The Bullwhip Effect

1
The Bullwhip Effect

• John H. Vande Vate
• Fall, 2002

2
Diagnosis Treatment

• What is it?
• Symptoms?
• Causes?
• Treatments
• Follow-up

3
What it is

• The Bullwhip Effect describes the phenomenon
  in which order variability is amplified as it
  moves up the supply chain from end-consumers
  through distribution and manufacturing to raw
  material suppliers.

4
Example

• Procter Gamble Pampers
• Smooth consumer demand
• Fluctuating sales at retail stores
• Highly variable demand on distributors
• Wild swings in demand on manufacturing
• Greatest swings in demand on suppliers

5
Illustration
Consumer Sales at Retailer
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Retailer's Orders to Distributor
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Illustration
Retailer's Orders to Distributor
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Retailer Order
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Distributor's Orders to PG
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Illustration
Distributors Orders to PG
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Distributor Order
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PG's Orders with 3M
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PG Order
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Illustration
Consumer Sales at Retailer
1000
900
800
700
600
Consumer demand
500
400
300
200
100
0
1
3
5
7
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PG's Orders with 3M
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PG Order
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What Are the Effects?

• What problems, costs, challenges does this create
  for the players in the supply chain?
• What problems does this create for the product in
  the market place?

10
The Effects

• Manufacturing Cost
• Capital Investment
• Operating costs
• Inventories
• Anticipatory
• Cycle
• Pipeline
• Safety stock
• Infrastructure
• Lead Time
• New product releases
• Order response time
• Shipping Receiving Cost
• Order processing

11
The Effects

• Customer Service Level
• Product availability
• Transport Cost
• Economies of scale
• Variability

12
The Causes

• Order batching
• Pricing Strategies
• Uncertain Supply
• Forecasting

13
Causes

• Order Batching
• Reduce processing costs
• Exploit economies of scale in transport
• Ordering cycles and planning cycles

14
Causes

• Pricing Strategies
• Promotions
• Reduce margin
• Advance demand
• Diversions
• Sales Targets Revenue Targets
• Reduce price at end of quarter to meet plans

15
Uncertain Supply

• Product on Allocation
• Customers place extra large orders to ensure they
  get their share

16
Forecasting

• More variability
• Poorer forecasts
• Less reliable supply

17
Treatments

• Information Sharing
• Wal-Mart provides POS info to PG
• Channel Alignment
• Coordination of promotions, transport, etc.
• Operational Efficiency
• Reducing cost and leadtime

18
Information Sharing

• Chrysler makes the cars
• Leer makes the seats
• Third party cuts sews fabric
• Milliken makes the fabric
• Dupont makes raw material

Shared schedule information
19
Information Sharing

• Chrysler makes the cars
• Leer makes the seats
• Third party cuts sews fabric
• Milliken makes the fabric
• Dupont makes raw material

Shared schedule information
20
BMW Daimler

• Fiber Optic controls
• Bosch integration
• Infineon switches
• Several other suppliers
• Shared visibility of components and alerts of
  shortages

21
VMI/CRP

• Vendor managed inventory/Continuous Replenishment
• Dell requires its suppliers to hold consignment
  inventory at a warehouse near the factory ---
  Vendor responsible for maintaining 2 weeks supply

22
Consumer Contact

• Maintain contact with end consumer (source of
  demand) to reduce reliability on information from
  channels
• Loyalty programs
• Coupons
• BMW model of ordering
• Disintermediate distribution
• Dell build-to-order
• GM build-to-order in Brazil

23
Information

• Information sharing from industrial customers
• VMI and CRP
• Contact with end consumers
• Disintermediate distributors
• Faster replenishment

24
Reducing Batch Sizes

• Reduce the cost of ordering automated ordering,
  VMI, etc.
• Facilitate consolidation
• multi-stop deliveries, pick-ups, milk-runs
• Shared inventory and transport (Dell)
• 3PLs help

25
Stabilize Prices

• Eliminate promotions (Everyday low prices)
• Stabilize Demand
• Auto manufacturers produce at a constant rate and
  drive demand with 0 financing, rebates, etc.
• Dell adjusts its offerings and pricing to reflect
  product availability

26
Eliminate Gaming

• Allocate based on historical sales rather than
  orders
• Intel case
• Promote orders far in advance
• Limit cancellations

27
Follow-up

• How well have these cures worked?
• Enormous investment of energy and money into
  these treatments
• The Bullwhip is alive and well
• Two cases

28
Dell

• Hard drives
• Relies on several sources
• Competition who gets what share
• Contingency if one has a problem
• Cultivation dont want just 1 disk drive maker
• Contracts for share
• X of volume to A, Y to B, etc.
• Implementation

29
Implementation

• Assume a 5 day production schedule
• 20 to A one day a week
• 40 to B two days a week
• 40 to C two days a week
• Mondays to A
• Tuesdays Wednesdays to B
• Thursdays Fridays to C
• Comments?

30
The Auto Industry

• Increasingly BTO
• Consumer contact
• Short replenishment cycles
• Small batch sizes
• Increasingly Lean
• As little as 2 hours inventory on site
• Sequencing Send supplier locked production
  schedule. Supplier sends parts in that order
• Frequent small deliveries (sometimes every 4 hrs)
• Coordinated supply with Milk runs, etc.

31
Auto Industry

• Keep production level
• Target daily production, e.g., 1,000/day
• Promotions, rebates, low financing to drive

32
Consequences

• BTO and shorted order-to-delivery means smaller
  bucket of orders in hand to sequence with

Before
After
Best Schedule 3R, 3B, 3G, 3Y
33
More Variable Usage

• Sequence under old method
• Sequence under BTO

34
Lean Prevents Pooling

• With releases every day or even several times per
  day, variability is transmitted to suppliers
• Study of one OEMs in-bound supply showed up to
  270 variation in day-to-day volumes ordered
• X today, 3X tomorrow, 1/3X next day

35
Consequences

• Supplier Capacity
• Supplier Inventory
• Transportation

36
Confounding Factor

• Product Diversification
• GM plans to launch a new vehicle every 23 days.
• BMW makes 1017 versions of the 7 series sedan

37
Next

• Inventory model to temper the Bull Whip Effect in
  lean/BTO environments
• November 19th Visitor from
• Peach State Integrated Technologies
• What they are doing with location models
• Yuri and his team are working on using those
  models to build low variance milk runs for Ford
  based on location models