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01a Bullwhip Effect

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The Bullwhip Effect Henry C. Co Technology and Operations Management, California Polytechnic and State University
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Page 1: 01a Bullwhip Effect

The Bullwhip Effect

Henry C. CoTechnology and Operations Management, California Polytechnic and State University

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The BullWhip Effect 2

Variability increases as one moves up the supply chain

Source: Johnson & Pike, 1999

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The Bullwhip Effect

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The Beer Game Role-playing simulation developed in the

1960’s at MIT’s Sloan School of Management Production and distribution of beer.

Players divide themselves into groups: Retailer, Wholesaler, Distributor, and Brewer.

Weekly consumer demand simulated by a deck of cards

Retailer sells from his inventory and reorders from the Wholesaler, who sells from his inventory and reorders from the Distributor, who in turn sells from his inventory and reorders from the Brewer, who finally sells from his inventory and restocks from his production.

Order processing delays; Shipping delays Inventory carrying costs; Stockout costs Players base their decisions strictly on the orders

they receive from their respective buyers.

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“ During the game emotions run high. Many players report feelings of frustration and helplessness. Many blame their teammates for their problems; occasionally heated arguments break out.”

“In virtually all cases, the inventory levels of the retailer decline, followed in sequence by a decline in the inventory of the wholesaler, distributor, and factory. As inventory falls, players tend to increase their orders. Players soon stock out. Backlogs of unfilled orders grow. Faced with rising orders and large backlogs, players dramatically boost the orders they place with their supplier. Eventually, the factory brews and ships this huge quantity of beer, and inventory levels surge. In many cases one can observe a second cycle.”

John Sterman, one of the original proponents of the Beer Game

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Stakeholders along supply chain Have different and frequently conflicting

objectives. Often operated independently.

The network can oscillate in very large swings as each organization in the supply chain seeks to solve the problem from its own perspective.

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Consequences of the Bullwhip Effect Lower revenues.

Stockouts and backlogs mean lost sales, as customers take their business elsewhere.

Higher costs. High carrying cost Stockout cost Distributors need to

expedite orders (at higher shipping expenses)

Manufactures need to adjust jobs (at higher setups and changeover expenses, higher labor expenses for overtime, perhaps even higher materials expenses for scarce components.)

All entities in the supply chain must also invest heavily in outsized facilities (plants, warehouses) to handle peaks in demand, resulting in alternating under or over-utilization.

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Worse quality. Quirky, unplanned

changes in production and delivery schedules disrupt and subvert control processes, begetting diverse quality problems that prove costly to rectify.

Poorer service. Irregular,

unpredictable production and delivery schedules also lengthen lead time, causing delay and customer dissatisfaction.

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Causes of Bullwhip Effect

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Demand variability, quality problems, strikes, plant fires, etc.

Variability coupled with time delays in the transmission of information up the supply chain and time delays in manufacturing and shipping goods down the supply chain create the bullwhip effect.

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1. Overreaction to backlogs2. Neglecting to order in an attempt to

reduce inventory3. No communication up and down the

supply chain4. No coordination up and down the

supply chain5. Delay times for information and

material flow

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6. Order batching - larger orders result in more variance. Order batching occurs in an effort to reduce ordering costs, to take advantage of transportation economics such as full truck load economies, and to benefit from sales incentives. Promotions often result in forward buying to benefit more from the lower prices.

7. Shortage gaming: customers order more than they need during a period of short supply, hoping that the partial shipments they receive will be sufficient.

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8. Demand forecast inaccuracies: everybody in the chain adds a certain percentage to the demand estimates. The result is no visibility of true customer demand.

9. Free return policies

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Countermeasures to the Bullwhip Effect

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1. Countermeasures to order batching2. Countermeasures to shortage gaming3. Countermeasures to fluctuating

prices4. Countermeasures to demand forecast

inaccuracies 5. Free return policies

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Order Batching High order cost is countered with Electronic

Data Interchange (EDI) and computer aided ordering (CAO). Full truck load economics are countered with third-

party logistics and assorted truckloads. Random or correlated ordering is countered with regular delivery appointments.

More frequent ordering results in smaller orders and smaller variance.

However, when an entity orders more often, it will not see a reduction in its own demand variance - the reduction is seen by the upstream entities.

Also, when an entity orders more frequently, its required safety stock may increase or decrease; see the standard loss function in the Inventory Management section.

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Shortage Gaming Proportional rationing schemes are

countered by allocating units based on past sales. Ignorance of supply chain conditions can be

addressed by sharing capacity and supply information.

Unrestricted ordering capability can be addressed by reducing the order size flexibility and implementing capacity reservations.

For example, one can reserve a fixed quantity for a given year and specify the quantity of each order shortly before it is needed, as long as the sum of the order quantities equals to the reserved quantity.

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Fluctuating Prices High-low pricing can be replaced with

every day low prices (EDLP). Special purchase contracts can be implemented in order to specify ordering at regular intervals to better synchronize delivery and purchase.

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Demand Forecast Inaccuracies Lack of demand visibility can be

addressed by providing access to point of sale (POS) data.

Changes in pricing and trade promotions and channel initiatives, such as vendor managed inventory (VMI), coordinated forecasting and replenishment (CFAR), and continuous replenishment can significantly reduce demand variance.

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Free Return Policies Free return policies are not addressed

easily. Often, such policies simply must be

prohibited or limited.

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Vendor Managed Inventory

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Popularized in the late 1980s by Wal-Mart and Procter & Gamble, VMI became one of the key programs in the grocery industry’s pursuit of “efficient consumer response” and the garment industry’s “quick response.”

Successful VMI initiatives have been trumpeted by other companies in the United States, including Campbell Soup and Johnson & Johnson, and by European firms like Barilla (the pasta manufacturer).

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The supplier—usually the manufacturer but sometimes a reseller or distributor—makes the main inventory replenishment decisions for the consuming organization. The supplier monitors the buyer’s inventory levels

(physically or via electronic messaging) and makes periodic resupply decisions regarding order quantities, shipping, and timing.

Transactions customarily initiated by the buyer (like purchase orders) are initiated by the supplier instead.

The purchase order acknowledgment from the supplier may be the first indication that a transaction is taking place; an advance shipping notice informs the buyer of materials in transit.

The VMI Partnership

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The manufacturer is responsible for both its own inventory and the inventory stored at is customers’ distribution centers.


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