پیش بینی حاصل تقسیم قابل پیش بینی برای مدیریت موجودی

Our empirical study of a large dataset of time series from a Fortune 100 firm found that QQ in the holdout sample can be predicted using just three variables from the estimation sample. Surprisingly, many highly touted time series metrics (e.g., the coefficient of variation and approximate entropy) and forecast accuracy metrics (e.g., the mean absolute percentage error) were not good predictors of QQ. We then validated this model on four additional datasets. This research contributes both to the research literature and to managers who need to decide whether an independent demand item should be managed with a TPOP or reorder point system.