US 2010/0169166 A1 · DATA QUALITY TESTS FOR USE IN A CAUSAL PRODUCT DEMAND FORECASTING SYSTEM

Abstract

An improved method for forecasting and modeling product demand for a product. The forecasting methodology employs a causal methodology, based on multiple regression techniques, to model the effects of various factors on product demand, and hence better forecast future patterns and trends, improving the efficiency and reliability of the inventory management systems. The improved method identifies linear dependent causal factors and removes redundant causal factors from the regression analysis. A product demand forecast is generated by blending forecast or expected values of the non-redundant causal factors together with corresponding regression coefficients determined through the analysis of historical product demand and factor information.

Claims6

Dependent claims

A computer-implemented method for forecasting product demand for a product, the method comprising the steps of:

maintaining, on a computer, an electronic database of historical product demand information and historical causal factor information for a plurality of factors influencing demand for said product;
analyzing, by said computer, said causal factor information to identify non-redundant causal factors;
analyzing, by said computer, said historical product demand information and said historical causal factor information for said product to determine a plurality of regression coefficients corresponding to said non-redundant causal factors;
and
blending, by said computer, said plurality of regression coefficients and future values for said corresponding non-redundant causal factors to determine a product demand forecast for said product;.

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Dependencies are inferred from the claim text.

Data quality tests for use in a causal product demand forecasting system

Life of this patent

Data quality tests for use in a causal product demand forecasting system

Life of this patent

Abstract

Claims6