Simulation-based demand forecast generation to analyze forecast accuracy and its influence on logistical performance

Managers face the problem of different demand models and forecast information for their products. Uncertainty and trends in forecasts influence the logistical performance of the companies and the question which planning method or planning parameter level fits best for the respective product is still open for practitioners. This paper gives an overview about practical inspired demand models to mimic different behaviours of customer provided forecasts, and presents a simulation based forecast generation module to analyse and improve forecast accuracy. The applications of this model presented in this paper show that measuring the forecast accuracy, understanding the forecasting behaviour, and applying respective correction methods is an important issue to be focussed in research.