forecasting, inventory, fill rate, Holt-Winters method, optimization, M3-Competition


Forecasting plays a central role in the efficient operation of a supply chain – i.e., the total costs and fill rate. As forecasts of demand are required on a regular basis for a very large number of products, the methods developed should be fast, flexible, user-friendly, and able to produce results that are reliable and easy to interpret by a manager. In this paper we show that the supply chain costs cannot be optimal if the forecasting method is treated separately from the inventory model. We analyse the performance of the joint optimization of the modified Holt-Winters forecasting method and a stock control policy and investigate the effect of different penalties for unsatisfied demand on the total cost and fill rate of the supply chain. From the results obtained with 1,428 real time series from M3-Competition we show that an essential reduction of supply chain costs and an increase of fill rate can be achieved if we use the joint model with the modified Holt-Winters method.