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1 1 The Bullwhip Effect John H. Vande Vate Fall, 2002

1 1 The Bullwhip Effect John H. Vande Vate Fall, 2002

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Page 1: 1 1 The Bullwhip Effect John H. Vande Vate Fall, 2002

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The Bullwhip Effect

John H. Vande Vate

Fall, 2002

Page 2: 1 1 The Bullwhip Effect John H. Vande Vate Fall, 2002

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Diagnosis & Treatment

• What is it?

• Symptoms?

• Causes?

• Treatments

• Follow-up

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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.

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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

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IllustrationConsumer Sales at Retailer

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Retailer's Orders to Distributor

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IllustrationRetailer's Orders to Distributor

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Distributor's Orders to P&G

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IllustrationDistributor’s Orders to P&G

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P&G's Orders with 3M

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IllustrationConsumer Sales at Retailer

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P&G's Orders with 3M

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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?

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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

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The Effects

• Customer Service Level– Product availability

• Transport Cost– Economies of scale

– Variability

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• Order batching• Pricing Strategies• Uncertain Supply• Forecasting

The Causes

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Causes

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

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Causes

• Pricing Strategies– Promotions

• Reduce margin• Advance demand• Diversions

– Sales Targets & Revenue Targets• Reduce price at end of quarter to meet

plans

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Uncertain Supply

Product on Allocation• Customers place extra large orders to

ensure they get “their share”

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Forecasting

More variability

Poorer forecasts

Less reliable supply

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Treatments

• Information Sharing– Wal-Mart provides POS info to P&G

• Channel Alignment– Coordination of promotions, transport, etc.

• Operational Efficiency– Reducing cost and leadtime

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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

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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

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BMW & Daimler

• Fiber Optic controls

• Bosch: integration

• Infineon: switches

• Several other suppliers

• Shared visibility of components and alerts of shortages

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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

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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

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Information

• Information sharing from industrial customers

• VMI and CRP• Contact with end consumers• Disintermediate distributors• Faster replenishment

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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)– 3PL’s help

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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

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Eliminate Gaming

• Allocate based on historical sales rather than orders

• Intel case

• Promote orders far in advance

• Limit cancellations

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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”

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Dell

• Hard drives

• Relies on several sources – Competition: who gets what share– Contingency: if one has a problem– Cultivation: don’t want just 1 disk drive maker

• Contracts for share– X% of volume to A, Y% to B, etc.

• Implementation

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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?

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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.

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Auto Industry

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

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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

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More Variable Usage

• Sequence under old method

• Sequence under BTO

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Lean Prevents Pooling

With releases every day or even several times per day, variability is transmitted to suppliers

Study of one OEM’s in-bound supply showed up to 270% variation in day-to-day volumes ordered

X today, 3X tomorrow, 1/3X next day…

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Consequences

• Supplier Capacity

• Supplier Inventory

• Transportation

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Confounding Factor

• Product Diversification– GM plans to launch a new vehicle every 23

days.– BMW makes 1017 versions of the 7 series

sedan– …

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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