System, method, and computer program product for forecasting weather-based demand using proxy data

• US 20040225556A1
• Filed: 11/12/2003
• Published: 11/11/2004
• Est. Priority Date: 01/18/1996
• Status: Active Grant

• Current Assignee: Planalytics, Inc.
• Original Assignee: Planalytics, Inc.
• Inventors: Walsh, Paul E., Kirk, William E., Miller, Eli H., Willen, Michael A., Estornell, David G.
• Granted Patent: US 7,844,517 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

Weather metrics data and a weather factor relationship knowledgebase are received and used to forecast the weather-based demand. The weather factor relationship knowledgebase can be a weather-impact model. The weather-impact model can comprise at least one of an empirical scoring matrix, a weather indices template, and a proxy model conditions template. The weather-impact model can be derived from an analysis of normalized proxy sales history data. Optionally, the weather-based demand can be scaled, deaggregated, or both.

Claims

1. A system for forecasting weather-based demand, comprising:

a recombination processor;

wherein;

said recombination processor is configured to receive weather metric data;

said recombination processor is configured to receive a weather factor relationship knowledgebase; and

said recombination processor is configured to produce normalized weather factor metric data.

2. The system of claim 1, wherein said weather factor relationship knowledgebase is a weather-impact model.

3. The system of claim 2, wherein said weather-impact model comprises at least one of an empirical scoring matrix, a weather indices template, and a proxy model conditions template.

4. The system of claim 2, wherein said weather-impact model is derived from an analysis of normalized proxy sales history data.

5. The system of claim 4, wherein said normalized proxy sales history data are derived from at least one of old sales history data for a product from an entity, sales history data for said product from a second entity, sales history data for said product from an outside source, sales history data for a category that includes said product, and sales history data for a proxy product that has a similar weather-based demand relationship as said product.

6. The system of claim 1, further comprising a volatility scaling processor;

wherein;

said volatility scaling processor is configured to receive said normalized weather factor metric data;

said volatility scaling processor is configured to receive volatility scale factor data; and

said volatility scaling processor is configured to produce scaled weather factor metric data.

7. The system of claim 6, further comprising a deaggregation processor;

wherein;

said deaggregation processor is configured to receive said scaled weather factor metric data;

said deaggregation processor is configured to receive deaggregation data; and

said deaggregation processor is configured to produce deaggregated weather factor metric data.

8. The system of claim 1, further comprising a deaggregation processor;

wherein;

said deaggregation processor is configured to receive said normalized weather factor metric data;

said deaggregation processor is configured to receive deaggregation data; and

said deaggregation processor is configured to produce deaggregated weather factor metric data.

9. A method for forecasting weather-based demand, comprising the steps of:

(1) receiving weather metrics data;

(2) receiving a weather factor relationship knowledgebase; and

(3) forecasting the weather-based demand by using the weather metrics data and the weather factor relationship knowledgebase.

10. The method of claim 9, wherein the weather factor relationship knowledgebase is a weather-impact model.

11. The method of claim 10, wherein the weather-impact model comprises at least one of an empirical scoring matrix, a weather indices template, and a proxy model conditions template.

12. The method of claim 10, wherein the weather-impact model is derived from an analysis of normalized proxy sales history data.

13. The method of claim 9, further comprising the step of:

scaling the weather-based demand.

14. The method of claim 9, further comprising the step of:

deaggregating the weather-based demand.

15. A computer program product for forecasting weather-based demand, said computer program product having computer program code means embodied in a computer useable medium, said computer program code means comprising:

a first program code means for receiving weather metrics data;

a second program code means for receiving a weather factor relationship knowledgebase; and

a third program code means for forecasting the weather-based demand by using the weather metrics data and the weather factor relationship knowledgebase.

16. The computer program product of claim 15, wherein the weather factor relationship knowledgebase is a weather-impact model.

17. The computer program product of claim 16, wherein the weather-impact model comprises at least one of an empirical scoring matrix, a weather indices template, and a proxy model conditions template.

18. The computer program product of claim 16, wherein the weather-impact model is derived from an analysis of normalized proxy sales history data.

19. The computer program product of claim 15, further comprising:

a fourth program code means for scaling the weather-based demand.

20. The computer program product of claim 15, further comprising:

a fourth program code means for deaggregating the weather-based demand.