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8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 2

1 Introduction ……………………………………………………………………………… 3

2 Essential Reading …………………………………………………………………….. 5
2.1 Types of Supply Chains …………………………………………………….. 5

2.2 Types of Decisions in Supply Chains ………………………………. 7

2.3 Efficient or Responsive: A Framework for Supply

Chain Strategy ……………………………………………………………………. 8

2.4 Improving Efficiency: The Bullwhip Effect …………………… 10

Demand Forecast Updating …………………………………………… 12

Order Batching …………………………………………………………………. 12

Price Fluctuations …………………………………………………………….. 13

Rationing and Shortage Gaming ……………………………………. 13
2.5 Improving Responsiveness …………………………………………….. 16

Delayed Differentiation ……………………………………………………. 17

Read-React Capability ……………………………………………………..18
2.6 Alignment of Incentives ………………………………………………….. 24

2.7 Supply Chain Design ………………………………………………………… 32

Degree of Proximity to Customers ……………………………….. 32

Degree of Centralization …………………………………………………. 36

Degree of Flexibility …………………………………………………………. 38

3 Supplemental Reading …………………………………………………………… 42
3.1 Supply Chain Risk Management …………………………………….. 42

4 Key Terms…………………………………………………………………………………46

5 Endnotes …………………………………………………………………………………… 47

6 Index ………………………………………………………………………………………….. 49

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Table of Contents

For the exclusive use of A. CAI, 2020.
This document is authorized for use only by AMANDA CAI in Supply Change Management IE-GY 7993 taught by THOMAS MAZZONE, NYU Tandon School of Engineering from Feb 2020 to
May 2020.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 3

1 INTRODUCTION
he supply chain for a product is the network of
organizations and activities involved in its production and
distribution. A car’s supply chain, for example, comprises

auto dealers, factories, component suppliers, semiconductor and
electronics producers, steel producers, plastics and chemicals
manufacturers, logistics service providers, and so on. All of these
organizations are directly involved in the flow of materials and
services necessary for the production and distribution of a car.
Other organizations, such as information technology service
providers and supply chain analytics companies, play crucial
supporting roles.

Traditionally, organizations in a supply chain have focused on their internal
operations without worrying about coordinating their activities with supply chain
partners. Even within an organization, activities are often housed in functional silos, such
as procurement, manufacturing, sales, and distribution. Each functional manager focuses
on improving the operations within his or her scope while taking the requirements of
other supply chain members as given. To exert control over activities within their scope,
organizations actively buffer themselves from suppliers and customers by establishing
rigid rules of interaction. For example, they may set long lead times and minimum order
sizes for customers so that they can manage their factory operations efficiently, or they
may impose penalties for nonfulfillment of procurement orders so that their suppliers
carry sufficient inventory.

However, academic research and industry experience beginning in the mid-1980s
have shown that organizations in a supply chain cannot exist in isolation; they neither
have control over their costs and profits nor are they able to manage their risk alone.
Instead, all organizations need effective supply chain management to coordinate across
organizational and functional boundaries. The supply chain function is responsible for
facilitating such coordination. It involves making decisions regarding supply chain
design, sharing information about demand and product availability with other members,
integrating production and distribution decisions, setting up long-term supplier
relationships, writing contracts to share the risks of demand and price uncertainty among
organizations, reducing lead time, and so on.

In recent years, various forces have heightened the importance of supply chain
management. Increasing product variety and shortening product life cycles have spurred
organizations to adopt new and innovative supply chain designs that are more responsive
to customers’ needs. The sharing of information and the emergence of new technologies
such as RFID (radio-frequency identification) have enabled firms to collaborate with one
another and to function like an integrated entity, reducing waste in the supply chain and
decreasing time to market. Globalization and the growth of emerging markets, especially
China, have lengthened and fragmented supply chains, renewing the focus on supply
chain design. The Internet is creating new methods of selling and of configuring supply
chains, turning customers into savvy purchasers. Natural disasters, accidents,
contamination, and global recession have turned the spotlight on supply chain risk

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 4

management, which is now managed at an organization’s most senior levels. And
concerns about environmental sustainability and impact have forced all organizations to
take responsibility for the entire life cycles of their products, wherever they may be in the
supply chain.

In the Essential Reading, we discuss the principles of supply chain management in the
context of these developments. We address questions such as:

• What are different types of supply chains? How do they fit different product
market requirements?

• What should be the goal of a supply chain—efficiency or responsiveness?

• How can a supply chain be coordinated across all organizations and activities
to deliver greater value?

• What should be the supply chain footprint of an organization?

• What are the sources of supply chain risk, and how can this risk be
managed?

In Sections 2.1 and 2.2 of this reading, we define terminology by describing the types
of supply chains and decisions in supply chain management (SCM). Section 2.3
introduces two broad supply chain designs—physically efficient and market responsive—
which are distinguished by product market characteristics and performance
requirements. Section 2.3 also describes methods to improve the efficiency of a supply
chain by mitigating the bullwhip effect, sharing information, and coordinating decisions
across partners, and presents methods to make a supply chain more responsive, such as
delayed differentiation and read-react capability. In Section 2.5, we explain how the
incentives of organizations in a supply chain can be aligned to facilitate collaboration and
maximize total profits. Finally, in Section 2.6 we describe the elements of supply chain
design, focusing on the trade-offs that lead to different footprints in different situations.

In the Supplemental Reading, we explore sources of supply chain risk and methods
for mitigating it—a topic that has gained visibility in recent years because of increased
globalization, attention to natural disasters, and political and terrorism-related risks.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 5

2 ESSENTIAL READING

Contrary to what the term suggests, a supply chain is usually a complex network. Figures
1 through 3 show some common types of supply chain networks, characterized by the
number of stages in each; the number of facilities, or locations, at each stage; and their
linkages. A serial supply chain, the simplest kind, moves products through sequential
stages, each served by a single facility. The well-known Beer Game, played in many supply
chain management courses, is a four-stage serial supply chain consisting of a factory, a
distributor, a wholesaler, and a retailer.a We will consider serial supply chains in many
sections in this reading because they provide a simple context to illustrate concepts.

In the serial supply chain in Figure 1, the factory produces goods and sells them to
the distributor, the distributor sells to the wholesaler, the wholesaler sells to the retailer,
and the retailer fulfills customer demand. Each location makes decisions about how much
quantity to procure from the upstream supplier (or, in the case of a factory, how much to
produce) in order to serve the demand from the downstream customer at minimum cost.
Upstream and downstream are relative terms: Goods generally flow from an upstream
location to a downstream one. Arrows in the diagram show the flow of goods from the
factory toward the retailer. Dashed lines show the flow of information, which can move
both upstream and downstream. For example, purchase orders flow from the retailer
toward the factory, whereas information on production schedules, fulfillment lead times,
and availability of inventory flows in the opposite direction.

Figure 1 Serial Supply Chain

Factors such as the nature of products and the number of suppliers and customers
pull an organization away from a serial supply chain. A distribution supply chain, shown
in Figure 2, has one upstream location, such as a factory or a warehouse, which supplies
several downstream locations that serve retail customers. The downstream supply chains
of retailers, pharmaceutical companies, and consumer packaged goods manufacturers are
typically distribution supply chains. An assembly network, shown in Figure 3, has many
suppliers whose products are combined into one complex product in the downstream
stage. The procurement function of a manufacturing organization is typically an assembly
network. Such a supply chain is useful when a buyer firm creates a portfolio of suppliers
differentiated by cost, quality, or responsiveness. It also represents the upstream supply
chain of a retailer that purchases different products from specialized manufacturers.

a A variation on this kind of supply chain is when a small supplier has a single large customer.

2.1 Types of Supply Chains

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 6

Figure 2 Distribution Supply Chain

Figure 3 Assembly Network

Most actual supply chains are combinations of serial, distribution, and assembly
stages. Moreover, in some supply chains, goods flow both upstream and downstream. For
example, manufacturers that recycle their products have closed-loop supply chains that not
only supply products to customers but also take back used merchandise for recycling or
remanufacturing. Logistics service providers such as UPS and FedEx, which handle
arbitrary physical flows between any pair of locations, have streamlined their operations
by designing their supply chains according to a hub-and-spoke model: Packages are fed
from local facilities (spokes) to centralized facilities (hubs), where they are sorted and
forwarded to their destinations.

Supply chains are said to be differentiated or fragmented when different stages are
owned by different organizations and to be vertically integrated when many stages are
internal to one organization. Most supply chains are vast and global. Multinational
corporations manage supply chains that consist of many internal facilities as well as

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 7

external suppliers and customers. Different firms in an industry can differ in their supply
chain configurations. For instance, consider two clothing retailers, American Apparel and
Forever 21, both U.S. chains based in Los Angeles. American Apparel is vertically
integrated—it produces knitwear in its own factory and then ships products to its own
stores. Forever 21, in contrast, subcontracts manufacturing with suppliers all over the
world.1

The supply chain decisions of an organization affect its logistics costs, inventory costs,
and labor costs. Logistics costs are incurred in the movement of goods across locations;
inventory costs are incurred in the storage of inventory in distribution centers,
warehouses, and retail locations; labor costs are incurred in the handling of goods
throughout the supply chain. All these costs add up to a substantial fraction of the total
cost of a product sold by a firm. Supply chain decisions also have revenue implications
when they improve product availability and increase the speed of introduction of new
products. Because of these broad cost and revenue implications, supply chain managers
can realize many types of objectives through their decisions: reducing cost, improving
product availability, minimizing risk, and reducing the cost to the environment.

Supply chain decisions can have either short- or long-term timeframes. Short-term
decisions involve procurement and production decisions, that is, the quantities of various
products and components to procure from upstream locations and the quantities of
finished goods, if any, to produce in order to serve demand. Such decisions are often
taken on a daily or weekly basis. Tools such as those described in Core Curriculum:
Managing Inventory (HBP No. 8016) are commonly used to make those decisions.

In large organizations, procurement and production decisions are executed through a
multifunctional process called Sales and Operations Planning (S&OP). This process
brings together the sales, production, logistics, and finance functions to share forecasts
and cost information necessary for decision making. Managers in different functional
roles possess different types of operational information about the areas under their
control, such as production, ordering, inventory holding costs, the demand received from
downstream locations, shipments from upstream, forecasts of future demand, and sales
promotion activities. S&OP facilitates share this information and coordinate decisions
across functional areas and geographical locations.

Long-term supply chain decisions pertain to an organization’s physical and its soft
infrastructure. In establishing its physical infrastructure, an organization chooses
upstream and downstream partners as well as deciding where to locate facilities of its
own, such as factories, warehouses, and customer service centers. These decisions depend
on the nature of the product, the degree of demand uncertainty, and factors related to the
locations of customers and suppliers such as costs, lead time, and risk of disruption. The
physical infrastructure of a supply chain is also known as the supply chain footprint.

Soft infrastructure decisions are those that determine the extent of coordination
across locations. At one extreme is a centralized supply chain, in which a designated
central authority makes procurement and production decisions at all locations and
collects cost, demand, lead time, and other operational information from all locations.
The organization playing that central coordinating role generally seeks to maximize the
total profit of the supply chain. Vendor managed inventory (VMI), in which a supplier
manages inventory of its product at its own as well as at its customers’ locations, is an

2.2 Types of Decisions in Supply Chains

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 8

example of a centralized supply chain. At the other extreme is a decentralized supply
chain, in which each location makes independent decisions and coordination is achieved
through contracts or incentive design. Between these two extremes, supply chain
locations may share information about the occurrence of demand, the availability of
inventory, production, shipments, and so on, but retain independent decision authority.

Note that the centralization or decentralization of decisions in a supply chain are
unrelated to the ownership of locations. A vertically integrated organization can have a
decentralized supply chain if decision rights are assigned to the managers at each location.
And two or more organizations in a differentiated supply chain can choose to coordinate
their decision making.

Consideration of the soft infrastructure of a supply chain is important because the
performance of each location depends not only on its own decisions but also on decisions
made at other locations. For example, if an upstream supplier does not maintain sufficient
stock, then a downstream customer may not receive the product when it needs it.
Similarly, if a downstream location places orders that are variable and inconsistent, the
upstream location will be forced to carry more safety stock as a hedge against uncertainty.
Therefore, the profit of each location in a supply chain can be improved through better
supply chain design and better coordination of actions taken by all locations.

What should a supply chain do particularly well? As we’ve seen so far, an organization
faces a myriad of choices when designing its supply chain. The supply chain strategy of an
organization can be structured according to the characteristics of its product.

One framework for making these decisions classifies products as either functional or
innovative.2 Functional products tend to have long life cycles of two years or more,
predictable demand with low average demand forecast error, low profit margins, low
product variety, low rates of stockout, and small price markdowns. Packaged foods sold in
a supermarket, personal care products, basic clothing and accessories, and many
industrial products generally have these characteristics. In contrast, innovative products
have short life cycles of three months to a year, unpredictable demand with high average
demand forecast error, high profit margins, high product variety, high rates of stockout,
and high price markdowns. Examples include products that have significant technology
or design components, such as consumer electronics, cell phones, fashion and seasonal
clothing, home furnishings, and toys.

In recent years, the rate of new product introduction has increased steadily.
Correspondingly, product variety has proliferated and life cycles have shortened.
Products that used to be functional have become innovative. Consider light bulbs:
whereas incandescent light bulbs are a functional product, energy-efficient versions have
the characteristics of innovative products because their technology undergoes rapid
improvements. In industries such as consumer packaged goods, a company with a
functional product may launch limited editions or promotional versions, which then have
short life cycles and unpredictable demand, making them innovative products.

The two types of products impose different costs on a supply chain. Thus, they
require different supply chain strategies. For functional products, physical costs—the costs
incurred in the production, distribution (transportation and warehousing), and storage of

2.3 Efficient or Responsive:
A Framework for Supply Chain Strategy

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 9

inventory—are the main consideration. To minimize these costs, an organization must
improve efficiency and will therefore gravitate toward a physically efficient supply chain
strategy.

For innovative products, market mediation costs dominate. These arise from demand
uncertainty and the subsequent mismatch of supply with demand, and they include the
costs of disposing of excess inventory, lost sales, and lost customer goodwill due to a
shortage or stockout. To reduce market mediation costs, an organization must improve
its responsiveness to fluctuations in demand and will thus choose a market responsive
supply chain strategy.

Table 1 compares the characteristics of physically efficient and market-responsive
supply chains. Since functional products have long life cycles, it is possible to forecast
their demand accurately. As a result, in physically efficient supply chains, production is
typically located in a low-cost location, such as in a foreign country or close to the supply
base, and is often outsourced to the most efficient or specialized suppliers. Transportation
is by low-cost means, such as sea routes, because inventory in the pipeline carries little
risk of obsolescence or demand uncertainty. Lean production methods are employed to
reduce inventory and capacity while increasing product availability. As a result of those
characteristics, physically efficient supply chains tend to be differentiated. The many
organizations in them share demand and production information with one another and
coordinate their decisions so that costs can be lowered throughout the supply chain.
Examples of products that have physically efficient supply chains include industrial
commodities such as chemicals, plastics, metals, and petroleum products, as well as
consumer packaged goods.

Table 1 Physically Efficient and Market-Responsive Supply Chain Attributes

Physically Efficient Market Responsive

Primary Purpose Meet predictable demand at lowest
cost

Minimize excess inventory and
stockouts by responding quickly to
unpredictable demand

Manufacturing
Focus

Achieve high efficiency Have excess capacity

Inventory
Strategy

Minimize inventory throughout the
chain

Deploy sufficient inventory to
respond to uncertainty

Lead-time Focus Reduce lead time as long as cost
remains low

Aggressively reduce lead time

Supply Chain
Coordination

Collaborate; centralize; share
information to cut costs

Achieve speed and flexibility

Product Design
Strategy

Maximize performance; minimize
cost

Invest in new product development
to improve effectiveness

Reprinted by permission of Harvard Business Review. Exhibit from Marshall L. Fisher, “What Is the Right Supply Chain for Your
Products?” Harvard Business Review (March–April 1997). Copyright © 1997 by the Harvard Business School Publishing Corporation;
all rights reserved.

The primary goal of a market-responsive supply chain is quickly reacting to changes
in demand, so short production lead times and flexibility are valuable capabilities. To
develop them, facilities are typically located close to the customer, excess capacity or
flexible capacity is built in so that production volume and mix can be changed quickly,

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 10

and the supply of raw material is ensured by investing in inventory. Firms in responsive
supply chains focus on reducing various components of lead time, such as in product
design, product launch, and replenishment. Inditex, a Spanish retail conglomerate that
owns the Zara clothing brand, is an example of a successful market-responsive firm. It
maintains tight control over lead times through its vertically integrated supply chain,
which allows it to take products from design to the store in only a few weeks. Another
example is Dell, which pioneered the direct-to-customer model in computer
manufacturing in order to reduce lead times.

The choice of supply chain strategy should inform an organization’s choice of
performance measures. As shown in Table 2, measures of cost, efficiency, and fulfillment
should be emphasized in physically efficient supply chains, whereas lead-time and
uncertainty-based measures are more appropriate for market-responsive supply chains. It
should be noted that market mediation costs, such as lost sales, are harder to measure
than physical costs. As a result, organizations tend to focus excessively on physical costs
and to drive toward efficiency in their supply chains regardless of their product
characteristics. This can result in a mismatch between supply chain characteristics and
business requirements.

Table 2 Choosing Measures to Gauge Supply Chain Performance

Performance Measure Physically Efficient
Supply Chain

Market-Responsive
Supply Chain

Production Cost Per Unit

þ

Logistics Cost Per Unit þ

Order Fill Rate þ

Capacity Utilization þ

Amount of Excess Inventory þ

Estimated Lost Sales þ

Various Lead Times:
1 from design to production
2 from production to launch
3 replenishment lead time

þ

Procter & Gamble discovered in the 1980s that even though consumer demand for
Pampers diapers showed little variation, there were huge fluctuations in the orders placed
by retail chains and wholesalers. Barilla SpA discovered a similar problem in the orders
for dry pasta received by its factories and distribution centers. At Hewlett-Packard,
retailers’ orders for printers were more variable than retail demand, and the variability in
orders for integrated circuits was even greater.

These three companies experienced a phenomenon known as the bullwhip effect, in
which the variability of demand increases as one moves upstream in a supply chain from
the retail customer to wholesalers, manufacturers, and suppliers. The fluctuations in retail

2.4 Improving Efficiency: The Bullwhip Effect

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 11

orders are larger than those in retail demand; the fluctuations in wholesale orders are
larger still, and so on.

Variance (Retail Demand) ≤ Variance (Retail Orders) ≤ Variance (Wholesale Orders)
≤ … ≤ Variance (Production)

Thus, demand information becomes increasingly distorted as it is passed along the
supply chain in the form of orders. The extent of the bullwhip effect at a given location
can be measured by the amplification factor, defined as the ratio of variance of orders to
variance of demand at that location.

Variance of orders placed by a locationAmplification Factor
Variance of demand received by that location

Values of this ratio greater than one denote amplification; values of less than one
denote attenuation. The higher the amplification, the more severe is the bullwhip effect.
Figure 4 illustrates the patterns in sales and orders that are commonly due to the
bullwhip effect.

Figure 4 Bullwhip Effect in Supply Chains

Source: V. Padmanabhan, Seungjin Whang, and Hau Lee, “Bullwhip Effect in Supply Chains,” Sloan Management Review 38, no. 3
(June 1997), Figure 1. Copyright © 1997 from MIT Sloan Management Review/Massachusetts Institute of Technology. All rights
reserved. Distributed by Tribune Media Services. Reprinted by permission.

The bullwhip effect is costly to all members of the supply chain but especially to
upstream members, which receive the most distorted demand information. Its
consequences are all-encompassing: they include excess inventory and capacity
investments, stockouts, overtime costs, poor demand forecasts, long lead times, and high
costs for corrections (such as expedited shipments). Thus, both the revenue and the costs
of each firm in the supply chain are adversely affected.

A firm seeking to mitigate the bullwhip effect cannot hope to do so by addressing its
consequences in isolation. Instead, it must confront the underlying causes and try to
achieve better coordination in its supply chain. Because of their far-reaching implications,
such initiatives generally require cross-functional teams and must be championed by
senior management.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 12

Four common factors in supply chains contribute to the bullwhip effect: demand
forecast updating, order batching, price fluctuations, and rationing and shortage gaming.3

Demand Forecast Updating
Each organization in a supply chain periodically observes demand (or procurement
orders) from its downstream customers. It uses this information as a signal to update its
forecast of future demand and to place procurement orders with suppliers. Those
suppliers, in turn, use those orders to update their forecasts of demand and place orders
with their suppliers. This is how noise in demand signals becomes amplified as it travels
upstream.

The degree of amplification depends on lead time and the forecasting method
employed. Hypothetically, if lead times were zero—and so information flows and
shipments from one stage of the supply chain to the next were instantaneous—then there
would be no bullwhip effect because managers would not need to update the demand
signals received from their customers. Instead, demand information would be
instantaneously relayed to the upstream locations in the supply chain.

In practice, however, a firm generally must project demand for a nonzero lead time.
This causes the bullwhip effect. For example, if there is a four-week lead time for a retailer
to receive new shipments from its supplier, then the retailer has to forecast its demand for
at least the next four weeks when placing an order today. The longer this lead time, the
longer is the forecast horizon, and the greater the amplification of the demand signal by
the retailer. Now consider the fate of the supplier who fulfills the retailer’s orders. If the
supplier also has a four-week lead time, then it must forecast the retailer’s orders for the
next four weeks, which means that it has to forecast consumer demand for about eight
weeks. Thus, lead times add up in the supply chain, leading to progressively noisier
forecasts based on progressively noisier input.

Any time-series forecasting method, such as exponential smoothing or moving
average, contributes to the bullwhip effect. However, the bullwhip effect can be worsened
when managers forecast manually, using their judgment to determine order quantities
instead of automated algorithms (such as exponential smoothing or moving average). In
doing so, they may overreact to changes in demand or may rely too heavily on recent
demand observations; this is called recency bias.

Order Batching
A company typically places replenishment orders with its suppliers less frequently than it
receives demand from its customers. It maintains inventory and thus places an order only
when the inventory runs low. This leads to ordering in batches. There are many economic
reasons for batching:

1 The company may follow a periodic inventory control system, so it may
place orders at fixed intervals (weekly or monthly) that coincide with its
planning cycle, whereas demand occurs continuously. (See Core Reading:
Managing Inventory [HBP No. 8016] for further detail on periodic inventory
control.)

2 Companies may seek to take advantage of economies of scale in ordering
costs and manufacturing setups. For example, the transportation cost per
unit when using a full truckload shipment is generally lower than when using
a less-than-full truckload shipment. Therefore, a buyer organization may

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 13

wait until it has enough accumulated order quantity to utilize a full truckload
shipment. The economic rationale for batching is explained by the economic
order quantity (EOQ) model. This model describes the total cost of fulfilling
demand per unit time as a sum of fixed ordering costs and variable inventory
holding costs. Those two cost components trade off against each other. As
the order batch size increases, fixed ordering cost decreases, but inventory
holding cost increases. Thus, the EOQ model states that this tradeoff
determines the order batch size that minimizes the total fulfillment cost.

3 Suppliers may impose minimum order quantity restrictions, compelling
their customers to order infrequently in large batches.

Order batching delays the propagation of demand signals in the supply chain. A
supplier receiving orders once a month receives no demand information for the rest of
the month. The supplier will have to forecast orders from its downstream customers for
longer time periods simply because those customers do not place frequent orders.
Therefore, the uncertainty faced by the supplier will be larger, contributing to the
bullwhip effect. Furthermore, if a product has a low demand rate, customers may place no
orders for several months and then unpredictably place a large order. Thus, the supplier is
forced to carry large amounts of inventory for long and unpredictable periods and may
even incur stockouts. The cost of the bullwhip effect in the supply chains for such
products will be large indeed.

Price Fluctuations
Suppose that the sales department of an organization offers price discounts to customers
in order to achieve sales targets and increase market share. This leads to a pattern in sales
called the hockey-stick effect, in which sales spike at the end of each month if sales
incentives are tied to monthly quotas, or at the end of each quarter if incentives are tied to
quarterly quotas.4 Even as the sales department achieves its targets, it induces volatility in
orders and makes it harder to fulfill demand, causing stockouts and further exacerbating
uncertainty in the supply chain. Thus, price discounts lead to a deterioration of the
performance of the supply chain and to costs on the organization’s manufacturing and
supply chain functions.

Rationing and Shortage Gaming
At the peak of the dot-com bubble, from 1999 to 2000, network-equipment customers,
anticipating shortages, placed orders for Cisco equipment that were significantly larger
than their actual needs. Cisco interpreted these orders as signals of rising demand. To
keep up with them, Cisco in turn placed big orders with suppliers of components, such as
chips and subassembly boards. When the bubble burst, Cisco’s customers canceled their
orders, and the company had to take an inventory write-off of $2.25 billion.5

Anticipated demand commonly exceeds manufacturing capacity during the launch of
a successful new product (e.g., Harry Potter books, a new gaming console from Microsoft
or Nintendo, a new and anticipated model of a luxury car) or when demand is increasing
and capacity expansion is costly and time-consuming. In such situations, manufacturers
have no alternative but to ration their production to their customers. Customers buy into
this game and exaggerate their needs in order to get a bigger allocation. Thus
manufacturers have difficulty determining the true needs of each customer and may
allocate too much product to customers with less demand and too little to those with high

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 14

demand. This, in turn, creates a feedback loop that exacerbates volatility in the supply
chain. Moreover, if the manufacturer ramps up capacity to respond to the large orders,
the capacity constraint is suddenly removed and orders drop precipitously. This cause of
the bullwhip effect, rationing and shortage gaming, leads to avoidable fluctuations in
upstream orders, capacity, and inventories, which are all expensive.

The four factors discussed above can be addressed by improving supply chain
coordination using three types of solutions, as summarized in Table 3: information
sharing, channel alignment, and operational efficiency. For instance, to mitigate the effect
of demand forecast updating, organizations in a supply chain should first and foremost
share demand and inventory information by setting up an electronic data interchange
(EDI). Information sharing reduces the information lead time in the supply chain and
enables each organization to plan according to end demand rather than orders placed by
organizations immediately downstream. However, EDI is just the foundation; it increases
transparency and discipline but doesn’t change the fact that organizations must still
respond to orders from downstream customers.

Table 3 Preventing Avoidable Fluctuations

In recent years, radio-frequency identification (RFID) has been increasingly used to
improve information richness, increase transparency, and reduce data errors in supply
chains. RFID tags attached to pallets (the unit of movement of goods in factories and
warehouses), case packs, and individual items can be scanned efficiently and cost-
effectively at various stages of the supply chain so that their exact location is known. For
example, a retailer would know how much inventory of different items is in shipment, a
manufacturer would know how much of its inventory is in a retailer’s backroom and how
much is on the selling floor, and so on. Manufacturers and retailers can then use such
information to anticipate future orders and plan their respective inventories to reduce the
bullwhip effect.

Supply chain organizations can realize considerable additional benefit by using
shared information to coordinate their forecasting, production, and stocking decisions.
Frameworks for such channel alignment include vendor managed inventory (VMI),

Information Sharing Channel Alignment Operational Efficiency

Demand
Forecast
Updating

Use electronic data
interchange (EDI)

Use point-of-sale data

Understand system
dynamics

Avoid multiple demand
forecasts

Make centralized ordering
decisions

Vendor-managed inventory
(VMI)

Discount for information
sharing

Consumer direct

Lead-time reduction

Echelon-based inventory
control

Order
Batching

EDI

Internet ordering

Mixed pallet shipments

Cross-docking

Logistics outsourcing

Reduction in fixed cost of
ordering by EDI

Price
Fluctuations

Continuous replenishment
program

Everyday low cost

Everyday low price

Activity based costing

Rationing and
Shortage
Gaming

Sharing sales, inventory,
and capacity data

Allocation based on past
sales

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 15

collaborative planning, forecasting, and replenishment (CPFR), and continuous
replenishment program (CRP). Those frameworks have been put to use by many large
organizations, including Campbell Soup, Nestlé, M&M, P&G, Scott Paper, and Unilever.
In VMI, a supplier has visibility and control over the inventory at the warehouses of its
downstream (retail) customer. The supplier decides periodically how much inventory to
replenish to these warehouses based on the rate of depletion. The downstream customer
does not need to place orders and the supplier does not need to forecast them. Instead, it
can integrate its production and downstream stocking decisions through echelon-based
inventory control. Unlike VMI, CPFR does not relinquish inventory control to the
supplier. Instead, it provides a model for sharing information about demand forecasts and
flow of goods across supply chain partners. The planning process is divided into common
steps, such as creating a business plan, generating sales forecasts, and generating orders.
All supply chain partners collaborate at each step of this process to make lock-step
decisions. CRP involves monitoring point-of-sale data continuously and replenishing
products only for the sold amount as needed in real time. Note that there are
commonalities across these frameworks. They seek to reveal information and synchronize
the actions of supply chain partners in order to reduce excess inventory and stockouts
throughout the supply chain.

Finally, since the amount of amplification caused by demand forecast updating
depends on lead time, reduction of lead time in the supply chain brings huge benefits to
the mitigation of bullwhip effect in the supply chain. This is accomplished by improving
operational efficiency in the supply chain, by, for instance, reducing ordering, production,
and shipment costs so that it becomes cost effective to order frequently in small
quantities.

A similar framework of methods can be used to mitigate the effect of order batching.
First, a supplier can improve its access to demand information through EDI so that it
does not have to wait for a downstream order to estimate demand. Instead, by
concurrently observing downstream demand and inventory levels, it can accurately
predict when the next downstream order will be placed and build inventory accordingly.
While this does not reduce order batching, it helps reduce uncertainty in planning.

Second, suppliers and buyers can use methods that make it economically feasible to
order in small batches. For instance, suppliers can set discounts for mixed pallet
shipments or an assortment of products that fill a truck rather than full-truck-load
shipments of single products. And they can outsource logistics to third-party providers
such as UPS and FedEx so that full shipments can be replaced by partially full shipments.

Finally, a supplier that produces slow-moving products (which have low demand
rates) and so must resort to order batching to turn a profit can focus on reducing the
fixed costs of ordering. Such a supplier may have a mismatch between its supply chain
design and the characteristics of demand for its products. It should consider locating its
facilities close to the customer, investing in flexible capacity, or implementing just-in-
time production. Those changes in supply chain design will enable the supplier to shift
production at no cost from one product to another so that producing small batches can be
cost effective.

Reducing price fluctuations is generally a matter of channel alignment. To reduce the
bullwhip effect caused by price fluctuations, organizations must coordinate internally
across functions. They need to modify incentives given by the sales department without
sacrificing the benefits of those incentives for the competitiveness of the organization.
Organizations also need to coordinate with customers so that they get the benefit of stable
and low prices without creating order variability. Methods such as everyday low cost

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 16

(EDLC), everyday low price (EDLP), and activity-based costing (ABC) are commonly
used for this purpose. These methods, along with VMI, CPFR, and CRP, are a part of a
larger initiative called Efficient Consumer Response (ECR), which focuses on the needs of
the consumer and seeks to optimize the entire supply chain to improve efficiency.

In the case of rationing and shortage gaming, manufacturers employ many
mechanisms to allocate scarce stock to customers: allocating capacity in proportion to
orders, in proportion to past sales and customer satisfaction, or on the basis of the
priority of customers. But many of those mechanisms do not solve the problem because
they do not induce buyers to truthfully report their requirements to the capacity-
constrained manufacturer.6 Manufacturers can eliminate gaming in shortage situations by
requiring customers to share sales and inventory data, imposing stricter return and order
cancellation policies, centralizing stocking decisions in the supply chain, or incentivizing
customers on the basis of their past ordering behavior.

As we have noted, products with short life cycles are increasingly common. An article of
fashion clothing, for example, typically has a selling season of two or three months but a
production lead time of nine to twelve months. Production orders must be placed well
before the start of the season to fulfill commitments through the complex supply chain.
Once the season starts, the firm has no recourse.

Two attributes of such products make them costly to manage: uncertain demand
forecasts and long lead times. It is difficult to forecast demand, and thus plan production,
for short-life-cycle products because there is typically no historical demand or sales data
available. In these instances, the time series forecasting models that are embedded in ERP
systems are not effective. Instead, managers must rely on their judgment and experience.
Such “judgmental forecasts” tend to be noisy, and so the firm loses revenue and incurs the
considerable cost of excess inventory. Long lead times exacerbate the problems of noisy
demand forecasts by making it harder for managers to react to changes in demand.
Managers of such products must focus on improving the speed of the supply chain—that
is, making it more responsive.

Managers can undertake many initiatives to develop responsive supply chains. They
can choose suppliers located close to the demand base that can provide shorter lead time
and integrate their processes better with the buyer firm. They can also coordinate
information sharing with suppliers, reserve production and distribution capacity in
advance, and pre-position raw materials so that production can be triggered at short
notice. Zara, which we mentioned earlier in discussing market-responsive supply chains,
provides a good example of such a supply chain. The company designs its products in-
house, maintains raw material inventories, produces in its own factories, ships all finished
merchandise to a central distribution facility, and then allocates merchandise to stores all
over the world several times a week. By tightly coordinating all these activities, Zara is
able to quickly respond to changes in demand and deliver “fast fashion.” Its supply chain
is so responsive that the total flow time of a product from design to store can be as little as
10 days.

While Zara’s supply chain design naturally facilitates responsiveness, many other
firms are entrenched in supply chains with long lead times. In such cases, responsiveness
can be developed in two ways: delayed differentiation or read-react capability.

2.5 Improving Responsiveness

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 17

Delayed Differentiation
Consider a firm producing a family of products that share parts. The production process
consists of common steps and points of differentiation. Common steps are those that are
undertaken for more than one product, whereas differentiation progressively determines
the identity of each product. Figure 5 depicts a manufacturing process consisting of
common stages of production and points of differentiation. The first differentiation
occurs after stage 1. The second differentiation occurs after stage 2 for products A and B,
and after stage 3 for products C and D.

Delayed differentiation, also known as postponement flexibility, postpones the point
of differentiation as late in the production-distribution supply chain as feasible. It reduces
the need for the firm to carry inventory of differentiated products subject to uncertain
demand. Instead, it carries inventory of undifferentiated products, called vanilla boxes,
which are converted into finished products late in the process when it is able to use more
accurate information about demand for each finished product. The firm has a shorter
effective lead time. The amount of safety stock of inventory needed by the firm decreases,
and costs of excess inventory and shortage decline.

Delayed differentiation capability can be developed by redesigning products to share
common modules, sequencing the production process so that points of differentiation
occur later in the process, and redesigning the supply chain so that differentiation tasks
can be pushed closer to the customer. A classic example of delayed differentiation is
provided by the manufacturing of knitwear, such as sweatshirts and T-shirts. Typically,
garments of different colors are produced by first dyeing yarn into various colors and
then knitting the yarn by a common process. By switching the sequence of dyeing and
knitting tasks, a firm can carry inventory of undyed rather than dyed garments and can
thus manage the uncertainty of demand for different colors with less stock.

Figure 5 A Manufacturing Process with Common Stages of Production and
Points of Differentiation

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 18

Read-React Capability
This capability seeks to reduce procurement lead times to such an extent that a firm can
utilize early demand signals to forecast demand and replenish merchandise in the middle
of the selling season or life cycle of a product. Figure 6 illustrates the timeline of activities
in a firm with read-react capability. The selling season is split into three parts. The firm
positions inventory for the first part, called the “read period,” in advance of the season by
relying on the forecasts of experts. Upon observing demand during this period, it updates
its demand forecast for the remaining season or product life cycle. It then places a
replenishment order, which arrives after a short lead time. The firm uses inventory from
the replenishment order to serve demand in the third part of the season.

Figure 6 Read-React Timeline

Read-react capability can be developed by reserving capacity with suppliers ahead of
time so that they will be able to produce the product on short notice, pre-positioning raw
materials at suppliers to cut down procurement lead time, and using algorithms to update
the demand forecast by observing initial demand during the read period. The production
capacity that is deployed during the middle of the selling season is called reactive
production capacity.

Read-react capability is used in many industries. A notable example is the skiwear
manufacturer Sport Obermeyer.7 Figure 7 illustrates the impact of read-react capability
on forecast accuracy at Sport Obermeyer. The top panel in the figure shows actual sales
for several items plotted against initial forecasts made ahead of the season. Note that the
forecasts have large errors. If Sport Obermeyer were to plan inventory for the entire
season based on these forecasts, it would bear considerable expense of excess inventory
and lost sales at the end of the season. The bottom panel shows forecasts made during the
season by extrapolating actual demand in the first 20% of the season. These forecasts are
remarkably more accurate. Thus, Sport Obermeyer developed reactive production
capacity so that it could take advantage of the more accurate in-season forecasts and thus
increase its sales revenue and profit.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 19

Figure 7 Effect of Read-React on Forecast Accuracy

Reprinted by permission of Harvard Business Review. Exhibit from Marshall L. Fisher, Janice H. Hammond, Walter R. Obermeyer,
and Ananth Raman, “Making Supply Meet Demand in an Uncertain World,” Harvard Business Review (May–June 1994). Copyright
© 1994 by the Harvard Business School Publishing Corporation; all rights reserved.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 20

Let’s illustrate the benefits of read-react capability through Interactive Illustration 1.
(We shall explain the computations for this interactive illustration later in this
discussion.) The interactive compares a firm that does not have read-react capability with
one that does. The former firm makes a single procurement decision before the start of
the selling season. The latter firm makes two procurement decisions: an initial buy before
the start of the selling season and a replenishment during the season after observing the
actual demand occurrence during the read period.

The selling price, procurement cost, and salvage value of leftover inventory can be
varied using the sliders in the interactive. We model demand using the normal probability
distribution.b Interactive Illustration 1 shows the mean and standard deviation of
demand for the read period and the react period. The demand during the react period is
correlated with the demand during the read period.

Interactive Illustration 1 Read-React

The firm that does not have read-react capability estimates the total demand for the
season. The mean of total demand for the season is the sum of the means of demand
during the read period and the react period. The standard deviation of the total demand
during the season depends on the standard deviations during the read period and the
react period, as well as on the correlation between them. For example, if the standard
deviation of read demand is 600, the standard deviation of react demand is 2,400, and the
correlation coefficient is 0.5, then the standard deviation of the demand for the entire
season will be the square root of (6002 + 2,4002 + 2 ∙ 0.5 ∙ 600 ∙ 2,400) = 2,750.

With this demand estimate, the nonread-react firm uses the newsvendor model to
decide its procurement quantity. In other words, the firm determines the optimal
inventory to buy in order to balance the costs of excess inventory and lost sales, which

b Actual computations will be more complex and will have to be done through simulation or
computational software packages.

Scan this QR code, click the image, or use this link to access the interactive illustration: bit.ly/hbsp2ukeAL8

https://s3.amazonaws.com/he-assets-prod/interactives/047_read_react/Launch.html

http://bit.ly/hbsp2ukeAL8

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 21

occur due to randomness of demand. The interactive shows the resulting procurement
quantity and the average profit that the firm can expect to make.

The read-react firm places an order at the start of the season to fulfill demand for the
read period. Unlike its nonread-react counterpart, it doesn’t have to be precise about
optimizing this inventory. On the contrary, it should order a little extra so that it does not
run out of stock in the first two weeks. This helps the firm satisfy customers and get a
good reading of demand. Moreover, its inventory risk is low because the inventory left
over after the first part can be sold off in the second part. After observing demand during
the read period, the firm updates its forecast and places a replenishment order according
to the newsvendor model. Let’s suppose for simplicity that the replenishment order
arrives the next day (it has zero lead time).

The interactive shows the resulting average profit and the average amount of
inventory bought under possible scenarios of demand for this firm. Observe that the read-
react firm always makes a higher profit than the nonread-react firm. Vary the parameters
of the model and explore their effect on the difference in profit. You will observe that the
higher the magnitude of the correlation coefficient between demand in the two periods,
the higher the percent increase in profit.

Now let us follow the details of the computations in this interactive illustration in
order to grasp the sources of increase in profit. Suppose that price = $10, procurement
cost = $5, and salvage value of leftover inventory = $4. For simplicity, let us suppose that
there are no markdowns or price changes in the middle of the season. Before the season
starts, the demand for this product is forecasted to be normally distributed with

mean =

10,000 and standard deviation = 2,750.

The newsvendor critical fractilec for the above values of price, cost, and salvage value
is (10–5)/(10–4) = 5/6. This fractile corresponds to a z-score of 0.967 from the standard
normal distribution. If the firm does not have read-react capability, it places a single
procurement order at the start of the season and does not plan to place a second order
midseason. According to the newsvendor formula, the order quantity that maximizes the
expected profit of the firm, given the above critical fractile and demand distribution, is
given by mean demand + z∙standard deviation of demand = 10,000 + 0.967∙2,750 = 12,660
units.

This gives the following performance characteristics (Numbers might not sum due to
rounding):

• Expected lost sales. The firm would not be able to meet the entire possible
range of demand because it carries limited inventory. If demand exceeds
12,660 units, the rest of the demand will be lost. For z = 0.967, the standard
normal loss function value is L(z) = 0.0887. Thus, the firm should expect to
lose sales of L(z)∙standard deviation = 0.0887∙2,750 = 243.9 units, on average,
due to demand uncertainty.
o Expected sales. The firm should expect, on average, to sell Mean

Demand – Expected Lost Sales = 10,000 – 243.9 = 9,756.1 units of the
product.

o Expected leftover inventory. The firm should expect that an inventory
of Q* – Expected Sales = 12,660 – 9,756.1 = 2,903.9 units will be left over
at the end of the season, on average.

c See Core Reading: Managing Inventory (HBP No. 8016) for an in-depth description of the newsvendor
model and the critical fractile.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 22

• Expected profit. These values will yield a total expected profit of Price ∙
Expected Sales + Salvage Value ∙ Expected Leftover Inventory – Cost ∙ Order
Quantity = $10 ∙ 9756.1 + 4 ∙ 2903.9 – 5 ∙ 12660 = $45,876.60.

Now suppose that the season is divided into two parts of two and eight weeks. Let X
denote the random demand for the first part and Y the random demand for the second
part. Suppose that the forecast of total demand is split as follows: X has mean 2,000 and
standard deviation 600, and Y has mean 8,000 and standard deviation 2,400. Historical
data about similar products sold in previous years tells the company that the demand
during the second part is correlated with the demand during the first part. That is, Y is
given by the following regression line estimated on historical data, with an R-square of
25%:

Y = 4,000 + 2∙X + random noise

This is equivalent to saying that X and Y follow a bivariate normal distribution with
correlation coefficient 0.5. Thus, after observing the first two weeks of demand, the firm
will know the value of X and can apply the above regression equation to forecast demand
for the rest of the season and order the optimal quantity according to the newsvendor
model.

The optimal expected profit for the firm in following the above two-part strategy
turns out to be $47,572, which represents a 3.7% improvement over the base case. This
increase represents gross profit, which will flow to the bottom line because none of the
fixed costs are affected. Since net profits in retailing are typically 1% to 5% of sales, this
increase is substantial.

This increase in profit stems from a simultaneous reduction in inventory and increase
in sales:

1 Splitting the selling season into two parts lowers the demand uncertainty in
each one. Thus, the firm needs less safety stock and less total inventory.
Indeed, the amount of merchandise ordered in the base case was 12,660,
whereas the total amount of merchandise ordered in the split case summed
over the two periods is an average of 12,163. This decreases the cost of excess
inventory.

2 The order the firm places for the second part of the season enables it to catch
up to demand volatility in the first part. If demand was high, then more
merchandise can be produced. Otherwise, less production is needed, and the
firm can instead focus on selling the available inventory. This ability to
adjust to demand volatility increases revenues. In our example, the total
expected sales in the base case was 9,830, whereas the total expected sales in
the split case is 9,956.

3 Demand from the early part of the season provides a more accurate forecast
of demand for the rest of the season. Thus, the firm can capture the demand
upside when the product turns out to be hot.

In this example, we used a conservative value of 0.5 for the correlation coefficient ρ
between demand during the two parts. You observed the effect of varying ρ on the
average profit through Interactive Illustration 1. In Figure 8, we depict this effect by
varying ρ while keeping X and Y fixed. The figure shows the percentage increase in profit
obtained from read-react capability compared to the base case for different values of ρ.
Observe that there is an increase in profit even when ρ = 0—that is, when the demand
during the first period conveys no information about demand during the second period.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 23

This increase is due to the first two reasons described above—that splitting the season
into two parts reduces inventory requirements and enables the firm to respond to
demand volatility. As ρ increases, the third reason begins to make a difference because the
value of forecast updating becomes more and more salient, resulting in larger increases in
profit.

Figure 8 Profit Increase Due to Implementation of Read-React Capability

It is useful to note that the read-react capability translates into not only higher
expected profit but also lower working capital needs. That’s because the firm needs less
inventory and thus has better cash flow. Moreover, since inventory levels are reduced, the
firm can provide higher variety and higher service levels to customers without investing
in additional warehousing or retail space.

To illustrate the benefits of the read-react capability, Interactive Illustration 1 has
not included real-world complications and circumstances. For an effective real-life
implementation, our example must be refined to incorporate features such as the
following:

• Orders placed midseason may not arrive immediately. Instead, the
replenishment quantity will become available to meet demand only after the
lead time has transpired and the shipment has been received. Thus, the
selling season must be divided into three parts, as shown in Figure 6. When
determining the replenishment order quantity after the read period, we must
account for the further depletion of stock that will take place before the order
is received.

• The supplier may charge a higher price to produce and ship products on
short notice in the middle of the season. This would somewhat erode the
benefit of the read-react capability. The initial and replenishment order
quantities must be adjusted to minimize the adverse impact of this increase
in price. The supplier would be economically justified to charge a higher
price because, although the retailer’s risk decreases when it has a responsive
supply chain, the supplier’s risk increases. For example, after the recession of
2007 to 2009, apparel retailers pressured their suppliers to cut lead times so
that the retailers could order closer to the season and thus lower their risk of
unsold inventory. Suppliers naturally resisted this pressure because of the

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 24

difficulty of scheduling shipment containers, labor, and factories at the last
minute and the increased risk of demand uncertainty.8

• Finally, when using historical data to estimate the regression equation shown
above, the firm must control for other factors that influence demand, such as
price changes during the season, promotions, and competition. Those
variables can change from one year to the next, so we must include variables
other than the read-period demand in the regression equation. Doing so will
improve the accuracy of the demand forecast obtained from the read period.

So far in this reading, we have implicitly assumed that all organizations in a supply chain
share the objective of increasing the total profit of the supply chain. However, the costs
and benefits of improving efficiency or responsiveness can accrue disproportionately. For
instance, the cost of reducing the bullwhip effect or making the supply chain more
responsive may be borne by one organization, but the benefit may accrue to another. In
reality, organizations have different and often conflicting objectives as they seek to
maximize their own profits. As a result, buyer-supplier relationships in supply chains can
be adversarial rather than collaborative.

The richness of practical considerations in supply chain coordination is exemplified
by a case study of how Procter & Gamble improved its relationship with Walmart.9
Consider the following quote from Sam Walton, Walmart’s founder, to Lou Pritchett,
Vice President for Sales at P&G:

Your company is just the hardest company we do business with. It just
seems to me that if you thought of my stores as an extension of your
company, we would have a totally different business relationship than
we have today.10

This conversation led to multiple initiatives that increased coordination between the
companies and their joint business over the subsequent decades. These initiatives
addressed not only cross-firm obligations but also within-firm incentive structures. They
involved setting up processes for periodically assessing the impact of business conditions
and technological changes on incentives in order to avoid misalignment and to improve
trust among supply chain partners.

Misalignment of incentives in a supply chain can be traced to three possible causes.11
The first is hidden action. Organizations in the supply chain can influence demand
through, for example, customer service, presentation of products, and advertising, but
organizations often cannot observe one another’s level of effort. If one organization in the
supply chain (say, the buyer) can make an effort to increase demand, coordination
becomes challenging because the cost of the effort is borne by that organization but the
benefit accrues to both the buyer and the supplier. If the effort is visible to both
organizations or can be verified after the fact, then they can share the cost. But if the effort
is not visible, then one organization does not know if the others are behaving in
everyone’s best interest.

The second is hidden information about costs, demand, capacities, and competitive
structure. Supply chain partners hide their information from one another because of a
lack of trust and bargaining games. Such cross-company problems are difficult to detect

2.6 Alignment of Incentives

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 25

because of culture, organizational structure, personalities, and even history. Hidden
information makes it impossible to design incentives optimally.

The third is badly designed incentives. In practice, firms set incentives for their
suppliers and customers on the basis of sales revenue, cost, profits, inventory shrinkage,
and so on. Too much or too little emphasis on any one variable can lead to badly designed
incentives and erosion of profit.

To align incentives, managers should first recognize how their suppliers’ and
customers’ decisions are affected by the incentives of their buyers and suppliers. If there is
indeed a problem, they should determine which of the three issues discussed above is at
its root. Hidden information, for instance, can be revealed by capturing data on relevant
variables and incorporating that data into performance evaluation processes. It can also
be revealed through various intermediaries; for example, third parties collect and validate
sales data, which then enables a manufacturer to incentivize a retailer based on sales
revenue.

The occurrence of hidden action and hidden information is illustrated by a practice
called “markdown money,” used by department store chains to share their risk of unsold
inventory with clothing suppliers. The chain buys products from the supplier at a fixed
wholesale price and sells them in its stores at a fixed list price. When the chain marks
down a product below list price, it charges a fraction of the markdown amount (called
chargeback) to the supplier. To justify these charges, department stores must maintain
detailed records of when the product was sold, at what price, and what deductions were
charged from the supplier. In the absence of such records, the supplier’s share of
markdowns cannot be determined because the actions of the department store are not
visible to the supplier. This can lead to a situation like the one we saw in May 2005 when
several clothing makers sued department store chains, including Saks Fifth Avenue and
Dillard’s, for withholding payments for clothes shipped and for deducting markdown
money from payments without authorization and without proper recordkeeping. To
avoid such conflicts, retailers and suppliers must work closely with one another to
determine their terms of trade as well as the mechanism by which compliance will be
established.12

One effective way to rectify badly designed incentives is to rewrite the contracts that
specify the decision rights for organizations in a supply chain. For example, a contract
may specify that the supplier firm decides the final selling price of the product, whereas
the buyer firm decides the quantity of inventory to be carried in retail stores. Contracts set
incentives for the stakeholders, such as transfer payments, prices for goods bought and
sold, and penalties for nonfulfillment of contractual duties. For example, the seller may be
held liable for a penalty if it does not meet the quantity, the quality, or the delivery
schedule for an order placed by the buyer. Contracts specify how merchandise will be
displayed in a retail store (if it is an end product), if unsold merchandise can be returned
to the supplier, and what compensation will be provided for it. They specify how the costs
of advertising and promotion will be shared between the buyer and seller. They also
describe what kind of monitoring will be conducted by stakeholders or by a third party to
verify fulfillment of the terms of the contract. One method of monitoring is by buyers and
sellers sharing demand, sales, or inventory information in order to increase transparency.
Thus, contracts determine the extent of coordination in a supply chain, the sharing of
risks and rewards, and collaboration in efforts to improve efficiency, quality, or other
performance goals.

From the perspective of an organization in a supply chain, contracts serve two broad
purposes. First, they determine the organization’s profit and risk. Second, they determine

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 26

whether the incentives of other organizations in the supply chain are aligned with it. If a
contract is not designed well, these two objectives would be in conflict with each other,
which could hurt the performance of the entire supply chain. That is, the higher your
share of profits, the less the decisions of the other organizations in the supply chain would
be aligned with your interests. To maximize the profit of the entire supply chain, it is not
sufficient that each organization seeks to maximize its own profit. Instead, the profits of
each can be improved only if the incentives of all are aligned and contractual terms are
chosen properly.

Let’s explore the implications of contract design on the alignment of incentives in a
supply chain through a simple hypothetical example of contracts between a single buyer
and a single supplier.

Suppose that ColorCraft is a producer of artistic greeting cards in a small town in
upstate New York. The company uses a special papermaking process with a long
production lead time. Cards for a holiday season must be designed and ordered weeks in
advance. Each card has a variable production cost of $1.50 and sells for $5, and unsold
cards have no residual value. Using historical data, the company forecasts that demand
for its greeting cards in the coming holiday season will be normally distributed with a
mean of 5,000 and standard deviation of 1,500 cards.

Ms. Marks, the owner of ColorCraft, has been running a vertically integrated
operation, making and selling cards from her shop. This year, she is interested in selling
through a retailer so that she can focus her staff on production quality. Let’s compare
these two options to determine the best one for Ms. Marks.

Vertically integrated supply chain: Based on tools provided by a local microbusiness
MBA student club, she uses the newsvendor model to determine the optimal inventory to
maximize her expected profit (Numbers might not sum due to rounding):13

• The newsvendor critical fractile for her price and cost values is (5 – 1.5)/5 =
0.7.

• This fractile corresponds to a z-score of 0.5244 from the standard normal
distribution.

• Thus, the optimal amount of inventory that she would produce for this
season is Q* = Mean Demand + z ∙ Standard Deviation of Demand = 5,000 +
0.5244∙1,500 = 5,787 cards.

• Her expected performance metrics will be as follows:
o Expected lost sales. For z = 0.5244, the standard normal loss function

value is L(z) = 0.1904. Thus, she should expect to lose sales of L(z) ∙
Standard Deviation = 0.1904∙1,500 = 285.6 cards, on average, due to
demand uncertainty.

o Expected sales. She should expect to sell Mean Demand – Expected Lost
Sales = 5,000 – 285.6 = 4,714.4 cards on average.

o Expected leftover inventory. She should expect that an inventory of Q*
– Expected Sales = 5,787 – 4,714.4 = 1,072.6 will be left over at the end of
the season on average.

o Expected profit. Her total expected profit will be Price∙Expected Sales –
Cost ∙ Inventory Level = $5 ∙ 4,714.4 – 1.5 ∙ 5,787 = $14,892.

Differentiated supply chain: Ms. Marks sells greeting cards to a local arts and crafts
retailer at a wholesale price of $3.50 each, and the retailer then sells them to customers for
$5 each. The retailer has the same demand forecast and decides ahead of the season how

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 27

many greeting cards to procure in order to maximize its own expected profit. Any leftover
cards have no residual value. This type of contract is called the wholesale price contract.

Let’s apply the same method we used for the centralized chain to assess the
performance of this decentralized chain (Numbers might not sum due to rounding):

• The newsvendor critical fractile for the retailer is (5 – 3.5)/5 = 0.3.
• This fractile corresponds to a z-score of – 0.5244 from the standard normal

distribution.
• Thus, the optimal amount of inventory that the retailer would order from

Ms. Marks for this season is Q* = Mean Demand + z ∙ Standard Deviation of
Demand = 5000 – 0.5244 ∙ 1,500 = 4,213 cards.

• The expected performance metrics for Ms. Marks and for the retailer will be
as follows:
o Ms. Marks makes a profit of $(3.50 – 1.50) ∙ 4213 = $8,426 because she

produces and sells 4,213 cards for $3.50 each and has a variable
production cost of $1.50 each.

o The retailer buys 4,213 cards but faces uncertain demand. We need to
apply formulas from the newsvendor model to calculate its expected
profit:
 Expected lost sales. For z = – 0.5244, the standard normal loss

function value is L(z) = 0.7148. Thus, the retailer should expect
to lose sales of L(z) ∙ Standard Deviation = 0.7148∙1,500 =
1,072.2 cards on average.

 Expected sales. The retailer should expect to sell Mean Demand
– Expected Lost Sales = 5,000 – 1,072.2 = 3,927.8 cards on
average.

 Expected leftover inventory. The retailer should expect that an
inventory of Q* – Expected Sales = 4,213 – 3,927.8 = 285.2 will
be left over at the end of the season on average.

 The expected profit of the retailer will be Price∙Expected Sales –
Cost ∙ Inventory Level = $5∙3,927.8 – 3.5∙4,213 = $4,894.

o Total profit of the supply chain will be equal to $(8,426 + 4,894) =
$13,320.

Observe that the decentralized supply chain stocks fewer greeting cards than the
centralized supply chain because the retailer’s risk-return trade-off is worse than Ms.
Marks’s in the centralized supply chain. The wholesale price contract has transferred the
entire risk of demand uncertainty to the retailer but not the entire profit. In particular, the
retailer loses $3.50 on each card unsold and makes a profit of $1.50 on each card sold,
whereas Ms. Marks was losing $1.50 on each card unsold and making a profit of $3.50 on
each card sold.

The stocking quantity in the centralized supply chain is called the first best solution
because it yields the highest possible expected profit. The decentralized supply chain
makes lower total profit than the centralized supply chain. This phenomenon, in which
the profit margin is split into two parts in the decentralized chain and each party tries to
maximize its own profit, is called double marginalization.

Is there a particular wholesale price that would maximize the expected profit for
ColorCraft in the decentralized supply chain? The answer is, “Yes,” as shown in Figure 9.
As the wholesale price increases, Ms. Marks makes a higher profit on every unit sold. But

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 28

the retailer orders progressively fewer units because its margin shrinks (Figure 10). The
net outcome of these two opposing forces is that there is an optimal wholesale price that
maximizes the expected profit for ColorCraft. Figure 9 shows that the optimal wholesale
price for Ms. Marks is about $4.20 per card.

Figure 9 Maximizing Profit in a Decentralized Supply Chain

Figure 9 also shows that the total profit of the decentralized supply chain decreases as
the wholesale price increases. Recall that the supply chain profit under the first best
solution was $14,892, which occurs when the wholesale price is exactly equal to
ColorCraft’s production cost, because it induces the retailer to order the first best
inventory quantity. As the wholesale price increases, the retailer orders less. Thus, the
supply chain profit decreases. The supply chain profit at a wholesale price of $4.20 is
$11,648. Figure 10 shows how the inventory stocking quantity ordered by the retailer
decreases in the wholesale price.

Figure 10 Inventory Stocking Quantity vs. Wholesale Price

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 29

The incentives of Ms. Marks and the retailer can be aligned by redesigning the
contract between them to eliminate double marginalization and achieve the first best total
expected profit. Table 4 describes the characteristics of some common contract types.
Any of these except the wholesale price contract can coordinate the ColorCraft supply
chain. But let’s consider how a buyback contract would work.

Table 4 Contract Characteristics

Contract
Type

Description Characteristics
Wholesale
Price
Contract

Supplier (upstream firm) offers a fixed
wholesale price w to retailer
(downstream firm).

Risk of demand uncertainty is borne
by retailer.

Simplest contract type; lowest
administration cost.

Buyback
Contract

Supplier sells each unit to the retailer
at a fixed wholesale price w. Retailer
returns unsold units to the supplier
and receives a buyback price b for
each unsold unit.

Risk of demand uncertainty is shared.

Used in book publishing and apparel
retailing industries.

It is not necessary that unsold units be
returned to supplier. Retailer may
salvage them and share the cost with
the supplier.

Revenue
Sharing
Contract

Supplier sells each unit to the retailer
at a fixed wholesale price w. Retailer
gives a fixed fraction p of the total
revenue to the supplier.

Risk of demand uncertainty is shared.

Used for contracts between movie
studios and rental firms in the video
rental industry.

Quantity
Flexibility
Contract

Supplier sells each unit to the retailer
at a fixed wholesale price w. Supplier
compensates the retailer for all its
losses on unsold inventory up to an
upper limit.

Retailer is fully protected from the risk
of demand uncertainty up to a limit.

Retailer bears the risk of demand
uncertainty above that limit.

Sales
Rebate
Contract

Supplier sells each unit to the retailer
at a fixed wholesale price w. Supplier
gives a rebate r to the retailer for each
unit sold above a threshold t.

Retailer bears a higher proportion of
the risk of demand uncertainty for
demand below the threshold than for
demand above the threshold.

Useful when retailer can exert effort
to increase demand.

Quantity
Discount
Contract

Supplier offers the retailer a wholesale
price that is decreasing in the number
of units ordered by the retailer.

Retailer bears the risk of demand
uncertainty.

Cost of administering the contract is
low.

Suppose that Ms. Marks offers to buy back unsold cards from the retailer for $2.86
each. The cost of production, wholesale price, and selling price are the same as before.
The buyback price transfers a part of the risk of unsold inventory from the retailer to Ms.
Marks, reducing the cost of unsold cards for the retailer. Thus, the retailer’s optimal order
quantity increases. In fact, we have set the buyback price in such a way that the
newsvendor critical fractile for the retailer becomes (5 – 3.50)/(5 – 2.86) = 0.7, the same as

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 30

that for the centralized supply chain. Therefore, the retailer’s optimal order quantity is
5,787 units.

Repeating the same computations as above, the retailer’s expected profit is $6,382,
Ms. Marks’s profit is $8,510, and the total expected profit of the decentralized supply
chain is $14,892. Thus, both parties’ expected profits increase, and the supply chain
achieves the first best order quantity and expected profit. We say that this supply chain is
coordinated.

Many combinations of wholesale price and buyback price can achieve coordination.
For example, if the wholesale price is $3.00 and the buyback price is $2.14, then the
retailer’s critical fractile is again 0.7, which leads to the first best order quantity and first
best total supply chain profit. In fact, for any wholesale price (w) between $1.50 and $5.00,
a buyback price (b) achieves coordination if it satisfies the following condition:

5 1.50.7
5 0.7

w wb
b

− −= ⇒ =
−

Figure 11 shows combinations of buyback and wholesale prices. Although they
achieve coordination (that is, they achieve 100% efficiency), they split the pie differently
between Ms. Marks and the retailer. The higher the wholesale price, the greater the share
of supply chain profits that accrues to Ms. Marks. Figure 12 illustrates this effect. She and
the retailer may bargain with each other on how to split the pie.

Figure 11 Optimal Buyback Price as a Function of Wholesale Price

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 31

Figure 12 Expected Profit as a Function of a Wholesale Price Under
Coordinating Buyback Contracts

Interactive Illustration 2 enables you to see the effect of different choices of
wholesale price and buyback price on the retailer’s inventory order quantity, expected
sales, and split of profits between the supplier and retailer. First set the buyback price to
zero in order to mimic the wholesale price contract. Vary the wholesale price and observe
the effect on the order quantity and profits. Then fix the wholesale price to any value and
vary the buyback price to see the effect on the order quantity and the price. Note how
there are many combinations of wholesale price and buyback price that coordinate the
channel, but allow profits to be split in different proportions across the supplier and the
retailer.

Buyback contracts are used in many settings. For example, luxury goods
manufacturers may prefer unsold merchandise to be returned rather than sold at a
discount so that they control pricing and brand. Book publishers take back unsold
merchandise so that it can be reallocated to other retailers or sold at a future date.
Buyback doesn’t necessarily have to involve the return of merchandise to the supplier.
The practice of “markdown money” described in Section 2.5 is also equivalent to a
buyback contract. In this practice, excess inventory is marked down and sold by the
retailer, but the cost of the markdown is shared with the supplier.

The above example shows how a poor choice of contract or price can reduce the
profits of both ColorCraft and the retailer. By choosing the buyback contract and setting
prices appropriately, it’s possible to coordinate ColorCraft’s supply chain. In practice,
contract design can be more complex because different firms may not agree on the
forecast of demand, there is competition, prices vary over time, and firms engage in sales
promotion or advertising to increase demand. The performance of the contracts listed in
Table 4 is affected by these considerations. Moreover we must keep in mind that
incentives can be misaligned for reasons other than contract design, as we discussed
earlier. It’s equally important to address hidden information and hidden action.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 32

Interactive Illustration 2 Buyback Pricing

The previous sections of this reading have looked at the decisions managers face as they
manage supply chains that already exist. We now turn to the decisions involved in supply
chain design, which involve the elements of physical infrastructure, or footprint, we
discussed in Section 2.2.

Degree of Proximity to Customers
As they establish their own facilities or choose external supply chain partners, firms
commonly must choose between locating close to the customer and farther from the
customer—in a foreign country, perhaps. Proximity to the customer shortens lead time,
which improves responsiveness and reduces inventory holding costs. But it often results
in higher production costs because it limits a firm’s sources of supply.

When proximity to the customer is not essential, the firm can choose a location that
provides a lower production cost but may entail a longer lead time and less
responsiveness. So, the location decision depends on differences in production costs and
lead time and the extent of demand uncertainty. The following example illustrates the
trade-off among these parameters.

Suppose that the per-unit cost for domestic production is cd and for production in a
foreign country is cf, with cd > cf. The replenishment lead time is Ld weeks for the domestic
location and Lf weeks for the foreign location, Ld < Lf. The firm follows a weekly

2.7 Supply Chain Design

Scan this QR code, click the image, or use this link to access the interactive illustration: bit.ly/hbsp2unKwOL

https://s3.amazonaws.com/he-assets-prod/interactives/014_buyback_pricing/Launch.html

http://bit.ly/hbsp2unKwOL

https://s3.amazonaws.com/he-assets-prod/interactives/014_buyback_pricing/Launch.html





  

Ld
Lf

  

Scan this QR code, click the image, or use this link to access the interactive illustration: bit.ly/hbsp2pHNTLD

https://s3.amazonaws.com/he-assets-prod/interactives/035_holding_costs_local_vs_faraway/Launch.html

http://bit.ly/hbsp2pHNTLD

https://s3.amazonaws.com/he-assets-prod/interactives/035_holding_costs_local_vs_faraway/Launch.html

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 34

locations is low, if demand uncertainty, σ, is high, if the inventory holding cost, h, is high,
or if the targeted service level, z, is high. Interactive Illustration 4 offers an intuitive way
to explore how holding costs, the cost of production, the in-stock rate, and demand (and
variance in demand) affect the decision to produce in a domestic or foreign location.
Observe from this interactive that for each combination of costs, the sourcing decision
depends on the domestic and foreign lead times.

Interactive Illustration 4 When to Produce in a Foreign Location

Interactive Illustration 5 shows the computation of total costs that are involved in
the comparison of domestic and foreign sourcing. It fixes the mean weekly demand and
the domestic lead time, and allows you to see the cost effect of changing any of the
remaining parameters. Besides procurement cost and holding cost, we have also included
transportation cost, which is often expressed as a percent of procurement cost. Therefore,
varying the transportation cost has the same type of effect as varying procurement cost.

Scan this QR code, click the image, or use this link to access the interactive illustration: bit.ly/hbsp2IV9AQp

https://s3.amazonaws.com/he-assets-prod/interactives/036_when_to_produce_faraway/Launch.html

http://bit.ly/hbsp2IV9AQp

https://s3.amazonaws.com/he-assets-prod/interactives/036_when_to_produce_faraway/Launch.html

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 35

Interactive Illustration 5 Domestic vs. Foreign Sourcing

The above trade-off is modulated by additional factors, such as supply chain risk. For
example, domestic production becomes more attractive in the following situations:

• When the exchange rate is volatile and the cost attractiveness of a foreign
sourcing facility is lower.

• When transportation cost rises or becomes more volatile. In recent years, the
cost of fuel has risen; as a result, transportation has become more expensive,
which has made domestic production more attractive.

• When products require a great deal of customization or have a significant
service component.

• When a firm wants to maintain control over its intellectual property.
To return to an earlier example, American Apparel finds it beneficial to produce

domestically because it focuses primarily on knitwear, which has a highly automated
manufacturing process that can be located in Los Angeles despite high labor costs. In
contrast, Forever 21 is able to provide a broad assortment of labor-intensive woven
garments, such as dress shirts and cashmeres, by locating in low-cost countries.

During the 1990s, many firms sought low-cost production locations in emerging
economies such as China. While this trend of offshoring continued into the 2000s, it
slowed significantly because of the rising cost of labor in China, higher transportation
costs, and increases in customization requirements in many industries. This resulted in
reshoring by firms that sought locations closer to their customers. Now, as demand grows
worldwide, many firms are deploying factories in emerging markets as well as in
developed countries to serve local demand in each market.

Scan this QR code, click the image, or use this link to access the interactive illustration: bit.ly/hbsp2IXu8YA

https://s3.amazonaws.com/he-assets-prod/interactives/020_local_vs/Launch.html

http://bit.ly/hbsp2IXu8YA

https://s3.amazonaws.com/he-assets-prod/interactives/020_local_vs/Launch.html

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 36

Degree of Centralization
This decision regarding degree of centralization will determine whether to have many
small facilities or one large one. A brick-and-mortar retail chain has hundreds of stores
spread throughout its market to serve customers in different regions. But the Internet
retailer Amazon.com had in its early years a single distribution center to fulfill demand
received through its website from all over the United States. A single, large location offers
benefits of economies of scale from two sources: lower overhead costs, and the pooling of
demand uncertainty across many locations. In 1979, Gary Eppen termed the second
source of benefit statistical economies of scale. 14

To illustrate this, suppose that a firm serves demand in N identical regions through a
facility in each location. Each region has normally distributed demand with mean μ and
standard deviation σ. The firm has identical costs of excess inventory or shortage at each
facility and thus wishes to provide the same in-stock rate.e The total inventory carried by
the firm is

( )μ σ μ σ+ = +N z N Nz

where z is the standard normal variable corresponding to the firm’s target in-stock rate.
Now suppose that the firm decides to carry inventory at a single centralized location,

similar to Amazon.com, and serve demand in all N regions from that location. To keep
things simple, suppose that demand is independent across the N regions—that is, there is
zero correlation between the demand in any two regions. (We will later explore the effect
of correlation through interactive illustrations.) The total demand at the centralized
location has

mean =

standard deviation =

μ
σ

This tells us that the total inventory carried by the firm at the centralized location is

N z Nμ σ+

Note that the effect of demand uncertainty now grows in the square root of the
number of locations, N, whereas it grew linearly in N when the firm had many locations.
Thus, aggregating demand at a central location enables the firm to reduce the cost of
demand uncertainty. This statistical economy of scale can be substantial in many
situations. It enables Amazon.com to sell slow-moving items whose demand is so small
and uncertain that they could not be sold profitably in a brick-and-mortar chain.

Interactive Illustration 6 enables you to visualize our comparison between
decentralized and centralized supply chains. Mean demand across the entire geographical
region is fixed. Vary the number of facilities, N, used to serve this demand. What effect
does this have on the total inventory required? In a similar way, vary the standard
deviation of demand and the in-stock rate to see how the difference in inventories

e In-stock rate is the probability that the entirety of a customer’s request can be immediately fulfilled
from stock. Firms typically have a target in-stock rate that corresponds to their business strategy. For
example, a firm that seeks to deliver a very high level of service would have a target in-stock rate over
90%. On the other hand, a firm whose strategy is to deliver the lowest-cost service might target its in-
stock rate nearer 70%. In-stock rate is explained in more detail in Core Reading: Managing Inventory
(HBP No. 8016).

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 37

between the decentralized and centralized supply chains increases. Finally, the interactive
allows you to vary the degree to which demand is correlated across facilities. The less
positively correlated the demand, the greater is the benefit of centralization.

Interactive Illustration 6 Statistical Economies of Scale

The benefit of statistical economies of scale increases when there is a negative
correlation in demand across locations—that is, when high demand at one location is
likely to be offset by low demand at another. On the other hand, it decreases when
demand is positively correlated across locations. Interactive Illustration 7 allows you to
grasp easily the effect of the total inventory of correlations going negative. The
decentralized supply chain in this interactive has two facilities. Vary the correlation of
demand across these facilities to observe how the inventory requirement changes for
decentralized and centralized scenarios. Correlation affects the standard deviation of total
demand across the two facilities. Thus, it influences the inventory requirement under the
centralized scenario.

Scan this QR code, click the image, or use this link to access the interactive illustration: bit.ly/hbsp2DYwNxf

https://s3.amazonaws.com/he-assets-prod/interactives/038_stat_economies_of_scale_many/Launch.html

http://bit.ly/hbsp2DYwNxf

https://s3.amazonaws.com/he-assets-prod/interactives/038_stat_economies_of_scale_many/Launch.html

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 38

Interactive Illustration 7 Statistical Economies of Scale with Negative
Correlation

While centralization provides the advantages of statistical economies of scale and
reduced overheads, there are some costs that must be taken into account. First, the larger
the facility, the more complex it is to manage. This complexity adds costs that erode
economies of scale. Second, when a firm serves demand in a large region from just one
central location, its transportation costs can be prohibitive. Moreover, it may not be able
to respond quickly to customer requirements. Therefore, firms sometimes set up multiple
facilities as they expand. Retailers, for example, add warehouses and distribution centers
as their store network expands. Amazon.com grew from one fulfillment center in 1997 to
eight in 1999 and was estimated to have 60 fulfillment centers in 2010, 28 of them in the
United States. 15, 16

Degree of Flexibility
Automobile plants typically produce two or more models of cars on a single assembly
line. Netflix ships a DVD to a customer from a distant distribution center if the one
closest to the customer is out of stock. Amazon.com follows a similar rule for shipping
books and other products bought on its website. Large retailers, such as Nordstrom and
Gap, ship products from one store to another when a stockout occurs. In general, when
an organization has facilities or supply chain partners in many locations, it must decide
whether to dedicate each one to a particular product or customer region, or to develop the
flexibility to serve more than one product or region from each location.

The ability to meet a customer’s demand from multiple locations enables an
organization to manage demand uncertainty with less capacity. For instance, consider the
scenarios shown in Figures 13 and 14. The firm in this example manufactures two
products, A and B, in two plants, P1 and P2. P1 has capacity K1, and P2 has capacity K2.
A and B are substitutes; a customer will buy either A or B but not both (as with car
models).

Scan this QR code, click the image, or use this link to access the interactive illustration: bit.ly/hbsp2IXufmY

https://s3.amazonaws.com/he-assets-prod/interactives/039_stat_economies_of_scale_negative_corr/Launch.html

http://bit.ly/hbsp2IXufmY

https://s3.amazonaws.com/he-assets-prod/interactives/039_stat_economies_of_scale_negative_corr/Launch.html

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 39

Figure 13 Dedicated Supply Chains for Two Products

Figure 14 Flexible Supply Chains for Two Products

In Figure 13, P1 is dedicated to product A and P2 is dedicated to product B. In
Figure 14, both plants can produce both products. Figure 15 shows the combinations of
demand for products A and B that can be met in the two scenarios. In Figure 13, demand
for product A can be met up to K1 and for B up to K2. The resulting sales of the two
products are represented by the part of the graph shaded gray. In Figure 14, additional
demand for product A can be met from P2 whenever there is low demand for B but high
demand for A. Likewise, additional demand for product B can be met from P1. These
additional sales are shown by the parts of the graph shaded blue and green. Thus, the firm
can achieve higher sales with the same level of capacity when that capacity is flexible.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 40

Figure 15 How Flexibility Increases Capacity

Flexibility comes in several varieties. The above example illustrates capacity flexibility,
where one plant is able to produce more than one product type by incurring negligible
switching costs. If A and B were two customer regions rather than two products, and P1
and P2 were different sourcing locations that could serve both regions, then the firm
would have logistical flexibility, or dynamic routing, where the firm would choose when to
serve a customer region from location A or B depending on the availability of the product
at the two locations. A third type of flexibility is with respect to time. If a firm is able to
compress its lead time, it can respond to shocks in demand while carrying less inventory.
This type of flexibility, which we discussed in Section 2.4 is called read-react. A fourth
type, also described in Section 2.4, is delayed differentiation, or postponement, which
allows a firm to produce vanilla box products through common activities and to delay
differentiation into customer- or market-specific products as late as possible. This
capability requires a combination of lead-time reduction, capacity flexibility, and product
redesign. Finally, a firm may achieve flexibility in its supply base by nurturing a portfolio
of suppliers. This strategy of multisourcing is advantageous in reducing the risk of supply
disruptions or other uncertainties in product supply.

Flexibility is expensive. Depending on the type, it may require investments in the
design of products, in the technology used in production and warehousing facilities, in
transportation, and in cross-training so workers can switch efficiently from one product
to another. It may also require flexibility from suppliers so that different products and
components can be shipped to a facility depending on its production mix. Finally,
achieving flexibility may depend on soft infrastructure, such as scheduling systems that
enable a firm to change production and sourcing decisions as needed.

The good news is that a firm does not need all its resources to be fully flexible. In a
landmark research paper on capacity flexibility, William Jordan and Stephen Graves
showed that most of the benefit can be obtained by linking locations with products in a
chain so that each location can produce two products.17 Figure 16 depicts such a supply
network.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 41

Figure 16 A Shortcut to Capacity Flexibility

If a multinational corporation has the ability to switch production from one country
to another in response to fluctuations in exchange rates, prices, and labor costs, then this
flexibility can be valued as a real option on the assets of the firm. The firm can then get
more from maximizing its flexibility than from hedging its exchange rate risk through
financial contracts.18, 19

Another decision, besides the above, involved in supply chain design is the degree of
outsourcing, often called the make-buy decision. This involves determining whether to
produce in-house or to outsource production to a third-party supplier. It depends on cost
considerations and ease of coordination.f On the one hand, in-house production provides

• better integration between design and production,
• control over a centralized supply chain, and
• the ability to capture the profits of intermediaries.

On the other hand, outsourcing provides
• specialization and access to advanced technology for complex products,
• flexibility of product and volume, and
• greater variety at lower capital investment.

The above decisions establish the physical infrastructure of the supply chain. In order
to make these decisions, a firm must determine the attractiveness of potential locations
relative to their costs, risks, demand projections, and availability of supply. It must also
construct long-term projections of cost competitiveness and risks. To assess the value of
various kinds of flexibility, it should simulate uncertainty in demand and supply and
evaluate how flexibility will be deployed. These inputs can then be used to configure the
firm’s supply chain.

f See Core Curriculum: Strategic Sourcing (HBP No. 8037) for much more on this topic.




For the exclusive use of A. CAI, 2020.
This document is authorized for use only by AMANDA CAI in Supply Change Management IE-GY 7993 taught by THOMAS MAZZONE, NYU Tandon School of Engineering from Feb 2020 to
May 2020.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 43

that depend on those commodities. A survey of 469 experts in diverse areas conducted by
the World Economic Forum’s Risk Response Network identified 50 types of global risk,
classified into five categories: economic, environmental, geopolitical, societal, and
technological.

Figure 17 Relative Importance of Different Types of Global Risks, Identified
by the World Economic Forum in its 2012 Global Risks Survey

Source: World Economic Forum, Global Risks 2013, reports.weforum.org/global-risks-2012.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 44

In the past two decades, supply chains have become more efficient through
globalization, use of lean production principles, and specialization of tasks. This efficiency
has increased global wealth, but it has also increased the vulnerability of all organizations
in a supply chain. To exploit economies of scale, critical inputs to an industry are now
often produced in a single large facility, and transportation is often handled through a
single high-volume link, such as a specific sea route or set of ports. And to cut costs,
organizations have reduced redundancy, waste, and inventories. As a result of both
efficiency measures, the effects of a disruption due to natural disasters and global
economic conditions are felt by distant organizations.

Regardless of the cause, supply chain disruptions can be extremely expensive. They
can lead to cost escalation, loss of revenue, loss of future business, or even complete
shutdown. And for public companies, just the announcement of a supply-chain
disruption can lead immediately to large declines in stock price as well as in profits the
year of the announcement and beyond.22, 23

The robustness of an organization in dealing with supply chain risk depends on the
structure of its supply chain.g Let’s consider several characteristics of supply chains, the
risks associated with them, and ways to mitigate those risks.

1 Single sourcing and specialization. As we’ve noted, lean production and the
focus on efficiency has made supply chains more vulnerable to disruptions. To
assess this risk, organizations should first and foremost increase transparency
throughout the supply chain. After its engine supplier halted production, for
example, the snowblower manufacturer Ariens began conducting financial
reviews of all its suppliers and developing alternative sources.

Organizations can decrease their reliance on single sourcing by building
redundancy and flexibility into their supply chains. (We discussed types of
flexibility in supply chains in Section 2.6 of this reading.)

Some firms carry several months of inventory of important raw materials
and components to mitigate the risk of supply chain disruption. For example,
Emerson Electric carries seven to eight months of inventory of critical parts for
which the company does not have an alternative source. The company decided
on this amount using cost/benefit evaluations and its projection of how long it
would take to restore supply in the event of a disruption.

2 Nature of relationship with suppliers and customers. Organizations can
strengthen their relationships with suppliers and customers in order to develop
capabilities to recover quickly from a disruption.

Consider what happened to Toyota in February 1997 when the only
factory supplying brake fluid proportioning valves to Toyota’s 20 automobile
plants in Japan suffered a major fire. This forced Toyota to shut down
production in the plants, which operated on just-in-time inventories of about
four hours, and hundreds of tiered suppliers ground to a halt. However, the
plants reopened within two days of this accident, and Toyota recovered to full
production soon thereafter. This remarkable recovery was possible because a
large number of firms from both within and outside the Toyota group

g For instance, supply chain and transportation risk experts associated with the WEF prioritized factors
that increased the vulnerability of supply chain networks as: reliance on oil, availability of shared
data/information, fragmentation along the value chain, extensive subcontracting, and supplier visibility.
See “New Models for Addressing Supply Chain and Transportation Risk,” World Economic Forum,
2012.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 45

immediately responded in a self-organized effort. Within days, firms with no
prior experience with these valves began manufacturing them. Thus, the
Toyota group was able to minimize damage because of its long-term
cooperative relationship with suppliers.24

Consider also a fire in March 2000 at a Royal Philips Electronics radio
frequency chip manufacturing plant in Albuquerque, New Mexico. Although
plant personnel extinguished the fire within 10 minutes, cleanup took several
weeks and production of several million chips was affected. Mobile phone
manufacturers Nokia and Ericsson accounted for 40% of the plant’s shipments.
Nokia responded to the disruption by intensifying its communication with
Philips and setting up alternative sources of supply—a crisis response process
the company had established over several years. Ericsson, however, did not
perceive a need for stepped-up action. As a result of these responses, Nokia was
able to expand its market share and profits, whereas Ericsson reported a loss of
$200 million due to component shortages.25

3 Complexity of product design and the supply chain network. The design and
introduction of new products often require a complex network of specialized
suppliers. This network is hard to manage. It can be subject to unanticipated
disruptions and delays as well as to issues related to vendor compliance. Woes
faced by Boeing and Airbus, the two largest airplane manufacturers in the
world, exemplify this complexity and the importance of enhancing
transparency and anticipating uncertainties. For Boeing, the launch of its 787
airplane was delayed by three years because of an unanticipated industry-wide
shortage of aerospace fasteners.26 The manufacturers of these fasteners, which
constitute barely 3% of the value of an aircraft, had consolidated and cut
capacity because of a drop in aircraft demand after 9/11. When demand later
picked up, it created a bullwhip situation, and the manufacturers were slow to
ramp up production. They were unable to read demand signals accurately
because Boeing was using a new supply chain structure to design the aircraft,
and so demand came from many suppliers. And Boeing was unable to fully
assess the impact of this problem, leading to several delay announcements over
a period of more than two years. Thus a seemingly inconsequential and low-
cost item brought down an entire supply chain.

Around the same time, but for different reasons, Airbus faced problems in
the manufacture of the A380, whose size and passenger capacity required a
bottom-up evaluation of every aspect of aircraft and airport operations. Deep
coordination was needed among internal and external teams to ensure
readiness for the new airplane. But Airbus encountered problems in executing
such coordination, such as design and manufacturing issues in integrating
subassemblies produced by many factories dispersed throughout Europe. The
result was frequent delay announcements, an increase in production cost,
nonfulfillment penalties of several million dollars, and a significant loss of
shareholder value.27

Boeing and Airbus both have complex product designs and vast supply
chains. Companies in such situations need to collaborate closely with their
supply chain partners, conduct detailed mapping of risks, subject their supply
chains to stress tests, and apply large-scale scenario planning to assess the
impact of failures on the development and production schedules of new
products.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 46

4 KEY TERMS
Assembly Network: A supply chain in which the number of locations decreases as one
moves downstream. Each location assembles products from many suppliers, then fulfills
demand from a single downstream location.

Bullwhip Effect: The phenomenon by which the variance of demand increases as one
moves upstream in a supply chain.

Buyback Contract: A procurement contract between a buyer and a seller in which the
seller offers the product to the buyer at a fixed wholesale price and accepts returns of
unsold inventory at a buyback price. The buyback price is less than the wholesale price.

Centralized Supply Chain: A supply chain in which all decisions, including
procurement, production, and distribution, are made centrally.

Decentralized Supply Chain: A supply chain in which different organizations
independently make decisions for the activities they manage.

Differentiated Supply Chain: A supply chain consisting of many organizations that own
different stages of production and distribution.

Distribution Supply Chain: A supply chain in which the number of locations increases
as one moves downstream. Each location receives product from a single supplier, then
fulfills demand from many downstream locations.

Double Marginalization: The phenomenon by which profit margin is split between
buyer and seller organizations in a decentralized supply chain. Double marginalization
leads to a decline in the total supply chain profit when each organization tries to
maximize its own profit.

Make-Buy Decision: The choice between producing a product in-house and buying it
from an external supplier.

Multisourcing: Sourcing from a portfolio of suppliers with varying cost, quality, and
fulfillment capabilities. Multisourcing enables a firm to adjust procurement quantities
sourced from each supplier to manage uncertainty and reduce risk.

Postponement Flexibility: The capability by which an organization can delay the time of
differentiation of its product to be closer to the time the demand occurs.

Reactive Production Capacity: Production capacity that is deployed during the middle of
a selling season to replenish product with a short lead time in reaction to the demand
observed during the read period.

Sales & Operations Planning (S&OP): An integrated process involving all functions of
an organization to share forecasts, past performance, and cost information, and to use
this information to make plans for sales, production, procurement, inventory, new
product launch, and resulting financial goals.

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 47

Serial Supply Chain: A supply chain in which product flows in a single sequence through
locations that are arranged in series.

Statistical Economies of Scale: The reduction in the cost of managing uncertainty that
occurs when demand from multiple customer locations is pooled and served from a single
location.

Supply Chain Coordination: The alignment of decisions across different stages of a
supply chain in order to maximize its total profit. Coordination takes place through
centralization of decision making, sharing of information, and design of incentives.

Supply Chain Footprint: The location of the parts of a supply chain, such as factories,
warehouses, and retail stores.

Vanilla Boxes: Undifferentiated products that can be converted into finished products
late in the process when more accurate forecasts of demand are available.

Vertically Integrated Supply Chain: A supply chain in which all stages are owned by a
single organization.

Wholesale Price Contract: A procurement contract between a buyer and a seller in which
the seller offers the product to the buyer at a fixed wholesale price and does not accept
any returns.

5 ENDNOTES

1 “Fast Fashion’s Challenge: Making Money With ‘Made In The USA’.” http://www.npr.org/2013/03/
13/174199449/fast-fashions-challenge-making-money-with-made-in-the-usa.

2 Marshall L. Fisher, “What Is the Right Supply Chain for Your Products?” Harvard Business Review,
March/April 1997, 75:2, pp. 105–116. Reprint # 97205.

3 Hau Lee, V. Padmanabhan, and Seungjin Whang, “The Bullwhip Effect in Supply Chains,” Sloan
Management Review, Spring 1997, 38:3.
4 Fangruo Chen, “Sales-Force Incentives and Inventory Management,” Manufacturing & Service
Operations Management, Spring 2000, 2:2.
5 Mor Armony and Erica L. Plambeck, “The Impact of Duplicate Orders on Demand Estimation and
Capacity Investment,” Management Science, October 2005, 51:10.
6 Gérard P. Cachon and Martin A. Lariviere, “Capacity Choice and Allocation: Strategic Behavior and
Supply Chain Performance,” Management Science, August 1999, 45:8.
7 Marshall L. Fisher, Janice H. Hammond, Walter R. Obermeyer, Ananth Raman, “Making Supply Meet
Demand in an Uncertain World,” Harvard Business Review. May/Jun 94, 72:3, pp. 83–93. Reprint #
94302.

8 See “Tug-of-War in Apparel World,” Wall Street Journal, July 16, 2010. http://online.wsj.com/article/
SB10001424052748703722804575369392983459752.html.

9 James K. Sebenius and Ellen Knebel, “Tom Muccio: Negotiating the P&G Relationship with Wal-Mart
(A)” HBS No. 907-013 (Boston: Harvard Business School, 2010).
10 James K. Sebenius and Ellen Knebel, “Tom Muccio: Negotiating the P&G Relationship with Wal-Mart
(A)” HBS No. 907-013 (Boston: Harvard Business School, 2010).

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 48

11 V. G. Narayanan and Ananth Raman, “Aligning Incentives in Supply Chains,” Harvard Business
Review, Nov 2004, 82:11, pp. 94–102.
12 “Suppliers to Saks Now Want to See the Receipts,” New York Times, July 15, 2005;
http://select.nytimes.com/gst/abstract.html?res=F70616FF3B540C768DDDAE0894DD404482&fta=y&in
camp=archive:article_related&smid=pl-share; “Stores and Vendors Take Their Haggling Over Payment
to Court,” New York Times, May 17, 2005; http://www.nytimes.com/2005/05/17/business/
17markdown.html?pagewanted=all; “Clothier’s Suit Says Saks Abused Markdown Deductions,” New
York Times, May 18, 2005. http://www.nytimes.com/2005/05/18/business/18saks.html
13 See Core Reading: Inventory Management (HBP No. 8016) for a in-depth description of the
newsvendor model and the critical fractile.
14 Gary D. Eppen, “The Effects of Centralization on Expected Costs in a Multi-Location Newsboy
Problem,” Management Science, May 1979, 25:5.
15 Securities and Exchange Commission, “Amazon.com Form 10-K” for fiscal years 1997–1999.
16 Wikipedia page of Amazon.com, http://en.wikipedia.org/wiki/Amazon.com. Accessed May 30, 2013.
17 William C. Jordan and Stephen C. Graves, “Principles on the Benefits of Manufacturing Process
Flexibility,” Management Science, April 1995, 41:4.
18 Bruce Kogut and Nalin Kulatilaka, “Operating Flexibility, Global Manufacturing, and the Option
Value of a Multinational Network,” Management Science, January 1994, 40:1.
19 Arnd Huchzermeier and Morris A. Cohen, “Valuing Operational Flexibility Under Exchange Rate
Risk,” Operations Research, Jan.–Feb. 1996, 44:1.
20 Paul Mozur, “Apple Supplier Foxconn Says Fight at Plant Spread Into Larger Unrest,” Wall Street
Journal, Sept. 24, 2012; http://online.wsj.com/article/
SB10000872396390444180004578015170427352146.html; Jessica E. Vascellaro, “Audit Faults Apple
Supplier,” Wall Street Journal, March 30, 2012 http://online.wsj.com/article/
SB10001424052702303404704577311943943416560.html; “Apple to Audit Supplier’s Pollution
Management,” Wall Street Journal, April 16, 2012; http://online.wsj.com/article/
SB10001424052702304299304577347294151002440.html; “Foxconn to Raise Salaries,” Wall Street
Journal, April 5, 2012. http://online.wsj.com/article/
SB10001424052702303302504577324780116867816.html
21 Timothy Aeppel, “A Snowblower Maker Braces for Slump’s Blizzard of Woe,” Wall Street Journal,
Nov. 7, 2008. http://online.wsj.com/article/SB122602502818007621.html.
22 K.B. Hendricks and V.R. Singhal, “ An Empirical Analysis of the Effect of Supply Chain Disruptions on
Long-Run Stock Price Performance and Risk of the Firm,” Production and Operations Management, 14
(2005), pp. 35–52.23 K.B. Hendricks and V.R. Singhal, “Association Between Supply Chain Glitches and
Operating Performance, Management Science 51 (2005), 695–711.
24 Toshihiro Nishiguchi, Alexandre Beaudet. “The Toyota Group and the Aisin Fire,” Sloan Management
Review, Fall 1998, 40:1, pp. 49–59.
25 Amit S. Mukherjee, “The Fire That Changed an Industry: A Case Study on Thriving in a Networked
World,” The Financial Times, October 1, 2008. http://www.ftpress.com/articles/article.aspx?p=1244469.
accessed on December 20, 2012.
26 Ravi Anupindi, “Boeing: The Fight For Fasteners,” William Davidson Institute at the University of
Michigan, Case No. 1-428-787, November 17, 2009.
27 William Schmidt, Ananth Raman, and Vishal Gaur, “Airbus A380: Turbulence Ahead,” HBS No. 609-
041 (Boston: Harvard Business School, 2010).

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 49

6 INDEX

Page numbers followed by f refer to figures. Page numbers followed by i refer to
interactive illustrations. Page numbers followed by t refer to tables.

activity-based costing (ABC), 16
advertising, 24, 25, 31
Airbus, 45
aircraft manufacturing, 45
Amazon.com, 36, 38
American Apparel, 7, 35
amplification factor, 11
assembly networks, 5, 6, 6f, 46
automated manufacturing process, 35

Barilla SpA, 10
Boeing, 45
book publishing and retailing, 29t, 31, 38
bullwhip effect, 4, 10–12, 11f, 13, 14, 15, 24, 45,

46
buyback contracts, 29–30, 29t, 31, 32i, 46

capacity allocation, 11, 13–14, 16, 18
capacity flexibility, 9, 9t, 15, 39–40, 39f, 41f
capacity utilization, 10t, 18, 38, 45
centralized decision making, 7, 14t, 16, 46
centralized facilities, 6, 36–38, 37i, 38i
centralized supply chains, 7, 8, 9t, 16, 27, 30,

36–38, 37i, 38i, 41, 46
channel alignment, 14–15, 14t
chargebacks, 25
China, 3, 35, 42
Cisco, 13
closed-loop supply chains, 6
clothing manufacturers, 16, 25, 35
clothing retailers, 7, 8, 10, 16, 35
clothing suppliers, 25
codes of conduct, 42
collaborative planning, forecasting, and

replenishment (CPFR), 15, 16
competition, 24, 31
competitiveness, 15, 41
compliance issues, 42, 45
consumer packaged goods, 5, 8, 9
continuous replenishment program (CRP), 14t,

15, 16
contracts, 3, 8, 25–26, 29, 29t, 31, 41. See also

buyback contracts; wholesale price contracts
coordinated supply chain, 3, 7–8, 9t, 11, 14, 16,

24, 25, 29, 30, 31, 41, 45, 47
cost hidden information, 24
cross-company initiatives, 24–25
cross-docking, 14t
cross-functional teams, 11
cross-training, 40
culture of company, 25
customer decisions, 25

customer interaction rules, 3
customer needs and requirements, 3, 16, 38
customer proximity, 9, 32–35, 33i, 35i
customer satisfaction, 16, 21
customer service, 7, 24
customization, 35

decentralized decision making, 8, 46
decentralized supply chains, 7–8, 27–28, 28f,

30, 36–39, 37i, 38i, 46
decision making, 3, 8, 15, 32, 34, 35, 41
decision making coordination, 5, 8, 9, 14, 47.

See also supply chain coordination
decision rights, 8, 25
delayed differentiation, 4, 16, 17, 17f, 40
Dell, 10
demand, 7, 12, 13, 15, 16, 20–21, 23, 24, 33, 35,

36–37, 37i, 38, 39, 40, 41, 42
demand data (demand signals), 3, 7, 8, 9, 11,

12, 13, 14, 15, 17, 18, 24, 25, 45
demand fluctuations, 9
demand forecasts, 8, 11, 14t, 15, 16, 18, 21–22,

24, 26, 31, 46
demand forecast updating, 12, 14, 14t, 15, 21
demand hidden information, 24
demand modeling, 20, 20i, 21
demand uncertainty, 3, 7, 9, 9t, 17, 21, 22, 24,

26, 27, 29t, 32, 34, 34i, 36, 38, 41, 46
demand variability (bullwhip effect), 10–11, 12
demand volatility, 22
department store chains, 25
design. See product design; supply chain design
differentiated supply chains, 6, 8, 9, 26–27, 46
differentiation, delayed, 4, 16, 17, 17f, 40
Dillard’s, 25
direct-to-customer model, 10
discounts, 13, 14t, 15, 29t, 31
disruptions, 7, 40, 42, 44–45
distribution centers, 7, 10, 16, 36, 38
distribution costs, 8
distribution decisions, 3, 46
distribution function, 3
distribution supply chains, 5–6, 6f, 17, 46
distributors, 5, 5f
domestic centralized supply chain facilities, 6,

36–38, 37i, 38i
domestic production facilities, 32–35, 33i, 35i
double marginalization, 27, 29, 46
downstream, 5, 6
dynamic routing, 40

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 50

economic order quantity (EOQ) model, 13
economic recessions, 2, 23, 42
economic risk, 43, 43f
economies of scale, 12, 36, 37, 37i, 38, 38i, 44
efficiency, 4, 9, 9t, 10, 10f, 14, 14t, 15, 16, 24,

25, 40, 44
Efficient Consumer Response (ECR), 16
electronic data interchange (EDI), 14, 14t
emerging economies, 3, 35
environmental impact, 4, 7, 42
environmental risk, 43, 43f
Ericsson, 4
everyday low cost (EDLC), 15–16
everyday low price (EDLP), 16
excess inventory, 9, 9t, 10t, 11, 15, 16, 17, 18,

20, 22, 31, 36
exchange rate, 35, 41
expected lost sales, 21, 26, 27
expected profit, 21, 22, 23, 23f, 26, 27, 28, 29,

30, 31f
expected sales, 21, 22, 26, 27, 31
exponential smoothing, 12

facilities centralized location, 6, 36–38, 37i, 38i
facilities flexibility, 39–40, 39f, 41f
factories, 3, 5, 7, 10, 14, 16, 24, 35, 42, 44, 45, 47
FedEx, 6, 15
finance function, 7
first best solution, 27, 28
flexibility, 38–40, 39f, 41f
floods, 42
fluctuations, 9, 10–11, 13, 14, 14t, 15, 41
forecasts, 7, 9, 14, 14t, 15, 16, 18, 19f, 21–22, 23,

26, 31, 46
forecast updating, 12, 14, 14t, 15, 21
foreign production facilities, 32–35, 33i, 35i
foreign supply chain facilities, 6, 36–38, 37i, 38i
Forever 21, 7, 35
fragmented supply chains, 3, 6
fuel costs, 35, 42
fulfillment centers, 38
functional managers, 3
functional products, 8–9
functional silos, 3

gaming in shortage situations, 12, 13–16, 14t
Gap (retailer), 38
geopolitical risk, 43, 43f
global economic conditions, 3, 42, 44
globalization, 3, 4, 44
global risks, 42–43, 43f
Graves, Stephen, 40

Hewlett-Packard, 10
hidden action, 14, 25, 31
hidden information, 24–25, 31
hockey-stick effect, 13
holding costs, 7, 13, 32–33, 33i, 34, 34i
hub-and-spoke supply chains, 6

incentives, 8, 13, 15, 24–26, 29, 31, 47
Inditex, 10
information flow, 5
information sharing, 14, 14t, 15, 16
infrastructure. See physical infrastructure; soft

infrastructure
innovative products, 8, 9
intellectual property, 35
inventory, 3, 5, 8, 9, 9t, 10, 12, 13, 17, 18, 20–

21, 20i, 22, 23, 26–27, 28, 28f, 29, 29t, 30, 31,
36–37, 40, 44

inventory control system, 12, 15
inventory costs, 7, 9, 13, 16, 17, 32–34, 33i, 35i
inventory data, 14, 14t, 16, 25
inventory holding costs, 7, 13, 32–33, 33i, 34
inventory risk, 21, 25
inventory shortages, 9, 17, 36, 45
inventory shrinkage, 25
inventory storage, 9
inventory strategy, 9t
inventory transportation, 9
inventory, vendor managed (VMI), 7–8, 14, 14t

Jordan, William, 40
just-in-time inventories, 44
just-in-time production, 15

labor costs, 7, 35, 41
labor practices, 42
labor scheduling, 24
labor unrest, 42
lead times, 3, 5, 7, 9–10, 9t, 10t, 11, 12, 14, 14t,

15, 16, 17, 18, 18f, 23, 26, 32, 33, 33i, 34, 35i,
40

lean production methods, 9, 44
life cycles of products, 3, 4, 8, 9, 16, 18
list prices, 25
location decisions, 5, 32–38, 33i, 35i, 37i, 38i
location flexibility, 39–40, 39f, 41f
logistical flexibility, 40
logistics costs, 7
logistics function, 7
logistics outsourcing, 14t, 15
logistics service providers, 3, 6, 14t, 17
long-term decisions, 7

make-buy decisions, 41, 46
managers, 3, 7, 8, 12, 16, 25, 32, 42
manufacturing costs, 13
manufacturing disruptions, 7, 40, 44–45
manufacturing location decisions, 32–35, 33i,

35i
markdown money, 25, 31
markdowns, 8, 21
market mediation costs, 9, 10
market-responsive supply chains, 4, 9–10, 9t,

10t, 16
market share, 13, 45
minimum order quantity restrictions, 3, 13
moving average, 12

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 51

multinational companies, 6, 41
multisourcing, 40, 46

natural disasters, 42
Netflix, 38
new product introductions, 7, 8, 13, 45
Nokia, 45
nonfulfillment penalties, 3, 25, 45
Nordstrom, 38

offshoring, 35
operational efficiency, 14, 14t, 15
order batching, 12–13, 14t, 15
organizational culture, 25
organizational structure, 8, 25
outsourcing, 9, 14t, 15, 41

penalties for nonfulfillment, 3, 25, 45
performance evaluation processes, 25
periodic inventory control, 12, 15
pharmaceutical companies, 5
Philips, 45
physical costs, 8–9, 10
physical infrastructure, 4, 7, 32, 41
physically efficient supply chains, 4, 9, 9t, 10,

10t
point-of-sale data, 14t, 15
postponement flexibility, 17, 40, 46
price discounts, 13, 15, 29t, 31
price fluctuations, 11, 13, 15, 41
price markdowns, 8, 21
price uncertainty, 3
Pritchett, Lou, 24
Procter & Gamble, 10, 24
procurement costs, 33, 34
procurement decisions, 7, 20–21, 20i, 46
procurement function, 5
product availability, 3, 7, 8, 9, 40
product design, 9t, 10, 16, 17, 40, 41, 56
production capacity, 16, 18, 46
production costs, 8, 10t, 15, 26, 28, 29, 32–33,

34, 34i, 45
production data, 9, 14
production decisions, 3, 7, 14, 15, 40, 46
production disruptions, 44–45
production flexibility, 39–40, 39f, 41f
production function, 7
production lead times, 9–10, 10t, 16, 26
production location, 9, 34–35, 34i, 35i, 41
production process with delayed

differentiation, 17, 17f
production rationing of new products, 13–14
production responsiveness, 16
production technology investment, 40
product life cycles, 3, 4, 8, 9, 16, 18
profit margins, 8, 27, 46
profit maximization, 7, 24, 26, 28, 28f, 47
promotions, 7, 8, 24, 25, 31
proximity to customers, 32–35, 33i, 35i

quantity discount contract, 29t
quantity flexibility contract, 29t
quotas, 13

radio-frequency identification (RFID), 3, 14
rationing, 13–14
raw material inventories, 10, 16, 18, 44
reactive production capacity, 18, 46
react period, 20, 20i
read period, 18, 18f, 20, 20i, 21, 23, 24, 46
read-react capability, 16, 18–24, 18f, 19f, 20i,

23f
recency bias, 12
recessions, 2, 23, 42
recycling, 6
regional facilities, 6, 36–38, 37i, 38i
remanufacturing, 6
replenishment lead times, 10t, 32, 46
reshoring, 35
responsiveness, 4, 5, 16, 24, 32. See also market-

responsive supply chains
retailers, 5, 5f, 7, 10–11, 12, 14, 22, 23, 25, 26,

27–28, 28f, 29–30, 29t, 31, 36, 38, 47
revenue sharing contract, 29t
risk management, 3–4, 7, 42–45, 43f
Royal Philips Electronics, 45

safety rules, 42
Saks Fifth Avenue, 25
sales & operations planning (S&OP), 7, 46
sales data, 14t, 16, 18, 19f, 25
sales department (sales function), 3, 13, 15
sales forecasts, 15
sales promotions, 7, 31
sales rebate contracts, 29t
salvage value of leftover inventory, 20, 20i, 21
Securities and Exchange Commission (SEC),

42
selling price, 20, 20i, 25, 29
senior management, 4, 11
serial supply chains, 5, 5f, 6, 47
shipping, 7, 8, 11, 12–13, 14, 14t, 15, 23, 24, 38,

40
shortage gaming, 12, 13–16, 14t
shortages, 9, 17, 36, 45
short-term decisions, 7
single sourcing, 44
societal risk, 43, 43f
soft infrastructure, 7, 8, 40
sourcing decisions, 34, 35i, 40
specialization, 41, 44
specialized manufacturers, 5, 9, 45
Sport Obermeyer, 18, 19f
statistical economies of scale, 36–37, 37i, 38,

38i, 47
stocking decisions, 14, 15, 16
stocking quantity, 27, 27, 28f
stockouts, 8, 9, 9t, 11, 13, 15, 38
subcontracting, 7
suppliers’ decisions, 25

8031 | Core Reading: SUPPLY CHAIN MANAGEMENT 52

supply chain coordination, 3, 7–8, 9t, 11, 14,
16, 24, 25, 29, 30, 31, 41, 45, 47

supply chain decisions, 3, 7
supply chain design, 3, 4, 6, 8, 14, 16, 17
supply chain disruptions, 7, 40, 42, 44–45
supply chain footprint, 7, 32, 47
supply chain function, 3, 13
supply chain organizations, 3
supply chain risk management, 3–4, 42–45, 43f
supply chain types, 5–7, 5f, 6f
sustainability, 4

technological risk, 43, 43f
timeframes of decisions, 7
Toyota, 44–45
training, 40
transportation costs, 8, 9, 12, 34, 35, 35i, 38
transportation disruptions, 42, 44
transportation investment, 40

uncertainties, 8, 9t, 10, 13, 15, 16, 40, 45. See

also demand uncertainty; price uncertainty
unsold merchandise, 23, 25, 26, 27, 29, 29t, 31,

46
UPS, 6, 15
upstream, 5, 6

vanilla boxes, 17, 40, 47
vendor compliance, 42, 45
vendor managed inventory (VMI), 7–8, 14, 14t
vertically integrated supply chains, 6, 7, 8, 10,

26, 47
volatility, 13, 14, 22, 23, 35, 42

Walmart, 24
Walton, Sam, 24
warehouses, 5, 7, 8, 14–15, 23, 38, 40, 42, 47
wholesale price, 25, 26, 27–28, 28f, 29, 29t, 30,

30f, 31, 31f
wholesale price contracts, 27, 29, 29t, 31, 47
wholesalers, 5, 5f, 10–11

Zara clothing brand, 10, 16

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Although you can leverage our expertise for any writing task, we have a knack for creating flawless papers for the following document types.

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Areas of Expertise

Although you can leverage our expertise for any writing task, we have a knack for creating flawless papers for the following document types.

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Trusted Partner of 9650+ Students for Writing

From brainstorming your paper's outline to perfecting its grammar, we perform every step carefully to make your paper worthy of A grade.

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Hire your preferred writer anytime. Simply specify if you want your preferred expert to write your paper and we’ll make that happen.

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You can purchase this feature if you want our writers to sum up your paper in the form of a concise and well-articulated summary.

Plagiarism Report

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Free Features $66FREE

Most Qualified Writer $10FREE
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Our Services

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We thoroughly read your final draft to identify errors.

Thorough Proofreading

We thoroughly read your final draft to identify errors.

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We understand your guidelines first before delivering any writing service. You can discuss your writing needs and we will have them evaluated by our dedicated team.

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What Will You Get?

Premium Quality

Experienced Writers

On-Time Delivery

24/7 Customer Support

Complete Confidentiality

Authentic Sources

Moneyback Guarantee

Order Tracking

Areas of Expertise

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Areas of Expertise

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Trusted Partner of 9650+ Students for Writing

Preferred Writer

Grammar Check Report

One Page Summary

Plagiarism Report

Free Features $66FREE

Our Services

Academic Writing

Professional Editing

Thorough Proofreading

Thorough Proofreading

Delegate Your Challenging Writing Tasks to Experienced Professionals

Check Out Our Sample Work

It May Not Be Much, but It’s Honest Work!

0+

Happy Clients

0+

Words Written This Week

0+

Ongoing Orders

0%

Customer Satisfaction Rate

Process as Fine as Brewed Coffee

Share Your Requirements

Place Order & Deposit Funds

Release Payment to Your Writer

See How We Helped 9000+ Students Achieve Success

We Analyze Your Problem and Offer Customized Writing

We Mirror Your Guidelines to Deliver Quality Services

We Handle Your Writing Tasks to Ensure Excellent Grades