METHODS AND SYSTEMS FOR FORECASTING PRODUCT DEMAND FOR SLOW MOVING PRODUCTS

摘要

An improved method for forecasting and modeling product demand for a slow moving product. The method includes the steps of maintaining a database of historical product demand information, calculating the average rate of sales (ARS) for a product from the historical demand information corresponding to the product, determining if the product is a slow moving product (SMP), and if the product is a SMP modifying the ARS using a mean reverting forecast method called GARCH (Generalized Autoregressive Conditional Heteroscedasticity) to accurately model the expected demand and variability of the slow moving product.