28-03-2014, 12:53 PM
The Bullwhip Effect In Supply Chains
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Abstract:
The bullwhip effect occurs when the demand order variabilities in the supply chain are amplified as they
moved up the supply chain. Distorted information from one end of a supply chain to the other can lead to
tremendous inefficiencies. Companies can effectively counteract the bullwhip effect by thoroughly
understanding its underlying causes. Industry leaders are implementing innovative strategies that pose
new challenges: 1. integrating new information systems, 2. defining new organizational relationships, and
3. implementing new incentive and measurement systems.
Distorted information from one end of a supply chain to the other can lead to tremendous
inefficiencies: excessive inventory investment, poor customer service, lost revenues, misguided
capacity plans, inactive transportation, and missed production schedules. How do exaggerated
order swings occur? What can companies do to mitigate them?
Causes of the Bullwhip Effect
Perhaps the best illustration of the bullwhip effect is the well-known "beer game." In the game,
participants (students, managers, analysts, and so on) play the roles of customers, retailers, wholesalers,
and suppliers of a popular brand of beer. The participants cannot communicate with each other and must
make order decisions based only on orders from the next downstream player. The ordering patterns
share a common, recurring theme: the variabilities of an upstream site are always greater than those of
the downstream site, a simple, yet powerful illustration of the bullwhip effect. This amplified order
variability may be attributed to the players' irrational decision making. Indeed, Sterman's experiments
showed that human behavior, such as misconceptions about inventory and demand information, may [4] cause the bullwhip effect.
Demand Forecast Updating
Every company in a supply chain usually does product forecasting for its production scheduling, capacity
planning, inventory control, and material requirements planning. Forecasting is often based on the order
history from the company's immediate customers. The outcomes of the beer game are the consequence
of many behavioral factors, such as the players' perceptions and mistrust. An important factor is each
player's thought process in projecting the demand pattern based on what he or she observes. When a
downstream operation places an order, the upstream manager processes that piece of information as a
signal about future product demand. Based on this signal, the upstream manager readjusts his or her
demand forecasts and, in turn, the orders placed with the suppliers of the upstream operation. We
contend that demand signal processing is a major contributor to the bullwhip effect.
For example, if you are a manager who has to determine how much to order from a supplier, you use a
simple method to do demand forecasting, such as exponential smoothing. With exponential smoothing,
future demands are continuously updated as the new daily demand data become available. The order
you send to the supplier reflects the amount you need to replenish the stocks to meet the requirements of
future demands, as well as the necessary safety stocks. The future demands and the associated safety
stocks are updated using the smoothing technique. With long lead times, it is not uncommon to have
weeks of safety stocks. The result is that the fluctuations in the order quantities over time can be much
greater than those in the demand data.
Order Batching
In a supply chain, each company places orders with an upstream organization using some inventory
monitoring or control. Demands come in, depleting inventory, but the company may not immediately place
an order with its supplier. It often batches or accumulates demands before issuing an order. There are
two forms of order batching: periodic ordering and push ordering.
How to Counteract the Bullwhip Effect
Understanding the causes of the bullwhip effect can help managers find strategies to mitigate it. Indeed,
many companies have begun to implement innovative programs that partially address the effect. Next we
examine how companies tackle each of the four causes. We categorize the various initiatives and other
possible remedies based on the underlying coordination mechanism, namely, information sharing,
channel alignment, and operational efficiency. With information sharing, demand information at a
downstream site is transmitted upstream in a timely fashion. Channel alignment is the coordination of
pricing, transportation, inventory planning, and ownership between the upstream and downstream sites in
a supply chain. Operational efficiency refers to activities that improve performance, such as reduced
costs and lead-time. We use this topology to discuss ways to control the bullwhip effect (see Table 1).
Break Order Batches
Since order batching contributes to the bullwhip effect, companies need to devise strategies that lead to
smaller batches or more frequent resupply. In addition, the counterstrategies we described earlier are
useful. When an upstream company receives consumption data on a fixed, periodic schedule from its
downstream customers, it will not be surprised by an unusually large batched order when there is a
demand surge.
One reason that order batches are large or order frequencies low is the relatively high cost of placing an
order and replenishing it. EDI can reduce the cost of the paperwork in generating an order. Using EDI,
companies such as Nabisco perform paperless, computer-assisted ordering (CAO), and, consequently,
customers order more frequently. McKesson's Economost ordering system uses EDI to lower the
transaction costs from orders by drugstores and other retailers." P&G has introduced standardized
ordering terms across all business units to simplify the process and dramatically cut the number of
[22]
invoices. And General Electric is electronically matching buyers and suppliers throughout the company.