Demand forecast updating bullwhip
The authors suggest several ways in which companies can counteract the bullwhip effect. Companies can make demand data from downstream available upstream.
Or they can bypass the downstream site by selling directly to the consumer.
HP’s product division was a victim of order swings that were exaggerated by the resellers relative to their sales; it, in turn, created additional exaggerations of order swings to suppliers.
In the past few years, the Efficient Consumer Response (ECR) initiative has tried to redefine how the grocery supply chain should work.1 One motivation for the initiative was the excessive amount of inventory in the supply chain.
However, as they examined the distributors’ orders, the executives were surprised by the degree of variability.
When they looked at P&G’s orders of materials to their suppliers, such as 3M, they discovered that the swings were even greater.
I am trying to calculate the effect of demand forecast updating to bullwhip effect in an organization, as of now i have already done the forward forecasting using ARIMA, Holt Winters and simple Moving average.
Demand variability increases as one moves up the supply chain away from the retail customer, and small changes in consumer demand can result in large variations in orders placed upstream.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, ineffective transportation, and missed production schedules. Its sales at retail stores were fluctuating, but the variabilities were certainly not excessive. Not long ago, logistics executives at Procter & Gamble (P&G) examined the order patterns for one of their best-selling products, Pampers.However, when they examined the orders from the reseller, they observed much bigger swings.Also, to their surprise, they discovered that the orders from the printer division to the company’s integrated circuit division had even greater fluctuations.