The impact of demand information in a supply chain with a seasonal ARIMA process

Supply chain dynamics are ascribed to the delays, distortions and amplifications in the flow of information across the supply chain. Demand is an important form of information that passes from one stage to another in a supply chain. During these transfers, the distortions of the demand information propagate upstream in an amplified form (described as the bullwhip effect). This paper addresses supply chain dynamics which are a method to enhance learning in supply chain system when demand information contains both seasonality and non-seasonality. Given a seasonal autoregressive integrated moving average (SARIMA) process of customer demand and lead times at each stagte, the generalized ordering policy at each stage is emplyed to control the tradeoffs between the variation in inventory and the variation in differencing orders. An expression of time series of the orders and inventories at each stage is derived. Also, explicit formulas of the bullwhip effect, a phenomenon in which variation in demand produces larger variations in upstram orders and inventory, are given. And the causes of the bullwhip effect are analyzed. This analysis shows how different demand information of supply chain systems can derive different mangerial insights because they provide different characteristics about the cause of the bullwhip effect. These observations are used to obtain managerial insights about mitigating the bullwhip effect. �� 2013 International Information Institute