HR3140 FINAL

CASE STUDY SEMICON INDIA

Assignment:
The assignment is to write a recommendations to Semicon HR based on your analysis of qualitative and
quantitative data. It should not be less than 1000 words and not more than 2000 words (without
appendices). Your recommendation should focus on summarizing key points and refer to details in the
appendices. Provide context by connecting the facts and data to your insights. Make your
recommendation with confidence based on your analysis.

Your analysis should include the following steps:

1. Identification of the central issue and problem statement for this case

2. From the data in the case which of the following hypotheses can be accepted and which can be
rejected.

• The attrition rate is high among employees whose pay is below the company’s midpoint
or industry average.

• Turnovers are due to involuntary resignations
• Attractive overseas opportunities are causing a high attrition rate
• Lack of promotion opportunities are causing high attrition.
• Unimpressive job profile and thereby dissatisfaction with the job is causing attrition
• Turnover rate is high among employees with shorter length of service.
• Employee rated as poor performers quit, leading to high attrition
• Relocation of employees is causing high turnover
• Offerings from the competition are causing high attrition rates.

3. Categorize the causes contributing to attrition

• External: these are related to the overall labour market and economy and not within
control of the organization.

• Internal: these are related Semicon and are within the control of Semicon
• Employee specific: these are related to the individual, such as gender, personal reasons

for leaving, Length of Service. These are not within the control of Semicon but are
helpful to understand the profile of those leaving.

4. Communicate your insights and observations from the data given that test the hypothesis.

• Note that it is important to know what different variables contribute to attrition and
which ones do not. Identifying that there is no strong relationship between variables is
just as helpful as identifying that there is a relationship.

5. Finally, what recommendations would you make to Semicon HR based on your observations?

HR3140 FINAL
CASE STUDY SEMICON INDIA
Assignment:

HN3140Final Case Study Rubric

HN3140 Final Case Rubric

Expectations
for Format

Professional Very Good Acceptable At Risk Unacceptable
5 4 3 2 1

Identification
of Main Issues/

Problems

(5)

• Clearly Identifies and understands
all the main issues in the case study
o Critique detailed and

multifaceted
o Demonstrates an

understanding

of case.

• Clearly Identifies and
understands most of the main
issues in the case study
o Critique detailed and

multifaceted
o Demonstrates an
understanding of case.

• Clearly identifies and understand
some of the issues in the case study
o Critique detailed and multifaceted
o Demonstrates an understanding

of case.

• Identifies and understand the
issues in the case study
o Critique is broad and

general
o Demonstrates a limited

understanding of the
case.

• An issue is identified
o No understanding

demonstrated

Analysis

(10)

• Insightful and thorough analysis of
all the issues using both qualitative
and quantitative case information

• Through analysis of most of the
issues using both qualitative and
quantitative case information

• Through analysis of some issues • Superficial analysis of most of
the issues

• Incomplete analysis of the
issues

Recommendati
ons

(10)

• Well documented and reasoned
recommendations addressing all
main issues

• Recommendations clearly
supported by analysis

• No irrelevant content

• Appropriate and well thought out
recommendations addressing
most issues

• Recommendations are clearly
supported by analysis

• Appropriate recommendations
addressing most issues.

• Recommendations are not fully
thought through and content is not
fully developed

• Recommendations are somewhat
supported by analysis

• May contain some irrelevant content

• Superficial analysis and/or
inappropriate
recommendations.

• Recommendations are not
well supported by analysis

• May contain irrelevant
content

• Recommendations are vague
and/or inappropriate.

•

Assignment
Format and

Sections

(5)

• Word count met
• Format is correct and professional

throughout

• Minimum Word count is met and
overage is within 5%

• Format is mostly correct and
professional, with some errors

• Minimum Word count is met and
overage is within 10%

• Some format errors such as
unprofessional margins or spacing.

• Minimum Word count is met
• Weak, unprofessional format.

• Word count is not met
• No attempt at appropriate

formatting

Fluency

and Tone

(5)

• Ideas are logically arranged
• Paragraphing is skillfully managed,

with natural transitions
• Sentences flow seamlessly and

naturally
• Tone is professional throughout

• Ideas are mostly logically
arranged, well enough to allow
reader comprehension

• Paragraphing is adequately
managed, with some
errors/awkwardness

• Sentences flow but lack
seamless, natural quality of level
5

• Tone is mostly professional, with
some errors in register

• Some ideas are logically arranged
• Paragraphing is poorly managed,

possibly lacking in transitions
• Sentences flow somewhat awkwardly
• Tone is often unprofessional, with

many errors in register
•

• Few ideas are logically
arranged

• Appropriate paragraphing is
largely absent, with no
transitions

• Sentences feel disjointed and
awkwardly linked

• Tone is mostly
unprofessional, often too
casual and conversational,
possibly with slang

• No logical organization of
paragraphs or sentences

• Difficult to follow ideas
• No paragraphing
• Sentences very and difficult to

read
• Tone is slangy and

unprofessional throughout
•

HN3140 Final Case Study Rubric

HN3140 Final Case Rubric

Grammar

(5)

• A wide range of structures used
• Consistently correct
• Superior style, with impactful

phrasing
Less than 3 spelling, grammar or

punctuation errors

• Some variety of structures
• Generally correct; minor errors

do not affect clarity or readability
• Adequate style, with some

impactful phrasing
• Less than 5 spelling, grammar or

punctuation errors

• Somewhat limited variety of
structures

• Errors are more frequent and
somewhat affect clarity and
readability

• Unimpactful style
Less than 7 spelling, grammar or
punctuation errors

• Little variety; structures are
repetitious

• Errors are very frequent and
limit clarity and readability.

• No demonstration of style
• More than 7 spelling,

grammar or punctuation
errors

• No variety; student
demonstrates no knowledge of
sentence structure and
connectives

• Sentences are consistently
incorrect and seriously distort
clarity

Spelling, grammar, and
punctuation errors throughout
the document

Total
/40 marks

SMU805

SEMICON INDIA: DEMYSTIFYING WORKFORCE ANALYTICS (A)

It was May 2015 and Filip Daw, a human capital strategist with a leading consulting firm in India,

had just wrapped up a meeting with the C-suite leaders of Semicon India (SI), a subsidiary of

Semicon Inc., a global leader in the semiconductor industry. The American parent had its operations

spread across more than 70 locations in 19 countries, and supplied microcontrollers and embedded

processors to automotive, networking, industrial and consumer product industries.

The semiconductor industry comprised three key activities – design, fabrication and assembly – in the

development and manufacturing of semiconductor chips. Of these, design was the most skill-

intensive activity and determined a company’s time to market. Thus, the design centres constituted a
core strategic unit of Semicon, and their productivity and turnaround capabilities directly impacted

its competitiveness as a supplier to customers in various end-user sectors.

In 2005, SI was established as a design centre, with an objective to leverage the low cost and easy

availability of talent in India. However, contrary to expectations, it suffered from high workforce

attrition that led to a decline in its productivity and not just lowered its competitive position in the

customers’ vendor selection process but also impeded it from responding to customers’ requests in
time. Daw was engaged to help understand the reasons for its high attrition and provide insights to

address the issue.

SI’s Human Resource (HR) department held several opinions as to reasons for the attrition. But Daw

knew that as a strategist, his insights must be driven by data rather than opinions. Identification and

analysis of the appropriate data would not only help determine the validity of the opinions held by

HR, but also unearth reasons that were beyond the obvious. In addition, what was challenging at that

point in time was that the design function, unlike sales, had no direct measure of productivity. Daw

therefore wondered if there was a metric that could be used as a proxy to measure productivity and

track the impact of attrition.

Industry Overview

Market Size

In 2015, the global revenue of the semiconductor industry was US$342.7 billion, and was projected

This case was written by Dr Fermin Diez, Professor Tan Hwee Hoon and Lakshmi Appasamy at the Singapore Management
University. The case was prepared solely to provide material for class discussion. The authors do not intend to illustrate either
effective or ineffective handling of a managerial situation. The authors may have disguised certain names and other identifying
information to protect confidentiality. The case is based on the article “Using an Analytical Approach to Increase Retention in
High-Growth Countries: An Example in India”, by Fermin Diez, published in WorldatWork Journal, Second Quarter 2009, and
has been developed with permission from WorldatWork [Contents © 2009. Reprinted with permission from WorldatWork. Content
is licensed for use by purchaser only. No part of this article may be reproduced, excerpted or redistributed in any form without
express written permission from WorldatWork. WorldatWork website: ww.worldatwork.org]

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SMU-20-0011(A) Semicon India: Demystifying Workforce Analytics

to reach more than US$655.6 billion by 2025.1 The Asia Pacific region accounted for over 50% of

the worldwide semiconductor market. India, at US$14.5 billion in 2015, was estimated to grow at a

compound annual growth rate (CAGR) of 29.4% to reach US$52.6 billion by 2020.2

The prospects of semiconductor and electronics sectors were intertwined, as the growth in one fuelled

the growth in the other. Increase in consumption of electronics, primarily mobile computing and

mobile telephony, drove up the demand for semiconductors. Indian electronic devices consumption

was on the rise, and was expected to grow at a CAGR of 41% to reach US$400 billion by 2020 from

US$75 billion in 2015.3

Furthermore, with the increased sophistication of semiconductor chip design, new possibilities had

opened up in unconventional areas such as nanoscience, remote sensing, biotechnology and

photonics; such advancements led to an increased semiconductor content in electronic devices.

Background of the Semiconductor Industry4

Production of the integrated chip, the most critical type of semiconductor, comprised three stages –
pre-fabrication (design), fabrication (fab), and test and assembly. In the design phase, the circuit

boards had a series of abstract representations of details of transistors that would be interconnected

by a circuit of wires. During fabrication, the circuits on the chip, detailed in the design, were built on

the silicon wafer in successive layers, while the assembly phase involved cutting the wafer into

individual chips and packaging them in a protective shell. The design phase was skill-intensive and

required investments in expensive Electronic Design Automation (EDA) software. The fabrication

phase was capital-intensive but the worker skill requirement was lower than the design phase. While

the assembly phase was also capital intensive, it was not as high as the fabrication phase, and its

worker skill requirement too was relatively lower.

Prior to globalisation, the semiconductor industry in the developed countries of the West was

vertically integrated, as the companies owned and operated facilities for all stages of semiconductor

production. However, as the assembly phase involved less-skilled labour, offshoring it to low-cost

geographies presented an easy and attractive alternative, and in the 1960s, offshoring started. Soon

after, in the 1970s, the fabrication phase too was offshored, and finally in the 1980s, the design phase,

which required access to highly-skilled labour such as design engineers, began to be offshored as

well.

The merchant chip producers who sold chips to end-use manufacturers were the first to offshore

production, while the captive producers who produced the chips for use in their own products started

later. Eventually, with technology diffusion and foreign investment stimulating the emergence of

local companies in Asia, offshoring gave way to outsourcing. Outsourcing resulted in reduced

investments in capacity and reduced risks of overcapacity while increasing access to a variety of chip

types for the Western semiconductor companies. The industry thus consisted of three types of players

– Integrated Device Manufacturers (IDM), fabless companies and foundries. The IDMs
manufactured and sold the chips; fabless companies designed and sold the chips but outsourced

1 Handel Jones, “Whitepaper: Semiconductor Industry from 2015 to 2025”, SEMI, 4 August 2015,
https://www.semi.org/en/semiconductor-industry-2015-2025, accessed December 2019.
2 “Electronics”, Indian Brand Equity Foundation, 6 June 2017, https://www.ibef.org/download/Electronics-June-2017 , accessed

December 2019.
3 Jaideep Shenoy, “Indian Electronics Market Expected to Reach $400 Billion by 2020: Study”, Times of India, 12 June 2017,
https://timesofindia.indiatimes.com/business/india-business/indian-electronics-market-expected-to-reach-400-billion-by-2020-

study/articleshow/59108734.cms, accessed in December 2019.
4 Clair Brown, Greg Linden and Jeffrey Macher, “Offshoring in the Semiconductor Industry: A Historical Perspective”, Brookings
Trade Forum, 2005, p. 279–333. JSTOR, www.jstor.org/stable/25058769, accessed in December 2019.

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https://www.semi.org/en/semiconductor-industry-2015-2025

https://www.ibef.org/download/Electronics-June-2017

https://timesofindia.indiatimes.com/business/india-business/indian-electronics-market-expected-to-reach-400-billion-by-2020-study/articleshow/59108734.cms

https://timesofindia.indiatimes.com/business/india-business/indian-electronics-market-expected-to-reach-400-billion-by-2020-study/articleshow/59108734.cms

http://www.jstor.org/stable/25058769

SMU-20-0011(A) Semicon India: Demystifying Workforce Analytics

manufacturing to foundries, and foundries manufactured the chips that were designed and sold by

others.

Design Service5

The increased outsourcing of assembly and fabrication had resulted in ‘fabless’ model firms that
offered design services on contract. On the other hand, the captive manufacturers and IDMs operated

their own exclusive offshore design centres in order to avoid IP exposure and to ensure performance

and reliability. Since designing required high skills, more engineers were engaged at this stage than

any other. Thus, offshoring and outsourcing was concentrated in Asian economies that had a

substantial pool of engineering talent. The complexity of the project, turnaround time and availability

of resources determined the size of the design teams in a company.

Designing involved three hierarchical stages – specification (which defined the behaviour, features
and functions of the chip), logic design (an abstract representation of signal processing within the

chip) and physical design (translation of the abstract into an actual network of wires and devices on

silicon layers). A prototype thus developed was tested in a hardware simulation of the system in

which the chip would be used. The software that would get embedded in the chip was developed

alongside. EDA software was used to realise the design and to automate the later stages of designing

that required lower engineering input. As demand for the sophistication of performance, reliability,

features and functions of products in which the chips were to be embedded increased, a larger number

of transistors had to be packed on each line width of the chip. With the increase in complexity of the

chips, and the fact that software had to be co-developed for better integration with end systems, the

engineering hours went up.

Companies established offshore design centres to gain access to specialised skilled labour, establish

closer contact with customers, and reduce cost. While the centres brought significant cost savings,

problems such as communication and coordination issues between offshore teams and parent

company also increased. This was in addition to the managerial challenges of assigning projects,

assessing team productivity and individual performance. The challenges were aggravated with

increased training and monitoring costs due to lower quality and productivity of inexperienced

engineers. Despite these challenges, offshoring of design centres had increased driven by the cost

advantages and proximity to production facilities and high-growth markets. The dynamic nature of

the electronics industry demanded new models and improved variants at a fast pace. Original

Equipment Manufacturers (OEMs) and product companies not only faced declining margins, they

also were under pressure to shorten product development/innovation cycles. Hence, they had started

outsourcing design services to low-cost centres in Asia. The contract design service centres that

designed the entire chip or undertook specific functions of design projects, such as physical design

and logic verification, for captive manufacturers and system companies were growing, especially in

Japan, Taiwan, China and India.

India6

The growth of the semiconductor design service industry in India was driven by the mature software

sector, emergence of the local market for electronic devices, availability of an English-speaking

skilled workforce, particularly, ample supply of electronics engineering graduates, and an influx of

foreign investment. International companies had either set up their subsidiaries that functioned as

5 Ibid.
6 India Brand Equity Foundation, “Semiconductor: Market and Opportunities”,
https://www.ibef.org/download/Semiconductors_220708 , accessed in December 2019.

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SMU-20-0011(A) Semicon India: Demystifying Workforce Analytics

offshore design centres in the country or outsourced their design requirements to Indian companies.

There were 125 design companies in India, and of the 25 world’s top semiconductor companies, 19

had already established subsidiaries in India. Large Indian IT companies such as Wipro, Tata

Consultancy and HCL Technologies had also embarked on providing design services. This was in

addition to the emergence of many start-ups in the sector with the high penetration of technology and

increase in foreign investments. Furthermore, in February 2007, the Indian government had rolled

out a host of incentives for the industry in its first-ever exclusive policy for sharing of up to 20%

capital expenses in the case of companies in Special Economic Zones (SEZ) and 25% for those in

non-SEZ, and up to 26% equity participation. The policy was anticipated to attract more players and

investments into India.

Most design companies in India were also moving up the value chain. They had started to produce

high-value front-end design in addition to the design centres of multinational firms undertaking end-

to-end design development of entire chips. This had led to a need for highly-specialised skills across

a wide range of design-related activities which the local engineers lacked. Thus, they faced steep

learning curves, resulting in delayed projects.

The Indian design services companies billed their clients in one of three methods – time and material,
fixed price or joint go-to-market. In the time and material method, billing was based on the actuals,

and in some cases was subjected to a ‘not-to-exceed’ clause. The fixed price method involved fixing
the deliverables by calculating the engineer-months required to complete the project. In the joint go-

to-market method, the captive manufacturers engaged the third-party service providers for design,

and paid for it in the form of royalties from the sale of end products. Thus, productivity was critical

to ensure sustainable revenues and any delays in executing the projects would severely impede the

earnings of the design service companies.

In 2015, foreign companies accounted for a majority of India’s US$12.9 billion semiconductor

design industry’s revenue. The design service industry was forecast to reach US$23-29 billion by

2020.7 A 2011 study by the Indian Semiconductor Association had estimated that the industry would

employ 230,000 people.8. The workforce comprised primarily graduates, of whom close to 60% had

only up to eight years of experience. Women accounted for 20% of the workforce; the embedded

software segment had a higher ratio of women than other segments.

Both public and private initiatives were underway to help develop the designing skills of the local

engineers as the more than 200,000 relevant engineering talent that the country produced annually

lacked the quality and level of skills required by the industry, with only 6% of this talent coming

from tier-one institutes of the country. The majority of the fresh relevant engineering graduates were

from the southern part of the country, as most of the universities offering relevant degrees remained

concentrated in the South. Notably, many of the experienced engineers, after a few years of working

and strengthening their basic skills, opted to enrol in higher education and specialisation courses as

it enhanced their domestic and overseas career prospects.

Commenting on the talent scenario, Daw said,

Despite all the efforts in the past few years to address the skills gap, access to high-quality

engineers remains a challenge, and experienced engineers are in high demand. In order to retain

7 “Indian Electronics & Semiconductor Association, Indian ESDM Industry Update: An IESA-EY Report”, February 2017,

https://meity.gov.in/writereaddata/files/Executive%20Summary%20of%20the%20IESA%20EY%20Report , accessed December

2019.
8 Indian Semiconductor Industry Association, “Study on Semiconductor Design, Embedded Software and Services Industry”, April
2011, https://meity.gov.in/writereaddata/files/Semiconductor06April11_020511 , accessed in December 2019.

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https://meity.gov.in/writereaddata/files/Semiconductor06April11_020511

SMU-20-0011(A) Semicon India: Demystifying Workforce Analytics

talent amidst high competition, pay-based solutions are deployed by the players in the industry,

and senior management appears to think that SI should adopt the same strategies, although from

my perspective, these strategies are not sustainable in the long run.

Semicon India

Company Overview

In 2005, Semicon had established operations in India with the aim of developing a Centre of

Excellence (CoE) in System on Chip (SoC) integration and IP core 9 design. The American parent,

Semicon Inc, with a revenue of US$26 billion in 2014, was one of the world’s largest semiconductor
companies. Its research and development, manufacturing and sales operations were spread across the

globe. It designed and manufactured embedded semiconductors for the automotive, consumer,

industrial, networking and wireless markets. SI operated two design facilities – one at its headquarters
at Noida (adjoining India’s capital, New Delhi) and the second at Bangalore, and developed software
and hardware designs for the wireless, networking and automotive markets. By 2015, the company

had expanded extensively, and in the past two years alone, it had invested over US$50 million and

filed over 30 patents.

Workforce Overview

Design projects were undertaken by composite teams that comprised members with diverse skills,

and each project, depending on its complexity, took from a few months up to a year to complete. By

2015, the Noida facility, a R&D centre, employed around 1,000 engineers who worked on advanced

technologies to develop digital and mixed-signal IPs and SoCs. The Bangalore facility, a software

centre, employed about 600 engineers who undertook the development of software platforms,

connectivity blocks, protocol stacks, OS porting and validation. SI planned to expand its operations

across the country, and to that end, the company needed to increase its design team by another 1,500

engineers over the next two years.

The skill level of entry-level engineers was diverse as they came from educational institutions of

varied standing. SI believed that compared to recruits from tier-two institutes, recruits from tier-one

institutes had the requisite soft skills along with better quality design skills. As an equal opportunity

employer, SI had a relatively substantial share of women in its workforce. India had a significant

number of women graduating each year as IT engineers; hence it was easy to recruit women into the

embedded software designing segment. However, the HR team believed that the attrition rate among

women was generally higher than men. Notably, the Bangalore facility, the software centre, had more

women than the Noida facility.

Workforce Management

Due to the extreme shortage of talent in the industry, there was stiff competition among companies

to attract and recruit talent. Poaching was rampant and the management and the HR team at SI

believed that most of its turnover was caused by higher pay offered by the competitors to lure its

experienced engineers. The demand for talent was not limited within the country but was widespread

in the region that was buzzing with outsourced and offshored semiconductor design and

9 A reusable unit of logic, cell or integrated chip design for which the design developer owns the intellectual property rights, which can

be licensed to other parties. IP cores are generally used as building blocks of larger software or hardware designs.

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SMU-20-0011(A) Semicon India: Demystifying Workforce Analytics

manufacturing activities. The HR team at SI strived to keep its median pay in line with that of the

industry’s median by closely watching salary movements in the market.

Appraisal of employees was based on forced curve performance management philosophy, and

accordingly the employees were rated on a 1 to 5 scale by their managers (refer to Exhibit 1 for SI’s
Performance Rating Scale). It was a practice at SI to conduct a survey among its employees to score

their team managers based on a set of leadership competencies. The score of each manager reflected

their competence as measured by the employees in their team.

In high growth markets such as India, there prevailed a dilemma over the frequency of promotions –
whether to promote employees who were not ready for higher responsibilities and then train them

along the way, or to wait until the employees were ready for promotion against the risk of losing

them to competition. SI had a career plan in place for its employees. The career plan established the

number of years between promotions. In addition, the company was required to promote no less than

15% of its employees at each level to maintain healthy levels of ‘build versus buy’ talent policies.
As for pay progression within and across levels, it observed the market pricing and adjusted its

midpoints.

Trial of Turnover

Historical High

Despite intense competition for design talent in the Indian market, SI had managed to retain its

workforce turnover rate at par with the industry average. According to its HR team, employees who

stayed for at least three years tended to remain with the company for a long time. SI primarily

deployed pay-related solutions to retain its employees by benchmarking competitors and matching

retention packages with industry trends. However, despite keeping up with the market averages,

turnover was high in some segments of the individual contributor (IC) population – the entry-level
analysts IC-1, and the next two levels – IC-2 (engineers) and IC-3 (senior engineers). At the IC-2

level, it was losing nearly as many people as it was hiring at entry-level (IC1), and it was hiring

nearly as many people at IC-3 as it was losing at the IC-2 level.

In 2015, SI’s turnover rate exceeded its historical average of 20%, alarming the management. If left
unchecked, the high turnover rate had the potential of impacting productivity and revenues of the

company. Daw summed up the challenge ahead of SI thus,

To ensure long-term sustainability and to strengthen its competitive position, it was not enough

to keep up with the industry’s average attrition rate that stood at 20%, or to solely rely on pay-
based solutions for retention. SI had to differentiate itself, add value and lower its turnover rate

below the industry average.

Betting on Analytics

While it was able to attract the right talent amidst a severe talent crunch, SI was unable to retain them.

Daw knew that although a zero turnover was unhealthy as well as unattainable, SI’s HR policies

would have to control the direction and the level of existing turnover such that the turnover rate

among the lowest performers was at the expected level, and the turnover rate among the highest

performers was brought to as close to zero as possible. According to Daw, this would warrant a

thorough data-driven analysis of the company’s recruitment, development and retention policies, and

how the policies influenced the turnover drivers.

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SMU-20-0011(A) Semicon India: Demystifying Workforce Analytics

Daw quickly got to the task at hand and listed the questions that needed to be addressed: What were

the potential drivers of turnover? Were the opinions held by the HR team valid? What were the

hypotheses to be drawn to test the impact of the drivers of turnover at SI? What data would he require

to analyse the hypotheses, and how would he source the data? Was there a means to extend the

responsibility of retention beyond the HR department and make team managers accountable? If yes,

how could he prove his claim of managers’ accountability towards retention?

Daw remained undaunted by the extensive volume of data that would be generated by the 1,600

strong workforce of SI. He was aware that if he got the fundamentals such as the hypotheses right,

the insights from the data analysis would help in identifying retention solutions, and hence support

SI’s business strategy. However, first and foremost, a proxy metric confirming the link between

productivity and retention had to be identified.

EXHIBIT 1: SEMICON’S PERFORMANCE RATING SCALE

Rating Definition Highlights

1 Overall performance, including both

results and behaviours, represents the

highest level of

contribution.

•

•
•

•

Exceeds all expectations
Difficult rating to achieve year over year
Highest opportunity for career
progression and development
Eligible for significant rewards

2 Overall performance, including both

results and behaviours, represents a

high level of contribution.

•
•
•

Meets all expectations and may exceed
some

Opportunity for career progression and
development
Eligible for competitive rewards

3 Overall performance, including both

results and behaviours, needs to

improve to increase overall

contribution.
•
•
•

Meets most expectations
Opportunity for career progression and
development targeted at improving
performance
Eligible for limited rewards

4 Overall performance, including both

results and behaviours, does not meet

the expected level of contribution.

•
•
•
•

Does not meet expectations.
Performance needs to improve
Identify and document actions
to improve
Development opportunities
targeted at improving performance in
current assignment
Not eligible for rewards

5 Less than six months active.

Source: Internal data from the company

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• Structure Bookmarks

Industry Overview
Market Size
Background of the Semiconductor Industry
Design Service
India
Semicon India
Company Overview
Workforce Overview
Workforce Management
Trial of Turnover
Historical High
Betting on Analytics
EXHIBIT 1: SEMICON’S PERFORMANCE RATING SCALE

SMU806

SEMICON INDIA: DEMYSTIFYING WORKFORCE ANALYTICS (B)

To unscramble the issues behind the high turnover rate at Semicon India, Daw formulated a series of

hypotheses and carried out a detailed data analysis. Based on the analysis, he made the following

observations.

Table 1: Job Levels and Turnover Drivers

Turnover Reasons
Job Levels

IC-1 IC-2 IC-3

Higher Studies 32% 16% 8%

Job Profile 25% 24% 31%

Relocation 24% 20% 8%

Better Pay 5% 10% 15%

Dissatisfaction with Managers 1% 4% 8%

Low Performance 5% 4%

Overseas Opportunity 2% 8%

Involuntary Resignations 3% 6% 15%

Performance Rating 1% 4%

Own Venture 2% 8%

Transfer 2% 8%

• At entry level, employees from tier-one technical institutes left sooner.

This case was written by Dr Fermin Diez, Professor Tan Hwee Hoon and Lakshmi Appasamy at the Singapore Management
University. The case was prepared solely to provide material for class discussion. The authors do not intend to illustrate either
effective or ineffective handling of a managerial situation. The authors may have disguised certain names and other identifying
information to protect confidentiality. The case is based on the article “Using an Analytical Approach to Increase Retention in
High-Growth Countries: An Example in India”, by Fermin Diez, published in WorldatWork Journal, Second Quarter 2009, and
has been developed with permission from WorldatWork [Contents © 2009. Reprinted with permission from WorldatWork. Content
is licensed for use by purchaser only. No part of this article may be reproduced, excerpted or redistributed in any form without
express written permission from WorldatWork. WorldatWork website: ww.worldatwork.org]

Copyright © 2020, Singapore Management University Version: 2020-05-18

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SMU-20-0011(B) Semicon India: Demystifying Workforce Analytics

Figure 1: Compa-Ratio1 Vs Performance Ratings

0.869

0.997 1.028 1.026
0.935

0.50

0.75

1.00

1.25

1.50

1 2 3 4 5

C
O

M
P

A
-R

A
T

IO

APPRAISAL GROUPING

Figure 2: Turnover by Performance

Rating

Rating 1
7%

Rating 2
34%

Rating 3
24%

Rating 4
4%

Rating 0,5
31%

• Almost all of the employees rated 4 tended to leave the company soon after appraisal.

1 Compa-ratio measures an employee’s pay relative to the midpoint of the pay range of the employee’s job/position. A compa-ratio of 1
means the employee pay is same as the midpoint of the pay range for his/her job; a compa-ratio of less than 1 means the employee’s pay
is below the midpoint of the pay range and a compa-ratio of more than 1 means the employee is earning above the midpoint. This is a
useful measure to determine if the employee is earning significantly more or significantly less than the midpoint of their range and decide

if he/she needs a salary freeze or hike.

2/4

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SMU-20-0011(B) Semicon India: Demystifying Workforce Analytics

Table 2: Managers and Attrition

Business

Group
Manager Turonver

Turnover

percentage

Manager

Performance

Rating

Employee

Survey

Manager

Score

A A1 3 (Rater 2,5) 3 (Rater 3) 67% 2 0.26

B B1 4 (Rater 1,2) 4 (Rater 3) 62% Quit 0.38

C C1 2 (Rater 1, 2) 2 (Rater 3) 50% 2 0.52

C C2 2 (Rater 1, 5) 1 (Rater 3) 50% 1 0.65

D D1 4 (Rater 1,2,5) 2 (Rater 3) 47% 1 0.06

A A2 5 (Rater 1, 2,5) 42% 1 0.23

E E1 4 (Rater 2,0) 40% 2 0.15

C C3 3 (Rater 1,2,) 38% 2 0.58

D D2 3 (Rater 2) 2 (Rater 3) 36% 2 0.29

C C4 2 (Rater 0) 1 (Rater 3) 33% 1 0.51

F F1 2 (Rater 2,0) 33% 2 0.52

G G1 5 (Rater 2,5,0) 31% 2 0.73

G G2 4 (Rater 2,5,0) 31% 2 0.61

G G3 4 (Rater 2,5,0) 1(Rater 3) 28% 2 0.44

H H1 4 (Rater 2,5) 1(Rater 3) 27% 2 0.28

C C5 1 (Rater 2) 2 (Rater 3,4) 27% 2 0.43

A A3 2 (Rater 2,5) 27% 2 0.18

B B2 2 (Rater 2,5) 27% 1 0.35

Figure 3: Attrition by Tenure

6

0%

50%
48%

A
tt

ri
ti

o
n

P
e

rc
e

n
t

40%

16%

9%

20% 21%

32%31%

30%

17%20%

10%

0%

< 6 Months 6 Months - 1 Year -1.5 1.5 Years -2 2 Years -2.5 2.5 Years -3 3 Years -3.5 > 3.5 Year s
1 Year Years Years Years Years Years

Tenure

• Men accounted for most of the attrition for employees below 2.5 years of tenure.

3/4

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SMU-20-0011(B) Semicon India: Demystifying Workforce Analytics

Figure 4: Promotion and Recruitment

Daw inferenced from the findings that SI’s promotion rates were lower than the established minimum

rate of 15%. While fresh recruits were assured at the time of recruitment that they would be promoted

after two years, the promotion rate did not concur with the assurance. The market midpoint

differentials2 between the three IC levels were in the order of 50% to 75%, while the market average

salary increase for last year was 13% to 16%. SI’s midpoints were calculated using the range
observed in the market and industry. SI’s midpoints differentials were roughly the same as the salary

increase that it provided.

What insights could Daw draw from the above observations to prove or disprove his hypotheses?

And based on those insights, what recommendations should he make to Semicon’s HR with regard
to recruitment, retention, talent development and women employees?

2 A pay range, which is the upper and lower limit of compensation, has a minimum, midpoint and a maximum. The midpoint is

equidistant from the minimum and maximum pay and is aligned to the market value of the job or simply put a fair price for the job based

on what the competitors are offering. Usually entry level employees are hired at or around the minimum pay and those who meet the
company’s performance expectations or exceed them are paid at or around the midpoint compensation and depending on factors such as
experience, tenure, performance, or the employee’s value to the organization employees are paid at or around the maximum
compensation. Companies typically have a pay range for each job and pay range is built with reference to the pay range that prevails in
the market for similar jobs. In large organisations with several jobs, the jobs with similar level of responsibilities and value to the

organisation are grouped together into grades and a pay range is built for each grade instead of each job. Midpoints of pay ranges are

compared and evaluated annually with that of the market/industry and ranges are adjusted as necessary to keep the pay structures
competitive. Midpoint differential is the difference between the midpoints of adjacent grades, in the case of SI it the difference between

the midpoints of IC-1, IC-2 and IC-3. It is usually expressed as a percentage increase: (Higher Midpoint-Lower Midpoint)/ Lower

Midpoint = Midpoint differential. The higher the midpoint differential between two grades, the higher the mid-point progression
between those two grades and reflects how pay increases between two grades in one’s salary structure.

4/4

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