Impact of Forecast Errors in CPFR Collaboration Strategy

Abstract

The primary objective of this research is to investigate the impact of random forecast error and bias forecast error in Collaborative Planning, Forecasting and Replenishment (CPFR) strategy on the cost of inventory management for both the manufacturer and retailer. Discrete-event simulation is used to develop a CPFR collaboration model where forecast, sales and inventory level information is shared between a retailer and a manufacturer. Based on the results of this study, we conclude that the higher random forecast error and negative bias forecast error increases the cost of inventory management for both the manufacturer and the retailer. When demand variability is high, a bias forecast error has a bigger impact on inventory management cost compared to a random forecast error for both the manufacturer and retailer. Also, a posi tive bias forecast error is more beneficial than a negative bias forecast error to gain maximum benefits of CPFR strategy.