Adjusting An Existing Forecasting Model When Some Future Demands Are Known In Advance: A Bayesian Technique

Abstract

The purpose of this research is to provide a model which can be used to adjust forecasts that are already available. It analyzes the components of the advanced demand, namely, the number of orders and their corresponding order size. It explores and analyzes the possibility of using the expected number of orders for a future period as the variable to be estimated. The Bayesian estimate of the expected number of orders is used in determining the adjusted forecast. A simulation is applied to calculate a ratio between the adjusting forecasting error and the original forecasting error. Results prove that the adjusted forecast provides greater accuracy for different probable values of getting an order in advance.