Unformatted text preview: e fluctuations.
Consider a retailer who tries to read market trends by app lying some forecasting
technique (e.g., exponential smoothing) to the order data. In so doing, a larger than
average sale in a single period could lead to the retailer adjusting his forecasts upward, so
that an even larger order would be placed to his upstream. When this practice is repeated
at upstream companies using the istorted orders from downstream, the
d than average sale could be greatly amplified. To avoid double or triple forecasting, actual
sales data (along with inventory information) need to be shared. P&G routinely receives
sell-through data from its major customers distribution centers and point-of-sales (POS)
data from some retail stores. IBM and HP ask for sell-through data as part of their
agreement with computer reseller. Using sell-through and/or POS data, manufacturers
can better forecast the demand and develop a better production plan that lowers the
overage and underage costs. Lee et al.  quantified the value of such information
Order batching results when a retailer orders in large batches, and therefore
infrequently. The upstream supplier consequently receives demand information only
infrequently, at the times when the retailer orders. This does not help the supplier in
providing good customer service. Sales information sharing by the retailer enables the
5 supplier to be better prepared for volatile market demand. The value of such sharing was
quantified in  and .
Promotions by the manufacturer to retailers can lead to erratic order patterns, but
also distort the true demand data to the manufacturer. Again, sales information sharing
helps to present a better picture.
Order rationing in times of shortages often leads retailers to inflate their orders in
order that they might gain a better share of the items in short supply. manufacturers not
realizing such gaming behaviors may be misled into believing a much higher demand
than otherwise. By having sales data, manufacturers would be in a much better position
to differentiate real demands and the so...
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This note was uploaded on 11/06/2013 for the course ISYE 6202 taught by Professor Staff during the Fall '08 term at Georgia Tech.
- Fall '08
- Industrial Engineering