US 5,596,493 A · Method for classifying sale amount characteristics, method for predicting sale volume, method for ordering for restocking, system for classifying sale amount characteristics and system for ordering for restocking

Abstract

POS data are entered at step S1. The input POS data are arranged and those data for a day on which there was no stock at the store opening time and for a day on which the goods are out of stock at the store closure time are discarded to formulate data sets of the daily sale amounts for individual goods. At step S3, non-routine goods are discarded. At step S4, basic statistic values of the goods, such as mean value, standard deviation, maximum value, minimum value, skewness value, kurtosis value, Geary value etc. of the daily sale amounts of the goods are calculated. At step S5, the goods are classified into one of preset plural types, such as Poisson type, normal type, causal type and other type. Besides, an optimum amount for restocking order is found on the basis of the class types.

Claims16

Dependent claims

A sale amount prediction method comprising the steps of:

entering POS data into a point-of-sale terminal;
calculating, within a computer and based upon the entered POS data, sale amount data of the individual goods for a predetermined time period;
calculating, within the computer and based upon the calculated sale amount data, a plurality of basic statistic parameters of daily sale amounts of said individual goods;
classifying, within the computer and based on said calculated basic statistic values, said individual goods by determining into which of a Poisson type, a normal type, a causal type, and another type not belonging to one of these types, the daily sale amount of the individual goods belongs;
and
predicting the sale amount of the individual goods based upon a characteristic value of the type into which the daily sale amount of the individual goods is classified.

3 more elements

A sale amount prediction system comprising:

POS data entry means for entering POS data;
sale amount data calculating means for calculating sale amount data of individual goods over a predetermined time period based on POS data not entered via said POS data entry means;
basic statistic parameter calculating means for calculating basic statistic parameters of daily sale amounts of said individual goods based on the sale amount data of said individual goods calculated by said sale amount calculating means;
and
means for classifying said individual goods by verifying, based upon the basic statistic parameters calculated by said basic statistic parameter calculating means, into which of a Poisson type, a normal type, a casual type, and an other type not belonging to these types, belongs the daily sale amount of the individual articles, to classify the individual goods;
and
sale amount prediction means for predicting a sale amount of the individual goods based upon characteristic values of the type into which the individual goods are classified by said classifying means.

4 more elements

Dependencies are inferred from the claim text.

Method for classifying sale amount characteristics, method for predicting sale volume, method for ordering for restocking, system for classifying sale amount characteristics and system for ordering for restocking

Life of this patent

Method for classifying sale amount characteristics, method for predicting sale volume, method for ordering for restocking, system for classifying sale amount characteristics and system for ordering for restocking

Life of this patent

Abstract

Claims16