Generating an optimized price schedule for a product

Abstract

Generating a price schedule involves generating a graph (50) having paths that include states (52) with values (54, 56, 58). The graph (50) is generated by determining the values (56, 58) of a successor state (52) from the values (56, 58) of a predecessor state (52). An optimal path is selected, and a price schedule is determined from the optimal path. Computing an elasticity curve involves having a demand model, values for demand model, and filter sets that restrict the values. Elasticity curves are determined by filtering the values using filter sets, and calculating the elasticity curve using the demand model. An best-fitting elasticity curve is selected. Adjusting a demand forecast value (56) includes estimating an inventory and a demand at a number of locations (24). An expected number of unrealized sales at each location (24) is calculated. An sales forecast value (56) is determined according to the expected number.

Description

RELATED APPLICATION [0001] This application claims benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application Ser. No. 60 / 238,676, filed Oct. 6, 2000.TECHNICAL FIELD OF THE INVENTION [0002] This invention relates in general to commercial environments, and more particularly to generating an optimized price schedule for a product. BACKGROUND OF THE INVENTION [0003] An important decision for a business to make is determining the prices of products, goods, or services offered by the business. Pricing decisions are important to a business's success or failure, since these decisions may have a critical impact on customer demand, profitability, and business operations. Informed pricing decisions, however, may be difficult to make, since these decisions may need to reflect a large number of business objectives and operating constraints, and may need to be made for a large number of items across a large number of sales locations. Moreover, pricing decisions may need to be frequently up...

AI Technical Summary

Benefits of technology

The present invention provides a method for generating an optimized price schedule by generating a transition graph with paths and states, and calculating the price schedule by filtering the values of the states using a demand model and elasticity curve. This method allows for the efficient generation of an optimized price schedule that maximizes business objectives while satisfying business constraints. The invention also takes into account the elasticity of a product and the uncertainty of a demand forecast or elasticity model to improve the accuracy of the optimization. The invention may be used to compute an optimal sequence of product markdowns, determine optimal start and end dates of a markdown horizon, and guide the decision of how many units of which product should be acquired for subsequent sale. The invention is well-suited for modern commercial environments such as those associated with marking down the price of a product to achieve a predetermined inventory target.

Problems solved by technology

Informed pricing decisions, however, may be difficult to make, since these decisions may need to reflect a large number of business objectives and operating constraints, and may need to be made for a large number of items across a large number of sales locations.

Optimizing price schedules, however, may be computationally difficult.

As a result, previous techniques for generating an optimized price schedule have been inadequate.

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