Stochastic characterization of upstream demand processes in a supply chain

In the supply chain management area, there has much recent attention to a phenomenon known as the bullwhip effect. The bullwhip effect represents the situation where demand variability increases as one moves up the supply chain. In this paper, we study this effect in an order-up-to supply-chain system when minimum Mean Square Error (MSE) optimal forecasting is employed as opposed to some commonly used simplistic forecasting schemes. We find that depending on the correlative structure of the demand process it is possible to reduce, or even eliminate (i.e., "de-whip"), the bullwhip effect in such a system by using an MSE-optimal forecasting scheme. Beyond the bullwhip effect, we also determine the exact time-series nature of the upstream demand processes.