The impact of forecasting methods on the bullwhip effect

This paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first-order autoregressive process describes the customer demand and an order-up-to inventory policy characterizes the replenishment decision. A bullwhip effect measure is derived for the optimal forecasting procedure that minimizes the mean-squared forecasting error for the specified demand process. Similar measures are obtained for the moving average and exponential smoothing methods. The findings indicate that different forecasting methods lead to bullwhip effect measures with distinct properties in relation to lead time and underlying parameters of the demand process. Moreover, a simple rule is established to help managers select a forecasting method that yields the lowest investory cost.