
36
25
37
21
31
28
22
43
33
32
38
26
28
26
26
27
40
24
29
27
37
20
37
31
30
39
34
33
43
31
36
29
30
37
31
25
33
33
25
25
29
37
28
38
39
21
28
36
30
32
35
21
18
29
26
27
30
32
35
25
25
28
24
33
28
30
26
36
33
27
28
24
27
40
25
29
33
32
24
22
26
37
28
29
35
26
33
23
27
34
29
25
36
35
31
32
36
32
29
39
32
33
30
20
36
31
34
33
32
24
24
26
37
33
27
22
30
27
37
26
34
30
32
36
30
33
35
24
31
27
27
26
32
35
25
30
14
36
34
30
28
35
31
32
28
24
40
31
24
30
33
28
21
31
38
34
26
27
34
28
18
26
28
34
28
34
24
32
34
30
33
37
36
30
33
32
35
33
30
31
22
29
33
26
23
32
28
29
28
32
41
35
29
34
26
28
35
32
17
33
35
37
25
33
33
26
36
35
27
26
30
25
28
32
36
33
31
34
24
28
29
38
32
29
31
25
30
37
34
25
19
29
32
22
36
31
24
37
36
31
27
26
21
41
31
24
30
24
19
37
41
21
21
32
19
20
27
34
37
36
45
31
33
30
29
36
18
23
37
36
36
30
29
33
39
27
27
28
29
35
24
26
32
31
31
26
18
29
37
28
22
38
26
31
31
41
27
35
27
38
32
33
30
34
32
38
27
29
31
14
33
30
31
35
27
31
34
33
27
37
37
21
22
32
20
38
28
31
22
29
33
36
26
17
25
29
41
39
38
36
33
22
32
34
25
29
23
30
26
30
29
32
27
26
35
34
30
29
41
26
37
25
33
43
29
37
42
29
28
30
39
34
28
24
34
29
35
27
42
37
42
31
29
37
30
30
18
22
24
40
35
32
38
32
36
34
19
32
31
30
29
36
33
36
36
25
33
24
32
27
34
27
28
27
40
26
30
26
31
28
24
35
31
25
29
38
31
23
30
40
33
30
27
30
31
30
30
30
25
36
32
32
26
34
31
28
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23
The data set is the Loan Processing Cycle Time for Chicago. We want to display and describe the variation in the process. Follow these instructions to create the Histogram:
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select Histogram from the menu.
4. Select Case Study Histogram from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Chicago Loan Processing Cycle Time from the menu in “First Variable”.
7. Click “OK”
8. Engine Room will generate a new worksheet entitled “Histogram”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Histogram and descriptive statisics?
Case Study Run Chart
Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Run Chart (Trend Chart in Engine Room):
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select Trend Chart from the menu.
4. Select Chicago Loan Processing Cycle Time from the menu in “Data”.
5. Select Date from the menu in “Time Period”.
6. Click “OK”
7. Engine Room will generate a new worksheet entitled “Trend”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Run Chart?
Case Study Control Chart
Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Individuals Chart (XmR in Engine Room):
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select XmR Chart from the menu.
4. Select Chicago Loan Processing Cycle Time from the menu in “Data”.
5. Select Date from the menu in “Time Period”.
6. Click “OK”
7. Engine Room will generate a new worksheet entitled “X and Moving Range”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Individuals Charts and descriptive statistics?
Case Study Pareto
Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0
The data set is from a checksheet. We want to display and describe the variation in the process. Follow these instructions to create the Pareto:
1. Click “Engine Room” from the toolbar above.
2. Select Define from the menu.
3. Select Pareto Analysis from the menu.
4. Select Case Study Pareto from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Number of Errors from the menu in “Data”.
7. Select Application Fields from the menu in “Category”.
8. Click “OK”
9. Engine Room will generate a new worksheet entitled “Pareto”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Pareto and descriptive statistics?
Case Study Correlation
Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
The data set is the number of loans processed per day.
We want to see if there is a strong relationship (correlation) between the loans processed per day and the number of personnel. Follow these instructions to perform correlation:
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select scatter plot from the menu.
4. Select Case Study Correlation from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Loans Processed from the menu in “Data”.
7.Select number of personnel from the menu in ‘Data-2 “.
8. Click “OK”
9. Engine Room will generate a new worksheet entitled “Scatter”.
When completed, answer the following questions:
1. How would you interpret the graph
2. What conclusions can you draw from p-value and the R-squared value?
Obtaining R Value
Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
This is the same data set we used for the scatter plot.
Now we want to obtain the “r” value (correlation coefficient) to help us detrmine the strength of the correlation. Follow these instructions to identify the correlation coefficient (a.k.a pearson coefficient):
1. Click “Insert” from the Excel toolbar above.
2. Select function from the menu.
3. Select statistical from the “Select a Category” menu
4. In the “Select a Function” menu, scroll down to PEARSON and select.
5. Click “OK”
6. To populate the field “Array 1”, in the excel worksheet select and highlight fields A1-A81.
7.To populate the field “Array 2”, in the excel worksheet select and highlight fields B1-B81
8. Click “OK”
9. Excel will generate an “r” value in the worksheet itself.
When completed, answer the following questions:
1. How would you interpret the “r” value (correlation coefficient)?
Case Study Regression
Loans Processed Loans per hour (average) (mins)
111 6.1
114 6.2
111 5.9
118 6.7
115 6.4
112 5.7
117 6.9
116 7
103 5.8
102 5.8
107 5.2
101 5.7
116 6.6
114 6.4
110 6
109 6
100 5.1
103 5.2
103 4.9
105 5.8
115 6.5
116 6.8
104 5.7
119 6.9
106 5.4
119 7
101 5.3
107 5.8
102 5.1
113 6.1
104 5.4
115 6.5
110 6
112 6
108 5.9
115 6.1
118 6.5
102 5.2
118 6.7
114 6.6
118 6.7
108 5.9
114 6.5
115 6.3
104 5.7
111 6.9
110 5.7
115 6.8
101 5.2
111 5.9
117 6.6
108 5.6
118 6.4
118 6.6
106 5.3
112 6
105 5.5
106 5.6
109 5.6
101 5.4
114 6.4
111 6.1
101 6.5
101 5.9
108 5.5
111 6.3
104 6
110 6.5
115 6.8
111 6.2
119 7
115 6.9
108 5.9
113 6.1
116 6.9
113 5.9
110 5.4
103 4.8
116 6.4
101 5.8
The data set is the Loans Processed.
We want to see if there is a correlation between the loans processed per hour and the total loans processed per day. Follow these instructions to perform regression:
1. Click “Engine Room” from the toolbar above.
2. Select Analyze from the menu.
3. Select Simple Regression from the menu.
4. Select Case Study Regression from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Loans Processed from the menu in the “Dependent Variable”.
7.Select Loans per hour from the menu in ‘Independent Variable”.
8. Click “OK”
9. Engine Room will generate a new worksheet entitled “Regression”.
When completed, answer the following questions:
1. How would you interpret the graph
2. What conclusions can you draw from p-value and the R-squared value?
Case Study Regression Results
SUMMARY OUTPUT 8.27 60.09
100 5.1
Regression Statistics 101 5.7
Multiple R 0.8193026767 101 5.3
R Square 0.671256876 101 5.2
Adjusted R Square 0.6670422206 101 5.4
Standard Error 3.2887153692 101 6.5
Observations 80 101 5.9
101 5.8
ANOVA 102 5.8
df SS MS F Significance F 102 5.1
Regression 1 1722.5793951901 1722.5793951901 159.26732 1.56980839556793E-20 102 5.2
Residual 78 843.6206048099 10.8156487796 103 5.8
Total 79 2566.2 103 5.2
103 4.9
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 103 4.8
Intercept 60.0865544884 3.983959925 15.0821181987 7.84476407641124E-25 52.1550977424 68.0180112345 104 5.7
X Variable 1 8.2681165172 0.6551537816 12.6201156889 1.56980839556406E-20 6.9638052344 9.5724278 104 5.4
104 5.7
104 6
Formula: y = 8.27x + 60.09 105 5.8
RESIDUAL OUTPUT 105 5.5
106 5.4
Observation Predicted Y Residuals 106 5.3
1 102.2539487261 -2.2539487261 106 5.6
2 107.2148186364 -6.2148186364 107 5.2
3 103.9075720295 -2.9075720295 107 5.8
4 103.0807603778 -2.0807603778 108 5.9
5 104.7343836812 -3.7343836812 108 5.9
6 113.8293118501 -12.8293118501 108 5.6
7 108.8684419398 -7.8684419398 108 5.5
8 108.0416302881 -7.0416302881 108 5.9
9 108.0416302881 -6.0416302881 109 6
10 102.2539487261 -0.2539487261 109 5.6
11 103.0807603778 -1.0807603778 110 6
12 108.0416302881 -5.0416302881 110 6
13 103.0807603778 -0.0807603778 110 5.7
14 100.6003254227 2.3996745773 110 6.5
15 99.7735137709 3.2264862291 110 5.4
16 107.2148186364 -3.2148186364 111 6.1
17 104.7343836812 -0.7343836812 111 5.9
18 107.2148186364 -3.2148186364 111 6.9
19 109.6952535916 -5.6952535916 111 5.9
20 108.0416302881 -3.0416302881 111 6.1
21 105.561195333 -0.561195333 111 6.3
22 104.7343836812 1.2656163188 111 6.2
23 103.9075720295 2.0924279705 112 5.7
24 106.3880069847 -0.3880069847 112 6
25 103.0807603778 3.9192396222 112 6
26 108.0416302881 -1.0416302881 113 6.1
27 108.8684419398 -0.8684419398 113 6.1
28 108.8684419398 -0.8684419398 113 5.9
29 106.3880069847 1.6119930153 114 6.2
30 105.561195333 2.438804667 114 6.4
31 108.8684419398 -0.8684419398 114 6.6
32 109.6952535916 -0.6952535916 114 6.5
33 106.3880069847 2.6119930153 114 6.4
34 109.6952535916 0.3047464084 115 6.4
35 109.6952535916 0.3047464084 115 6.5
36 107.2148186364 2.7851813636 115 6.5
37 113.8293118501 -3.8293118501 115 6.1
38 104.7343836812 5.2656163188 115 6.3
39 110.5220652433 0.4779347567 115 6.8
40 108.8684419398 2.1315580602 115 6.8
41 117.136558457 -6.136558457 115 6.9
42 108.8684419398 2.1315580602 116 7
43 110.5220652433 0.4779347567 116 6.6
44 112.1756885467 -1.1756885467 116 6.8
45 111.348876895 -0.348876895 116 6.9
46 107.2148186364 4.7851813636 116 6.4
47 109.6952535916 2.3047464084 117 6.9
48 109.6952535916 2.3047464084 117 6.6
49 110.5220652433 2.4779347567 118 6.7
50 110.5220652433 2.4779347567 118 6.5
51 108.8684419398 4.1315580602 118 6.7
52 111.348876895 2.651123105 118 6.7
53 113.0025001984 0.9974998016 118 6.4
54 114.6561235019 -0.6561235019 118 6.6
55 113.8293118501 0.1706881499 119 6.9
56 113.0025001984 0.9974998016 119 7
57 113.0025001984 1.9974998016 119 7
58 113.8293118501 1.1706881499
59 113.8293118501 1.1706881499
60 110.5220652433 4.4779347567
61 112.1756885467 2.8243114533
62 116.3097468053 -1.3097468053
63 116.3097468053 -1.3097468053
64 117.136558457 -2.136558457
65 117.9633701087 -1.9633701087
66 114.6561235019 1.3438764981
67 116.3097468053 -0.3097468053
68 117.136558457 -1.136558457
69 113.0025001984 2.9974998016
70 117.136558457 -0.136558457
71 114.6561235019 2.3438764981
72 115.4829351536 2.5170648464
73 113.8293118501 4.1706881499
74 115.4829351536 2.5170648464
75 115.4829351536 2.5170648464
76 113.0025001984 4.9974998016
77 114.6561235019 3.3438764981
78 117.136558457 1.863441543
79 117.9633701087 1.0366298913
80 117.9633701087 1.0366298913
Case Study Regression Results
Y
Predicted Y
Loans per hour (average) (mins)
Loans Processed
Loans per hour (average) (mins) Line Fit Plot
X and Moving Range
Date Chicago Loan Processing Cycle Time Average – X 30
1-Jan 39 Median – Range 5
2-Jan 25 LCL – X 14
3-Jan 26 UCL – X 45
4-Jan 45 UCL – Range 19
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
67% of the variation in total loans processed is explained by loans processed per hour. ** Since this is transactional data, this is considered a high r-squared value.
High R-Square value
The E-20 means there are 20 zeros before the 1.56981…so this number is effectively zero. Since this is less than 0.05 we reject the null hypothesis that m= 0. In practical terms, this indicates a strong correlation between loans per hour and total loans processed per day.
Low P-value so Strong Correlation indicated.
X and Moving Range
39 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
45 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
20 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
14 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
39 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
41 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
38 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
15 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
Data1
Average
UCL
LCL
Date
Chicago Loan Processing Cycle Time
X Chart
XMRData-4
37987 5 19.325
14 5 19.325
1 5 19.325
19 5 19.325
15 5 19.325
3 5 19.325
5 5 19.325
3 5 19.325
7 5 19.325
0 5 19.325
2 5 19.325
3 5 19.325
7 5 19.325
5 5 19.325
13 5 19.325
0 5 19.325
2 5 19.325
1 5 19.325
6 5 19.325
6 5 19.325
14 5 19.325
2 5 19.325
13 5 19.325
3 5 19.325
0 5 19.325
2 5 19.325
9 5 19.325
12 5 19.325
18 5 19.325
23 5 19.325
5 5 19.325
7 5 19.325
5 5 19.325
2 5 19.325
11 5 19.325
6 5 19.325
0 5 19.325
7 5 19.325
4 5 19.325
13 5 19.325
17 5 19.325
9 5 19.325
1 5 19.325
4 5 19.325
0 5 19.325
9 5 19.325
16 5 19.325
5 5 19.325
5 5 19.325
7 5 19.325
2 5 19.325
13 5 19.325
2 5 19.325
4 5 19.325
3 5 19.325
6 5 19.325
5 5 19.325
7 5 19.325
16 5 19.325
7 5 19.325
8 5 19.325
2 5 19.325
5 5 19.325
4 5 19.325
4 5 19.325
9 5 19.325
16 5 19.325
13 5 19.325
8 5 19.325
13 5 19.325
5 5 19.325
1 5 19.325
4 5 19.325
8 5 19.325
11 5 19.325
3 5 19.325
5 5 19.325
1 5 19.325
2 5 19.325
1 5 19.325
3 5 19.325
5 5 19.325
21 5 19.325
15 5 19.325
3 5 19.325
2 5 19.325
1 5 19.325
4 5 19.325
6 5 19.325
4 5 19.325
3 5 19.325
Range
Average
UCL(R)
Date
Range
Range Chart
XMRData-3
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
XMRData-2
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
XMRData-1
Date Chicago Loan Processing Cycle Time Average Range R-Mean UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Jan 25 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Jan 26 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Jan 45 29.5384615385 19 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Jan 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Jan 22 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Jan 25 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Jan 32 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Jan 32 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Jan 30 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Jan 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Jan 26 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Jan 21 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Jan 34 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Jan 34 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Jan 32 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Jan 33 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Jan 27 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Jan 21 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Jan 35 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Jan 37 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Jan 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Jan 27 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Jan 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Jan 20 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Jan 32 29.5384615385 12 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Jan 14 29.5384615385 18 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Jan 37 29.5384615385 23 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Jan 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Feb 39 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Feb 34 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Feb 25 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Feb 31 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Feb 31 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Feb 24 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Feb 28 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Feb 41 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Feb 24 29.5384615385 17 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Feb 33 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Feb 34 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Feb 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Feb 30 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Feb 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Feb 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Feb 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Feb 27 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Feb 34 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Feb 23 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Feb 25 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Feb 29 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Feb 32 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Feb 26 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Feb 31 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Feb 38 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Feb 22 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Feb 29 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Mar 37 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Mar 35 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Mar 30 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Mar 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Mar 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Mar 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Mar 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Mar 32 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Mar 19 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Mar 24 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Mar 23 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Mar 27 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Mar 19 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Mar 30 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Mar 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Mar 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Mar 31 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Mar 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Mar 28 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Mar 31 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Mar 36 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Mar 15 29.5384615385 21 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Mar 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Mar 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Mar 31 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Mar 30 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Mar 28 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Mar 32 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Mar 29 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
XMRData
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
XBSData
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
HistData
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 Average StdDev X Bar Bar S Bar LCL – S UCL – S LCL – X UCL – X
1 37987 37988 37989 37990 37991 37992 37993 37994 37995 37996 37997 37998 37999 38000 38001 38002 38003 38004 38005 38006 38007 38008 38009 38010 38011 38012 38013 38014 38015 38016 38017 38018 38019 38020 38021 38022 38023 38024 38025 38026 38027 38028 38029 38030 38031 38032 38033 38034 38035 38036 38037 38038 38039 38040 38041 38042 38043 38044 38045 38046 38047 38048 38049 38050 38051 38052 38053 38054 38055 38056 38057 38058 38059 38060 38061 38062 38063 38064 38065 38066 38067 38068 38069 38070 38071 38072 38073 38074 38075 38076 38077 38032 26.4133804475 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076
2 39 25 26 45 30 27 22 25 32 32 30 33 26 21 34 34 32 33 27 21 35 37 24 27 27 29 20 32 14 37 32 39 34 36 25 31 31 24 28 41 24 33 34 30 30 21 37 32 27 34 36 23 25 29 32 26 31 38 22 29 37 35 30 34 30 21 37 24 32 19 24 23 27 19 30 27 32 31 29 28 31 36 15 30 33 31 30 34 28 32 29 29.5384615385 5.706346744 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076
HistData-1
Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
1082 37
1083 24
1084 36
1085 31
1086 30
1087 37
1088 22
1089 20
1090 19
1091 29
1092 32
1093 22
1094 32
1095 41
1096 35
1097 37
1098 31
1099 32
1100 36
1101 36
1102 23
1103 37
1104 34
1105 31
1106 44
1107 30
1108 30
1109 32
1110 28
1111 20
1112 35
1113 24
1114 28
1115 33
1116 27
1117 26
1118 36
1119 32
1120 35
1121 28
1122 36
1123 31
1124 26
1125 27
1126 32
1127 31
1128 29
1129 34
1130 37
1131 24
1132 29
1133 37
1134 20
1135 33
1136 33
1137 22
1138 24
1139 22
1140 31
1141 25
1142 30
1143 22
1144 34
1145 37
1146 20
1147 23
1148 39
1149 19
1150 20
1151 25
1152 21
1153 27
1154 33
1155 31
1156 21
1157 34
1158 25
1159 35
1160 24
1161 23
1162 28
1163 31
1164 27
1165 29
1166 29
1167 25
1168 28
1169 29
1170 24
1171 19
1172 29
1173 42
1174 32
1175 35
1176 33
1177 32
1178 30
1179 18
1180 31
1181 20
1182 36
1183 21
1184 25
1185 39
1186 25
1187 30
1188 27
1189 29
1190 35
1191 34
1192 29
1193 32
1194 32
1195 43
1196 29
1197 40
1198 32
1199 25
1200 27
1201 33
1202 26
1203 27
1204 26
1205 24
1206 31
1207 27
1208 20
1209 27
1210 33
1211 25
1212 31
1213 30
1214 32
1215 36
1216 27
1217 32
1218 32
1219 32
1220 36
1221 39
1222 34
1223 24
1224 33
1225 30
1226 35
1227 34
1228 30
1229 32
1230 42
1231 24
1232 34
1233 34
1234 26
1235 28
1236 35
1237 30
1238 31
1239 38
1240 22
1241 32
1242 32
1243 22
1244 23
1245 35
1246 35
1247 31
1248 33
1249 36
1250 37
1251 24
1252 23
1253 33
1254 21
1255 34
1256 32
1257 28
1258 31
1259 29
1260 34
1261 17
1262 34
1263 22
1264 21
1265 34
1266 23
1267 41
1268 31
1269 31
1270 28
1271 26
1272 34
1273 20
1274 24
1275 21
1276 32
1277 30
1278 29
1279 27
1280 36
1281 25
1282 33
1283 23
1284 34
1285 33
1286 28
1287 17
1288 27
1289 29
1290 29
1291 32
1292 43
1293 30
1294 25
1295 29
1296 27
1297 28
1298 31
1299 31
1300 40
1301 28
1302 26
1303 33
1304 33
1305 33
1306 22
1307 40
1308 36
1309 27
1310 30
1311 40
1312 22
1313 26
1314 26
1315 29
1316 36
1317 22
1318 38
1319 24
1320 36
1321 29
1322 29
1323 35
1324 33
1325 31
1326 26
1327 27
1328 25
1329 26
1330 30
1331 32
1332 34
1333 32
1334 29
1335 42
1336 33
1337 25
1338 27
1339 26
1340 26
1341 15
1342 46
1343 20
1344 40
1345 26
1346 33
1347 22
1348 28
1349 25
1350 34
1351 34
1352 31
1353 25
1354 37
1355 23
1356 38
1357 23
1358 31
1359 32
1360 38
1361 28
1362 35
1363 24
1364 25
1365 29
1366 34
1367 33
1368 33
1369 38
1370 23
1371 30
1372 28
1373 33
1374 21
1375 35
1376 33
1377 35
1378 25
1379 31
1380 28
1381 24
1382 35
1383 30
1384 26
1385 30
1386 30
1387 30
1388 33
1389 24
1390 39
1391 31
1392 27
1393 22
1394 30
1395 23
1396 25
1397 28
1398 32
1399 25
1400 31
1401 34
1402 37
1403 21
1404 31
1405 36
1406 34
1407 25
1408 33
1409 34
1410 26
1411 35
1412 27
1413 24
1414 25
1415 26
1416 28
1417 31
1418 29
1419 33
1420 43
1421 18
1422 27
1423 23
Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
1082 37
1083 24
1084 36
1085 31
1086 30
1087 37
1088 22
1089 20
1090 19
1091 29
1092 32
1093 22
1094 32
1095 41
1096 35
1097 37
1098 31
1099 32
1100 36
1101 36
1102 23
1103 37
1104 34
1105 31
1106 44
1107 30
1108 30
1109 32
1110 28
1111 20
1112 35
1113 24
1114 28
1115 33
1116 27
1117 26
1118 36
1119 32
1120 35
1121 28
1122 36
1123 31
1124 26
1125 27
1126 32
1127 31
1128 29
1129 34
1130 37
1131 24
1132 29
1133 37
1134 20
1135 33
1136 33
1137 22
1138 24
1139 22
1140 31
1141 25
1142 30
1143 22
1144 34
1145 37
1146 20
1147 23
1148 39
1149 19
1150 20
1151 25
1152 21
1153 27
1154 33
1155 31
1156 21
1157 34
1158 25
1159 35
1160 24
1161 23
1162 28
1163 31
1164 27
1165 29
1166 29
1167 25
1168 28
1169 29
1170 24
1171 19
1172 29
1173 42
1174 32
1175 35
1176 33
1177 32
1178 30
1179 18
1180 31
1181 20
1182 36
1183 21
1184 25
1185 39
1186 25
1187 30
1188 27
1189 29
1190 35
1191 34
1192 29
1193 32
1194 32
1195 43
1196 29
1197 40
1198 32
1199 25
1200 27
1201 33
1202 26
1203 27
1204 26
1205 24
1206 31
1207 27
1208 20
1209 27
1210 33
1211 25
1212 31
1213 30
1214 32
1215 36
1216 27
1217 32
1218 32
1219 32
1220 36
1221 39
1222 34
1223 24
1224 33
1225 30
1226 35
1227 34
1228 30
1229 32
1230 42
1231 24
1232 34
1233 34
1234 26
1235 28
1236 35
1237 30
1238 31
1239 38
1240 22
1241 32
1242 32
1243 22
1244 23
1245 35
1246 35
1247 31
1248 33
1249 36
1250 37
1251 24
1252 23
1253 33
1254 21
1255 34
1256 32
1257 28
1258 31
1259 29
1260 34
1261 17
1262 34
1263 22
1264 21
1265 34
1266 23
1267 41
1268 31
1269 31
1270 28
1271 26
1272 34
1273 20
1274 24
1275 21
1276 32
1277 30
1278 29
1279 27
1280 36
1281 25
1282 33
1283 23
1284 34
1285 33
1286 28
1287 17
1288 27
1289 29
1290 29
1291 32
1292 43
1293 30
1294 25
1295 29
1296 27
1297 28
1298 31
1299 31
1300 40
1301 28
1302 26
1303 33
1304 33
1305 33
1306 22
1307 40
1308 36
1309 27
1310 30
1311 40
1312 22
1313 26
1314 26
1315 29
1316 36
1317 22
1318 38
1319 24
1320 36
1321 29
1322 29
1323 35
1324 33
1325 31
1326 26
1327 27
1328 25
1329 26
1330 30
1331 32
1332 34
1333 32
1334 29
1335 42
1336 33
1337 25
1338 27
1339 26
1340 26
1341 15
1342 46
1343 20
1344 40
1345 26
1346 33
1347 22
1348 28
1349 25
1350 34
1351 34
1352 31
1353 25
1354 37
1355 23
1356 38
1357 23
1358 31
1359 32
1360 38
1361 28
1362 35
1363 24
1364 25
1365 29
1366 34
1367 33
1368 33
1369 38
1370 23
1371 30
1372 28
1373 33
1374 21
1375 35
1376 33
1377 35
1378 25
1379 31
1380 28
1381 24
1382 35
1383 30
1384 26
1385 30
1386 30
1387 30
1388 33
1389 24
1390 39
1391 31
1392 27
1393 22
1394 30
1395 23
1396 25
1397 28
1398 32
1399 25
1400 31
1401 34
1402 37
1403 21
1404 31
1405 36
1406 34
1407 25
1408 33
1409 34
1410 26
1411 35
1412 27
1413 24
1414 25
1415 26
1416 28
1417 31
1418 29
1419 33
1420 43
1421 18
1422 27
1423 23
Chart4
37987 5 19.325
14 5 19.325
1 5 19.325
19 5 19.325
15 5 19.325
3 5 19.325
5 5 19.325
3 5 19.325
7 5 19.325
0 5 19.325
2 5 19.325
3 5 19.325
7 5 19.325
5 5 19.325
13 5 19.325
0 5 19.325
2 5 19.325
1 5 19.325
6 5 19.325
6 5 19.325
14 5 19.325
2 5 19.325
13 5 19.325
3 5 19.325
0 5 19.325
2 5 19.325
9 5 19.325
12 5 19.325
18 5 19.325
23 5 19.325
5 5 19.325
7 5 19.325
5 5 19.325
2 5 19.325
11 5 19.325
6 5 19.325
0 5 19.325
7 5 19.325
4 5 19.325
13 5 19.325
17 5 19.325
9 5 19.325
1 5 19.325
4 5 19.325
0 5 19.325
9 5 19.325
16 5 19.325
5 5 19.325
5 5 19.325
7 5 19.325
2 5 19.325
13 5 19.325
2 5 19.325
4 5 19.325
3 5 19.325
6 5 19.325
5 5 19.325
7 5 19.325
16 5 19.325
7 5 19.325
8 5 19.325
2 5 19.325
5 5 19.325
4 5 19.325
4 5 19.325
9 5 19.325
16 5 19.325
13 5 19.325
8 5 19.325
13 5 19.325
5 5 19.325
1 5 19.325
4 5 19.325
8 5 19.325
11 5 19.325
3 5 19.325
5 5 19.325
1 5 19.325
2 5 19.325
1 5 19.325
3 5 19.325
5 5 19.325
21 5 19.325
15 5 19.325
3 5 19.325
2 5 19.325
1 5 19.325
4 5 19.325
6 5 19.325
4 5 19.325
3 5 19.325
Range
Average
UCL(R)
Date
Range
Range Chart
Case Study Histogram
Chicago Loan Processing Cycle Time
45
20
24
31
24
29
28
34
33
25
25
25
24
30
30
32
31
27
21
36
28
35
35
26
42
35
29
22
29
26
32
27
28
28
26
30
32
36
28
39
22
30
32
24
31
31
45
36
25
37
21
31
28
22
43
33
32
38
26
28
26
26
27
40
24
29
27
37
20
37
31
30
39
34
33
43
31
36
29
30
37
31
25
33
33
25
25
29
37
28
38
39
21
28
36
30
32
35
21
18
29
26
27
30
32
35
25
25
28
24
33
28
30
26
36
33
27
28
24
27
40
25
29
33
32
24
22
26
37
28
29
35
26
33
23
27
34
29
25
36
35
31
32
36
32
29
39
32
33
30
20
36
31
34
33
32
24
24
26
37
33
27
22
30
27
37
26
34
30
32
36
30
33
35
24
31
27
27
26
32
35
25
30
14
36
34
30
28
35
31
32
28
24
40
31
24
30
33
28
21
31
38
34
26
27
34
28
18
26
28
34
28
34
24
32
34
30
33
37
36
30
33
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The data set is the Loan Processing Cycle Time for Chicago. We want to display and describe the variation in the process. Follow these instructions to create the Histogram:
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select Histogram from the menu.
4. Select Case Study Histogram from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Chicago Loan Processing Cycle Time from the menu in “First Variable”.
7. Click “OK”
8. Engine Room will generate a new worksheet entitled “Histogram”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Histogram and descriptive statisics?
Case Study Run Chart
Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Run Chart (Trend Chart in Engine Room):
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select Trend Chart from the menu.
4. Select Chicago Loan Processing Cycle Time from the menu in “Data”.
5. Select Date from the menu in “Time Period”.
6. Click “OK”
7. Engine Room will generate a new worksheet entitled “Trend”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Run Chart?
Case Study Control Chart
Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Individuals Chart (XmR in Engine Room):
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select XmR Chart from the menu.
4. Select Chicago Loan Processing Cycle Time from the menu in “Data”.
5. Select Date from the menu in “Time Period”.
6. Click “OK”
7. Engine Room will generate a new worksheet entitled “X and Moving Range”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Individuals Charts and descriptive statistics?
Case Study Pareto
Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0
The data set is from a checksheet. We want to display and describe the variation in the process. Follow these instructions to create the Pareto:
1. Click “Engine Room” from the toolbar above.
2. Select Define from the menu.
3. Select Pareto Analysis from the menu.
4. Select Case Study Pareto from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Number of Errors from the menu in “Data”.
7. Select Application Fields from the menu in “Category”.
8. Click “OK”
9. Engine Room will generate a new worksheet entitled “Pareto”.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Pareto and descriptive statistics?
Case Study Correlation
Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
The data set is the number of loans processed per day.
We want to see if there is a strong relationship (correlation) between the loans processed per day and the number of personnel. Follow these instructions to perform correlation:
1. Click “Engine Room” from the toolbar above.
2. Select Measure from the menu.
3. Select scatter plot from the menu.
4. Select Case Study Correlation from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Loans Processed from the menu in “Data”.
7.Select number of personnel from the menu in ‘Data-2 “.
8. Click “OK”
9. Engine Room will generate a new worksheet entitled “Scatter”.
When completed, answer the following questions:
1. How would you interpret the graph
2. What conclusions can you draw from p-value and the R-squared value?
Obtaining R Value
Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
This is the same data set we used for the scatter plot.
Now we want to obtain the “r” value (correlation coefficient) to help us detrmine the strength of the correlation. Follow these instructions to identify the correlation coefficient (a.k.a pearson coefficient):
1. Click “Insert” from the Excel toolbar above.
2. Select function from the menu.
3. Select statistical from the “Select a Category” menu
4. In the “Select a Function” menu, scroll down to PEARSON and select.
5. Click “OK”
6. To populate the field “Array 1”, in the excel worksheet select and highlight fields A1-A81.
7.To populate the field “Array 2”, in the excel worksheet select and highlight fields B1-B81
8. Click “OK”
9. Excel will generate an “r” value in the worksheet itself.
When completed, answer the following questions:
1. How would you interpret the “r” value (correlation coefficient)?
Case Study Regression
Loans Processed Loans per hour (average) (mins)
111 6.1
114 6.2
111 5.9
118 6.7
115 6.4
112 5.7
117 6.9
116 7
103 5.8
102 5.8
107 5.2
101 5.7
116 6.6
114 6.4
110 6
109 6
100 5.1
103 5.2
103 4.9
105 5.8
115 6.5
116 6.8
104 5.7
119 6.9
106 5.4
119 7
101 5.3
107 5.8
102 5.1
113 6.1
104 5.4
115 6.5
110 6
112 6
108 5.9
115 6.1
118 6.5
102 5.2
118 6.7
114 6.6
118 6.7
108 5.9
114 6.5
115 6.3
104 5.7
111 6.9
110 5.7
115 6.8
101 5.2
111 5.9
117 6.6
108 5.6
118 6.4
118 6.6
106 5.3
112 6
105 5.5
106 5.6
109 5.6
101 5.4
114 6.4
111 6.1
101 6.5
101 5.9
108 5.5
111 6.3
104 6
110 6.5
115 6.8
111 6.2
119 7
115 6.9
108 5.9
113 6.1
116 6.9
113 5.9
110 5.4
103 4.8
116 6.4
101 5.8
The data set is the Loans Processed.
We want to see if there is a correlation between the loans processed per hour and the total loans processed per day. Follow these instructions to perform regression:
1. Click “Engine Room” from the toolbar above.
2. Select Analyze from the menu.
3. Select Simple Regression from the menu.
4. Select Case Study Regression from the menu in “Select Worksheet”.
5. Click “OK”
6. Select Loans Processed from the menu in the “Dependent Variable”.
7.Select Loans per hour from the menu in ‘Independent Variable”.
8. Click “OK”
9. Engine Room will generate a new worksheet entitled “Regression”.
When completed, answer the following questions:
1. How would you interpret the graph
2. What conclusions can you draw from p-value and the R-squared value?
Case Study Regression Results
SUMMARY OUTPUT 8.27 60.09
100 5.1
Regression Statistics 101 5.7
Multiple R 0.8193026767 101 5.3
R Square 0.671256876 101 5.2
Adjusted R Square 0.6670422206 101 5.4
Standard Error 3.2887153692 101 6.5
Observations 80 101 5.9
101 5.8
ANOVA 102 5.8
df SS MS F Significance F 102 5.1
Regression 1 1722.5793951901 1722.5793951901 159.26732 1.56980839556793E-20 102 5.2
Residual 78 843.6206048099 10.8156487796 103 5.8
Total 79 2566.2 103 5.2
103 4.9
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 103 4.8
Intercept 60.0865544884 3.983959925 15.0821181987 7.84476407641124E-25 52.1550977424 68.0180112345 104 5.7
X Variable 1 8.2681165172 0.6551537816 12.6201156889 1.56980839556406E-20 6.9638052344 9.5724278 104 5.4
104 5.7
104 6
Formula: y = 8.27x + 60.09 105 5.8
RESIDUAL OUTPUT 105 5.5
106 5.4
Observation Predicted Y Residuals 106 5.3
1 102.2539487261 -2.2539487261 106 5.6
2 107.2148186364 -6.2148186364 107 5.2
3 103.9075720295 -2.9075720295 107 5.8
4 103.0807603778 -2.0807603778 108 5.9
5 104.7343836812 -3.7343836812 108 5.9
6 113.8293118501 -12.8293118501 108 5.6
7 108.8684419398 -7.8684419398 108 5.5
8 108.0416302881 -7.0416302881 108 5.9
9 108.0416302881 -6.0416302881 109 6
10 102.2539487261 -0.2539487261 109 5.6
11 103.0807603778 -1.0807603778 110 6
12 108.0416302881 -5.0416302881 110 6
13 103.0807603778 -0.0807603778 110 5.7
14 100.6003254227 2.3996745773 110 6.5
15 99.7735137709 3.2264862291 110 5.4
16 107.2148186364 -3.2148186364 111 6.1
17 104.7343836812 -0.7343836812 111 5.9
18 107.2148186364 -3.2148186364 111 6.9
19 109.6952535916 -5.6952535916 111 5.9
20 108.0416302881 -3.0416302881 111 6.1
21 105.561195333 -0.561195333 111 6.3
22 104.7343836812 1.2656163188 111 6.2
23 103.9075720295 2.0924279705 112 5.7
24 106.3880069847 -0.3880069847 112 6
25 103.0807603778 3.9192396222 112 6
26 108.0416302881 -1.0416302881 113 6.1
27 108.8684419398 -0.8684419398 113 6.1
28 108.8684419398 -0.8684419398 113 5.9
29 106.3880069847 1.6119930153 114 6.2
30 105.561195333 2.438804667 114 6.4
31 108.8684419398 -0.8684419398 114 6.6
32 109.6952535916 -0.6952535916 114 6.5
33 106.3880069847 2.6119930153 114 6.4
34 109.6952535916 0.3047464084 115 6.4
35 109.6952535916 0.3047464084 115 6.5
36 107.2148186364 2.7851813636 115 6.5
37 113.8293118501 -3.8293118501 115 6.1
38 104.7343836812 5.2656163188 115 6.3
39 110.5220652433 0.4779347567 115 6.8
40 108.8684419398 2.1315580602 115 6.8
41 117.136558457 -6.136558457 115 6.9
42 108.8684419398 2.1315580602 116 7
43 110.5220652433 0.4779347567 116 6.6
44 112.1756885467 -1.1756885467 116 6.8
45 111.348876895 -0.348876895 116 6.9
46 107.2148186364 4.7851813636 116 6.4
47 109.6952535916 2.3047464084 117 6.9
48 109.6952535916 2.3047464084 117 6.6
49 110.5220652433 2.4779347567 118 6.7
50 110.5220652433 2.4779347567 118 6.5
51 108.8684419398 4.1315580602 118 6.7
52 111.348876895 2.651123105 118 6.7
53 113.0025001984 0.9974998016 118 6.4
54 114.6561235019 -0.6561235019 118 6.6
55 113.8293118501 0.1706881499 119 6.9
56 113.0025001984 0.9974998016 119 7
57 113.0025001984 1.9974998016 119 7
58 113.8293118501 1.1706881499
59 113.8293118501 1.1706881499
60 110.5220652433 4.4779347567
61 112.1756885467 2.8243114533
62 116.3097468053 -1.3097468053
63 116.3097468053 -1.3097468053
64 117.136558457 -2.136558457
65 117.9633701087 -1.9633701087
66 114.6561235019 1.3438764981
67 116.3097468053 -0.3097468053
68 117.136558457 -1.136558457
69 113.0025001984 2.9974998016
70 117.136558457 -0.136558457
71 114.6561235019 2.3438764981
72 115.4829351536 2.5170648464
73 113.8293118501 4.1706881499
74 115.4829351536 2.5170648464
75 115.4829351536 2.5170648464
76 113.0025001984 4.9974998016
77 114.6561235019 3.3438764981
78 117.136558457 1.863441543
79 117.9633701087 1.0366298913
80 117.9633701087 1.0366298913
Case Study Regression Results
Y
Predicted Y
Loans per hour (average) (mins)
Loans Processed
Loans per hour (average) (mins) Line Fit Plot
X and Moving Range
Date Chicago Loan Processing Cycle Time Average – X 30
1-Jan 39 Median – Range 5
2-Jan 25 LCL – X 14
3-Jan 26 UCL – X 45
4-Jan 45 UCL – Range 19
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
67% of the variation in total loans processed is explained by loans processed per hour. ** Since this is transactional data, this is considered a high r-squared value.
High R-Square value
The E-20 means there are 20 zeros before the 1.56981…so this number is effectively zero. Since this is less than 0.05 we reject the null hypothesis that m= 0. In practical terms, this indicates a strong correlation between loans per hour and total loans processed per day.
Low P-value so Strong Correlation indicated.
X and Moving Range
39 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
45 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
20 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
14 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
39 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
41 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
38 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
15 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
Data1
Average
UCL
LCL
Date
Chicago Loan Processing Cycle Time
X Chart
XMRData-4
37987 5 19.325
14 5 19.325
1 5 19.325
19 5 19.325
15 5 19.325
3 5 19.325
5 5 19.325
3 5 19.325
7 5 19.325
0 5 19.325
2 5 19.325
3 5 19.325
7 5 19.325
5 5 19.325
13 5 19.325
0 5 19.325
2 5 19.325
1 5 19.325
6 5 19.325
6 5 19.325
14 5 19.325
2 5 19.325
13 5 19.325
3 5 19.325
0 5 19.325
2 5 19.325
9 5 19.325
12 5 19.325
18 5 19.325
23 5 19.325
5 5 19.325
7 5 19.325
5 5 19.325
2 5 19.325
11 5 19.325
6 5 19.325
0 5 19.325
7 5 19.325
4 5 19.325
13 5 19.325
17 5 19.325
9 5 19.325
1 5 19.325
4 5 19.325
0 5 19.325
9 5 19.325
16 5 19.325
5 5 19.325
5 5 19.325
7 5 19.325
2 5 19.325
13 5 19.325
2 5 19.325
4 5 19.325
3 5 19.325
6 5 19.325
5 5 19.325
7 5 19.325
16 5 19.325
7 5 19.325
8 5 19.325
2 5 19.325
5 5 19.325
4 5 19.325
4 5 19.325
9 5 19.325
16 5 19.325
13 5 19.325
8 5 19.325
13 5 19.325
5 5 19.325
1 5 19.325
4 5 19.325
8 5 19.325
11 5 19.325
3 5 19.325
5 5 19.325
1 5 19.325
2 5 19.325
1 5 19.325
3 5 19.325
5 5 19.325
21 5 19.325
15 5 19.325
3 5 19.325
2 5 19.325
1 5 19.325
4 5 19.325
6 5 19.325
4 5 19.325
3 5 19.325
Range
Average
UCL(R)
Date
Range
Range Chart
XMRData-3
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
XMRData-2
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
XMRData-1
Date Chicago Loan Processing Cycle Time Average Range R-Mean UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Jan 25 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Jan 26 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Jan 45 29.5384615385 19 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Jan 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Jan 22 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Jan 25 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Jan 32 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Jan 32 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Jan 30 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Jan 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Jan 26 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Jan 21 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Jan 34 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Jan 34 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Jan 32 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Jan 33 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Jan 27 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Jan 21 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Jan 35 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Jan 37 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Jan 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Jan 27 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Jan 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Jan 20 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Jan 32 29.5384615385 12 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Jan 14 29.5384615385 18 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Jan 37 29.5384615385 23 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Jan 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Feb 39 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Feb 34 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Feb 25 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Feb 31 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Feb 31 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Feb 24 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Feb 28 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Feb 41 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Feb 24 29.5384615385 17 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Feb 33 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Feb 34 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Feb 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Feb 30 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Feb 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Feb 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Feb 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Feb 27 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Feb 34 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Feb 23 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Feb 25 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Feb 29 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Feb 32 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Feb 26 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Feb 31 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Feb 38 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Feb 22 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Feb 29 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Mar 37 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Mar 35 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Mar 30 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Mar 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Mar 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Mar 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Mar 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Mar 32 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Mar 19 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Mar 24 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Mar 23 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Mar 27 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Mar 19 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Mar 30 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Mar 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Mar 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Mar 31 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Mar 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Mar 28 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Mar 31 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Mar 36 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Mar 15 29.5384615385 21 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Mar 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Mar 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Mar 31 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Mar 30 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Mar 28 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Mar 32 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Mar 29 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
XMRData
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
XBSData
Date Chicago Loan Processing Cycle Time Average Range R-Median UCL – Range LCL – X UCL – X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
HistData
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 Average StdDev X Bar Bar S Bar LCL – S UCL – S LCL – X UCL – X
1 37987 37988 37989 37990 37991 37992 37993 37994 37995 37996 37997 37998 37999 38000 38001 38002 38003 38004 38005 38006 38007 38008 38009 38010 38011 38012 38013 38014 38015 38016 38017 38018 38019 38020 38021 38022 38023 38024 38025 38026 38027 38028 38029 38030 38031 38032 38033 38034 38035 38036 38037 38038 38039 38040 38041 38042 38043 38044 38045 38046 38047 38048 38049 38050 38051 38052 38053 38054 38055 38056 38057 38058 38059 38060 38061 38062 38063 38064 38065 38066 38067 38068 38069 38070 38071 38072 38073 38074 38075 38076 38077 38032 26.4133804475 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076
2 39 25 26 45 30 27 22 25 32 32 30 33 26 21 34 34 32 33 27 21 35 37 24 27 27 29 20 32 14 37 32 39 34 36 25 31 31 24 28 41 24 33 34 30 30 21 37 32 27 34 36 23 25 29 32 26 31 38 22 29 37 35 30 34 30 21 37 24 32 19 24 23 27 19 30 27 32 31 29 28 31 36 15 30 33 31 30 34 28 32 29 29.5384615385 5.706346744 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076
HistData-1
Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
1082 37
1083 24
1084 36
1085 31
1086 30
1087 37
1088 22
1089 20
1090 19
1091 29
1092 32
1093 22
1094 32
1095 41
1096 35
1097 37
1098 31
1099 32
1100 36
1101 36
1102 23
1103 37
1104 34
1105 31
1106 44
1107 30
1108 30
1109 32
1110 28
1111 20
1112 35
1113 24
1114 28
1115 33
1116 27
1117 26
1118 36
1119 32
1120 35
1121 28
1122 36
1123 31
1124 26
1125 27
1126 32
1127 31
1128 29
1129 34
1130 37
1131 24
1132 29
1133 37
1134 20
1135 33
1136 33
1137 22
1138 24
1139 22
1140 31
1141 25
1142 30
1143 22
1144 34
1145 37
1146 20
1147 23
1148 39
1149 19
1150 20
1151 25
1152 21
1153 27
1154 33
1155 31
1156 21
1157 34
1158 25
1159 35
1160 24
1161 23
1162 28
1163 31
1164 27
1165 29
1166 29
1167 25
1168 28
1169 29
1170 24
1171 19
1172 29
1173 42
1174 32
1175 35
1176 33
1177 32
1178 30
1179 18
1180 31
1181 20
1182 36
1183 21
1184 25
1185 39
1186 25
1187 30
1188 27
1189 29
1190 35
1191 34
1192 29
1193 32
1194 32
1195 43
1196 29
1197 40
1198 32
1199 25
1200 27
1201 33
1202 26
1203 27
1204 26
1205 24
1206 31
1207 27
1208 20
1209 27
1210 33
1211 25
1212 31
1213 30
1214 32
1215 36
1216 27
1217 32
1218 32
1219 32
1220 36
1221 39
1222 34
1223 24
1224 33
1225 30
1226 35
1227 34
1228 30
1229 32
1230 42
1231 24
1232 34
1233 34
1234 26
1235 28
1236 35
1237 30
1238 31
1239 38
1240 22
1241 32
1242 32
1243 22
1244 23
1245 35
1246 35
1247 31
1248 33
1249 36
1250 37
1251 24
1252 23
1253 33
1254 21
1255 34
1256 32
1257 28
1258 31
1259 29
1260 34
1261 17
1262 34
1263 22
1264 21
1265 34
1266 23
1267 41
1268 31
1269 31
1270 28
1271 26
1272 34
1273 20
1274 24
1275 21
1276 32
1277 30
1278 29
1279 27
1280 36
1281 25
1282 33
1283 23
1284 34
1285 33
1286 28
1287 17
1288 27
1289 29
1290 29
1291 32
1292 43
1293 30
1294 25
1295 29
1296 27
1297 28
1298 31
1299 31
1300 40
1301 28
1302 26
1303 33
1304 33
1305 33
1306 22
1307 40
1308 36
1309 27
1310 30
1311 40
1312 22
1313 26
1314 26
1315 29
1316 36
1317 22
1318 38
1319 24
1320 36
1321 29
1322 29
1323 35
1324 33
1325 31
1326 26
1327 27
1328 25
1329 26
1330 30
1331 32
1332 34
1333 32
1334 29
1335 42
1336 33
1337 25
1338 27
1339 26
1340 26
1341 15
1342 46
1343 20
1344 40
1345 26
1346 33
1347 22
1348 28
1349 25
1350 34
1351 34
1352 31
1353 25
1354 37
1355 23
1356 38
1357 23
1358 31
1359 32
1360 38
1361 28
1362 35
1363 24
1364 25
1365 29
1366 34
1367 33
1368 33
1369 38
1370 23
1371 30
1372 28
1373 33
1374 21
1375 35
1376 33
1377 35
1378 25
1379 31
1380 28
1381 24
1382 35
1383 30
1384 26
1385 30
1386 30
1387 30
1388 33
1389 24
1390 39
1391 31
1392 27
1393 22
1394 30
1395 23
1396 25
1397 28
1398 32
1399 25
1400 31
1401 34
1402 37
1403 21
1404 31
1405 36
1406 34
1407 25
1408 33
1409 34
1410 26
1411 35
1412 27
1413 24
1414 25
1415 26
1416 28
1417 31
1418 29
1419 33
1420 43
1421 18
1422 27
1423 23
Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
1082 37
1083 24
1084 36
1085 31
1086 30
1087 37
1088 22
1089 20
1090 19
1091 29
1092 32
1093 22
1094 32
1095 41
1096 35
1097 37
1098 31
1099 32
1100 36
1101 36
1102 23
1103 37
1104 34
1105 31
1106 44
1107 30
1108 30
1109 32
1110 28
1111 20
1112 35
1113 24
1114 28
1115 33
1116 27
1117 26
1118 36
1119 32
1120 35
1121 28
1122 36
1123 31
1124 26
1125 27
1126 32
1127 31
1128 29
1129 34
1130 37
1131 24
1132 29
1133 37
1134 20
1135 33
1136 33
1137 22
1138 24
1139 22
1140 31
1141 25
1142 30
1143 22
1144 34
1145 37
1146 20
1147 23
1148 39
1149 19
1150 20
1151 25
1152 21
1153 27
1154 33
1155 31
1156 21
1157 34
1158 25
1159 35
1160 24
1161 23
1162 28
1163 31
1164 27
1165 29
1166 29
1167 25
1168 28
1169 29
1170 24
1171 19
1172 29
1173 42
1174 32
1175 35
1176 33
1177 32
1178 30
1179 18
1180 31
1181 20
1182 36
1183 21
1184 25
1185 39
1186 25
1187 30
1188 27
1189 29
1190 35
1191 34
1192 29
1193 32
1194 32
1195 43
1196 29
1197 40
1198 32
1199 25
1200 27
1201 33
1202 26
1203 27
1204 26
1205 24
1206 31
1207 27
1208 20
1209 27
1210 33
1211 25
1212 31
1213 30
1214 32
1215 36
1216 27
1217 32
1218 32
1219 32
1220 36
1221 39
1222 34
1223 24
1224 33
1225 30
1226 35
1227 34
1228 30
1229 32
1230 42
1231 24
1232 34
1233 34
1234 26
1235 28
1236 35
1237 30
1238 31
1239 38
1240 22
1241 32
1242 32
1243 22
1244 23
1245 35
1246 35
1247 31
1248 33
1249 36
1250 37
1251 24
1252 23
1253 33
1254 21
1255 34
1256 32
1257 28
1258 31
1259 29
1260 34
1261 17
1262 34
1263 22
1264 21
1265 34
1266 23
1267 41
1268 31
1269 31
1270 28
1271 26
1272 34
1273 20
1274 24
1275 21
1276 32
1277 30
1278 29
1279 27
1280 36
1281 25
1282 33
1283 23
1284 34
1285 33
1286 28
1287 17
1288 27
1289 29
1290 29
1291 32
1292 43
1293 30
1294 25
1295 29
1296 27
1297 28
1298 31
1299 31
1300 40
1301 28
1302 26
1303 33
1304 33
1305 33
1306 22
1307 40
1308 36
1309 27
1310 30
1311 40
1312 22
1313 26
1314 26
1315 29
1316 36
1317 22
1318 38
1319 24
1320 36
1321 29
1322 29
1323 35
1324 33
1325 31
1326 26
1327 27
1328 25
1329 26
1330 30
1331 32
1332 34
1333 32
1334 29
1335 42
1336 33
1337 25
1338 27
1339 26
1340 26
1341 15
1342 46
1343 20
1344 40
1345 26
1346 33
1347 22
1348 28
1349 25
1350 34
1351 34
1352 31
1353 25
1354 37
1355 23
1356 38
1357 23
1358 31
1359 32
1360 38
1361 28
1362 35
1363 24
1364 25
1365 29
1366 34
1367 33
1368 33
1369 38
1370 23
1371 30
1372 28
1373 33
1374 21
1375 35
1376 33
1377 35
1378 25
1379 31
1380 28
1381 24
1382 35
1383 30
1384 26
1385 30
1386 30
1387 30
1388 33
1389 24
1390 39
1391 31
1392 27
1393 22
1394 30
1395 23
1396 25
1397 28
1398 32
1399 25
1400 31
1401 34
1402 37
1403 21
1404 31
1405 36
1406 34
1407 25
1408 33
1409 34
1410 26
1411 35
1412 27
1413 24
1414 25
1415 26
1416 28
1417 31
1418 29
1419 33
1420 43
1421 18
1422 27
1423 23
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Important Distinctions
Defective
Defect
Discrete Data: Defect vs. Defective
Any nonconformance; may have multiple “defects”
per unit
Use: “c” or “u” charts
A unit or product that contains one or more defects
(i.e. it does not matter the amount of defects it is
either right or wrong)
Use: “p” or “np” charts
31
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Presenter
Presentation Notes
Notes:
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Summary of Variation and Control Charts
Control limits are calculated from the process data;
specification limits come from the customer: they are
both important
Process variation can be stable and still be
unacceptable; to reduce common cause variation,
make fundamental improvements to the vital few
root causes
Variation is the “voice of the process” – learn to
listen and respond appropriately
32
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Presenter
Presentation Notes
Notes:
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Interpret Control Chart
or Run Chart
Develop solutions for
special causes and
implement as
appropriate
Investigate the specific
data points related to
the special causes
Special Causes
Develop solutions for
the “vital few” process
and input Xs
Common
Causes
Investigate all of the
variation by identifying
the “vital few” process
Xs and input Xs
Response Strategy Summary
33
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Presenter
Presentation Notes
Notes:
Understanding the source of variation is important to devising a sound strategy for process control and improvement. The source of variation has important consequences for the type of actions required.
If a process exhibits common cause variation the appropriate action is to investigate all of the data points. Finding the “vital few” causal factors (Xs) that explain common cause variation is more difficult than finding causal factors for special causes because they are not as obvious.
If a process exhibits special cause variation the appropriate action is to investigate those specific data points related to the special cause signals. In most cases the investigation will reveal important causal factors (Xs) related to the special cause (s). The results of the investigation should be integrated into an action plan for immediately addressing the special causes.
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What is a Process Monitoring Plan?
The Process Monitoring Plan Includes:
CTQ – The measurable requirement (Critical to Quality aspect)
the customer has of the process.
Process Steps Where the CTQ is Measured – The step in the
process where the CTQ will be measured and data collected.
Data Collection Method – A description of the method that will
be followed to collect the data.
Data Collection Frequency – The frequency that the data will be
collected (hourly, daily, twice a week, monthly, etc.).
Owner – The person responsible for collecting the data.
Process
Monitoring Plan
34
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What you learned during this section:
What is meant by process control
The types of control charts
How to develop a monitoring plan
Summary of Section
35
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Control – Process Control
Dashboards
Process Monitoring
Introduction to Process Management
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
36
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Understand what a dashboard is
Understand the questions to consider when developing a
dashboard
Utilize a dashboard example to begin development of your
project dashboard
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
37
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A process dashboard provides a visual picture of the process through data diagrams and charts.
Visualizing your process allows you to fully comprehend process performance and communicate
it to your champions and stakeholders.
Preliminary Process Dashboard
Customer: Applicant CTQ Spec: 100%
Process: New Business
Department: Customer Engagement
Owner: M. Gunner Projects: 0
88 Defects/28908 Opps
Weighted average: 5-7 opportunities/unit
4.4 Sigma without India.
India Sigma is 3.6 on 100% QA. Improving steadily.
Some Customer
Satisfaction COPQ
Defects
0
2
4
6
8
10
12
14
16
18
20
Unplanned Emp. AbsenceCustomer Not Available for
Call Back
Rejected System Downtime Hold for Sup Approval
Category
#
O
bs
er
va
tio
ns
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
38
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In planning for the design of a process dashboard you must select which
chart/tool is the best to use to display process performance and results. To do
this, you must first decide what you want the process dashboard to tell or
describe about the process it is monitoring.
Some key questions your process dashboard should answer:
1. Is my process capable? Is it meeting customer requirements?
2. If it isn’t meeting customer requirements, what might be driving the
lack of capability? What is the biggest defect contributing to the overall
defect rate?
3. How much variation is in my process?
Preliminary Process Dashboard
39
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Used to confirm relationship between two variablesAnalysisScatter Plot
Type of chart used to display data related to a process
variable in sequence over time to identify changes
MonitoringRun Charts
Used to track the relationship between two sets of data
over time
AnalysisRegression (Advanced tool)
Used to depict percentages of total in a circular diagramDisplayPie Chart
Used to identify and prioritize problems or causes of
problems
Monitoring/AnalysisPareto Analysis
Used to display frequency of data in column form. Also
used to prepare Pareto charts
MonitoringHistogram
Used to help understand variation and to control and
improve a process
MonitoringControl Charts
Used to brainstorm and logically organize possible
causes for a particular effect
AnalysisCause and Effect Diagrams
Used to display simple comparisons between series of
data
DisplayBar Chart
PurposeTypeChart/Tool
It is not necessary to use all of the charts, just choose the ones that best suit the type of data and purpose of
display for your process.
Overview of Data Tools
40
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√Run ChartPercent of Invoices that are received via electronic data interchange
EDI InvoicingInvoice
OutputProcessInputDisplayMeasurementCustomer
Requirement or
Process
Indicator
Unit Being
Processed
√Histogram and/or Run
Chart
Customer Set-Up: Time form CMM
launch to input completed
Credit Approval: Time from credit
application hand-off to credit application
approved/rejected.
Lease/Sale Contract: Time from lease
created to lease activated
Case Creation: Time from lease created
to delivery case created
Order Fulfillment Sub-
process Cycle times
Order
√Run ChartPercent of Invoices that are adjustedAdjustments
A method for organizing and identifying your preliminary dashboard
Preliminary Dashboard Measurement
Plan Matrix – Example
Dashboard
Measurement
Plan
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In addition to tracking and monitoring process results during the Control
phase, it also important to track and monitor financial results.
Teams should include financial metrics in the dashboard design to
continuously track the financial impact of the improved process and to
ensure that the organization has realized the benefits that the project
projected.
Additional Dashboard Metrics
42
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Financial Metrics Commonly Tracked:
Project Benefits Projected vs. Actual
Cost of Poor Quality (COPQ)
Often tracked for individual projects
and also as a rollup metric for all
projects
Guidelines:
Most financial benefits from projects are tracked over a 12 month period
of time after implementation
Remember to involve Finance representatives in dashboard design to
agree on what financial metrics will be tracked and how they will be
measured.
Financial Dashboard Metrics Considerations
43
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Cycle
Time
Sales Sigma
Accuracy
Accuracy
Defects
What Should Your Gauges/Dials Be?
Process Dashboard
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The dashboard is the key communication tool to the organization that indicates process performance and the health of the process. The dashboard, provides the means for assuring continuing effective and efficient process performance; or detecting defects requiring removal; or, special cause variation requiring troubleshooting; or, triggering the need for new process design or reengineering to restore performance at a level that meets our customer’s needs. The dashboard indicators should tie to process goals and strategic objectives.
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The dashboard is:
A business management tool
Set of critical indicators
It serves as a control infrastructure for existing improvement
projects once they go into the control phase
It can also serve as the platform for identifying new improvement
projects
An indicator system that must be developed, tested, and
recalibrated as requirements and measurement systems change
Dashboard Attributes
45
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How do you want the information displayed for your
indicators/measures?
To what level do you want to “drill down” in the
information?
How might you want to segment the information for
making critical decisions?
Who should have access to the information?
Key Questions for Developing Your Dashboard
46
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What you learned during this section:
Understand what a dashboard is
Understand the questions to consider when developing a
dashboard
Utilize a dashboard example to practice developing a
dashboard for your project
Summary of Section
47
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End of Lesson: Control – Process Control
Lean Six Sigma Training
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Control – Response Planning
Action Planning
Process Reviews
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
1
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Understand the purpose and benefits of regular process
reviews
Understand the role of the process owner in monitoring
and responding to process issues
By the end of this section, you will be able to:
Overview – Purpose – Objectives – Key Topics
2
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Process
Reviews
External
Environmental
Information
Internal
Environmental
Information
Satisfied
With Indicators?
– Yes –
Continue Control
Actions
Satisfied
With Indicators?
– No –
Plan & Implement
Improvement
Actions
Dashboard
Indicators
Process Reviews
3
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The Dashboard is the mechanism used to monitor and assess process
performance and determine what actions to take. During process review
meetings the process owner and team will review dashboard results and
determine what remedial actions need to be taken.
Process Reviews
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http://images.google.com/imgres?imgurl=http://www.ace.net.nz/miata/graphics/dashboard.gif&imgrefurl=http://www.ace.net.nz/miata/ogg1e.html&h=360&w=480&sz=126&tbnid=kiy13Mmo43QJ:&tbnh=94&tbnw=125&start=1&prev=/images?q=dashboard&hl=en&lr=&ie=UTF-8
http://images.google.com/imgres?imgurl=http://www.ace.net.nz/miata/graphics/dashboard.gif&imgrefurl=http://www.ace.net.nz/miata/ogg1e.html&h=360&w=480&sz=126&tbnid=kiy13Mmo43QJ:&tbnh=94&tbnw=125&start=1&prev=/images?q=dashboard&hl=en&lr=&ie=UTF-8
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When to review?
Process Owners hold regular (monthly, weekly) updates with their
Process Teams
Receive updates on process performance
Conduct question and answer session
Perform joint problem solving
Reinforcing success
Conducting Process Review Meetings
5
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How often should Process Owners review processes?
Formal audits/reviews conducted under the auspices of an
outside authority.
Formal meeting of Process Owner and Sub-Process
Owners. Used primarily when processes and sub processes
are performing within expected parameters and are meeting
or exceeding goals. Can occur within regular operations
reviews.
Less formal meeting of Process Owner and Sub-Process
Owners. Detailed review of sub-process dashboards and
performance.
Informal meeting with Sub-Process Owners. Detailed review
similar to the bi-weekly to monthly review. Used primarily
when sub-processes are critical to overall process cycle
times or sub-processes are performing poorly.
Quarterly to
Annually
Monthly to
Quarterly
Bi-weekly to
Monthly
As Needed
Process Reviews by Process Owner
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The timing of the review meetings is typically set at the discretion of the Process Owner and sometimes at the request of the team.
Some factors that affect the frequency of reviews are:
– Poorly performing processes/sub-processes (more frequent reviews)
– Processes/sub-processes cycle times (completion of a cycle provides better information mid-cycle)
– Availability of data (updated date is needed since last review meeting)
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Process review meetings should be structured to address these types of questions
and trigger the appropriate response to address gaps.
1. How is the process performing compared to the goals we set for it? Are there gaps?
Why or why not?
2. How are the sub-processes performing against the goals? Are they stable? Are they
capable? How should we respond?
3. How does our process compare to our competitors, or those “best in class”?
4. Are we maintaining gains made by our changes – e.g. Quick Wins, DMAIC or DFSS
projects?
5. Are we making changes in one part of our process that could impact another part of
our process or impact another process? Will it help or hurt? Are other project teams
making changes that impact our process?
Process Review Questions
7
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6. Are we measuring the right process indicators? Do they predict how well our process
outputs will satisfy customers? Are there better indicators we should be measuring?
7. Do we need to make changes to: Measures? Training? Staffing? Rewards?
Communications and feedback? Goals? Resource allocation? Action plans?
8. Are our work procedures being used? Why or why not?
9. What do we need to communicate to Leadership and to our process teams?
10. How can we recognize process contributions and successes?
Process Review Questions (Continued)
8
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Review Dashboards
Sigmas
Trends
Specific Transactions
Perform Analysis
Special/Common Causes (Stability)
Root Causes
Assess Capability
Identify Next Steps
Stabilization
Management Emphasis & Inspection
Project Scoping
Training
Advanced Statistical Tools
QRB Report-Out
Monthly (3rd week of each month)
2 hours or as needed
Standardized Meeting Agendas with
Action Items
Process Owner Report-Outs
Champion
Process Owner(s)
MBB or Quality Analyst
Quality Leader, if appropriate
Customers, when appropriate
WHAT WHEN
HOW WHO
Example Guidelines for Process Review Meetings
9
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Consequences of not having an accountable process owner:
Defects start to occur and remain unchecked
Internal complaints go unaddressed
Changing customer needs are not identified, let alone planned for
Improvement projects aren’t identified or implemented on a timely basis
Teamwork and morale deteriorate
Creating an environment of process accountability is important:
Establishing what results and processes the Process Team will be accountable for (set goals)
Explaining those expectations to the Process Team Leader and assuring understanding
Giving the Process Team and Process Owner the tools, resources and information to
succeed
Measuring and giving performance feedback (timely, specific, accurate to all levels of the
team)
Applying judgment in evaluation of performance
Process Accountability
10
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What you learned during this section:
The purpose and benefits of regular process reviews
The role of the process owner in monitoring and
responding to process issues
Summary of Section
11
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Control – Response Planning
Action Planning
Process Reviews
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
12
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Understand what response planning is
Understand the course of action to take if out of control
issues should occur
Troubleshoot to fix common and special cause
problems
By the end of this section, you will be able to:
Overview – Purpose – Objectives – Key Topics
13
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What is a Response Plan?
A response plan is a documented method for how a process
owner/team should respond to any out-of-control conditions
that may occur in a process
A good response plan will help ensure a timely and
appropriate response to processing problems as they occur,
thereby decreasing the risk of defects getting to the
customer
Response Plan
14
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Provides a response if the process should fail to meet customer
requirements for each variable (both the X and Y)
OwnerTimingActionMeasure
Specific
Action to be
Taken
Responsibility
to Take Action
Timing of Action
What is a Response Plan?
15
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All Xs and Ys that are being monitored must be included in the response plan.
For each measurement tracked, document the specific action to be taken when an out-of-control event occurs. The action that is taken will depend on the severity of the situation. If the situation is minor, specific corrective actions can be executed as planned. In the event of a serious problem, the process owner may need to become more involved. The timing of the response should also be included in the response plan. The plan should specify a time frame in which the team needs to respond for each out-of-control situation. Finally, the person responsible for each X and Y must be named in the response plan.
Be specific about action to be taken. Remember to operationally define any terms that may be ambiguous so that little confusion exists about the specific response needed.
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Looks
Like
Type
Common
Cause
Variation
Special
Cause
Variation
Action To Be Taken
Study individual
points or specific
cluster of points
to determine what
was reason for
difference
Make changes to sustain or
prevent special causes in the
future
Study all data
points collectively
to better
understand
sources of
variation
Make basic process change to
reduce common cause variation,
shift the average, or both
What should you do when you are not Satisfied
with Current Performance?
16
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Yes No Are there differences in the methods used by different employees?
Yes No Has there been a significant change in the internal/external
environment?
Yes No Is the process affected by predictable conditions?
Yes No Were any untrained employees involved in the process at any
time?
Yes No Has there been a change in the supplier of inputs to the process?
Yes No Has there been a change in policies or procedures?
Yes No Could the employees be afraid to report “bad news?”
Common Questions for Investigating an Out-Of-
Control Process
17
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Strategy for Eliminating Special Causes of Variation
Work to get special causes signaled
quickly. Use early warning indicators
throughout your operation.
Immediately search for cause when a
control chart gives a signal that a special
cause has occurred.
Find out what was different on that
occasion.
Keep asking – “Why”
Do not make fundamental changes in the
process.
Immediate remedy to contain any damage.
Remove assignable cause and seek ways
to prevent that special cause from
recurring, or if results are good, retain that
lesson.
Timely Data
Search for
Cause
No Changes
Prevent and
Retain
18
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Quick hit tools the team can use to analyze, troubleshoot, and diagnose
why a process is not performing up to requirements:
Cause and Effect Diagram
Value-Add/Non Value-Add Process Analysis
Process Step
Time (Minutes)
Value-Added
Nonvalue-added
Transferring
Retrieving Information
Reviewing
Prep/Set-up
Waiting for Help
Total
1 2 3 4 5 6 7 8 9 10 Total %Total
1 5 3 2 4 2 8 2 5 8 40 100%
4
5
16
8
40
4
10%
12.5%
40%
20%
10%
100%
3 7.5%
Problem
Statement
Main Category A
Main Category C
Main Category B
Potential
Root Cause
Cause
Cause
Cause
Potential
Root Cause
Potential
Root Cause
Tools for Quick Process Analysis, Diagnosis, and
Remedy
19
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What you learned during this section:
What response planning is
The course of action to take if out of control issues should
occur
How to troubleshoot to fix common and special cause
problems
Summary of Section
20
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End of Lesson: Control – Response Planning
Lean Six Sigma Training
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21
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Control – Project Documentation
Solution Replication and Closure
Communicate Project Outcomes
Document and Standardize
Lean Six Sigma Training
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1
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Understand the purpose and importance of standards to
effective Control
Understand the use and importance of documenting
procedures
Understand some of the keys to success and pitfalls with
writing procedures
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
2
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Definition
A documented method which identifies in detail all the steps
necessary to produce a product or meet a desired service
outcome.
They are a written agreement between the associate and the
company regarding how the job will be done.
Questions to ask when there is trouble with a Standard
Practice:
Do we have a standard practice?
Does the employee know the standard practice?
Does the employee use the standard practice?
Do we enforce the standard practice?
What are Standard Practices?
3
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Everyone does things in a different way
Some individual learning and improvement
No group learning
No accepted methods
Right Amount
Best available methods are used
Less wasted effort
Group and individual learning
Methods are improved
People are frustrated
Creativity is stifled
No learning and improvement
People fight the system, cut corners
Too Little
Too Much
Degrees of Standardization
4
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Greater process variation
Unhappy customers
Lack of organizational learning
Inability to hold the gains of
improvement efforts
Lack of agreement among employees
on how to do the job
Increased supervisory time and training
required
Costs of Not Standardizing
5
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Documentation is Critical to:
Describe the flow of the process and standardize
procedures for operating the process
Provide approved information for all current and
future employees who will need it
Increase organizational learning and provide
training materials
Use results in consistent operating procedures
and reduced process variation
A necessary step to ensure that the learning
gained via Process Management is shared and
institutionalized
Why Document?
6
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A procedure is the documented sequence of
steps and other instructions necessary to carry
out an activity.
Documentation – Procedures
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What is a Procedure
Procedures are the details behind the activities documented on the business process map.
They serve as a method for every employee to gain an understanding in their context of the
process.
Purpose
To gather process skill in written form and to make it easier for everyone to do his/her work.
Questions To Ask When There Is Trouble with Procedures:
Do we have a standard procedure?
Does the employee know the standard procedure?
Does the employee use the standard procedure? (Do we enforce the standard
procedure?)
In Summary…
A procedure is a written agreement between an associate and the company regarding
how the job will be done.
Documentation – Procedures
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Pitfalls in Writing Procedures
Not involving the affected persons in the creation of the procedures
Not testing the procedures
Omitting information
Results to be obtained
How to do a step
Lowering the importance of procedures
Not readily available
Ignored by management
No method to update procedures
Obsolete procedures not destroyed
Procedure documentation is not readily available
9
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Procedures Example
Standardized
Procedures
10
1.0 Activity: Conduct Market Analysis including Market Segmentation
Description: Marketing group will gather market research information and conduct analysis
including identification of competitor intelligence and market segmentation.
Tools:
Various Market Research Reports
Buying Process and Market Map Tools
Timing:
Within 3 weeks of market data availability
Deliverable:
Buying process to uncover key customer behavioral objectives that we want to
change and one which will give the maximum leverage in driving business
Responsibility:
Marketing Group taking the lead, but involving Sales
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Direct Ways
Observation
Ask associates directly, “What difficulties do you have following
the procedures? Are there any ways to make the work easier
and get the results we need?”
Indirect Ways
Observe the last time the instruction was revised. If the instructions
have stayed the same for six months, do associates really use
them?
Checking Procedures
11
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What you learned during this section:
The purpose and importance of standards to effective
Control
The use and importance of documenting procedures
Some of the keys to success and pitfalls with writing
procedures
Summary of Section
12
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Control – Project Documentation
Solution Replication and Closure
Communicate Project Outcomes
Document and Standardize
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
13
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Understand key considerations to making communication
effective
Understand the key elements of a Communication Plan
Develop a Communication Plan
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
14
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The #1 Reason communications efforts fail to achieve the level of
understanding and influence intended is due to:
E-mails, large meetings, print announcements, and
even videos alone tend to:
Be ignored
Fail to engage recipients in active thinking
Focus on “What’s in it for the company” rather
than credibly persuade “What’s in it for the
individual”
Method of Communication
Effective Communication Reviewed
15
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Have a clear message
Involve and engage your audience
Be candid
Demonstrate, don’t lecture
Follow up
Communication of the improvement project message should be
80% Face to Face meetings
80%
20%
Face to Face
Company Wide
Project Communication Reviewed
16
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The Final Communication Plan should be developed once the documentation has
been completed. The basic components of the Communication Plan include:
Target Audience:
Identify the project audience(s) – include internal and external stakeholder
groups.
The “What” (message):
Assess information needs – determine what groups need to know, want to know,
and expect. NOTE: Utilize project resources only on communicating information
that contributes to success or where a lack of communication can lead to
failure.
Identify key project messages, announcements, that need to be delivered on
the project outcomes.
When:
Define when communications will be provided to the different stakeholder
groups.
Developing a Communication Plan – What to
Include
Communication
Plan
17
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The Method:
Identify the best media and methods available to communicate, e.g. face to face
meetings, presentations, e-mail – remember people absorb information in different
ways.
Owner:
Assign responsibilities for creating and delivering the various types of
communications. At this point, the process owner should be utilized to aid in
communicating the project results.
Required Approval:
Document the approval process needed for any of the communications.
Feedback Loop:
Create internal and external feedback loops to help evaluate the effectiveness of
communications.
Developing a Communication Plan – What to
Include
18
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Audience What When Method Owner Required
Approval
Feedback
Loop
Leadership Overview of
Solutions
Financial
Benefits
Project
End Date
(October
1st)
Leadership
Team Meeting
Black Belt /
Green Belt
and
Process
Owner
Sponsor Discussion
All employees Overview of
Solutions
October
15th
Gallery Walk
in Lunch
Room
Black Belt /
Green Belt
and Team
Sponsor Feedback
Cards
Operations Detailed
Solutions
October
6th
Meeting Black Belt /
Green Belt
and Team
Sponsor Discussion
Communication Plan Example
19
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What you learned during this section:
The key considerations to making communication effective
The key elements of a Communication Plan
How to develop a Communication Plan
Summary of Section
20
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Control – Project Documentation
Solution Replication and Closure
Communicate Project Outcomes
Document and Standardize
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
21
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Understand the process of replicating opportunities from
project solutions to other parts of the organization
Understand the roles of the team and the process to
transition the project outcomes to the process owner
By the end of this section, you will be able to:
Overview – Objectives – Key Topics
22
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Replication opportunities are key learnings and documented
solutions that may be applicable to other processes or projects.
Looking for these opportunities can:
Increase process improvement in other areas
Reduce resource time solving similar problems
Increase customer satisfaction in other areas of the business
Solution Replication Opportunities
23
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Look for replication
opportunities across the
organization that have similar
processes
Solution Replication Opportunities – Organization
24
Level 1 Processing Processing Processing
Chicago London Singapore
Process
Improvement
Accomplished
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Look for replication
opportunities across the “end to
end” process either upstream or
downstream
Level 3
Accounts Payable Process
Re
plic
ate
Process
Improvement
Accomplished
Re
pli
ca
te
Solution Replication Opportunities – Process
25
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1. Identify existing improvement efforts or problems within the
organization that relate to the process improvement outcomes of
your project.
2. Develop a project charter summarizing problems and goals of the
replication opportunity.
3. Develop a summary of the “just completed” project outcomes that
include the following deliverables:
Lessons learned from project
Project Charter
Key metrics and how they link to potential replication opportunity
All final project documentation (including control plan and dashboards
for use as best practice sharing)
Action plan with owners to transition project outcomes to new process
Solution Replication Opportunities – Process
26
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Once the process is in control, the final step of the project team
is to transition the new process to the process owner.
The materials include:
All project outcomes
Project binders
Process monitoring plans
Training materials
Transition to Process Owner
27
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What Does Successful Transition Mean?
1. The process is completely integrated into the organization
and under control.
2. The process owner has approved all deliverables and has
agreed to take ownership of the project outcomes.
3. The process will be managed by the outcomes of the project,
including all monitoring techniques defined in the Control
Phase.
4. The project team is no longer needed to monitor and make
adjustments to the process.
28
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Black Belt /
Green Belt
Ensure that an actionable, measurable and
comprehensive Monitoring Plan is defined, communicated
and implemented
Jointly ensure that the handoff to the Process Owner is
successful
Process Owner
Sponsor
Project Team
Commit to own the project outcomes and Monitoring Plan
Designate the appropriate resources to manage the plan
Ensure the project outcomes meet strategic objectives
Jointly ensure that the handoff to the Process Owner is
successful
Monitor the ongoing compliance to the Monitoring Plan
Assist in designing and implementing the Monitoring Plan
If applicable, members of the team should assist the
Process Owner in managing the ongoing Monitoring Plan
Roles of a Successful Transition
29
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Once Transition is Complete, the
Project Team Should Celebrate
Their Success
Celebrate Success
30
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What you learned during this section:
The process of replicating opportunities from project
solutions to other parts of the organization
The roles of the team and the process to transition the
project outcomes to the process owner
Summary of Section
31
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End of Lesson: Control – Project Documentation
Lean Six Sigma Training
Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl
32
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Lean Six Sigma
Green Belt
Simulated Project Workbook
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1Copyright © 2016 Acuity Institute LLC. All rights reserved.
Simulated Project Overview
Welcome to the Lean Six Sigma Green Belt Simulated Project.
At Acuity Institute we recognize that not every individual has the opportunity to complete an
actual Lean Six Sigma project while completing training, therefore we have created a real world
simulated project that takes students from the beginning to the end of a problem and solution.
The simulated project helps to build the students understanding of the concepts taught in
training and provides practical application of the tools. Students complete the course better
prepared to apply what they have learned in the real world.
The simulation is based on a hypothetical company (Simco International or “SI”) that faces many
of the same problems companies are dealing with today. The simulation is designed to illustrate
the entire business improvement effort through every phase of the Lean Six Sigma DMAIC
methodology. Students complete challenging exercises (project deliverables) which build on
previously learned tools and concepts taught in training. When complete, students have a
significant perspective on what true business improvement means and a tangible “project story”
that they can utilize throughout their process improvement journey.
There is no comparison to Acuity Institute’s Simulated Project in the marketplace.
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Simulated Project Deliverables
Acuity Institute’s Lean Six Sigma Green Belt Simulated Project includes 32 project deliverables which are
introduced throughout the DMAIC Methodology.
Define Measure Analyze Improve Control
1. Project Charter
Development
2. SIPOC
3. As-Is Process
Mapping
4. Quick Win
Opportunities
5. Identify
Stakeholders
6. Develop
Stakeholder Map
7. Stakeholder
Management Plan
8. Communication
Plan
9. VOC Questions
10.CTQ Determination
11. Operational
Definitions
12. Data Collection
Planning
13. Histogram
14. Run Chart
15. Control Chart
16. Sigma
Performance
(DPMO)
17. Cause and Effect
Analysis
18. Lean Process
Analysis
19. Pareto
20. Box Plots
21. Correlation
Analysis
22. Regression
Analysis
23. Solution Selection
Matrix
24. Cost/Benefit
Analysis
25. Mitigating Risks
(FMEA)
26. Pilot Plan
27. Implementation
Planning
28. Storyboarding
29. Process
Monitoring Plan
30. Dashboard
Development
31. Response
Planning
32. Final Project
Storyboard
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Simulated Project Templates
There are “blank” templates for you to complete for all 32 Simulated Project deliverables. The templates are
located in the “LSS GB_SI Project Templates” file folder. The templates are developed in common formats
(MS Word, MS Excel, or MS PowerPoint). To access the templates you will need to download this file folder
onto your computer.
For your reference, the name of the specific template that you are to complete is included in the instructions
of the project deliverable you are working on (example: “SI Project Template: Project Charter
Development_SI”). Please note, answers are provided as a reference point for many of the project
deliverables. In most cases we do not recommend updating your answers to match the answers provided. It
is important for your answers to be authentic to your experience as you complete the Simulated Project.
In addition to the project templates, the “LSS GB_SI Project Templates” file folder also contains the MS
Excel file “LSS SI Data File”. This file includes data to be used for various Simulated Project deliverables.
This course includes step by step instructions on how to complete these deliverables using both SigmaXL
and Minitab statistical analysis software.
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Lean Six Sigma – Simco International
Define Phase
1
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Simco International – Define Phase Deliverables
Deliverable Page Lesson
(Deliverable Originated From)
Project Charter Development 3 Project Charter
SIPOC 10 Process Definition
As-Is Process Mapping 15 Process Definition
Quick Win Opportunities 21 Process Definition
Identify Stakeholders 26 Stakeholder Management
Develop Stakeholder Map 31 Stakeholder Management
Stakeholder Management Plan 36 Stakeholder Management
Communication Plan 41 Stakeholder Management
VOC Questions 46 Voice of Customer
CTQ Determination 51 Voice of Customer
2
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Lean Six Sigma – Project Simulation
Project Charter Development
3
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Objective
Develop key sections of a Project Charter for the Simco International (SI) Consumer Home
Loan project.
Instructions
Utilize the information from the Simco International Overview information on the following
pages to draft the following Project Charter elements in the worksheet below:
Problem Statement
Project Goals
Prepare your findings.
PROJECT DESCRIPTION
Problem
Statement
Project
Goals
Project Charter Development
SI Project Template: Project Charter Development_SI
4
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Simco International “SI” is a global financial services company
that conducts business in 84 different countries. During the
past 2 years SI has fallen from the 3rd largest financial services
provider to 6th in the world. The primary reason for this decline
is poor customer service which is driving customers to SI’s
competition.
SI recently formed multiple Lean Six Sigma teams to address
their customer service issues. In selecting the Lean Six Sigma
projects, SI studied their organization to learn where customer
expectations were being least met. Through this process they
learned that their Global Consumer Home Loan division was
performing well below customer expectations, therefore the
“Home Loan” Lean Six Sigma project was initiated.
Simco International Overview
5
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During the pre-project research, SI learned that it required an
average of 22 days to process home loans. Their competition
was completing the same process in 15 days. The process
time of 15 days was what home loan customers consider to be
Critical to Quality (CTQ). By not meeting the CTQ of 15 days,
SI estimated that it was losing $26.2 million in lost revenues
and $2.4 million in process inefficiencies per year.
The primary goal of the “Home Loan” Lean Six Sigma team is
to meet customer expectations for consumer home loans
throughout the world. If the team achieves this goal, they
believe that they will be well positioned to re-capture market
share, increase revenues, and improve customer satisfaction.
Simco International Overview
6
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Please Do Not Proceed Forward
Project Charter Development
7
For additional information
about this concept, see
Lesson 3 Project Charter, in
the Project Charter section.
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PROJECT DESCRIPTION
Business Case Increasing customer satisfaction will assist SI to re-capture market
share and ultimately increase revenues while improving process
efficiencies.
Problem Statement The Global Consumer Home Loan process cycle time currently
averages 22 days to complete, which exceeds customer expectation by
7 days.
Project Goals Reduce the Consumer Home Loan process cycle time by 32% by
September 1st. Improve process accuracy by 50%.
Estimated Benefits ($$) Increased revenues by $20 million and reduced process costs by
$650,000.
Project Scope Area of
Focus:
Consumer Home Loan processes in Singapore,
Chicago, and London.
Includes: Home Loan Customer, Real Estate Agent,
Underwriting, Credit Agency, processing of application,
and approval/denial of home loan
Excludes: Accounts Payables and Receivables, re-finance
processes
Start Point: When a customer requests a loan
Stop Point: Home loan acceptance or rejection package is
received by the customer
SI Project Charter
* Additional Project Charter information has been provided for your reference.
8
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PROJECT RESOURCES
Team Members Function in the Business Project Role
Time Dedicated to
Project (Hrs/Week)
John Davis VP of Operations Sponsor 1-2
Susan Terrell Performance Improvement Expert Master Black Belt 2
Steve McCaffrey Project Manager Black Belt / Green Belt 25
Ellen Mobley Finance Team Member 8-16
Rod Elway Operations SME Team Member 8-16
Erin Anderson Processing SME Team Member 8-16
Owen Atwater Sales SME Team Member 8-16
Additional Support Legal, Compliance, Information Technology, External Business Partners
PROJECT MILESTONES
Milestone Phase Start Date Completion Date
Define January 1st In Progress
Measure April 1st June 15th
Analyze June 1st June 30th
Improve July 1st July 31st
Control August 1st August 30th
Closure August 30th September 30th
SI Project Charter
* Additional Project Charter information has been provided for your reference.
9
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SIPOC
Lean Six Sigma – Project Simulation
10
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Objective
Develop a SIPOC for the SI Consumer Home Loan process.
Instructions
Complete the worksheet on the following page by utilizing the SI Overview
and Project Charter to develop the SIPOC.
Prepare your findings.
SIPOC
SI Project Template: SIPOC_SI
11
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Utilize the SI Overview and Project Charter to complete each element of the SIPOC diagram.
Suppliers Inputs Process Outputs Customers
• • 1. • •
• • 2. • •
• • 3. • •
• • 4. • •
SIPOC
12
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Tips in SIPOC completion:
– Brainstorm information that is common to all home loan processes.
– Work backwards when completing the SIPOC.
– Start by identifying the customers first, then the process outputs.
– Identify the process start and stop points, then complete the remaining steps (you can identify more than the 4 high-level steps provided if needed).
– Finally, define the inputs and suppliers.
– The suppliers may be the customers as well.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Please Do Not Proceed Forward
SIPOC
13
For additional information
about this concept, see
Lesson 5 Process
Definition, in the SIPOC
section.
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Suppliers Inputs Process Outputs Customers
• Home Loan
Customer
• Application 1.Receive
Application
• Home Loan
Acceptance
Package
• Home Loan
Customer
• Real Estate
Agents
(Partners)
• Customer
Information
(Bank,
Employment,
etc.)
2.Complete
Application
Process
• Home Loan
Rejection
Package
• Real Estate
Agents
(Partners)
• Credit
Agency
• Credit Score 3.Complete
Underwriting
Process
• Loan
Products
4.Send
Notification
SI SIPOC
14
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As-Is Process Mapping
Lean Six Sigma – Project Simulation
15
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Objective
Develop the as-is process map for the SI Consumer Home Loan process.
Instructions
Using the description of the SI Consumer Home Loan process on the
following page, develop a deployment flow chart process map.
Document each step in the process
Align the steps with the personnel (deployment flow chart)
Prepare your findings.
As-Is Process Mapping
SI Project Template: As Is Process Mapping_SI
16
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Primary People and Departments Involved in the SI Home Loan Process
Home Loan Customer
Real Estate Agent (RA)
Home Loan Process Flow
The SI Consumer Home Loan process starts when a customer contacts a Real Estate Agent (RA) to request a loan.
The RA’s are located across the country. The RA mails the customer a home loan application which is to be
completed and mailed back to the RA. The RA forwards the application to their local SI Mortgage Sales Associate
(MSA). The MSA’s are organized by region. The MSA forwards the application to an SI Loan Processor (LP). There
are LP’s in every local SI office. The LP reviews the application. The LP contacts the customer to request additional
information (bank info, employment info, etc.). The customer gathers the additional information and mails it to the LP.
With the additional information, the LP reviews the application and additional information to ensure that it is complete.
If there is missing or incorrect information, the LP contacts the customer to make the necessary corrections. If the
information is correct, the LP forwards the information to an SI Loan Officer (LO). There are LO’s in every local SI
office. Certain LO’s are responsible for managing each of the Local SI offices. The LO reviews the customer
information to determine the loan qualifications for final determination (acceptance or rejection). When this is
complete, the LO forwards the final determination to the LP. If the loan is accepted, the LP creates an SI “Home Loan
Acceptance Package”. If the loan is rejected, the LP creates an SI “Home Loan Rejection Package”. When this is
complete, the LP forwards the final determination package to the MSA. When the MSA receives the package they
schedule a meeting with the RA to review the final determination package. The RA reviews the final determination
package. The RA sends the final determination package to the customer. When the customer receives the final
determination package the SI Consumer Home Loan process is complete.
SI Mortgage Sales Associate (MSA)
SI Loan Processor (LP)
SI Loan Officer (LO)
As-Is Process Mapping
17
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Tips in sub-process mapping:
– Clarify the boundaries of the process first by identifying the start and stop points.
– Document (brainstorm) the steps/activities that occur during the process.
– Combine and eliminate any duplicate process steps that team members repeated.
– Organize steps into logical order using the direction of flow arrows.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Please Do Not Proceed Forward
As-Is Process Mapping
18
For additional information
about this concept, see
Lesson 5 Process
Definition, in the Process
Mapping section.
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Simco International “As-Is” Process Map (Page 1)
Re
al
Es
ta
te
Ag
en
t
(R
A)
SI
M
or
tg
ag
e
Sa
le
s
As
so
cia
te
( M
SA
)
SI
L
oa
n
Pr
oc
es
so
r
(L
P)
SI
L
oa
n
O
ffi
ce
r
(L
O
)
Ho
m
e
Lo
an
Cu
st
om
er
Contact RA to
request loan
Mail loan
application to
customer
Complete loan
application
Mail loan
application to
RA
Forward
application to
MSA
Forward
application to
LP
Review
application
Request
additional info
from customer
Gather
additional
information
Mail additional
information to
LP
Go to Step 12
(Next Page)
Review
application
and additional
information
1
2
3 4
5
6
7 8
9 10
11
SI As-Is Process Map
19
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Notes:
The above process map is known as a Deployment Flow Chart (DFC). A DFC is a type of process map. It is a graphical display of the actions and activities of a business process and their alignment with resources. DFC’s are particularly helpful when multiple and diverse groups have accountability in the process being managed.
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Simco International “As-Is” Process Map (Page 2)
SI
L
oa
n
O
ffi
ce
r
(L
O
)
SI
L
oa
n
Pr
oc
es
so
r
(L
P)
SI
M
or
tg
ag
e
Sa
le
s
As
so
cia
te
(M
SA
)
Re
al
Es
ta
te
Ag
en
t
(R
A)
Ho
m
e
Lo
an
Cu
st
om
er
Go to Step 8
(Previous Page)
Is info
complete?
Forward
customer info
to LO
Determine
loan
qualification
Send final
determination
to LP
Is loan
accepted?
Create SI
Home Loan
acceptance
package
Create SI
Home Loan
rejection
package
Forward final
determination
package to
MSA
Schedule
meeting with
RA to review
final package
Review final
package
Send final
package to
customer
Receive final
determination
package
Yes
No No
Yes
12
13
14 15
16
17
18 19
20
21 22
23
SI As-Is Process Map
20
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Quick Win Opportunities
Lean Six Sigma – Project Simulation
21
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Objective
Identify Quick Wins for the SI Consumer Home Loan process.
Instructions
Using the worksheet on the following page, utilize the outcomes of your
charter, SIPOC, and process mapping to identify quick wins.
Brainstorm a few opportunities for quick improvements to the process
Complete the remaining sections by answering “Yes” or “No” to each
category
Decide on the Quick Wins based on your analysis
Prepare your findings.
Quick Win Opportunities
SI Project Template: Quick Win Opportunities_SI
22
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Quick Win
Opportunity
Easy to
Implement
Reversible Fast to
Implement
Within
Team’s
Control
Cheap to
Implement
Quick Win Opportunities
23
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Please Do Not Proceed Forward
Quick Win Opportunities
24
For additional information
about this concept, see
Lesson 5 Process
Definition, in the Quick Wins
section.
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Quick Win
Opportunity
Easy to
Implement
Reversible Fast to
Implement
Within
Team’s
Control
Cheap to
Implement
Have application
mailed directly to
LP from Customer
Yes Yes Yes Yes Yes
Have application
completed with LP via
phone, remove paper
application
Yes Yes No Yes No
Gather additional
information from
customer via phone
Yes Yes Yes Yes Yes
Remove MSA Position
from process
Yes No No No Yes
Have LP determine
loan qualification
No Yes No No Yes
SI Quick Win Opportunities
25
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Identify Stakeholders
Lean Six Sigma – Project Simulation
26
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Objective
Develop a list of Stakeholders for the SI Consumer Home Loan project.
Instructions
Using the list of potential stakeholders below, complete the worksheet on the following page
to identify the actual stakeholders of the SI process
Identify stakeholders by name
Determine the stakeholder type: external, internal, or supplier
Prepare your findings.
Name Function / Organization Name Function / Organization
John Davis VP, Operations/Sponsor Susan Terrell MBB
Jason Cody IT Systems Analyst Sean White Compliance Officer
Vince Joseph VP, Accounts Payable Lori Emtman Equifax Credit Agency
Home Loan Customers NA Chris Simms VP, Sales
Barbara Kissinger VP, Processing Steven O’Malley Loan Officer
Sandra Williams Real Estate Agent, Chicago Lynn Washington Real Estate Agent, Los Angeles
Xiu Len Real Estate Agent, Singapore Mark Clayton Real Estate Agent, London
Petra Lubiwitz VP, Underwriting Davin Carter Accounts Payable Rep
Identify Stakeholders
SI Project Template: Identify Stakeholders_SI
27
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Identify Stakeholders
Stakeholder Name Type
28
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Please Do Not Proceed Forward
Identify Stakeholders
29
For additional information
about this concept, see
Lesson 6 Stakeholder
Management, in the
Stakeholder Analysis
section.
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Stakeholder Name Type
Lori Emtman (Equifax Credit Agency) Supplier
Sandra Williams (Real Estate Agent, Chicago) Supplier/External
Xiu Len (Real Estate Agent, Singapore) Supplier/External
Mark Clayton (Real Estate Agent, London) Supplier/External
Lynn Washington (Real Estate Agent, Los Angeles) Supplier/External
John Davis (VP, Operations/Sponsor) Internal
Chris Simms (VP, Sales) Internal
Barbara Kissinger (VP, Processing) Internal
Steven O’Malley (Loan Officer) Internal
Petra Lubiwitz (VP, Underwriting) Internal
Jason Cody (IT Systems Analyst) Internal
Vince Joseph (VP, Accounts Payable) Internal
Susan Terrell (MBB) Internal
Sean White (Compliance Officer) Internal
Davin Carter (Accounts Payable Rep) Internal
Home Loan Customers External
SI Stakeholders
30
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Develop Stakeholder Map
Lean Six Sigma – Project Simulation
31
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Objective
Develop a Stakeholder Map for the SI Consumer Home Loan project.
Instructions
Using the summary developed by the team on their current perceptions of the stakeholders
on the project, complete the stakeholder map on the following page.
Prepare your findings.
Name Influence Impact of Change Perception on Project
1. Lori Emtman Low Low Has heard about it and wants problem solved
2. Sandra Williams Medium High Has been calling team members about project status
3. Xiu Len Low High Not aware of project or Lean Six Sigma
4. Mark Clayton Medium High Has resisted change in the past
5. John Davis High High Very supportive and engaged in project
6. Chris Simms High Medium Understands need, wants to know more
7. Barbara Kissinger High High Has expressed dissatisfaction with scope
8. Steven O’Malley Medium Medium Wanted to participate on team
9. Petra Lubiwitz Low Medium Was involved in drafting original charter
10.Home Loan Customers Low High Not aware of project
Develop Stakeholder Map
SI Project Template: Develop Stakeholder Map_SI
32
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In
flu
en
ce
Impact of change
H
M
L
L M H
Enthusiast
Neutral
Opponent
Develop Stakeholder Map
33
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Please Do Not Proceed Forward
Develop Stakeholder Map
34
For additional information
about this concept, see
Lesson 6 Stakeholder
Management, in the
Stakeholder Analysis
section.
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In
flu
en
ce
Impact of change
H
M
L
L M H
1
2
3
4
56 7
8
9 10
Enthusiast
Neutral
Opponent
SI Stakeholder Map
35
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Stakeholder Management Plan
Lean Six Sigma – Project Simulation
36
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Objective
Develop a Stakeholder Management Plan for the SI Consumer Home Loan
project.
Instructions
Using the Stakeholder Map from the previous deliverable, use the worksheet
on the following page to develop a management plan for the stakeholders
you select.
Which stakeholders need to be influenced?
How will this occur?
Prepare your findings.
Stakeholder Management Plan
SI Project Template: Stakeholder Management Plan_SI
37
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Stakeholder Objective Actions
Stakeholder Management Plan
38
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Please Do Not Proceed Forward
Stakeholder Management Plan
39
For additional information
about this concept, see
Lesson 6 Stakeholder
Management, in the
Stakeholder Analysis
section.
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Stakeholder Objective Actions Completion
Date
Owner
#5 Utilize influence
with #7 to help
gain support
Review charter
Discuss help needed in working
with #7
March 2nd Steve M.
#7 Gain support in
processing
department
Help sell project
to associates
Schedule one-on-one meeting to
review project charter and scope
Discuss communication support
needed in Processing
Gain commitment for support
March 3rd Erin A.
#4 Overcome
resistance to
project initiative
Schedule one-on-one meeting to
review project charter
Take feedback and initiate follow-
up meeting
Escalate if necessary
March 15th Rod E.
#3, #6. #10 Gain
understanding of
project
Schedule one-on-one meeting to
review project charter
Take feedback and initiate follow-
up meeting
Gain commitment for support
March 15th Steve M.
SI Stakeholder Management Plan
* Additional Stakeholder Management Plan information has been provided for your reference.
40
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Communication Plan
Lean Six Sigma – Project Simulation
41
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Objective
Develop a Communication Plan for the SI Consumer Home Loan project.
Instructions
Use the worksheet on the following page to develop a communication plan for
the target audience(s) for the project.
Who needs to receive communication about the project?
What kind of information will be communicated?
When/how often will communication take place?
What will be the method of delivery?
Prepare your findings.
Communication Plan
SI Project Template: Communication Plan_SI
42
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Audience What When Method
Communication Plan
43
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Please Do Not Proceed Forward
Communication Plan
44
For additional information
about this concept, see
Lesson 6 Stakeholder
Management, in the
Communication Planning
section.
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Audience What When Method Owner Required
Approval
Feedback
Loop
Champion /
Sponsor
Status Reports
Milestones
Obstacles /
Resources
Scope Reviews
Bi-Monthly / As
Needed
Face to Face Project Lead MBB Minutes
from
Meeting
Stakeholders Status Reports
Milestones
Completion of
Phases / As
Needed
Face to Face
Memo’s/Email
Owners on
Stakeholder
Management
Plan
Champion /
Sponsor /
MBB
Minutes
from
Meeting
MBB Status Reports
Milestones
Obstacles /
Resources
Scope Reviews
Bi-Monthly / As
Needed
Face to Face Project Lead None Minutes
from Team
Meeting
Legal /
Compliance /
Finance / IT
Status Reports As Needed Face to Face
Department
Meeting
Project Lead MBB Minutes
from
Meeting
Organization
(Sales,
Processing,
Underwriting)
Project Results End of Project Email
Town Hall
Project Team Champion /
Sponsor /
MBB
Surveys
Customers /
Credit Agencies
Update New
Process
End of Project Update Materials Real Estate
Agents
Champion /
Sponsor /MBB
Surveys
SI Communication Plan
* Additional Communication Plan information has been provided for your reference.
45
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VOC Questions
Lean Six Sigma – Project Simulation
46
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Objective
Develop a list of VOC questions for the SI Consumer Home Loan process.
Instructions
Using the worksheet on the following page, develop a list of VOC questions
you feel will gather information on SI’s customer requirements.
Prepare your findings.
VOC Questions
SI Project Template: VOC Questions_SI
47
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Brainstorm 5-7 SI VOC Questions (Be as detailed as possible)
VOC Questions
VOC Questions
1.
2.
3.
4.
5.
6.
7.
48
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Defining the right questions to ask customers can be difficult. Being too broad with questions can lead to non-measurable responses. However, being too specific can direct customer responses and lead to narrow issue identification. Make sure your questions have a good mix of open-ended (i.e. summary or free form) and close-ended (i.e. rating 1 through 4) criteria.
Another pit fall in collecting VOC is to utilize the questions to collect data on the existing process. Try and avoid questions that will identify the current performance or roles within the process. This information will be determined in the Measure Phase.
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Please Do Not Proceed Forward
VOC Questions
49
For additional information
about this concept, see
Lesson 7 Voice of
Customer, in the What is
Voice of Customer section.
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Example SI VOC Questions
1. How long did it take for you to receive your Home Loan?
2. On a scale of 1-4, with 1 being completely dissatisfied and 4 being completely
satisfied, how satisfied were you with this time?
3. What would have been an acceptable timeframe to receive your Home Loan?
4. On a scale of 1-4, with 1 being completely dissatisfied and 4 being completely
satisfied, how satisfied were you with your overall Home Loan experience?
5. Why did you rate your experience this way?
6. Did SI fail to meet your service expectations in any way?
SI VOC Questions
50
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CTQ Determination
Lean Six Sigma – Project Simulation
51
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Objective
Identify “Customer Needs” and “CTQ’s” for the SI Consumer Home Loan
process.
Instructions
Using the worksheet on the following page, identify the remaining “Customer
Needs” from the “Customer Issues” listed. Once complete, translate the
“Customer Needs” into “CTQs”.
Prepare your findings.
CTQ Determination
SI Project Template: CTQ Determination_SI
52
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Translate the following VOC into CTQ’s
Segment Customer Issue Customer Need CTQ
External It takes too long to process loans Reduce loan
processing
cycle time
15 day loan
processing cycle
time
External There are too many errors on the
final determination packages
Reduce errors on
final determination
package
100% accuracy on
final determination
package
External It is very difficult to reach anyone at
SI
Internal No clear roles and responsibilities to
who owns the loan process
Internal Too much time is spent reviewing the
application
CTQ Determination
53
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Tips in CTQ determination:
– Document the need, not the solution (this is done in the Improve Phase).
– Use measurable terms.
– Avoid words like “should” or “must”.
Utilize the previous pages as a guide for CTQ determination.
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Please Do Not Proceed Forward
CTQ Determination
54
For additional information
about this concept, see
Lesson 7 Voice of
Customer, in the How to
Translate VOC into CTQs
section.
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Segment Customer Issue Customer Need CTQ
External It takes too long to process loans Reduce loan
processing
cycle time
15 day loan
processing cycle
time
External There are too many errors on the
final determination packages
Reduce errors on
final determination
package
100% accuracy on
final determination
package
External It is very difficult to reach anyone at
SI
First call contact
with SI personnel
100% first call
contact
Internal No clear roles and responsibilities to
who owns the loan process
Clearly defined and
documented roles
and responsibilities
100%
documentation of
roles and
responsibilities
Internal Too much time is spent reviewing the
application
Reduce loan
reviewing time
2 day loan
reviewing time
SI CTQ Determination
55
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Lean Six Sigma – Simco International
Measure Phase
1
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Simco International – Measure Phase Deliverables
Deliverable Page Lesson
(Deliverable Originated From)
Operational Definitions 3 Data Collection
Data Collection Planning 8 Data Collection
Histogram 13 Describe & Display Data
Run Chart 20 Describe & Display Data
Control Chart 27 Describe & Display Data
Sigma Performance (DPMO) 34 Baseline Performance
2
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Operational Definitions
Lean Six Sigma – Project Simulation
3
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Objective
Develop operational definitions for some of the measures identified in the X/Y
Matrix for the Consumer Home Loan process.
Instructions
Using the worksheet on the following page, develop specific operational
definitions for each measure identified.
Prepare your findings.
Operational Definitions
SI Project Template: Operational Definitions_SI
4
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% of Defective Incoming
Applications
Application Cycle Time per
Department Segment
# of Final Determination
Packages with Errors
Total Loan Processing Cycle
Time
Operational DefinitionPerformance Measure
Operational Definitions
5
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Please Do Not Proceed Forward
Operational Definitions
6
For additional information
about this concept, see
Lesson 10 Data Collection,
in the Operational
Definitions section.
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Performance Measure Operational Definition
Total Loan Processing Cycle
Time
The total time in business days from when a customer submits the
application to when the loan is mailed by location
# of Final Determination
Packages with Errors
The total # of final determination packages that have an inaccurate
field by defect type (name, address, loan #, loan amount, loan
duration, city, state) from total packages processed
% of Defective Incoming
Applications
The total # of applications that are inaccurate (by type) or
incomplete when received from the customer divided by the total #
of applications received
Application Cycle Time Per
Department Segment
The total time in business days to complete the application
processing per department (RA, MSA, LP, LO)
SI Operational Definitions
7
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Data Collection Planning
Lean Six Sigma – Project Simulation
8
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Objective
Develop a data collection plan for the SI Consumer Home Loan process.
Instructions
Using the worksheet on the following page, develop a data collection plan for
the performance measures previously identified.
Prepare your findings.
Data Collection Planning
SI Project Template: Data Collection Planning_SI
9
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Measure Type of
Measure
Type of
Data
Operational Definitions Sampling Display
Total Loan
Processing
Cycle Time
The total time in days from when a
customer submits the application to
when the loan is mailed by location;
Time stamp calculation in SI database
SI Database: Sample
of 105 Loans (1/1-
3/31) from Chicago,
London, Singapore
Histogram,
Run Chart,
Control Chart
# of Final
Determination
Packages with
Errors
The total # of final determination
packages that have an inaccurate field
by defect type (name, address, loan #,
loan amount, loan duration, city, state)
from total packages processed; Check
Sheet completed by associates
Real Time: Sample of
240 Determination
Packages (April) from
Chicago, London,
Singapore
Pareto
% of Defective
Incoming
Applications
The total # of applications that have an
inaccurate field (by type) or incomplete
when received from the customer
divided by the total # of applications
received; Check Sheet completed by
associates
Real Time: Sample of
240 Applications
(April) from Chicago,
London, Singapore
Pareto
Application
Cycle Time Per
Department
Segment
The total time in days to complete the
application processing per department
(RA, MSA, LP, LO); Time stamp
calculation in SI database
SI Database: Sample
of 105 Applications
(1/1-3/31) from
Chicago, London,
Singapore
Histogram,
Run Chart,
Control Chart;
Pareto by
department
Data Collection Planning
10
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Please Do Not Proceed Forward
Data Collection Planning
11
For additional information
about this concept, see
Lesson 10 Data Collection,
in the Collecting Data
section.
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Measure Type of
Measure
Type of
Data
Operational Definitions Sampling Display
Total Loan
Processing
Cycle Time
Output Continuous The total time in days from when a
customer submits the application to
when the loan is mailed by location;
Time stamp calculation in SI database
SI Database: Sample
of 105 Loans (1/1-
3/31) from Chicago,
London, Singapore
Histogram,
Run Chart,
Control Chart
# of Final
Determination
Packages with
Errors
Output Discrete The total # of final determination
packages that have an inaccurate field
by defect type (name, address, loan #,
loan amount, loan duration, city, state)
from total packages processed; Check
Sheet completed by associates
Real Time: Sample of
240 Determination
Packages (April) from
Chicago, London,
Singapore
Pareto
% of Defective
Incoming
Applications
Input Discrete The total # of applications that have an
inaccurate field (by type) or incomplete
when received from the customer
divided by the total # of applications
received; Check Sheet completed by
associates
Real Time: Sample of
240 Applications
(April) from Chicago,
London, Singapore
Pareto
Application
Cycle Time Per
Department
Segment
Process Continuous The total time in days to complete the
application processing per department
(RA, MSA, LP, LO); Time stamp
calculation in SI database
SI Database: Sample
of 105 Applications
(1/1-3/31) from
Chicago, London,
Singapore
Histogram,
Run Chart,
Control Chart;
Pareto by
department
SI Data Collection Plan
12
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Histogram
Lean Six Sigma – Project Simulation
13
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Objective
Create a Histogram from the Chicago Total Loan Processing Cycle
Time data and conduct initial analysis.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Chicago Cycle Time”. Utilize your
statistical software to display and describe the variation in the process
using a “Histogram.”
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Histogram and
descriptive statistics?
Histogram
SI Project Template: Histogram_SI
14
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Please Do Not Proceed Forward
Histogram
15
For additional information
about this concept, see
Lesson 11 Describe and
Display Data, in the
Understanding Variation
section.
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Histogram
SigmaXL Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Chicago Cycle Time”.
We want to display and describe the variation in the process.
Follow these instructions to create the Histogram:
1. Select “SigmaXL” from the toolbar in Excel
2. Select “Graphical Tools” from the menu
3. Select “Histograms & Descriptive Statistics” from the menu
4. Select “Use entire data table” from the data window
5. Select “Next”
6. Select “Numeric Data Variables (Y)” to move the Chicago Loan Processing Cycle
Time data set into the function window
7. Select “OK”
8. SigmaXL will generate a new worksheet “Hist Descript”
16
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SI Histogram
SigmaXL Results
* Additional information is provided (which we do not always use) when you perform this analysis.
17
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SI Team Analysis
– Large variation and spread in cycle time
– No data points are below the CTQ of 15 days
– 2 loans took considerably more time to complete than the rest of the data set
– Data is non-normal as identified by the p-value less than 0.05 from the Anderson-Darling Normality Test
Copyright © 2016 Acuity Institute LLC. All rights reserved.
SI Histogram
Minitab Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Chicago Cycle Time”.
We want to display and describe the variation in the process.
Follow these instructions to create the Histogram:
1. Copy the entire data set including the header
2. Open the Minitab software
3. Paste the data set into Column 1 (C1) of Minitab
4. Select “Paste as a single column”
5. Select “OK”
6. Select “Stat” from the toolbar
7. Select “Basic Statistics” from the menu
8. Select “Graphical Summary” from the menu
9. Highlight “C1 Chicago Loan” from the menu
10. Click on “Select”
11. Select “OK”
12. Minitab will generate a summary with the Histogram and descriptive statistics for
Chicago Cycle Time
18
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SI Histogram
Minitab Results
* Additional information is provided (which we do not always use) when you perform this analysis.
19
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SI Team Analysis
– Large variation and spread in cycle time
– No data points are below the CTQ of 15 days
– 2 loans took considerably more time to complete than the rest of the data set
– Data is non-normal as identified by the p-value less than 0.05 from the Anderson-Darling Normality Test
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Run Chart
Lean Six Sigma – Project Simulation
20
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Objective
Create a Run Chart from the Chicago Total Loan Processing Cycle Time
data and conduct initial analysis.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Chicago Cycle Time”. Utilize your statistical
software to display and describe the variation in the process using a “Run”
chart.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Run Chart?
Run Chart
SI Project Template: Run Chart_SI
21
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Please Do Not Proceed Forward
Run Chart
22
For additional information
about this concept, see
Lesson 11 Describe and
Display Data, in the Types
of Variation section.
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Run Chart
SigmaXL Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Chicago Cycle Time”.
We want to display and describe the variation in the process.
Follow these instructions to create the Run Chart:
1. Select “SigmaXL” from the toolbar in Excel
2. Select “Graphical Tools” from the menu
3. Select “Run Chart” from the menu
4. Select “Use entire data table” from the data window
5. Select “Next”
6. Select “Numeric Data Variables (Y)” to move the Chicago Loan Processing Cycle
Time data set into the function window
7. Select “Show Mean”
8. Select “OK”
9. SigmaXL will generate a new worksheet “Run Chart”
23
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SI Run Chart
SigmaXL Results
24
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Notes:
SI Team Analysis
– Large variation and spread in cycle time
– 2 loans took considerably more time to complete than the rest of the data set
– Cycle time is not trending upwards or downwards
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Run Chart
Minitab Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Chicago Cycle Time”.
We want to display and describe the variation in the process.
Follow these instructions to create the Run Chart:
1. Copy the entire data set including the header
2. Open the Minitab software
3. Paste the data set into Column 1 (C1) of Minitab
4. Select “Paste as a single column”
5. Select “OK”
6. Select “Stat” from the toolbar
7. Select “Quality Tools” from the menu
8. Select “Run Chart” from the menu
9. Select “Subgroups across rows of” from the menu
10. Click inside the data box
11. Highlight “C1 Chicago Loan” from the menu
12. Click on “Select”
13. Select “OK”
14. Minitab will generate a summary with the Run Chart and descriptive statistics for Chicago Cycle
Time
25
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SI Run Chart
Minitab Results
* Additional information is provided (which we do not always use) when you perform this analysis.
26
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Notes:
SI Team Analysis
– Large variation and spread in cycle time
– 2 loans took considerably more time to complete than the rest of the data set
– Cycle time is not trending upwards or downwards
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Control Chart
Lean Six Sigma – Project Simulation
27
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Objective
Create a Control Chart from the Singapore Total Loan Processing
Cycle Time data and conduct initial analysis.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore Cycle Time”. Utilize your
statistical software to display and describe the variation in the process
using an “Individuals & Moving Range” control chart.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Individuals & Moving
Range control chart and special cause tests?
Control Chart
SI Project Template: Control Chart_SI
28
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Please Do Not Proceed Forward
Control Chart
29
For additional information
about this concept, see
Lesson 11 Describe and
Display Data, in the Types
of Variation section.
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Presenter
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When you see this symbol, please do not continue forward in the materials.
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Control Chart
SigmaXL Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore Cycle Time”.
We want to display and describe the variation in the process.
Follow these instructions to create the Control Chart:
1. Select “SigmaXL” from the toolbar in Excel
2. Select “Control Charts” from the menu
3. Select “Individuals & Moving Range” from the menu
4. Select “Use entire data table” from the data window
5. Select “Next”
6. Select “Numeric Data Variables (Y)” to move Singapore Cycle Time data set into the
function window
7. Select “Tests for Special Causes”
8. Select “OK”
9. SigmaXL will generate a new worksheet “Indiv & MR Charts“
30
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SI Control Chart
SigmaXL Results
31
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SI Team Analysis
– Process is not in statistical control due to failing one of the tests for special cause variation (4 out of 5 points more than 1 standard deviation from center line, on one side of center line)
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Control Chart
Minitab Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore Cycle Time”.
We want to display and describe the variation in the process.
Follow these instructions to create the Control Chart:
1. Copy the entire data set including the header
2. Open the Minitab software
3. Paste the data set into Column 1 (C1) of Minitab
4. Select “Paste as a single column”
5. Select “OK”
6. Select “Stat” from the toolbar
7. Select “Control Charts” from the menu
8. Select “Variables Charts for Individuals” from the menu
9. Select “I-MR” menu
10. Highlight “C1 Singapore Cycle Time” from the menu
11. Click on “Select”
12. Select “I-MR Options…”
13. Select “Tests”
14. Select “Perform all tests for special causes” from the drop down menu
15. Select “OK”
16. Select “OK”
17. Minitab will generate the I-MR Charts for Singapore Cycle Time
32
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SI Control Chart
Minitab Results
33
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SI Team Analysis
– Process is not in statistical control due to failing one of the tests for special cause variation (4 out of 5 points more than 1 standard deviation from center line, on one side of center line)
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Sigma Performance (DPMO)
Lean Six Sigma – Project Simulation
34
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Objective
Calculate Sigma Performance for Chicago Final Determination Package accuracy.
Instructions
Utilize the information below and complete the fields for Units, Defects, and Opportunities.
Total number of loans = 240
Total number defects = 72
Total number of critical fields to customer = 7
Calculate the DPMO and Sigma for accuracy. Sigma can be found on the abridged sigma
table on the following page.
Prepare your findings.
DPMO = 1M
Units x Opportunities
Defects
_______ Units
_______ Defects
_______ Opportunities
_____________ DPMO
_____________ Sigma
( )
( ) ( )=
Sigma Performance (DPMO)
SI Project Template: Sigma Performance_SI
35
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Yield Sigma DPMO Yield Sigma DPMO
99.99966% 6.00 3.4 98.60966% 3.70 13,903
99.99946% 5.90 5.4 98.21356% 3.60 17,864
99.99915% 5.80 8.5 97.72499% 3.50 22,750
99.99867% 5.70 13 97.12834% 3.40 28,717
99.99793% 5.60 21 96.40697% 3.30 35,930
99.99683% 5.50 32 95.54345% 3.20 44,565
99.99519% 5.40 48 94.52007% 3.10 54,799
99.99277% 5.30 72 93.31928% 3.00 66,807
99.98922% 5.20 108 91.92433% 2.90 80,757
99.98409% 5.10 159 90.31995% 2.80 96,800
99.97674% 5.00 233 88.49303% 2.70 115,070
99.96631% 4.90 337 86.43339% 2.60 135,666
99.95166% 4.80 483 84.13447% 2.50 158,655
99.93129% 4.70 687 81.99519% 2.40 184,060
99.90323% 4.60 968 78.81446% 2.30 211,855
99.86501% 4.50 1,350 75.80363% 2.20 241,964
99.81342% 4.40 1,866 72.57469% 2.10 274,253
99.74449% 4.30 2,555 69.14625% 2.00 308,538
99.65330% 4.20 3,467 65.54217% 1.90 344,578
99.53388% 4.10 4,661 61.79114% 1.80 382,089
99.37903% 4.00 6,210 57.92597% 1.70 420,740
99.18025% 3.90 8,198 53.98278% 1.60 460,172
98.92759% 3.80 10,724 50.00000% 1.50 500,000
Abridged Sigma Table
Abridged Process Sigma Conversion Table
36
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Sheet1
Yield Sigma DPMO Yield Sigma DPMO
99.99966% 6.00 3.4 98.60966% 3.70 13,903
99.99946% 5.90 5.4 98.21356% 3.60 17,864
99.99915% 5.80 8.5 97.72499% 3.50 22,750
99.99867% 5.70 13 97.12834% 3.40 28,717
99.99793% 5.60 21 96.40697% 3.30 35,930
99.99683% 5.50 32 95.54345% 3.20 44,565
99.99519% 5.40 48 94.52007% 3.10 54,799
99.99277% 5.30 72 93.31928% 3.00 66,807
99.98922% 5.20 108 91.92433% 2.90 80,757
99.98409% 5.10 159 90.31995% 2.80 96,800
99.97674% 5.00 233 88.49303% 2.70 115,070
99.96631% 4.90 337 86.43339% 2.60 135,666
99.95166% 4.80 483 84.13447% 2.50 158,655
99.93129% 4.70 687 81.99519% 2.40 184,060
99.90323% 4.60 968 78.81446% 2.30 211,855
99.86501% 4.50 1,350 75.80363% 2.20 241,964
99.81342% 4.40 1,866 72.57469% 2.10 274,253
99.74449% 4.30 2,555 69.14625% 2.00 308,538
99.65330% 4.20 3,467 65.54217% 1.90 344,578
99.53388% 4.10 4,661 61.79114% 1.80 382,089
99.37903% 4.00 6,210 57.92597% 1.70 420,740
99.18025% 3.90 8,198 53.98278% 1.60 460,172
98.92759% 3.80 10,724 50.00000% 1.50 500,000
Sheet2
Sheet3
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Please Do Not Proceed Forward
Sigma Performance (DPMO)
37
For additional information
about this concept, see
Lesson 12 Baseline
Performance, in the
Sigma section.
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Baseline Performance
240 Units
72 Defects
7 Opportunities
42,857 DPMO
3.2 Sigma
DPMO = 1M Units x Opportunities
Defects
( 240 )
=
( 72 )
( 7 )
SI Sigma Performance
38
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Lean Six Sigma – Simco International
Analyze Phase
1
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Simco International – Analyze Phase Deliverables
Deliverable Page Lesson
(Deliverable Originated From)
Cause and Effect Analysis 3 Root Cause Analysis
Lean Process Analysis 8 Lean Process Analysis
Pareto 18 Graphical Data Analysis
Box Plots 25 Graphical Data Analysis
Correlation Analysis 32 Graphical Data Analysis
Regression Analysis 39 Statistical Data Analysis
2
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Cause and Effect Analysis
Lean Six Sigma – Project Simulation
3
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Objective
Develop cause and effect relationships for the SI Consumer Home Loan
process problem statement.
Instructions
Complete the “Process” component of the Fishbone diagram on the following
page.
Then, circle all significant Potential Root Causes in the entire Fishbone.
Prepare your findings.
Cause and Effect Analysis
SI Project Template: Cause and Effect Analysis_SI
4
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Loan Processing Cycle Time in
Chicago Takes an Average of
31 Days to Complete
People
Process
Staffing not aligned with
peak volume
It is difficult to handle the volume
at different times throughout the year
The LP does not know which
forms to use for different loan types
The Loan Processor often
does the job of the Loan Officer
Waiting for information
from another department
Unclear number of loans
required to complete per day
Internal mail department only
picks up and delivers once a day
Work load for Loan Processors and
Loan Officers is inconsistent
It is difficult for the LP to
understand the
LO final determination
Waiting for applications and information in the mail
The LP was not trained on
different loan types
Work load for Loan Processors and
Loan Officers is inconsistent
Cause and Effect Analysis
5
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Notes:
The above cause-and-effect diagram was generated by the project team for the Chicago loan processing cycle time.
Note the problem statement (primary effect) that is being analyzed at the head of the diagram and the corresponding major categories (or “bones”) of Process and People.
Take a moment to review the causes and effects for each category and their relationships to the overall problem.
Utilize your understanding of the process to create potential root causes. Remember to ask the question “Why?”.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Please Do Not Proceed Forward
Cause and Effect Analysis
6
For additional information
about this concept, see
Lesson 14 Root Cause
Analysis, in the Root Cause
Analysis section.
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Loan Processing Cycle Time in
31 Days to Complete
People
Chicago Takes an Average of
Process
Staffing not aligned with
peak volume
It is difficult to handle the volume
at different times throughout the year
The LP does not know which
forms to use for different loan types
The Loan Processor often
does the job of the Loan Officer
Requirement to send
everything by regular mail
No Process Controls
Waiting for information
from another department
Unclear how long it should
take to perform
individual tasks
Unclear number of loans
required to complete per day
Internal mail department only
picks up and delivers once a day
One mail person
on staff
Work load for Loan Processors and
Loan Officers is inconsistent
It is difficult for the LP to
understand the
LO final determination
Budget only
allows for one
mail person
Waiting for applications and information in the mail
The LP was not trained on
different loan types
Work load for Loan Processors and
Loan Officers is inconsistent
SI Cause and Effect Analysis
7
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Lean Process Analysis
Lean Six Sigma – Project Simulation
8
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Lean Process Analysis
Objective
Complete a Lean Analysis for the SI Consumer Home Loan process.
Instructions
Using the descriptions below and the “SI Deployment Flowchart with Time” (on the following
pages), complete the Lean Analysis worksheet (value-add/non value-add) on the following
page.
Calculate the total value-add and non value-add steps, total time, and % of total time.
Prepare your findings.
Value-Added Questions:
1.Change the process?
2.Customer recognizes the value?
3.Done right the first time?
4.Required by law or regulation?
Non Value-Added Examples:
– Waiting – Storing – Counting
– Inspecting – Recording – Obtaining
– Approvals – Reviewing – Copying
– Reworking – Filing – Tracking
SI Project Template: Lean Process Analysis_SI
9
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Lean Process Analysis
Process Step 1 2 3 4 5 6 7 8 9 1
0
1
1
1
2
1
3
1
4
1
5
1
6
1
7
1
8
1
9
2
0
2
1
2
2
2
3
Total
Steps
Total
Time
% of
Total
Time
Time (Hours)
Value-Added
Non Value-
Added
Delay
Set-up
Inspection
Transporting
Rework
10
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SI Cycle Time Per Process Step
Process
Step
Cycle Time
(Hours)
1 1/2
2 32
3 2
4 32
5 8
6 8
7 1
8 1/2
Process
Step
Cycle Time
(Hours)
9 2
10 32
11 1
12 1/2
13 1/2
14 1
15 1/2
16 1/2
Process
Step
Cycle Time
(Hours)
17 1
18 1
19 8
20 1/2
21 1
22 32
23 1/2
11
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Lean Process Analysis – SI As-Is Process
Map
SIMCO International “As-Is” Process Map (Page 1)
R
ea
l
Es
ta
te
Ag
en
t
(R
A)
SI
M
or
tg
ag
e
Sa
le
s
As
so
ci
at
e
(M
SA
)
SI
L
oa
n
Pr
oc
es
so
r
(L
P)
SI
L
oa
n
O
ffi
ce
r
(L
O
)
H
om
e
Lo
an
C
us
to
m
er
Contact RA to
request loan
Mail loan
application to
customer
Complete loan
application
Mail loan
application to
RA
Forward
application to
MSA
Forward
application to
LP
Review
application
Request
additional info
from customer
Gather
additional
information
Mail additional
information to
LP
Go to Step 12
(Next Page)
Review
application
and additional
information
1
2
3 4
5
6
7 8
9 10
11
12
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Lean Process Analysis – SI As-Is Process
Map
SIMCO International “As-Is” Process Map (Page 2)
SI
L
oa
n
O
ffi
ce
r
(L
O
)
SI
L
oa
n
Pr
oc
es
so
r
(L
P)
SI
M
or
tg
ag
e
Sa
le
s
As
so
ci
at
e
(M
SA
)
R
ea
l
Es
ta
te
Ag
en
t
(R
A)
H
om
e
Lo
an
C
us
to
m
er
Go to Step 8
(Previous Page)
Is info
complete?
Forward
customer info
to LO
Determine
loan
qualification
Send final
determination
to LP
Is loan
accepted?
Create SI
Home Loan
acceptance
package
Create SI
Home Loan
rejection
package
Forward final
determination
package to
MSA
Schedule
meeting with
RA to review
final package
Review final
package
Send final
package to
customer
Receive final
determination
package
Yes
No No
Yes
12
13
14 15
16
17
18 19
20
21 22
23
13
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Please Do Not Proceed Forward
Lean Process Analysis
14
For additional information
about this concept, see
Lesson 15 Lean Process
Analysis, in the Lean
Process Analysis and
Measures section.
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SI Lean Process Analysis
Process Step 1 2 3 4 5 6 7 8 9 1
0
1
1
1
2
1
3
1
4
1
5
1
6
1
7
1
8
1
9
2
0
2
1
2
2
2
3
Total
Steps
Total
Time
% of
Total
Time
Time (Hours) 23 166 Hrs 100%
Value-Added x x x x x x 6 6 Hrs 4%
Non Value-Added x x x x x x x x x x x x x x x x x 17 160 Hrs 96%
Delay x 1 .5 Hrs .5%
Set-up x x 2 2 Hrs 1%
Inspection x x 2 1 Hour .5%
Transporting x x x x x x x 7 144.5 Hrs 87%
Rework x x x x x 5 12 Hrs 7%
15
See SI Cycle Time Per Process Step
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SI Lean Process Analysis
Simco International “As-Is” Process Map (Page 1)
Re
al
Es
ta
te
Ag
en
t
(R
A)
SI
M
or
tg
ag
e
Sa
les
As
so
cia
te
(M
SA
)
SI
L
oa
n
Pr
oc
es
so
r
(L
P)
SI
L
oa
n
Of
fic
er
(L
O)
Ho
m
e
Lo
an
Cu
sto
m
er
Contact RA to
request loan
Mail loan
application to
customer
Complete loan
application
Mail loan
application to
RA
Forward
application to
MSA
Forward
application to
LP
Review
application
Request
additional info
from customer
Gather
additional
information
Mail additional
information to
LP
Go to Step 12
(Next Page)
Review
application
and additional
information
1
2
3 4
5
6
7 8
9 10
11
X = Non Value-Added Step
X
X
X
X
X
X
X
X
X
16
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SI Lean Process Analysis
Simco International “As-Is” Process Map (Page 2)
SI
L
oa
n
O
ffi
ce
r
(L
O
)
SI
L
oa
n
Pr
oc
es
so
r
(L
P)
SI
M
or
tg
ag
e
Sa
le
s
As
so
cia
te
(M
SA
)
Re
al
Es
ta
te
Ag
en
t
(R
A)
Ho
m
e
Lo
an
Cu
st
om
er
Go to Step 8
(Previous Page)
Is info
complete?
Forward
customer info
to LO
Determine
loan
qualification
Send final
determination
to LP
Is loan
accepted?
Create SI
Home Loan
acceptance
package
Create SI
Home Loan
rejection
package
Forward final
determination
package to
MSA
Schedule
meeting with
RA to review
final package
Review final
package
Send final
package to
customer
Receive final
determination
package
Yes
No No
Yes
12
13
14 15
16
17
18 19
20
21 22
23
X
X
X X
X
XXX
X = Non Value-Added Step
17
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Process Stratification and Analysis – Pareto
Lean Six Sigma – Project Simulation
18
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Objective
Create a Pareto Chart from the # of Final Determination Packages with Errors for
London and conduct initial analysis.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is from a check sheet and is located in the worksheet “# of Package
Errors”. Utilize your statistical software to display and describe the variation in the
process using a Pareto Chart.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Pareto?
Prepare your findings.
Pareto
SI Project Template: Pareto_SI
19
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Please Do Not Proceed Forward
Pareto
20
For additional information
about this concept, see
Lesson 16 Graphical Data
Analysis, in the Analyzing
Data Graphically section.
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Pareto
SigmaXL Instructions
Open up the Excel file “LSS SI Data File”.
The data set is from a check sheet and is located in the worksheet “# of Package
Errors”.
We want to display and describe the variation in the process.
Follow these instructions to create the Pareto:
1. Click “SigmaXL” from the toolbar in Excel
2. Select “Graphical Tools” from the menu
3. Select “Basic Pareto Chart” from the menu
4. Select “Use entire data table” from the data window
5. Click “Next”
6. Select “Pareto Category (X)” to move Application Fields data set into the function
window
7. Select “Optional Numeric Count (Y)” to move Number of Errors data set into the
function window
8. Select “Finish”
9. SigmaXL will generate a new worksheet “Pareto”
21
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SI Pareto
SigmaXL Results
22
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SI Team Analysis
– Loan Amount and Name account for 86% of the total final determination package errors.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Pareto
Minitab Instructions
The following are the instructions to complete this deliverable using Minitab.
Open up the Excel file “LSS SI Date file”
The data set is from a check sheet and is located in the worksheet “# of Package Errors”
We want to display and describe the variation in the process
Follow these instructions to create the Pareto:
1. Copy the entire data set including the headers
2. Open the Minitab software
3. Paste the data set into Minitab
4. Select “Stat” from the toolbar
5. Select “Quality Tools” from the menu
6. Select “Pareto Chart” from the menu
7. Click inside the data box for “Defects or attribute data in:”
8. Highlight “C1 Application Fields” from the menu
9. Click on “Select”
10. Highlight “C2 Numbers of Errors” from the menu
11. Click on “Select” to add to “Frequencies in”
12. Select “OK”
13. Minitab will generate a Pareto Chart for # of Package Errors
23
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SI Pareto
Minitab Results
24
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SI Team Analysis
– Loan Amount and Name account for 86% of the total final determination package errors.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Process Stratification and Analysis – Box Plots
Lean Six Sigma – Project Simulation
25
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Objective
Create a Box Plot from the SI Loan Processing Cycle Time from all 3 locations and
conduct initial analysis.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is located in the worksheet “Cycle Time for 3 Locations”. We want to
display and describe the variation in the process. Utilize your statistical software to
display and describe the variation in the process using a Box Plot.
When completed, answer the following questions:
1. How would you describe the variation in the data?
2. What conclusions can you draw from the Box Plot?
Prepare your findings.
Box Plots
SI Project Template: Box Plots_SI
26
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Please Do Not Proceed Forward
Box Plots
27
For additional information
about this concept, see
Lesson 16 Graphical Data
Analysis, in the Analyzing
Data Graphically section.
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Box Plots
SigmaXL Instructions
Open up the Excel file “LSS SI Data File”.
The data set is located in the worksheet “Cycle Time for 3 Locations”.
We want to display and describe the variation in the process.
Follow these instructions to create the Pareto:
1. Click “SigmaXL” from the toolbar in Excel
2. Select “Graphical Tools” from the menu
3. Select “Boxplots” from the menu
4. Select “Use entire data table” from the data window
5. Click “Next”
6. Select “Numeric Data Variables (Y)” 3 times to move cycle time data sets into the
function window
7. Select “Show Legend”
8. Select “OK”
9. SigmaXL will generate a new worksheet “Boxplot”.
28
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SI Box Plots
SigmaXL Results
29
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SI Team Analysis
Chicago has the highest average between the 3 sites
Chicago has 2 significant outliers
– Both Chicago and Singapore have significant variation
– London variation is less than the other sites and the average cycle time is below the CTQ of 15 days
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Box Plots
Minitab Instructions
Open up the Excel file “LSS SI Data File”.
The data set is located in the worksheet “Cycle Time for 3 Locations”.
We want to display and describe the variation in the process.
Follow these instructions to create the Box Plot:
1. Copy the entire data set including the headers
2. Open the Minitab software
3. Paste the data set into Minitab
4. Select “Graph” from the toolbar
5. Select “Boxplot” from the menu
6. Select “Simple” from the menu under “Multiple Y’s”
7. Select “OK”
8. Click inside the data box for “Graph variables”
9. Highlight “C1 Chicago Cycle Time” from the menu
10. Click on “Select” (repeat for C2 and C3)
11. Select “OK”
12. Minitab will generate a Boxplot for Cycle Time for 3 Locations
30
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SI Box Plots
Minitab Results
31
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SI Team Analysis
Chicago has the highest average between the 3 sites
Chicago has 2 significant outliers
– Both Chicago and Singapore have significant variation
– London variation is less than the other sites and the average cycle time is below the CTQ of 15 days
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Correlation Analysis
Lean Six Sigma – Project Simulation
32
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Objective
Create a Scatter Diagram from data to determine correlation and conduct initial
analysis.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore LP Cycle Time”. We want to determine if
there is a strong relationship (correlation) between the Singapore LP Cycle Time (X)
and the Singapore Total Cycle Time (Y). Utilize your statistical software to perform
correlation.
When completed, answer the following question:
1. How would you interpret the graph?
Prepare your findings.
Correlation Analysis
SI Project Template: Correlation Analysis_SI
33
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Please Do Not Proceed Forward
Correlation Analysis
34
For additional information
about this concept, see
Lesson 16 Graphical Data
Analysis, in the Analyzing
Data Graphically section.
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Correlation Analysis
SigmaXL Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore LP Cycle Time”.
We want to determine if there is a strong relationship (correlation) between the
Singapore LP Cycle time (X) and the Singapore Total Cycle Time (Y).
Follow these instructions to perform correlation:
1. Click “SigmaXL” from the toolbar in Excel
2. Select “Graphical Tools” from the menu
3. Select “Scatter Plots” from the menu
4. Select “Use entire data table” from the data window
5. Click “Next“
6. Select the first measure “Singapore Total Cycle Time”
7. Select “Singapore Total Cycle Time” for your Numeric Response (Y)
8. Select “Singapore LP Cycle Time” for your Numeric Predictor (X1)
9. Click “OK”
10. SigmaXL will generate a new worksheet “Scatterplot”.
35
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SI Correlation Analysis
SigmaXL Results
36
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Notes:
SI Team Analysis
– A possible positive correlation exists between the Singapore LP Cycle Time and the Singapore Total Cycle Time
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Correlation Analysis
Minitab Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore LP Cycle Time”.
We want to determine if there is a strong relationship (correlation) between the Singapore LP
Cycle time (X) and the Singapore Total Cycle Time (Y).
Follow these instructions to perform correlation:
1. Copy the entire data set including the headers
2. Open the Minitab software
3. Paste the data set into Minitab
4. Select “Graph” from the toolbar
5. Select “Scatterplot” from the menu
6. Select “With Regression” from the menu
7. Select “OK”
8. Click inside the data box for “Y variables”
9. Highlight “C2 Singapore Total Cycle Time” from the menu
10. Click on “Select” to move under “Y variables”
11. Highlight “C3 Singapore LP Cycle Time” from the menu
12. Click on “Select” to move under “X variables”
13. Select “OK”
14. Minitab will generate a Scatterplot for Singapore LP Cycle Time
37
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SI Correlation Analysis
Minitab Results
38
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Notes:
SI Team Analysis
– A possible positive correlation exists between the Singapore LP Cycle Time and the Singapore Total Cycle Time
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Regression Analysis
Lean Six Sigma – Project Simulation
39
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Objective
Conduct Regression Analysis from data and conduct root cause analysis.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore LP Cycle Time”. We want to determine if
there is a statistical correlation between the Singapore LP Cycle Time (X) and the
Singapore Total Cycle Time (Y). Utilize your statistical software to perform Regression
Analysis.
When completed, answer the following questions:
1. How would you interpret the output of the analysis?
2. What conclusions can you draw from the p-value and the R2 value?
Prepare your findings.
Regression Analysis
SI Project Template: Regression Analysis_SI
40
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Please Do Not Proceed Forward
Regression Analysis
41
For additional information
about this concept, see
Lesson 17 Statistical Data
Analysis, in the Hypothesis
Testing Tools section.
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Regression Analysis
SigmaXL Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore LP Cycle Time”.
We want to see if there is a statistical correlation between the Singapore LP Cycle time (X) and
the Singapore Total Cycle Time (Y).
Follow these instructions to perform Regression:
1. Select “SigmaXL” from the toolbar in Excel
2. Select “Statistical Tools” from the menu
3. Select “Regression” from the menu
4. Select “Multiple Regression” from the menu
5. Select “Use entire data table” from the data window
6. Select “Next”
7. Select the first measure “Singapore Total Cycle Time”
8. Select “Numeric Response (Y)” to move Singapore Total Cycle Time data set into the function
window
9. Select “Continuous Predictors (X)” 1 time to move the cycle time data set for Singapore LP Cycle
Time into the function window
10. Select “OK”
11. SigmaXL will generate a new worksheet “Multiple Regression“ and a second worksheet “Mult
Reg Residuals”
42
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SI Regression Analysis
SigmaXL Results
* Additional information is provided (which we do not always use) when you perform this analysis.
43
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Notes:
SI Team Analysis
– R-Sq = 47.1% of the variation in the process output is accounted for by the model
– P-Value < 0.05, the Singapore LP Cycle Time does influence the Singapore Total Cycle Time
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Regression Analysis
Minitab Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “Singapore LP Cycle Time”.
We want to see if there is a statistical correlation between the Singapore LP Cycle time (X) and the
Singapore Total Cycle Time (Y).
Follow these instructions to perform Regression:
1. Copy the entire data set including the headers
2. Open the Minitab software
3. Paste the data set into Minitab
4. Select “Stat” from the toolbar
5. Select “Regression” from the menu
6. Select “Fitted Line Plot…” from the menu
7. Click inside the data box for “Response “(Y)”
8. Highlight “C2 Singapore Total Cycle Time” from the menu
9. Click on "Select”
10. Click inside the data box for “Predictor “(X)”
11. Highlight “C3 Singapore LP Cycle Time” from the menu
12. Click on "Select”
13. Select “OK”
14. Minitab will generate a Fitted Line Plot and summary for Singapore Cycle Time
44
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SI Regression Analysis
Minitab Results
* Additional information is provided (which we do not always use) when you perform this analysis.
45
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Notes:
SI Team Analysis
- R-Sq = 47.1% of the variation in the process output is accounted for by the model
- P-Value < 0.05, the Singapore LP Cycle Time does influence the Singapore Total Cycle Time
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Lean Six Sigma – Simco International
Improve Phase
1
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Simco International – Improve Phase Deliverables
Deliverable Page Lesson
(Deliverable Originated From)
Solution Selection Matrix 3 Identify & Select Solutions
Cost/Benefit Analysis 8 Financial Impact of Solutions
Mitigating Risks (FMEA) 13 Risk Planning and Testing
Pilot Plan 18 Risk Planning and Testing
Implementation Planning 23 Implement Solution
Storyboarding 28 Implement Solution
2
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Solution Selection Matrix
Lean Six Sigma – Project Simulation
3
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Objective
Complete a Solution Selection Matrix for the SI Consumer Home Loan process.
Instructions
Utilize the worksheet on the following page to complete the Solution Selection Matrix.
Rate each solutions impact on the criteria using the following scale (1=low impact,
3=medium impact, 9=high impact). Impact for each criteria should be calculated as follows:
Sigma Impact = rate the solutions impact on improving sigma
Time Impact = rate the solutions impact on time investment needed to implement
Cost / Benefit Impact = rate the solutions impact of financial benefits over costs
Other Impacts = rate the solutions impact to other criteria (organization, morale, etc)
Multiply each rating by the weighting for the criteria and document the totals for each
solution.
Rank the solutions from highest to lowest and select the solutions for the SI process.
Prepare your findings.
Solution Selection Matrix
SI Project Template: Solution Selection Matrix_SI
4
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Criteria Total Rank
Weight
Solutions Rating Score Rating Score Rating Score Rating Score
Have LP determine loan
qualification
Develop email/internet based
system to exchange information
and remove paperwork
Combine LP and MSA processes
to eliminate MSA from loan
processing
Develop online application
submission with mandatory fields
and accuracy checks
Identify and track process
segment requirements on
processing time and accuracy
3 2 3 1
Sigma Impact Time Impact Cost/ Benefit
Impact
Other Impacts
Solution Selection Matrix Worksheet
Develop training program on
different types of loans for LP
5
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Please Do Not Proceed Forward
Solution Selection Matrix
6
For additional information
about this concept, see
Lesson 20 Identify and
Select Solutions, in the
Select Solutions section.
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Criteria Total Rank
Weight
Solutions Rating Score Rating Score Rating Score Rating Score
Develop training program on
different types of loans for LP
3 9 9 18 1 3 3 3 33 5
Have LP determine loan
qualification
9 27 3 6 3 9 1 1 43 3
Develop email/internet based
system to exchange
information and remove
paperwork
9 27 1 2 9 27 9 9 65 1
Combine LP and MSA
processes to eliminate MSA
from loan processing
3 9 9 18 3 9 3 3 39 4
Develop online application
submission with mandatory
fields and accuracy checks
3 9 1 2 9 27 9 9 47 2
Identify and track process
segment requirements on
processing time and accuracy
1 3 3 6 1 3 3 3 15 6
Sigma Impact Time Impact Cost/ Benefit
Impact
Other Impacts
3 2 3 1
SI Solution Selection Matrix
7
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Cost/Benefit Analysis
Lean Six Sigma – Project Simulation
8
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Objective
Complete a Cost/Benefit Analysis for the SI Consumer Home Loan process.
Instructions
Using the costs and benefits below, utilize the worksheet on the following page to complete
the Cost/Benefit Analysis.
Total all costs and benefits and calculate net benefits
Would you recommend implementing the solutions based on the results?
Prepare your findings.
Implementation Costs Project Benefits
Hardware – SI Loan System development = $300,000 Temporary Headcount Eliminated – 15 people @ all 3 sites =
$10,000/year
Hardware – 50 PC’s with Processing Software = $1,200/each MSA/LO Processing Time Eliminated – 5 FTE’s @ all 3 sites
= $35,000/year
Consultant Training – 2 IT Consultants @ 24hrs/week for 3
weeks (includes all 3 sites) = $100/hr.
Improved cycle time – interest accrued earlier by 80% of total
loan volume = $125,000
Training Site – Training facility @ 3 days/week for 3 weeks =
$200/day
Reduction in Mail Cost – elimination of application and loan
mail costs by 80% of loan volume ($10 per approved loan @
~ 3,152 loans) = $31,520
Increased customer retention revenue ~ 300 customers
annually @ 10% interest on $200,000 home loan = $6MM
Cost/Benefit Analysis
SI Project Template: Cost Benefit Analysis_SI
9
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Implementation Costs: Measurement Variable Cost Estimate Total
Hardware
Hardware
Consultant Training
Training Site
Total Costs
Benefits: Measurement Variable Benefit Estimate Total
Temporary Headcount
Eliminated
MSA/LO Processing Time
Eliminated
Improved Cycle Time
Mail Cost Reduction
Increased Customer Retention
Total Benefits
Net Benefit (equals total benefits, less costs)
Cost/Benefit Analysis
10
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Cost/Benefit Analysis
11
For additional information
about this concept, see
Lesson 21 Financial Impact
of Solutions, in the
Cost/Benefit section.
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Implementation Costs: Measurement Variable Cost Estimate Total
Hardware SI Loan System Development $300,000 $300,000
Hardware 50 PC’s with Processing Software $1,200/each $60,000
Consultant Training 2 IT Consultants @ 24hrs./week for 3 weeks
(includes all 3 sites)
$100/hr. $14,400
Training Site Training facility @ 3 days/week for 3 weeks $200/day $1,800
Total Costs $376,200
Benefits: Measurement Variable Benefit Estimate Total
Temporary Headcount Eliminated 15 people @ all 3 sites $10,000/year $150,000
MSA/LO Processing Time Eliminated 5 FTE’s @ all 3 sites $35,000/year $175,000
Improved Cycle Time Interest accrued earlier by 80% of total loan
volume
$125,000/year $125,000
Mail Cost Reduction Elimination of application and loan mail
costs by 80% of loan volume ($10 per
approved loan @ ~ 3,152 loans)
$31,520/year $31,520
Increased Customer Retention 300 customers annually @ 10% interest on
$200K home loan
$6MM $6MM
Total Benefits ~$6.5MM
Net Benefit (equals total benefits, less costs) ~$6.1MM
SI Cost/Benefit Analysis
12
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Mitigating Risks (FMEA)
Lean Six Sigma – Project Simulation
13
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Objective
Complete a Failure Modes and Effects Analysis for the SI Consumer Home Loan
process.
Instructions
Utilize the worksheet on the following page to complete an FMEA.
Complete the possible Effect, Cause and Current Controls for each Error listed.
Rate each error for the listed criteria using the following scale (1=low, 3=medium,
9=high). Each criteria should be calculated as follows:
Frequency = a value reflecting the likelihood that the error will occur
Severity = a value reflecting the degree of adversity the errors effect
Detection = a value reflecting the ease or likelihood that the error will be visible or
noticed (a score of 9 is not good in this case)
Multiply all of the values and document the totals for each error (Risk Priority Number
or RPN).
Document any countermeasures to eliminate and/or monitor (recommended actions).
Prepare your findings.
Mitigating Risks (FMEA)
SI Project Template: Mitigating Risks_SI
14
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LP sends final
package to
customer
LP determines
loan
qualification
LP reviews
paper
application
Customer
completes
online
application
Item or Process
Step
Final package is
not sent
Loan is
incorrectly
denied
Application is
missing
information
System does
not accept
application
Recommended
Action
R
P
N
D
E
T
E
C
T
I
O
N
Current
Controls
O
C
C
U
R
R
E
N
C
E
Potential
Cause(s)
S
E
V
E
R
I
T
Y
Potential
Effect(s) of
Failure
Potential Failure
Mode
Mitigating Risks (FMEA) Worksheet
15
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Please Do Not Proceed Forward
Mitigating Risks (FMEA)
16
For additional information
about this concept, see
Lesson 22 Risk Planning
and Testing, in the Plan for
Risks section.
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LP sends final
package to
customer
LP determines loan
qualification
LP reviews paper
application
Customer submits
application online
Item or Process
Step
Add procedure for
mailing, internal
audit
273Manual Check3Loan package is
sitting in outgoing
mail
3Customer does not
receive loan
package
Final package is
not sent
Internal audit,
document
procedures
819Minimal1Inaccurate
qualification was
completed
9Customer is denied
loan
Loan is incorrectly
denied
None (low RPN)91Manual Check1Customer failed to
provide all
information
9Application is sent
back to customer,
delay in processing
Application is
missing information
Auto notification of
system down
Manual submission
of application
2439Minimal3System is down9Customer unable to
submit online
application
System does not
accept application
Recommended
Action
R
P
N
D
E
T
E
C
T
I
O
N
Current ControlsO
C
C
U
R
R
E
N
C
E
Potential
Cause(s)
S
E
V
E
R
I
T
Y
Potential Effect(s)
of Failure
Potential Failure
Mode
SI Mitigating Risks (FMEA)
17
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Pilot Plan
Lean Six Sigma – Project Simulation
18
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Objective
Complete a Pilot Plan for the SI Consumer Home Loan process.
Instructions
Utilize the worksheet on the following page to complete the Pilot Plan.
The following parameters have been determined by the team:
Both the new SI Home Loan Process and SI Loan System will be piloted
The pilot will be conducted in the Chicago site
The pilot will take place in the first 2 weeks of July
5 LP’s will be trained on the new process and system
Northwest Regional customers will have their loans processed with the
new process and system
Prepare your findings.
Pilot Plan
SI Project Template: Pilot Plan_SI
19
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4. What materials are required to conduct the
training?
3. Who will deliver the training?
2. Who will be trained?
1. When and where will the training take place?
Training Plan
4. How is Pilot failure defined?
3. How is Pilot success defined?
2. Who and how will the data be collected?
1. What will be measured (CTQs)?
Data Collection Plan
4. Who will be involved in the pilot?
3. Where will the pilot take place (business,
location)?
2. When will the pilot occur (dates from start to
stop)?
1. What processes will be piloted?
Scope of Pilot
Description
(be as detailed as possible)
Task/Deliverable
Pilot Plan
20
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Pilot Plan
21
For additional information
about this concept, see
Lesson 22 Risk Planning
and Testing, in the Test
Solutions section.
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Task/Deliverable Description
(be as detailed as possible)
Scope of Pilot
1. What processes will be piloted? The new SI Consumer Home Loan process and Loan System
2. When will the pilot occur (dates from start to stop)? July 1 – July 15
3. Where will the pilot take place (business, location)? Chicago site
4. Who will be involved in the pilot? Northwest Regional customers, 5 LP’s, LP Manager, Northwest Regional RA
Data Collection Plan
1. What will be measured (CTQs)? 15 day loan processing cycle time
100% accuracy on final determination packages
2 day loan reviewing time
2. Who and how will the data be collected? Project team will collect data using SI Loan System for cycle time CTQ’s and
tick sheets for accuracy CTQ
3. How is Pilot success defined? Meet or exceed CTQ’s
4. How is Pilot failure defined? Do not meet 2 or more CTQ’s
Training Plan
1. When and where will the training take place? June 21 – 23 in the Chicago Training Room
2. Who will be trained? 5 LP’s, LP Manager, Northwest Regional RA
3. Who will deliver the training? Project Team on SI Consumer Home Loan process, IT Consultants on Loan
System
4. What materials are required to conduct the training? To-Be Process Map, Standard Operating Procedures, Roles and
Responsibilities, PC’s installed with Loan System, LCD projector
SI Pilot Plan
22
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Implementation Planning
Lean Six Sigma – Project Simulation
23
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Objective
Develop an Implementation Plan for the SI Consumer Home Loan process.
Instructions
Using the worksheet on the following page, develop an implementation plan
for the new process.
Who will be responsible for leadership of the implementation?
Document any barriers you feel the team will have to overcome in order
for implementation to be successful and actions required to mitigate
them.
Develop the training plan:
– Who will need to be trained in the new process?
– What will they be trained on?
– What materials will be required to conduct the training? (perhaps
the same materials in the pilot)
– How long will the training occur and who will conduct it?
Prepare your findings.
Implementation Planning
SI Project Template: Implementation Planning_SI
24
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Leadership
Implementation Owner(s)
Training Owner(s)
Process Owner(s)
Barriers to Success
Barriers Actions Necessary to Overcome Barriers Owner
Training Plan
Group To Be
Trained
Description of Training Materials Required Length of
Training
Trainer(s)
Implementation Planning
25
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Implementation Planning
26
For additional information
about this concept, see
Lesson 23 Implement
Solution, in the
Implementation Planning -
Technical section.
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Barbara KissingerProcess Owner(s)
Steve McCaffrey, Erin AndersonTraining Owner(s)
Steve McCaffrey, Erin AndersonImplementation Owner(s)
Leadership
SI Implementation Plan
Erin A.Approval from Processing VP, begin scheduling earlyPulling associates from floor for training
Steve M.Approval from IT VP and assignment of resourcesIT resources needed to build new system
Erin A.Gain leadership support, Process Owners to work with
associates
Resistance to combining LO and LP roles and
eliminating MSA responsibility from process
OwnerActions Necessary to Overcome BarriersBarriers
Barriers to Success
Erin A.½ DayBinderProcess review, roles and responsibilitiesAgents
Erin A.½ DayBinderProcess review, roles and responsibilitiesSales
Steve M.,
Erin A.
3 DaysBinder (new process,
SOP’s, R&R’s), PC’s
Process review, Internet System review, roles and
responsibilities
Processing
Trainer(s)Length of
Training
Materials RequiredDescription of TrainingGroup To
Be Trained
Training Plan
27
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Storyboarding
Lean Six Sigma – Project Simulation
28
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Objective
Develop a “1 page” Storyboard for the SI Consumer Home Loan project.
Instructions
Using the worksheet on the following page, develop a “1 page” storyboard for
communication to the organization through the Improve phase.
Document key deliverables from each phase of the project under the
designated sections
Be creative…think about the story you are trying to tell and the key
deliverables you want the organization to see that will help sell the
project outcomes
Use graphs, statements and visual aides
Prepare your findings.
Storyboarding
SI Project Template: Storyboarding_SI
29
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Background DEFINE
MEASURE ANALYZE IMPROVE
Storyboarding
30
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Storyboarding
31
For additional information
about this concept, see
Lesson 23 Implement
Solution, in the
Implementation Planning -
Cultural section.
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Background DEFINE
MEASURE ANALYZE IMPROVE
During the past 2 years SI has fallen
from the 3rd largest financial services
provider to 6th in the world. The
primary reason for this decline is
poor customer service which is
driving customers to our competition.
Through analyzing our processes we
learned that our Global Consumer
Home Loan division was performing
well below customer expectations,
therefore the “Home Loan” Lean Six
Sigma project was initiated.
Team Members Project Role
John Davis Sponsor
Susan Terrell Master Black Belt
Steve McCaffrey Black / Green Belt
Ellen Mobley Team Member
Rod Elway Team Member
Erin Anderson Team Member
Owen Atwater Team Member
Project Goals (by September 1st):
1.Reduce the Consumer Home Loan process cycle
time by 45%
2.Improve process accuracy by 50%
CTQ’s:
15 day loan processing cycle time
100% final determination accuracy
100% documented roles and responsibilities
2 day loan reviewing time
0
5
10
15
20
25
30
35
40
45
20
.0
24
.3
28
.7
33
.0
37
.3
41
.7
46
.0
50
.3
54
.7
59
.0
63
.3
67
.7
72
.0
Chicago Loan Processing Cycle Time
Accuracy Baseline Sigma for
Chicago = 3.2
Root Causes:
1.Too Much Inter-
Department
Processing Time
2.Staffing Model Not
Aligned with Peak
Volume
3. Incoming
Applications are
Inaccurate
4.No Process
Controls
5.Non Value-Added
Process Steps
Median: 30.00
0.90
5.90
10.90
15.90
20.90
25.90
30.90
35.90
40.90
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 9910
1
10
3
10
5
10
7
10
9
11
1
11
3
11
5
11
7
11
9
12
1
12
3
12
5
Ru
n
Ch
ar
t -
C
hi
ca
go
L
oa
n
Pr
oc
es
si
ng
C
yc
le
T
im
e Project
Benefits =
~$6.1MM
Pilot Results
Baseline Performance
SI Storyboard
32
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Chart4
6.5140688934 12
7.4594354069 19
8.48613712 41
9.5910158579 28
10.7688579977 3
12.012272298 0
13.3116277219 0
14.6550611711 0
16.0285628548 1
17.4161441501 0
18.800089363 0
20.1612889329 0
21.4796475287 1
22.7345563899
23.9054154296
24.9721872717
25.9159628042
26.7195161675
27.3678265349
27.8485446582
28.1523839526
28.2734188254
28.2092768612
27.9612161566
27.5340842817
26.9361607397
26.1788900765
25.2765176574
24.2456443015
23.1047192105
21.8734927916
20.5724519549
19.2222602603
17.8432239533
16.4548026025
15.0751799165
13.7209066056
12.4066231116
11.1448659099
9.9459571253
8.8179736125
7.7667885908
6.7961765134
5.9079701595
5.1022579739
4.3776094181
3.7313164606
3.1596402307
2.6580531625
2.2214685423
1.8444511161
1.5214041911
1.2467303849
1.0149647441
0.820880325
0.6595674476
0.526488703
0.4175123991
0.3289274931
0.2574432146
0.2001765506
0.154630596
0.1186665005
0.0904714014
0.0685243583
0.0515619239
0.0385446163
0.0286252189
0.0211195366
0.0154799812
0.0112721549
0.0081544364
0.0058604562
0.0041842669
0.0029679584
0.0020914463
0.0014641518
0.0010183005
0.0007035845
0.0004829555
0.000329343
0.0002231209
0.0001501697
0.0001004096
0.0000666988
0.0000440161
0.0000288573
0.0000187954
0.0000121617
0.0000078179
0.0000049927
0.0000031676
0.0000019966
0.0000012502
0.0000007777
0.0000004806
0.0000002951
0.00000018
0.0000001091
0.0000000657
0.0000000393
Chicago Loan Processing Cycle Time
Sheet134
Sheet133
Sheet132
Sheet131
Sheet130
Sheet129
Sheet128
Sheet127
1 2
Sheet126
Sheet125
Sheet124
Chicago Loan Processing Cycle Time
Chicago Cycle Time
Chicago Loan Processing Cycle Time
30
30
27
31
31
21
32
28
31
30
28
35
26
55
32
24
34
28
40
31
32
36
31
34
29
34
28
30
30
35
22
23
32
33
32
28
41
32
34
20
31
31
29
30
35
30
28
31
29
31
37
36
21
27
28
33
32
32
24
29
72
35
28
21
32
32
29
37
32
29
33
20
31
34
23
33
36
31
30
26
25
37
35
30
33
23
30
27
35
35
36
29
25
35
38
26
24
25
36
31
33
28
34
25
32
Sheet2
Sheet3
Hist Descript
SigmaXLChartSheet Chicago Loan Processing Cycle Time
Count = 105
Mean = 31
Stdev = 6.4196
Range = 52.0
Minimum = 20
25th Percentile (Q1) = 28
50th Percentile (Median) = 31
75th Percentile (Q3) = 34.00
Maximum = 72
95% CI Mean = 29.76 to 32.2
95% CI Sigma = 5.65 to 7.43
1
6.5140688934
7.4594354069
8.48613712
9.5910158579
10.7688579977
12.012272298
13.3116277219
14.6550611711
16.0285628548
17.4161441501
18.800089363
20.1612889329
21.4796475287
22.7345563899
23.9054154296
24.9721872717
25.9159628042
26.7195161675
27.3678265349
27.8485446582
28.1523839526
28.2734188254
28.2092768612
27.9612161566
27.5340842817
26.9361607397
26.1788900765
25.2765176574
24.2456443015
23.1047192105
21.8734927916
20.5724519549
19.2222602603
17.8432239533
16.4548026025
15.0751799165
13.7209066056
12.4066231116
11.1448659099
9.9459571253
8.8179736125
7.7667885908
6.7961765134
5.9079701595
5.1022579739
4.3776094181
3.7313164606
3.1596402307
2.6580531625
2.2214685423
1.8444511161
1.5214041911
1.2467303849
1.0149647441
0.820880325
0.6595674476
0.526488703
0.4175123991
0.3289274931
0.2574432146
0.2001765506
0.154630596
0.1186665005
0.0904714014
0.0685243583
0.0515619239
0.0385446163
0.0286252189
0.0211195366
0.0154799812
0.0112721549
0.0081544364
0.0058604562
0.0041842669
0.0029679584
0.0020914463
0.0014641518
0.0010183005
0.0007035845
0.0004829555
0.000329343
0.0002231209
0.0001501697
0.0001004096
0.0000666988
0.0000440161
0.0000288573
0.0000187954
0.0000121617
0.0000078179
0.0000049927
0.0000031676
0.0000019966
0.0000012502
0.0000007777
0.0000004806
0.0000002951
0.00000018
0.0000001091
0.0000000657
0.0000000393
20.0
24.3
28.7
33.0
37.3
41.7
46.0
50.3
54.7
59.0
63.3
67.7
72.0
12
19
41
28
3
0
0
0
1
0
0
0
1
Hist Descript
Chicago Loan Processing Cycle Time
Run Chart
SigmaXLChartSheet $A$1 1 Chicago Loan Processing Cycle Time RunChart 30.44 Chicago Loan Processing Cycle Time
Chicago Cycle Time 1 30 30.0 105 30
2 30 30.0 30
106 3 27 27.0 30
4 31 31.0 0 30
5 31 31.0 105 30
6 21 21.0 -105 30
Mean 7 32 32.0 30
8 28 28.0 30
9 31 31.0 30
10 30 30.0 30
11 28 28.0 30
12 35 35.0 30
13 26 26.0 30
14 34 34.0 30
15 32 32.0 30
16 24 24.0 30
17 34 34.0 30
18 28 28.0 30
19 40 40.0 30
20 31 31.0 30
21 32 32.0 30
22 36 36.0 30
23 31 31.0 30
24 34 34.0 30
25 29 29.0 30
26 34 34.0 30
27 28 28.0 30
28 30 30.0 30
29 30 30.0 30
30 35 35.0 30
31 22 22.0 30
32 23 23.0 30
33 32 32.0 30
34 33 33.0 30
35 32 32.0 30
36 28 28.0 30
37 41 41.0 30
38 32 32.0 30
39 34 34.0 30
40 20 20.0 30
41 31 31.0 30
42 31 31.0 30
43 29 29.0 30
44 30 30.0 30
45 35 35.0 30
46 30 30.0 30
47 28 28.0 30
48 31 31.0 30
49 29 29.0 30
50 31 31.0 30
51 37 37.0 30
52 36 36.0 30
53 21 21.0 30
54 27 27.0 30
55 28 28.0 30
56 33 33.0 30
57 32 32.0 30
58 32 32.0 30
59 24 24.0 30
60 29 29.0 30
61 34 34.0 30
62 35 35.0 30
63 28 28.0 30
64 21 21.0 30
65 32 32.0 30
66 32 32.0 30
67 29 29.0 30
68 37 37.0 30
69 32 32.0 30
70 29 29.0 30
71 33 33.0 30
72 20 20.0 30
73 31 31.0 30
74 34 34.0 30
75 23 23.0 30
76 33 33.0 30
77 36 36.0 30
78 31 31.0 30
79 30 30.0 30
80 26 26.0 30
81 25 25.0 30
82 37 37.0 30
83 35 35.0 30
84 30 30.0 30
85 33 33.0 30
86 23 23.0 30
87 30 30.0 30
88 27 27.0 30
89 35 35.0 30
90 35 35.0 30
91 36 36.0 30
92 29 29.0 30
93 25 25.0 30
94 35 35.0 30
95 38 38.0 30
96 26 26.0 30
97 24 24.0 30
98 25 25.0 30
99 36 36.0 30
100 31 31.0 30
101 33 33.0 30
102 28 28.0 30
103 34 34.0 30
104 25 25.0 30
105 32 32.0 30
Run Chart
Run Chart - Chicago Loan Processing Cycle Time
Mean: 30.44
Indiv & MR Charts
SigmaXL Control Charts tests $A$1 IMR 6.3461538462 31 imean Chicago Loan Processing Cycle Time
Chicago Cycle Time 1 30 30 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154 indvmean
105 2 30 0 30 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
106 3 27 3 27 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
4 31 4 31 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
5 31 0 31 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
6 21 10 21 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
7 32 11 32 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
8 28 4 28 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
9 31 3 31 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
10 30 1 30 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
11 28 2 28 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
12 35 7 35 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
13 26 9 26 14.1219312602 31 47.8780687398 29 0 6.3461538462 20.7328846154
14 55 29 55 14.1219312602 31 47.8780687398 23 0 6.3461538462 20.7328846154
15 32 23 32 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
16 24 8 24 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
17 34 10 34 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
18 28 6 28 14.1219312602 31 47.8780687398 12 0 6.3461538462 20.7328846154
19 40 12 40 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
20 31 9 31 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
21 32 1 32 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
22 36 4 36 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
23 31 5 31 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
24 34 3 34 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
25 29 5 29 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
26 34 5 34 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
27 28 6 28 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
28 30 2 30 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
29 30 0 30 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
30 35 5 35 14.1219312602 31 47.8780687398 13 0 6.3461538462 20.7328846154
31 22 13 22 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
32 23 1 23 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
33 32 9 32 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
34 33 1 33 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
35 32 1 32 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
36 28 4 28 14.1219312602 31 47.8780687398 13 0 6.3461538462 20.7328846154
37 41 13 41 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
38 32 9 32 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
39 34 2 34 14.1219312602 31 47.8780687398 14 0 6.3461538462 20.7328846154
40 20 14 20 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
41 31 11 31 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
42 31 0 31 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
43 29 2 29 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
44 30 1 30 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
45 35 5 35 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
46 30 5 30 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
47 28 2 28 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
48 31 3 31 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
49 29 2 29 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
50 31 2 31 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
51 37 6 37 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
52 36 1 36 14.1219312602 31 47.8780687398 15 0 6.3461538462 20.7328846154
53 21 15 21 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
54 27 6 27 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
55 28 1 28 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
56 33 5 33 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
57 32 1 32 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
58 32 0 32 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
59 24 8 24 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
60 29 5 29 14.1219312602 31 47.8780687398 43 0 6.3461538462 20.7328846154
61 72 43 72 14.1219312602 31 47.8780687398 37 0 6.3461538462 20.7328846154
62 35 37 35 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
63 28 7 28 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
64 21 7 21 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
65 32 11 32 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
66 32 0 32 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
67 29 3 29 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
68 37 8 37 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
69 32 5 32 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
70 29 3 29 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
71 33 4 33 14.1219312602 31 47.8780687398 13 0 6.3461538462 20.7328846154
72 20 13 20 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
73 31 11 31 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
74 34 3 34 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
75 23 11 23 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
76 33 10 33 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
77 36 3 36 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
78 31 5 31 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
79 30 1 30 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
80 26 4 26 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
81 25 1 25 14.1219312602 31 47.8780687398 12 0 6.3461538462 20.7328846154
82 37 12 37 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
83 35 2 35 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
84 30 5 30 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
85 33 3 33 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
86 23 10 23 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
87 30 7 30 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
88 27 3 27 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
89 35 8 35 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
90 35 0 35 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
91 36 1 36 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
92 29 7 29 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
93 25 4 25 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
94 35 10 35 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
95 38 3 38 14.1219312602 31 47.8780687398 12 0 6.3461538462 20.7328846154
96 26 12 26 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
97 24 2 24 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
98 25 1 25 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
99 36 11 36 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
100 31 5 31 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
101 33 2 33 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
102 28 5 28 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
103 34 6 34 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
104 25 9 25 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
105 32 7 32 14.1219312602 31.00 47.8780687398
Indiv & MR Charts
Individuals - Chicago Loan Processing Cycle Time
1
1
Mean CL: 31.00
Indiv - Tests
MR - Chicago Loan Processing Cycle Time
Tests for Special Causes - Indiv - Chicago Loan Processing Cycle Time
Number of Data Points Failing Tests = 2
Observation No. Test 1: 1 point
more than 3 sigma from CL Test 2: 9 points
in a row on same side of CL Test 3: 6 points
in a row all increasing or all decreasing Test 4: 14 points
in a row alternating up and down Test 5: 2 out of 3 points
more than 2 sigma from CL (same side) Test 6: 4 out of 5 points
more than 1 sigma from CL (same side) Test 7: 15 points
in a row within 1 sigma from CL (either side) Test 8: 8 points
in a row more than 1 sigma from CL (either side)
14 x
61 x
Chart5
30 30
30 30
27 30
31 30
31 30
28 30
32 30
28 30
31 30
30 30
28 30
35 30
26 30
34 30
32 30
24 30
34 30
28 30
31 30
31 30
32 30
36 30
31 30
34 30
29 30
34 30
28 30
30 30
30 30
35 30
25 30
27 30
32 30
33 30
32 30
28 30
32 30
32 30
34 30
37 30
31 30
31 30
29 30
30 30
35 30
30 30
28 30
31 30
29 30
31 30
37 30
36 30
31 30
27 30
28 30
33 30
32 30
32 30
24 30
29 30
34 30
35 30
28 30
32 30
32 30
32 30
29 30
37 30
32 30
29 30
33 30
20 30
31 30
34 30
28 30
33 30
36 30
31 30
30 30
26 30
25 30
37 30
35 30
30 30
33 30
29 30
30 30
27 30
35 30
35 30
36 30
29 30
25 30
35 30
38 30
26 30
24 30
25 30
36 30
31 30
33 30
28 30
34 30
25 30
32 30
3 30
6 30
5 30
7 30
7 30
6 30
6 30
4 30
4 30
7 30
1 30
12 30
7 30
4 30
5 30
6 30
9 30
8 30
6 30
7 30
Run Chart - Chicago Loan Processing Cycle Time
Median: 30.00
Sheet134
Sheet133
Sheet132
Sheet131
Sheet130
Sheet129
Sheet128
Sheet127
1 2
Sheet126
Sheet125
Sheet124
Chicago Loan Processing Cycle Time
Dataxl1
Sum of Number of Errors 44 Application Fields
0 Total
Loan Amount 26 0.5909090909 26
Name 12 0.8636363636 38
Address 3 0.9318181818 41
Loan Duration 2 0.9772727273 43
City 1 1 44
Loan # 0 1 44
State 0 1 44
1
Sheet24
Sheet23
Sheet22
Sheet21
Sheet20
Sheet19
Sheet18
Sheet17
1 2
Sheet16
Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0
Dataxl1 (2)
Sum of Number of Errors 44 82 7 Loan Amount 26 0.5909090909
Application Fields Total 0 Name 12 0.8636363636
Loan Amount 26 59% 26 Address 3 0.9318181818
Name 12 86% 38 100 Loan Duration 2 0.9772727273
Address 3 93% 41 City 1 1
Loan Duration 2 98% 43 Loan # 0 1
City 1 100% 44 State 0 1
Loan # 0 100% 44
State 0 100% 44
Dataxl1 (3)
Sum of Number of Errors 44 Application Fields
0 Total
Loan Amount 26 0.5909090909 26
Name 12 0.8636363636 38
Address 3 0.9318181818 41
Loan Duration 2 0.9772727273 43
City 1 1 44
Loan # 0 1 44
State 0 1 44
1
# of Package Errors
Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0
44
Sheet13
Sheet12
Sheet11
Sheet10
Sheet8
Sheet7
4286
0
4286
0
2
Sheet5
Chicago Loan Processing Cycle Time RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
30 1 15 11 3
30 2 15 9 4
27 3 14 7 3
31 4 16 8 3
31 3 16 10 4
21 4 11 3 3
32 5 16 8 3
28 6 14 5 3
31 3 16 8 4
30 4 15 8 3
28 2 14 9 3
35 3 18 13 2
26 4 13 6 3
55 5 28 15 7
32 3 16 11 2
24 2 12 6 4
34 3 17 11 3
28 4 14 7 3
40 2 20 16 2
31 3 16 9 3
32 4 16 9 3
36 2 18 11 2
31 3 16 9 3
34 3 17 10 4
29 2 15 9 5
34 2 17 10 4
28 1 14 8 3
30 1 15 9 3
30 2 15 9 2
35 3 18 11 3
22 2 11 7 1
23 3 12 7 3
32 4 16 10 2
33 5 17 10 3
32 4 16 10 3
28 3 14 8 3
41 4 21 12 4
32 3 16 10 3
34 2 17 10 3
20 3 10 6 2
31 4 16 9 3
31 3 16 9 3
29 2 15 9 3
30 2 15 9 3
35 2 18 11 4
30 3 15 9 3
28 3 14 8 3
31 2 16 9 3
29 1 15 9 3
31 2 16 9 3
37 3 19 11 4
36 4 18 11 4
21 3 11 6 2
27 2 14 8 3
28 1 14 8 3
33 2 17 10 3
32 3 16 10 3
32 4 16 10 3
24 4 12 7 3
29 4 15 9 4
72 3 36 22 6
35 4 18 11 5
28 4 14 8 3
21 5 11 6 4
32 3 16 10 3
32 3 16 10 4
29 2 15 9 2
37 1 19 11 4
32 2 16 10 3
29 3 15 9 3
33 2 17 10 3
20 3 10 6 2
31 3 16 9 3
34 4 17 10 3
23 3 12 7 2
33 2 17 10 2
36 3 18 11 3
31 4 16 9 1
30 3 15 9 3
26 2 13 8 4
25 2 13 8 3
37 2 19 11 4
35 2 18 11 4
30 3 15 9 4
33 3 17 10 3
23 4 12 7 2
30 3 15 9 3
27 4 14 8 3
35 5 18 11 4
35 4 18 11 4
36 3 18 11 5
29 2 15 9 3
25 1 13 8 2
35 2 18 11 4
38 3 19 11 4
26 4 13 8 3
24 5 12 7 3
25 4 13 8 4
36 3 18 11 4
31 4 16 9 3
33 5 17 10 3
28 4 14 8 3
34 3 17 10 3
25 4 13 8 3
32 5 16 10 4
Sheet4
Sheet3
Chicago Loan Processing Cycle Time Chicago Loan Processing Cycle Time
RA Cycle Time RA Cycle Time
MSA Cycle Time MSA Cycle Time
LP Cycle Time LP Cycle Time
LO Cycle Time LO Cycle Time
Sheet45
Sheet44
Sheet43
Sheet42
Sheet40
Sheet39
4286
0
4286
0
2
Sheet37
Chicago Loan Processing Cycle Time RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
30 1 15 11 3
30 2 15 9 4
27 3 14 7 3
31 4 16 8 3
31 3 16 8 4
21 4 11 3 3
32 5 16 8 3
28 6 14 5 3
31 3 16 8 4
30 4 15 8 3
28 2 14 9 3
35 3 18 12 2
26 4 13 6 3
55 5 28 15 7
32 3 16 11 2
24 2 12 6 4
34 3 17 11 3
28 4 14 7 3
40 2 20 16 2
31 3 16 9 3
32 4 16 9 3
36 2 18 14 2
31 3 16 9 3
34 3 17 10 4
29 2 15 7 5
34 2 17 11 4
28 1 14 10 3
30 1 15 11 3
30 2 15 11 2
35 3 18 11 3
22 2 11 8 1
23 3 12 5 3
32 4 16 10 2
33 5 17 8 3
32 4 16 9 3
28 3 14 8 3
41 4 21 12 4
32 3 16 10 3
34 2 17 12 3
20 3 10 5 2
31 4 16 8 3
31 3 16 9 3
29 2 15 10 3
30 2 15 10 3
35 2 18 12 4
30 3 15 9 3
28 3 14 8 3
31 2 16 10 3
29 1 15 11 3
31 2 16 10 3
37 3 19 12 4
36 4 18 11 4
21 3 11 5 2
27 2 14 9 3
28 1 14 10 3
33 2 17 11 3
32 3 16 10 3
32 4 16 9 3
24 4 12 5 3
29 4 15 6 4
72 3 36 27 6
35 4 18 8 5
28 4 14 7 3
21 5 11 1 4
32 3 16 10 3
32 3 16 9 4
29 2 15 10 2
37 1 19 13 4
32 2 16 11 3
29 3 15 9 3
33 2 17 11 3
20 3 10 5 2
31 3 16 9 3
34 4 17 10 3
23 3 12 7 2
33 2 17 12 2
36 3 18 12 3
31 4 16 10 1
30 3 15 9 3
26 2 13 7 4
25 2 13 8 3
37 2 19 12 4
35 2 18 11 4
30 3 15 8 4
33 3 17 10 3
23 4 12 5 2
30 3 15 9 3
27 4 14 6 3
35 5 18 8 4
35 4 18 9 4
36 3 18 10 5
29 2 15 9 3
25 1 13 9 2
35 2 18 11 4
38 3 19 12 4
26 4 13 6 3
24 5 12 4 3
25 4 13 4 4
36 3 18 11 4
31 4 16 8 3
33 5 17 8 3
28 4 14 7 3
34 3 17 11 3
25 4 13 5 3
32 5 16 7 4
Sheet36
Sheet35
Chicago Loan Processing Cycle Time Chicago Loan Processing Cycle Time
RA Cycle Time RA Cycle Time
MSA Cycle Time MSA Cycle Time
LP Cycle Time LP Cycle Time
LO Cycle Time LO Cycle Time
Sheet56
Sheet55
Sheet54
Sheet53
Sheet51
Sheet50
4286
0
4286
0
2
Sheet48
Chicago Loan Processing Cycle Time RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
30 1 15 11 3
30 2 15 9 4
27 3 14 7 3
31 4 16 8 3
31 3 16 8 4
21 4 11 3 3
32 5 16 8 3
28 6 14 5 3
31 3 16 8 4
30 4 15 8 3
28 2 14 9 3
35 3 18 12 2
26 4 13 6 3
55 5 28 15 7
32 3 16 11 2
24 2 12 6 4
34 3 17 11 3
28 4 14 7 3
40 2 20 16 2
31 3 16 9 3
32 4 16 9 3
36 2 18 14 2
31 3 16 9 3
34 3 17 10 4
29 2 15 7 5
34 2 17 11 4
28 1 14 10 3
30 1 15 11 3
30 2 15 11 2
35 3 18 11 3
22 2 11 8 1
23 3 12 5 3
32 4 16 10 2
33 5 17 8 3
32 4 16 9 3
28 3 14 8 3
41 4 21 12 4
32 3 16 10 3
34 2 17 12 3
20 3 10 5 2
31 4 16 8 3
31 3 16 9 3
29 2 15 10 3
30 2 15 10 3
35 2 18 12 4
30 3 15 9 3
28 3 14 8 3
31 2 16 10 3
29 1 15 11 3
31 2 16 10 3
37 3 19 12 4
36 4 18 11 4
21 3 11 5 2
27 2 14 9 3
28 1 14 10 3
33 2 17 11 3
32 3 16 10 3
32 4 16 9 3
24 4 12 5 3
29 4 15 6 4
72 3 36 27 6
35 4 18 8 5
28 4 14 7 3
21 5 11 1 4
32 3 16 10 3
32 3 16 9 4
29 2 15 10 2
37 1 19 13 4
32 2 16 11 3
29 3 15 9 3
33 2 17 11 3
20 3 10 5 2
31 3 16 9 3
34 4 17 10 3
23 3 12 7 2
33 2 17 12 2
36 3 18 12 3
31 4 16 10 1
30 3 15 9 3
26 2 13 7 4
25 2 13 8 3
37 2 19 12 4
35 2 18 11 4
30 3 15 8 4
33 3 17 10 3
23 4 12 5 2
30 3 15 9 3
27 4 14 6 3
35 5 18 8 4
35 4 18 9 4
36 3 18 10 5
29 2 15 9 3
25 1 13 9 2
35 2 18 11 4
38 3 19 12 4
26 4 13 6 3
24 5 12 4 3
25 4 13 4 4
36 3 18 11 4
31 4 16 8 3
33 5 17 8 3
28 4 14 7 3
34 3 17 11 3
25 4 13 5 3
32 5 16 7 4
Sheet47
Sheet46
Chicago Loan Processing Cycle Time Chicago Loan Processing Cycle Time
RA Cycle Time RA Cycle Time
MSA Cycle Time MSA Cycle Time
LP Cycle Time LP Cycle Time
LO Cycle Time LO Cycle Time
Chicago Cycle Time with Pilot
Loan # Chicago Loan Processing Cycle Time
1 30
2 30
3 27
4 31
5 31
6 28
7 32
8 28
9 31
10 30
11 28
12 35
13 26
14 34
15 32
16 24
17 34
18 28
19 31
20 31
21 32
22 36
23 31
24 34
25 29
26 34
27 28
28 30
29 30
30 35
31 25
32 27
33 32
34 33
35 32
36 28
37 32
38 32
39 34
40 37
41 31
42 31
43 29
44 30
45 35
46 30
47 28
48 31
49 29
50 31
51 37
52 36
53 31
54 27
55 28
56 33
57 32
58 32
59 24
60 29
61 34
62 35
63 28
64 32
65 32
66 32
67 29
68 37
69 32
70 29
71 33
72 20
73 31
74 34
75 28
76 33
77 36
78 31
79 30
80 26
81 25
82 37
83 35
84 30
85 33
86 29
87 30
88 27
89 35
90 35
91 36
92 29
93 25
94 35
95 38
96 26
97 24
98 25
99 36
100 31
101 33
102 28
103 34
104 25
105 32
1 3
2 6
3 5
4 7
5 7
6 6
7 6
8 4
9 4
10 7
11 1
12 12
13 7
14 4
15 5
16 6
17 9
18 8
19 6
20 7
Sheet61
Normal Random Data (1)
Chicago Pilot Loan Processing Time
3
6
5
7
7
6
6
4
4
7
1
12
7
4
5
6
9
8
6
7
Run Chart (2)
SigmaXLChartSheet $B$1 1 Chicago Loan Processing Cycle Time RunChart 30.00 Chicago Loan Processing Cycle Time
Chicago Cycle Time Per Dept 1 30 30.00 125 30
Nonparametric Runs Test: Chicago Loan Processing Cycle Time 2 30 30.00 30
126 3 27 27.00 30
Number of Runs about Median: 57 4 31 31.00 0 30
Expected Number of Runs about Median: 63 5 31 31.00 125 30
Number of Points above Median: 60 6 28 28.00 -125 30
Number of Points equal to or below Median: 65 Median 7 32 32.00 30
P-Value for Clustering: 0.1248 8 28 28.00 30
P-Value for Mixtures: 0.8752 9 31 31.00 30
P-Value for Lack of Randomness (2-Sided): 0.2496 10 30 30.00 30
11 28 28.00 30
Number of Runs Up or Down: 82 12 35 35.00 30
Expected Number of Runs Up or Down: 83 13 26 26.00 30
P-Value for Trends: 0.4154 14 34 34.00 30
P-Value for Oscillation: 0.5846 15 32 32.00 30
16 24 24.00 30
17 34 34.00 30
18 28 28.00 30
19 31 31.00 30
20 31 31.00 30
21 32 32.00 30
22 36 36.00 30
23 31 31.00 30
24 34 34.00 30
25 29 29.00 30
26 34 34.00 30
27 28 28.00 30
28 30 30.00 30
29 30 30.00 30
30 35 35.00 30
31 25 25.00 30
32 27 27.00 30
33 32 32.00 30
34 33 33.00 30
35 32 32.00 30
36 28 28.00 30
37 32 32.00 30
38 32 32.00 30
39 34 34.00 30
40 37 37.00 30
41 31 31.00 30
42 31 31.00 30
43 29 29.00 30
44 30 30.00 30
45 35 35.00 30
46 30 30.00 30
47 28 28.00 30
48 31 31.00 30
49 29 29.00 30
50 31 31.00 30
51 37 37.00 30
52 36 36.00 30
53 31 31.00 30
54 27 27.00 30
55 28 28.00 30
56 33 33.00 30
57 32 32.00 30
58 32 32.00 30
59 24 24.00 30
60 29 29.00 30
61 34 34.00 30
62 35 35.00 30
63 28 28.00 30
64 32 32.00 30
65 32 32.00 30
66 32 32.00 30
67 29 29.00 30
68 37 37.00 30
69 32 32.00 30
70 29 29.00 30
71 33 33.00 30
72 20 20.00 30
73 31 31.00 30
74 34 34.00 30
75 28 28.00 30
76 33 33.00 30
77 36 36.00 30
78 31 31.00 30
79 30 30.00 30
80 26 26.00 30
81 25 25.00 30
82 37 37.00 30
83 35 35.00 30
84 30 30.00 30
85 33 33.00 30
86 29 29.00 30
87 30 30.00 30
88 27 27.00 30
89 35 35.00 30
90 35 35.00 30
91 36 36.00 30
92 29 29.00 30
93 25 25.00 30
94 35 35.00 30
95 38 38.00 30
96 26 26.00 30
97 24 24.00 30
98 25 25.00 30
99 36 36.00 30
100 31 31.00 30
101 33 33.00 30
102 28 28.00 30
103 34 34.00 30
104 25 25.00 30
105 32 32.00 30
106 3 3.00 30
107 6 6.00 30
108 5 5.00 30
109 7 7.00 30
110 7 7.00 30
111 6 6.00 30
112 6 6.00 30
113 4 4.00 30
114 4 4.00 30
115 7 7.00 30
116 1 1.00 30
117 12 12.00 30
118 7 7.00 30
119 4 4.00 30
120 5 5.00 30
121 6 6.00 30
122 9 9.00 30
123 8 8.00 30
124 6 6.00 30
125 7 7.00 30
Run Chart (2)
Run Chart - Chicago Loan Processing Cycle Time
Median: 30.00
Hist Descript
SigmaXLChartSheet Chicago Pilot Loan Processing Time
Count = 20
Mean = 6
Stdev = 2.3170
Range = 11.0
Minimum = 1
25th Percentile (Q1) = 4.2500
50th Percentile (Median) = 6
75th Percentile (Q3) = 7.00
Maximum = 12
95% CI Mean = 4.92 to 7.1
95% CI Sigma = 1.76 to 3.38
An
1
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
1
0
1
3
2
5
5
1
1
0
0
1
0
Hist Descript
Chicago Pilot Loan Processing Time
Step 3 Corr
LO Cycle Time MSA Cycle Time LP Cycle Time SUMMARY OUTPUT MSA Cycle Time
5 15 9
2 15 9 Regression Statistics
3 14 8 Multiple R 1
1 16 9 R Square 1
5 16 9 Adjusted R Square 1
2 14 8 Standard Error 1
1 16 10 Observations 105
3 14 8
3 16 9 ANOVA
5 15 9 df SS MS F Significance F
4 14 8 Regression 2 307 154 606 0
3 18 11 Residual 102 26 0
3 13 8 Total 104 333
1 17 10
4 16 10 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
3 12 7 Intercept 2 0 4 0 1 2 1 2
4 17 10 LP Cycle Time 1 0 32 0 1 2 1 2
4 14 8 LO Cycle Time 0 0 2 0 0 0 0 0
4 16 9
3 16 9 SUMMARY OUTPUT LP Cycle Time
2 16 10
5 18 11 Regression Statistics
3 16 9 Multiple R 1
4 17 10 R Square 1
3 15 9 Adjusted R Square 1
5 17 10 Standard Error 0
3 14 8 Observations 105
5 15 9
4 15 9 ANOVA
3 18 11 df SS MS F Significance F
2 13 8 Regression 2 123 62 582 0
1 14 8 Residual 102 11 0
5 16 10 Total 104 134
1 17 10
2 16 10 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
3 14 8 Intercept -0 0 -1 0 -1 0 -1 0
2 16 10 MSA Cycle Time 1 0 32 0 1 1 1 1
4 16 10 LO Cycle Time -0 0 -1 0 -0 0 -0 0
5 17 10
4 19 11 SUMMARY OUTPUT LO Cycle Time
2 16 9
5 16 9 Regression Statistics
1 15 9 Multiple R 0
4 15 9 R Square 0
4 18 11 Adjusted R Square 0
3 15 9 Standard Error 1
5 14 8 Observations 105
4 16 9
4 15 9 ANOVA
1 16 9 df SS MS F Significance F
4 19 11 Regression 2 25 13 9 0
3 18 11 Residual 102 149 1
5 16 9 Total 104 175
4 14 8
5 14 8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
5 17 10 Intercept -1 1 -1 0 -3 1 -3 1
3 16 10 MSA Cycle Time 1 0 2 0 0 1 0 1
2 16 10 LP Cycle Time -1 0 -1 0 -1 0 -1 0
1 12 7
4 15 9
5 17 10
2 18 11
2 14 8
3 16 10
3 16 10
3 16 10
4 15 9
6 19 11
4 16 10
2 15 9
4 17 10
1 10 6
3 16 9
5 17 10
3 14 8
4 17 10
6 18 11
2 16 9
3 15 9
2 13 8
2 13 8
5 19 11
3 18 11
3 15 9
3 17 10
3 15 9
3 15 9
1 14 8
3 18 11
2 18 11
4 18 11
3 15 9
3 13 8
4 18 11
5 19 11
1 13 8
3 12 7
2 13 8
4 18 11
2 16 9
1 17 10
5 14 8
4 17 10
2 13 8
3 16 10
Step 3 Data
MSA Cycle Time LP Cycle Time LO Cycle Time
15 9 5
15 9 2
14 8 3
16 9 1
16 9 5
14 8 2
16 10 1
14 8 3
16 9 3
15 9 5
14 8 4
18 11 3
13 8 3
17 10 1
16 10 4
12 7 3
17 10 4
14 8 4
16 9 4
16 9 3
16 10 2
18 11 5
16 9 3
17 10 4
15 9 3
17 10 5
14 8 3
15 9 5
15 9 4
18 11 3
13 8 2
14 8 1
16 10 5
17 10 1
16 10 2
14 8 3
16 10 2
16 10 4
17 10 5
19 11 4
16 9 2
16 9 5
15 9 1
15 9 4
18 11 4
15 9 3
14 8 5
16 9 4
15 9 4
16 9 1
19 11 4
18 11 3
16 9 5
14 8 4
14 8 5
17 10 5
16 10 3
16 10 2
12 7 1
15 9 4
17 10 5
18 11 2
14 8 2
16 10 3
16 10 3
16 10 3
15 9 4
19 11 6
16 10 4
15 9 2
17 10 4
10 6 1
16 9 3
17 10 5
14 8 3
17 10 4
18 11 6
16 9 2
15 9 3
13 8 2
13 8 2
19 11 5
18 11 3
15 9 3
17 10 3
15 9 3
15 9 3
14 8 1
18 11 3
18 11 2
18 11 4
15 9 3
13 8 3
18 11 4
19 11 5
13 8 1
12 7 3
13 8 2
18 11 4
16 9 2
17 10 1
14 8 5
17 10 4
13 8 2
16 10 3
Step 2 Corr
Step 2 Data
LO Cycle Time LP Cycle Time
5 9
2 9
3 8
1 9
5 9
2 8
1 10
3 8
3 9
5 9
4 8
3 11
3 8
1 10
4 10
3 7
4 10
4 8
4 9
3 9
2 10
5 11
3 9
4 10
3 9
5 10
3 8
5 9
4 9
3 11
2 8
1 8
5 10
1 10
2 10
3 8
2 10
4 10
5 10
4 11
2 9
5 9
1 9
4 9
4 11
3 9
5 8
4 9
4 9
1 9
4 11
3 11
5 9
4 8
5 8
5 10
3 10
2 10
1 7
4 9
5 10
2 11
2 8
3 10
3 10
3 10
4 9
6 11
4 10
2 9
4 10
1 6
3 9
5 10
3 8
4 10
6 11
2 9
3 9
2 8
2 8
5 11
3 11
3 9
3 10
3 9
3 9
1 8
3 11
2 11
4 11
3 9
3 8
4 11
5 11
1 8
3 7
2 8
4 11
2 9
1 10
5 8
4 10
2 8
3 10
UserInfo
Number of Variables 3 Variable 1 MSA Cycle Time 1 3 4 0 90 95 A 0 0 Keep in ©
Variable 2 LP Cycle Time 2 95 B 0 Keep in
Variable 3 LO Cycle Time 3 C 0 Keep in
Variable 4 0 0 D
Variable 5 0 0 E
Variable 6 0 0 F
Variable 7 0 0 G
DO NOT MAKE ANY CHANGES TO THIS SHEET!!
MRData
RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
1 15 9 5
4 15 9
2 14 8
5 16 9
1 16 9
4 14 8 2
5 16 10 1
3 14 8 3
3 16 9 3
1 15 9 5
2 14 8 4
3 18 11 3
2 13 8 3
6 17 10 1
2 16 10 4
2 12 7 3
3 17 10 4
2 14 8 4
2 16 9 4
3 16 9 3
4 16 10 2
2 18 11 5
3 16 9 3
3 17 10 4
2 15 9 3
2 17 10 5
3 14 8 3
1 15 9 5
2 15 9 4
3 18 11 3
2 13 8 2
4 14 8 1
1 16 10 5
5 17 10 1
4 16 10 2
3 14 8 3
4 16 10 2
2 16 10 4
2 17 10 5
3 19 11 4
4 16 9 2
1 16 9 5
4 15 9 1
2 15 9 4
2 18 11 4
3 15 9 3
1 14 8 5
2 16 9 4
1 15 9 4
5 16 9 1
3 19 11 4
4 18 11 3
1 16 9 5
1 14 8 4
1 14 8 5
1 17 10 5
3 16 10 3
4 16 10 2
4 12 7 1
1 15 9 4
2 17 10 5
4 18 11 2
4 14 8 2
3 16 10 3
3 16 10 3
3 16 10 3
1 15 9 4
1 19 11 6
2 16 10 4
3 15 9 2
2 17 10 4
3 10 6 1
3 16 9 3
2 17 10 5
3 14 8 3
2 17 10 4
1 18 11 6
4 16 9 2
3 15 9 3
3 13 8 2
2 13 8 2
2 19 11 5
3 18 11 3
3 15 9 3
3 17 10 3
2 15 9 3
3 15 9 3
4 14 8 1
3 18 11 3
4 18 11 2
3 18 11 4
2 15 9 3
1 13 8 3
2 18 11 4
3 19 11 5
4 13 8 1
2 12 7 3
2 13 8 2
3 18 11 4
4 16 9 2
5 17 10 1
1 14 8 5
3 17 10 4
2 13 8 2
3 16 10 3
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Lean Six Sigma – Simco International
Control Phase
1
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Notes:
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Simco International – Control Phase Deliverables
Deliverable Page Lesson
(Deliverable Originated From)
Process Monitoring Plan 3 Process Control
Dashboard Development 10 Process Control
Response Planning 15 Response Planning
Final Project Storyboard 20 Project Documentation
2
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Process Monitoring Plan
Lean Six Sigma – Project Simulation
3
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Notes:
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Objective
Create a Process Monitoring Plan for the SI Consumer Home Loan process.
Instructions
Using the worksheet on the following page, develop a process monitoring
plan for the ongoing monitoring of the new process.
Identify the process step(s) where the CTQs will be measured
Document the data collection process
Finally, document the frequency you feel the data will need to be
collected and who will have ownership of the collection
Prepare your findings.
Process Monitoring Plan
SI Project Template: Process Monitoring Plan_SI
4
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CTQ #1: 15 Day Loan Processing Cycle Time
Owner Responsible
for Collection
Data
Collection
Frequency
Data Collection MethodProcess Steps Where
the CTQ is Measured
CTQ #2: 2 Day Loan Reviewing Time
Process Steps Where
the CTQ is Measured
Data Collection Method Data
Collection
Frequency
Owner Responsible
for Collection
CTQ #3: 100% Final Determination Package Accuracy
Process Steps Where
the CTQ is Measured
Data Collection Method Data
Collection
Frequency
Owner Responsible
for Collection
Process Monitoring Plan
5
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Notes:
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Please Do Not Proceed Forward
Process Monitoring Plan
6
For additional information
about this concept, see
Lesson 25 Process Control,
in the Process Monitoring
section.
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CTQ #1: 15 Day Loan Processing Cycle Time
Process Steps
Where the CTQ
is Measured
Data Collection Method Data
Collection
Frequency
Owner
Responsible for
Collection
Customer
receives final
determination
package (either
internet or mail)
1. Loan cycle time for Internet will be
collected through the SI Loan
System; Mail will be collected from
the date the customer submits the
application to the date of the
outgoing final package (+5 days for
shipping)
2. Query will be run each week to pull
loan data
3. All loans processed will be entered
into the SI Quality Assurance
spreadsheet and Control Charts and
Sigma’s will be created
Weekly Processing
Manager
SI Process Monitoring Plan
7
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Notes:
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CTQ #2: 2 Day Loan Reviewing Time
Process
Steps Where
the CTQ is
Measured
Data Collection Method Data Collection
Frequency
Owner
Responsible for
Collection
LP
determines
loan
qualification
1. Loan cycle time for Internet will be
collected through the SI Loan System;
Mail will be collected from the date of
the incoming application to the date
the final determination package letter
is generated
2. Query will be run each week to pull
loan data
3. All loans processed will be entered
into the SI Quality Assurance
spreadsheet and Control Charts and
Sigma’s will be created
Weekly Processing
Manager
SI Process Monitoring Plan
8
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Notes:
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CTQ #3: 100% Final Determination Package Accuracy
Process Steps
Where the CTQ
is Measured
Data Collection Method Data
Collection
Frequency
Owner
Responsible
for Collection
Generate
(Internet) or
create final
determination
package
1. A sample of 50 loans per week will be
pulled for inspection using an accuracy
tick sheet
2. Accuracy data will be entered into the SI
Quality Assurance spreadsheet and
Pareto Charts and Sigma’s will be
created
Weekly Processing
Manager
SI Process Monitoring Plan
9
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Dashboard Development
Lean Six Sigma – Project Simulation
10
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Objective
Create a Dashboard for the SI Consumer Home Loan process.
Instructions
Open up the Excel file “LSS SI Data File”.
The data set is in the worksheet “SI Quality Assurance”.
Develop a dashboard from the data that has been collected so far in the
Control Phase.
Utilize whatever graphical display tools and calculations you feel would
summarize the current process performance of the new SI loan process.
Utilize the following page to arrange these tools and calculations in the format
of a dashboard.
Prepare your findings.
Dashboard Development
SI Project Template: Dashboard Development_SI
11
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Dashboard Development
12
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Presenter
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Notes:
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Please Do Not Proceed Forward
Dashboard Development
13
For additional information
about this concept, see
Lesson 25 Process Control,
in the Dashboards section.
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Chicago Loan Processing Cycle Time (Sigma = 3.6)
Chicago LP Reviewing Time (Sigma = 3.0) Chicago Package Accuracy (Sigma = 3.5)
Count 3 1 1 0
Percent 60.0 20.0 20.0 0.0
Cum % 60.0 80.0 100.0 100.0
Co
un
t
Pe
rc
en
t
Loan Fields OtherNameAddressLoan Amount
5
4
3
2
1
0
100
80
60
40
20
0
Pareto Chart
SI Dashboard
16141210864
12
10
8
6
4
2
0
Fr
eq
ue
nc
y
Mean 8.98
StDev 2.290
N 50
Normal
Histogram of Chicago Loan Processing Cycle Time
50454035302520151051
3.0
2.5
2.0
1.5
1.0
Observation
Ch
ica
go
LP
Lo
an
R
ev
iew
ing
Ti
me
Run Chart (Mean 1.52)
14
8
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Notes:
- The SI Team used statistical analysis software to create the graphs for the new process dashboard.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Response Planning
Lean Six Sigma – Project Simulation
15
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Objective
Develop a Response Plan for the SI Consumer Home Loan process.
Instructions
Using the worksheet on the following page, develop a response plan for the
ongoing monitoring of the new process.
What actions should be taken if the process goes out of control?
How frequently should action be taken?
Who will own taking the action?
Prepare your findings.
Response Planning
SI Project Template: Response Planning_SI
16
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LP Reviewing
Time
Loan
Accuracy
Loan
Processing
Cycle Time
OwnerTimingActionMeasure
Response Planning
17
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Please Do Not Proceed Forward
Response Planning
18
For additional information
about this concept, see
Lesson 26 Response
Planning, in the Action
Planning section.
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Processing
Manager
Analysis should take place when
process has been out of control
for 2 weeks or more.
Quick Win improvements should
be continuous
New DMAIC project should be
implemented if process is out of
control >2 months
1. Review qualification procedures with LP’s
2. Look for causal relationships (special or common)
3. Continue to monitor and initiate Quick Win
improvement for special cause and initiate a new
DMAIC project for common cause
LP
Reviewing
Time
Processing
Manager
Analysis should take place when
process has been out of control
for 2 weeks or more.
Quick Win improvements should
be continuous
New DMAIC project should be
implemented if process is out of
control >2 months
1. Review incoming application accuracy from
customers
2. Review qualification procedures with LP’s
3. Identify and stratify accuracy defects by type
4. Look for causal relationships (special or common)
5. Continue to monitor and initiate Quick Win
improvement for special cause and initiate a new
DMAIC project for common cause
Loan
Accuracy
Processing
Manager
Analysis should take place when
process has been out of control
for 2 weeks or more.
Quick Win improvements should
be continuous
New DMAIC project should be
implemented if process is out of
control >2 months
1. Identify and stratify overall cycle time defects by
location, day of week, and process segment
2. Look for causal relationships (special or common)
3. Check that SI Loan System has been functioning
properly
4. Continue to monitor and initiate Quick Win
improvements for special cause and initiate a new
DMAIC project for common cause
Loan
Processing
Cycle Time
OwnerTimingActionMeasure
SI Response Plan
19
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Final Project Storyboard
Lean Six Sigma – Project Simulation
20
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Final Project Storyboard
SI Project Template: Final Project Storyboard_SI
Objective
Develop a Final Project Storyboard for the SI Consumer Home Loan project.
Instructions
Using the “Final Project Storyboard” template, develop the Final Project Storyboard for
communication to the organization about the entire SI Consumer Home Loan project.
The Final Project Storyboard is a presentation and visual depiction of the steps you took during
each phase of the DMAIC process. It communicates key deliverables and accomplishments
that were completed during the project (i.e. steps, tasks, key deliverables, and results). The
project story brings all the work and effort you put into your project to life through a storyboard
presentation.
Document key deliverables from each phase of the project under the designated sections of the
“Final Project Storyboard” template
For each phase where applicable, use a combination of graphs, pictures, statements and
annotations
Be creative…think about the story you are trying to tell and the key deliverables you want the
organization to see that will help sell the overall project story
Prepare your findings.
21
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Notes:
The Final Project Storyboard is different from the “1 Page” storyboard you completed in the Improve Phase. The Final Project Storyboard consists of 7 slides (we highly recommend keeping it to 7 slides total).
Slide 1: Cover
Slide 2: Define Phase Outcomes
Slide 3: Measure Phase Outcomes
Slide 4: Analyze Phase Outcomes
Slide 5: Improve Phase Outcomes
Slide 6: Control Phase Outcomes
Slide 7: Project Takeaways/Lessons Learned
Copyright © 2016 Acuity Institute LLC. All rights reserved.
SI Final Project Storyboard – Example #1
This is an example of a poor SI Final Project Storyboard slide (from the Improve Phase)
22
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Notes:
– This is an example of one slide from a poor SI Final Project Storyboard. This example has a simple screen shot of one deliverable from the Improve Phase. A screen shot without any annotations does not mean much (what does the tool tell you?). Also, what about the other deliverables from the Improve Phase.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
SI Final Project Storyboard – Example #2
This is an example of a good SI Final Project Storyboard slide (from the Analyze Phase)
23
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Notes:
This is an example of one slide from a good SI Final Project Storyboard. This example includes graphs, charts and annotations from the entire Analyze Phase.
Please do not copy this slide for your SI Final Project Storyboard.
Copyright © 2016 Acuity Institute LLC. All rights reserved.
Please Do Not Proceed Forward
Final Project Storyboard
24
For additional information
about this concept, see
Lesson 27 Project
Documentation, in the
Solution Replication and
Closure section.
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Presentation Notes
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This eBook is for personal use only. Please DO NOT use this eBook for presentations and training facilitation purposes.
Lean Six Sigma Green Belt eBook
eBook Overview
LSS Introduction
Lean Six Sigma Overview
Lean Six Sigma Improvement Methodologies
Lean Six Sigma Roles
Define Phase
Define Overview
Project Charter
Project Management
Process Definition
Stakeholder Management
Voice of Customer
Measure Phase
Measure Overview
Identify Measures
Data Collection
Describe and Display Data
Baseline Performance
Analyze Phase
Analyze Overview
Root Cause Analysis
Lean Process Analysis
Graphical Data Analysis
Statistical Data Analysis
Identify Root Causes
Improve Phase
Improve Overview
Identify and Select Solutions
Financial Impact of Solutions
Risk Planning and Testing
Implement Solution
Control Phase
Control Overview
Process Control
Response Planning
Project Documentation
Lean Six Sigma Green Belt Simulated Project Workbook
Simulated Project Overview
Define Phase Deliverables
Project Charter Development
SIPOC
As-Is Process Mapping
Quick Win Opportunities
Identify Stakeholders
Develop Stakeholder Map
Stakeholder Management Plan
Communication Plan
VOC Questions
CTQ Determination
Measure Phase Deliverables
Operational Definitions
Data Collection Planning
Histogram
Run Chart
Control Chart
Sigma Performance (DPMO)
Analyze Phase Deliverables
Cause and Effect Analysis
Lean Process Analysis
Process Stratification and Analysis – Pareto
Process Stratification and Analysis – Box Plots
Correlation Analysis
Regression Analysis
Improve Phase Deliverables
Solution Selection Matrix
Cost/Benefit Analysis
Mitigating Risks (FMEA)
Pilot Plan
Implementation Planning
Storyboarding
Control Phase Deliverables
Process Monitoring Plan
Dashboard Development
Response Planning
Final Project Storyboard
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