An empirical investigation of comparative performance of approximate and exact corrections of the bias in Croston's method in forecasting lumpy demand

A positive bias in Croston's method, which had been developed to forecast intermittent demand, was reported by Syntetos and Boylan (2001). They proposed an approximate correction. Subsequently, Shale et al. (2006) proposed an 'exact' correction. Both corrections were derived analytically. The mathematical analysis establishes the superiority of the exact correction over both Croston's method and the approximate correction. We empirically investigate whether or not there are significant improvements in statistical forecast accuracy as well as inventory control performance obtained by applying the approximate or exact correction when forecasting lumpy demand. Using extensive simulation experiments, we find overall superior forecast accuracy of the bias correction methods over both simple exponential smoothing and Croston's methods. However, the exact correction yielded the same or only marginally better accuracy measures compared with the approximate correction. Moreover, in terms of inventory control performance, we observe marginal differences in inventory on hand and backlogs.