The Value of Information Sharing in the Retail Supply Chain

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PREVIEW Retail supply chains are complex, with each company in the chain having multiple echelons of distribution. Forecasting and requirements planning are further challenged by managers’ reliance on “local” rather than chain-wide retail demand to make key operational decisions. A frequent consequence is the bullwhip effect . Using two case studies, Tonya and Ram show how information sharing – both within the company’s boundaries and with external partners – can mitigate the bullwhip effect and reduce supplychain costs.

the retail level. Each individual company in the supply chain forecasts its demand, plans its stocking levels, and makes its replenishment decisions independent of the other companies. It is typical to see retail distribution centers (DCs) forecasting store shipments, and then ordering from the manufacturer based on these forecasted needs. Meanwhile, the manufacturer stocks its DC based on its own forecasts of retail requirements. Such independent forecasting by members in the supply chain gives rise to what is called the bullwhip effect, which refers to the increased volatility in orders as these propagate through the supply chain. The inherent volatility in orders makes forecasting more difficult, leads to unwarranted increases in inventory throughout the supply chain, and results in inefficient use of working capital and production capacity. Further, products that have volatile demand at the customer level face the added risk of higher stock-outs. The bullwhip effect originally was named by planners at Procter and Gamble (P&G) who coined the term



retail supply chain is a network of firms, activities, organizations, and technologies. The network procures raw material from vendors, transforms the materials into intermediate and finished product, and distributes finished product to retail outlets. Many retail supply chains are complex, with companies in the supply chain having multiple echelons of distribution. In a multitiered supply chain, decisions are often based on “local” information, rather than actual demand at

Tonya Boone is an Associate Professor of Operations & Information Technology at the Mason School of Business at the College of William & Mary. Tonya’s research concentrates on the areas of sustainable supply chains and managing knowledge organizations. She is the editor of the book New Directions of Supply Chain Management: Technology, Strategy, and Implementation.

Ram Ganeshan is an Associate Professor and Area Chair of Operations & Information Technology Group at the Mason School of Business at the College of William & Mary. Ram’s primary research focus is on designing and managing effective supply chains. In 2001, he was awarded the Wickham Skinner Early Career prize for his research on supply-chain management. He is coeditor of the book Quantitative Models for Supply Chain Management.


FORESIGHT Issue 9 Spring 2008

after observing erratic swings in orders and inventory for their Pampers disposable diapers. Although the retail demand for the Pampers brand was fairly constant, retailers were changing their forecasts based on their own idiosyncratic planning processes. Some, for example, were adjusting forecasts for promotions or perceived requirements. These adjustments were sending a distorted signal of actual retail demand up the chain. Wholesalers based their planning on these signals, which amplified the errors in demand forecasts when they placed their wholesale orders with the manufacturer. It was as if demand was responding to the crack of a whip. P&G also discovered that its own orders to material suppliers, such as 3M, followed a similar pattern: wild fluctuations in orders that bore little resemblance to the actual demand for diapers (Siems,...
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