Spot market profit optimization system

• US 7,908,164 B1
• Filed: 08/09/2005
• Issued: 03/15/2011
• Est. Priority Date: 08/09/2005
• Status: Active Grant

• Current Assignee: PROS Incorporated (PROS Holdings, Inc.)
• Original Assignee: SignalDemand, Inc. (PROS Holdings, Inc.)
• Inventors: Verma, Sushil Kumar, Pierce, Robert D., Troyer, Charles R., Lee, Hau Leung
• Primary Examiner(s): Hayes; John W
• Assistant Examiner(s): NELSON, FREDA ANN
• Application Number:
  US11/200,548
• Time in Patent Office: 2,044 Days
• Field of Search: 705/1, 705/7, 705/10, 705/28, 705/36, 705/400, 705/1.1, 700/100, 700/103
• US Class Current: 705/7.35
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0283 Price estimation or determination

Abstract

A profit optimization system takes account of supply-side and demand-side factors in optimizing profit for an organization. The profit optimization system uses an optimization model to optimize profit in a spot market. The model takes into account which parts the organization uses to assemble various products. Demand curves are used to characterize the quantity of each product that will be demanded as a function of price on the spot market. Supply model data is used to determine which mix of products can be sold in view of parts availability. Using the demand model and supply model data, the optimization model can recommend a set of prices to use for selling the organization'"'"'s products. The model ensures that the organization has sufficient resources available to produce the products and enforces user-supplied business rules and other constraints.

Claims

1. A method for using a profit optimization model in a computer-implemented system having a microprocessor to allow an organization that assembles multiple products from parts to optimize profit when selling the products, comprising:

populating at least one database with demand model data and supply model data using the microprocessor, wherein the demand model data includes demand curve data for each of the multiple products and wherein the supply model data includes structural attributes that define which of the parts can be used to assemble each of the products; and

using the profit optimization model on the computer-implemented system to optimize the organization'"'"'s profit in selling the products, wherein using the profit optimization model includes identifying which prices are to be used in selling each of the multiple products, wherein the price for each product is identified at least in part using the demand curve data for each product to determine what quantity of each product will be demanded at the price for each product while the supply model data is used to ensure that the quantity of each product that will be demanded at the price for each product can be manufactured using parts available to the organization, and wherein using the profit optimization model further comprises using the profit optimization model to identify which prices are to be used to sell the products based at least partly on structural attribute data defining which parts are used to form each of multiple assemblies and which assemblies are used to form each of the multiple products.

2. The method defined in claim 1 further comprising performing preoptimization operations using the profit optimization model on the computer-implemented system, wherein performing the preoptimization operations includes determining whether committed sales of the products exceed how many products can be assembled from the parts that are available.

3. The method defined in claim 1 further comprising performing preoptimization operations using the profit optimization model on the computer-implemented system, wherein performing the preoptimization operations includes determining whether committed sales of the products exceed how many products can be assembled from the parts that are available and, if the committed sales exceed how many products can be assembled, holding constant oversold quantity variables at levels that allow the profit optimization model to produce a valid profit optimization result.

4. The method defined in claim 1 further comprising performing preoptimization operations using the profit optimization model on the computer-implemented system, wherein performing the preoptimization operations includes determining whether lower bound sales quantities for each product can be assembled from the parts that are available to the organization and, if the lower bound sales quantities for each product cannot be met, repairing the lower bound sales quantities by lowering the lower bound sales quantities to levels that allow the profit optimization model to produce a valid profit optimization result.

5. The method defined in claim 1 wherein using the profit optimization model on the computer-implemented system to optimize the organization'"'"'s profit comprises producing a production plan using the supply model data and the quantities of each product that will be demanded.

6. The method defined in claim 1 wherein the profit optimization model optimizes spot market profits and wherein the parts available to the organization include parts already in inventory, the method further comprising using the profit optimization model on the computer-implemented system to optimize the organization'"'"'s profit in selling the products while ensuring that the products can be assembled using primarily the parts already in inventory.

7. The method defined in claim 1 wherein using the profit optimization model further comprises using attributed source codes to specify a quality for a generic part that is used in forming the products.

8. The method defined in claim 1 wherein using the profit optimization model further comprises using generic piece codes, generic assembly codes, and attributed source codes to specify which parts are used in forming the products.

9. The method defined in claim 1 wherein using the profit optimization model further comprises optimizing profit by performing optimization operations on only a subset of the products sold by the organization.

10. The method defined in claim 1 wherein using the profit optimization model further comprises using user-supplied business rules in optimizing the profit.

11. The method defined in claim 1 wherein using the profit optimization model further comprises using user-supplied business rules in optimizing the profit, wherein the user-supplied business rules include at least one rule on the relative pricing of the products.

12. The method defined in claim 1 wherein using the profit optimization model further comprises using the profit optimization model to enforce business rules that require that the price of one grade of meat must be higher than the price of another grade of meat.

13. The method defined in claim 1 wherein using the profit optimization model further comprises using the profit optimization model to enforce business rules that require that the price of one program of meat must be higher than the price of another program of meat.

14. The method defined in claim 1 wherein using the profit optimization model further comprises using risk parameters in the profit optimization model that quantify how much profit risk the organization wants to accept for each product.

15. The method defined in claim 1 wherein using the profit optimization model further comprises:

using at least one parameter to represent quantities of the products that have already been committed to be shipped; and

using at least one parameter to represent a starting inventory.

16. The method defined in claim 1 wherein using the profit optimization model further comprises using spot price variables to represent spot prices for the products ordered and delivered during a spot sales period.

17. The method defined in claim 1 wherein using the profit optimization model further comprises using spot quantity variables representing spot quantities for the products ordered and delivered during a spot sales period.

18. The method defined in claim 1 further comprising using demand estimation tools to extract the demand curves from sales data.