Econometric optimization engine

• US 7,302,410 B1
• Filed: 12/22/2000
• Issued: 11/27/2007
• Est. Priority Date: 12/22/2000
• Status: Expired due to Fees

• Current Assignee: Acoustic, L.P.
• Original Assignee: DemandTec Inc. (International Business Machines Corporation)
• Inventors: Venkatraman, Krishna, Lee, Hau, Delurgio, Phil, Neal, Michael, Valentine, Suzanne
• Primary Examiner(s): PATEL, JAGDISH
• Application Number:
  US09/741,959
• Time in Patent Office: 2,531 Days
• Field of Search: 705/36, 705/1, 705/26
• US Class Current: 705/35
• CPC Class Codes: G06Q 20/201 Price look-up processing, e.g. updating
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

A preferred set of prices for a plurality of products, generally demand coefficients is provided. Cost data including activity-based costs is also received. A preferred set of prices that will provided a local optimum for the preferred set of prices which maximizes profit is then determined. In one embodiment, a sales model and a cost model are created. A plurality of rules is specified. The preferred set of prices is then determined based on the sales model, the cost model, and the plurality of rules.

Claims

1. A computer-implemented method for determining a preferred set of prices for a plurality of products, the method being implemented as a plurality of program instructions in a computer system, the method comprising:

receiving, using the computer system, a plurality of demand coefficients;

receiving, using the computer system, known cost data including activity-based costs;

inputting, using the computer system, missing or incomplete cost data to give inputted cost data;

combining using the computer system, said known cost data with said inputted cost data to give a combined cost data set;

generating, using the computer system, a sales model from the plurality of demand coefficients;

generating, using the computer system, a cost model from the combined cost data set, and wherein the activity-based costs include variable costs and fixed costs, further wherein said cost model determines a total cost for each product in a given demand group in a given store for a given time period by computing a cost for each selected costing activity;

receiving, using the computer system, a set of actual prices;

initializing, using the computer system, a set of incumbent prices to the set of actual prices;

generating a local optimum by applying, using the computer system, the set of incumbent prices to the sales model and the cost model wherein the local optimum for the preferred set of prices maximizes profit; and

generating the preferred set of prices by applying, using the computer system, the local optimum prices to the sales model and the cost model in an iterative manner until the preferred set of prices is reached.

2. The method, as recited in claim 1, further comprising specifying, using the computer system, a plurality of rules, and wherein the generation of the preferred set of prices comprises:

determining, using the computer system, a set of starting prices; and

wherein the generation of the local optimum for the preferred set of prices for the plurality of products includes complying with the plurality of rules, further wherein said plurality of rules constrain the preferred set of prices to fall within limits conforming to business strategy.

3. The method, as recited in claim 1, wherein the cost data is from an individual store and the preferred set of prices is generated for said individual store.

4. The method, as recited in claim 1, wherein the cost data is from a cluster of stores and the preferred set of prices is generated for said cluster of stores.

5. The method, as recited in claim 1, further comprising:

generating, using the computer system, equivalent prices for said plurality of products by dividing individual product prices by a standardized unit of measure; and

incorporating, using the computer system, said equivalent prices into said sales model.

6. The method, as recited in claim 1, wherein said demand group is a set of highly substitutable products.

7. An apparatus for determining a preferred set of prices for a plurality of products, the apparatus comprising:

an econometric engine configured to receive a plurality of demand coefficients and to generate a sales model from the plurality of demand coefficients;

a financial engine configured to receive known cost data including activity-based costs and to impute missing or incomplete cost data to give imputed cost data, the financial engine also configured to combine said known cost data with said imputed cost data to give a combined cost data set, the financial engine further configure to generate a cost model from the combined cost data set, and wherein the activity-based costs include variable costs and fixed costs, further wherein said cost model determines a total cost for each product in a given demand group in a given store for a given time period by computing a cost for each selected costing activity; and

an optimization engine configured to receive a set of actual prices and to initialize a set of incumbent prices to the set of actual prices, the optimization engine also configured to generate a local optimum by applying the set of incumbent prices to the sales model and the cost model wherein the local optimum for the preferred set of prices maximizes profit, the optimization engine further configured to generate the preferred set of prices by applying the local optimum prices to the sales model and the cost model in an iterative manner until the preferred set of prices is reached.

8. The apparatus as recited in claim 7, wherein the optimization engine is further configured to specify a plurality of rules, and wherein the generation of the preferred set of prices includes determining a set of starting prices;

and wherein the generation of the local optimum for the preferred set of prices for the plurality of products includes complying with the plurality of rules, further wherein said plurality of rules constrain the preferred set of prices to fall within limits conforming to business strategy.

9. The apparatus as recited in claim 7, wherein the cost data is from an individual store and the preferred set of prices is generated for said individual store.

10. The apparatus as recited in claim 7, wherein the cost data is from a cluster of stores and the preferred set of prices is generated for said cluster of stores.

11. The apparatus as recited in claim 7, wherein the econometric engine is further configured to generate equivalent prices for said plurality of products by dividing individual product prices by a standardized unit of measure, and to incorporate said equivalent prices into said sales model.

12. The apparatus as recited in claim 7, wherein said demand group is a set of highly substitutable products.