A modified Teunter-Syntetos-Babai method for intermittent demand forecasting

Intermittent demand refers to the specific demand pattern with frequent periods of zero demand. It occurs in a variety of industries including industrial equipment, automotive and specialty chemicals. In some industries or some sectors of industry, even majority of products are in intermittent demand pattern. Due to the usually small and highly variable demand sizes, accurate forecasting of intermittent demand has always been challenging. However, accurate forecasting of intermittent demand is critical to the effective inventory management. In this study we present a band new method - modified TSB method for the forecasting of intermittent demand. The proposed method is based on TSB method, and adopts similar strategy, which has been used in mSBA method to update demand interval and demand occurrence probability when current demand is zero. To evaluate the proposed method, 16289 daily demand records from the M5 data set that are identified as intermittent demands according to two criteria, and an empirical data set consisting three years’ monthly demand history of 1718 medicine products are used. The proposed mTSB method achieves the best results on MASE and RMASE among all comparison methods on the M5 data set. On the empirical data set, the study shows that mTSB attains an ME of 0.07, which is the best among six comparison methods. Additionally, on the MSE measurement, mTSB shows a similar result as SES, both of which outperform other methods.