Forecasting of intermittent demands under the risk of inventory obsolescence

Abstract

AbstractCroston and the other related methods, such as Syntetos‐Boylan approximation (SBA), are the most popular methods recommended in the literature for intermittent demand forecasting. However, these conventional methods are not considered suitable in inventory obsolescence as they do not update their forecast in the periods of zero demand. Therefore, in order to add to the methods suitable for the inventory obsolescence issue, we propose a new method that imparts flexibility to the SBA method. The proposed method updates forecast each period by the use of distinct smoothing constants for interdemand intervals. The method is further examined extensively on a simulated dataset considering gradual and abrupt obsolescence and an empirical dataset from the automotive sector. The study is not limited to assessing the forecasting accuracy but also focuses upon the inventory performance of the considered methods. The study results indicate the effectiveness of the proposed method, particularly under increased risk of obsolescence.