8/3/2019 Chapter 14 - Bullwhip Effect

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Slide 1

All slides in this file are copyrighted by

Grard Cachon and Christian Terwiesch.

Any instructor that adopts Matching

Supply with Demand: An Introduction to

Operations Managementas a required

text for their course is free to use andmodify these slides as desired. All

others must obtain explicit written

permission from the authors to use these

slides.

Chapter 14

Bullwhip Effect

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Slide 2

The Bullwhip Effect

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Slide 3

What is the bullwhip effect?

Demand variability increases as you move up the supply chain from

customers towards supply

Custom

er

RetailerDistributorFactoryTier 1 SupplierEquipment

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Slide 4

Bullwhip effect in the US PC supply chain

Semiconductor

1995 1996 1997 1998 1999 2000 2001

-40%

-20%

0%

20%

40%

60%

80%

PC

Semiconductor

Equipment

Changes in

demand

Semiconductor

1995 1996 1997 1998 1999 2000 2001

-40%

-20%

0%

20%

40%

60%

80%

PC

Semiconductor

Equipment

Changes in

demand

Annual percentage changes in demand (in $s) at three levels of the semiconductor supply

chain: personal computers, semiconductors and semiconductor manufacturing equipment.

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Slide 5

Consequences of the bullwhip effect

Inefficient production or excessive inventory.

Low utilization of the distribution channel.

Necessity to have capacity far exceeding average demand.

High transportation costs.

Poor customer service due to stockouts.

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Slide 6

Causes of the bullwhip effect

Order synchronization

Order batching

Trade promotions and forward buying

Reactive and over-reactive ordering

Shortage gaming

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Order synchronization

Customers order on the same

order cycle, e.g., first of themonth, every Monday, etc.

The graph shows simulated

daily consumer demand (solid

line) and supplier demand(squares) when retailers order

weekly: 9 retailers order on

Monday, 5 on Tuesday, 1 on

Wednesday, 2 or Thursday and

3 on Friday.

0

10

20

30

40

50

60

70

Time (each p eriod equ als o ne d ay)

Units

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Order batching

Retailers may be required to

order in integer multiples ofsome batch size, e.g., case

quantities, pallet quantities, full

truck load, etc.

The graph shows simulateddaily consumer demand (solid

line) and supplier demand

(squares) when retailers order

in batches of 15 units, i.e.,

every 15th demand a retailer

orders one batch from thesupplier that contains 15 units.

0

10

20

30

40

50

60

70

Time (each p eriod equ als o ne d ay)

Units

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Trade promotions and forward buying

Supplier gives retailer a temporary discount, called a trade promotion.

Retailer purchases enough to satisfy demand until the next trade promotion.

Example: Campbells Chicken Noodle Soup over a one year period:

One retailers buy

Time (weeks)

Ca

ses

Shipments

Consumption

0

1000

2000

3000

4000

5000

6000

7000

Dec

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Cases

Total shipments and consumption

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Reactive and over-reactive ordering

Each location forecasts demand to determine shifts in the demand process.

How should a firm respond to a high demand observation?

Is this a signal of higher future demand or just random variation in

current demand?

Hedge by assuming this signals higher future demand, i.e. order more

than usual.

Rational reactions at one level propagate up the supply chain.

Unfortunately, it is human to overreact, thereby further increasing the

bullwhip effect.

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Shortage gaming

Setting:

Retailers submit orders for delivery in a future period.

Supplier produces.

If supplier production is less than orders, orders are rationed, i.e.,

retailers are put on allocation.

to secure a better allocation, the retailers inflate their orders, i.e., order

more than they need

So retailer orders do not convey good information about true demand

This can be a big problem for the supplier, especially if retailers are later

able to cancel a portion of the order:

Orders that have been submitted that are likely be canceled are called

phantom orders.

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Strategies to combat the bullwhip effect

Information sharing:

Collaborative Planning, Forecasting and Replenishment (CPFR)

Smooth the flow of products

Coordinate with retailers to spread deliveries evenly.

Reduce minimum batch sizes.

Smaller and more frequent replenishments (EDI).

Eliminate pathological incentives

Every day low price

Restrict returns and order cancellations Order allocation based on past sales in case of shortages

Vendor Managed Inventory (VMI): delegation of stocking decisions

Used by Barilla, P&G/Wal-Mart and others.