Using imperfect advance demand information in forecasting

In this paper, we consider the demand-forecasting problem of a make-to-stock system operating in a business-to-business environment where some customers provide information on their future orders, which are subject to changes in time, hence constituting imperfect advance demand information (ADI). The demand is highly volatile and non-stationary not only because it is subject to seasonality and changing trends but also because some individual client demands have significant influence on the total demand. In such an environment, traditional forecasting methods may result in highly inaccurate forecasts, since they are mostly developed for the total demand based only on the demand history, not making use of demand information and ignoring the effects of individual order patterns of the customers. We propose a forecasting methodology that makes use of individual ordering pattern histories of the product–customer combinations and the current build up of orders. Moreover, we propose making use of limited judgemental updates on the statistical forecasts prior to the use of ADI.