Systems and methods for recommending business decisions utilizing weather driven demand data and opportunity and confidence measures

• US 7,184,965 B2
• Filed: 10/29/2003
• Issued: 02/27/2007
• Est. Priority Date: 10/29/2003
• Status: Active Grant

• Current Assignee: Planalytics, Inc.
• Original Assignee: Planalytics, Inc.
• Inventors: Willen, Michael, Walsh, Paul, Estornell, David, Kowa, Mike, Pearson, Doug, Fox, Frederic
• Primary Examiner(s): Jeanty; Romain
• Assistant Examiner(s): Jarrett; Scott L.
• Application Number:
  US10/695,445
• Publication Number:
  US 20050096947A1
• Time in Patent Office: 1,217 Days
• Field of Search: 705/7, 705/8, 705/10
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

Systems and methods to generate business recommendations for specific business actions based on weather element forecasts and known relationships between a business activity and weather elements are provided. The system includes a confidence level filter, an opportunity matrix filter, a weather decision point generator, a business rule recommendation engine and a business rule knowledge database. Methods to generate a business recommendation for a business activity are also provided. The methods include receiving weather driven demand data, assigning opportunity measures to each of the data points, identifying weather decision points based on opportunity measures, and applying business weather rules to the weather decision points to generate business recommendations. In a further feature, a weather element relationship and/or a weather element forecast confidence level is assigned to each data point within the weather driven demand data. These confidence levels are then factored in to determine weather decision points.

Claims

1. A weather-based decision system for providing business recommendations based on a set of weather driven demand data, comprising:

a confidence level filter configured to assign a first confidence level to data within the set of weather driven demand data based on a probability that a weather element forecast is accurate and a second confidence level to said data within the set of the weather driven demand data based on a strength of a correlation between a product or service being considered and one or more weather elements;

an opportunity matrix filter coupled to said confidence level filter and configured to assign an opportunity level to said data within the set of weather driven demand data based upon said first confidence level and said second confidence level;

a weather decision point generator coupled to said opportunity matrix filter and configured to identify a weather driven demand data point of said data within the set of the weather driven demand data as a weather decision point;

a business rule recommendation engine coupled to said weather decision point generator and configured to provide a business recommendation; and

a business rules knowledge database coupled to said business rule recommendation engine and configured to contain business rules;

wherein the weather driven demand data indicates how a business activity is influenced by said one or more weather elements.

2. The weather-based decision system of claim 1, further comprising a graphical user interface configured to display the weather driven demand data, said weather decision points, and said business recommendation.

3. The weather-based decision system of claim 1, further comprising an external database interface configured to access one or more external databases.

4. The weather-based decision system of claim 1, wherein said weather decision point generator is configured to identify said weather decision point by examining said first confidence level, said weather element forecast, and said opportunity level for said weather driven demand data point.

5. The weather-based decision system of claim 1, wherein said probability is based on a relationship between the weather element forecast and at least one weather element prediction.

6. The weather-based decision system of claim 5, wherein said at least one weather element prediction is based upon trends in weather element measurements.

7. A method of generating a business recommendation for a business activity based on one or more weather elements, comprising:

(a) receiving weather driven demand data for a set of time periods;

(b) assigning a first confidence level to the weather driven demand data based on a strength of a correlation between a product or service being considered and the one or more weather elements;

(c) assigning a second confidence level to the weather driven demand data based on a probability that a weather element forecast is accurate;

(d) assigning an opportunity level to the weather driven demand data based upon the first confidence level and the second confidence level;

(e) identifying a weather driven demand data point of the set of the weather driven demand data as a weather decision point based on the first confidence level, the second confidence level, and the opportunity level associated with the weather driven demand data point; and

(f) applying business weather rules to the weather decision point identified in step (e), thereby generating the business recommendation;

wherein the weather driven demand data indicates how the business activity is influenced by the one or more weather elements.

8. The method of claim 7, wherein step (a) comprises:

receiving a plurality of weather element relationships for the business activity.

9. The method of claim 7, further comprising:

(g) assigning the first confidence level by a geographic location for the weather driven demand data, wherein step (e) further comprises using the first confidence level to identify the weather decision point.

10. The method of claim 7, further comprising:

(g) assigning the first confidence level by a time period for the weather driven demand data, wherein step (e) comprises using the weather first confidence level to identify the weather decision point.

11. The method of claim 7, further comprising:

(g) assigning the second confidence level by a geographic location, wherein step (e) comprises using the second confidence level to identify the weather decision point.

12. The method of claim 7, further comprising:

(g) assigning the second confidence level by a time period, wherein step (e) further comprises using the second confidence level to identify the weather decision point.

13. The method of claim 7, wherein step (e) further comprises using opportunity matrix rules generated from historical business activity results that were influenced by the one or more weather elements to provide the opportunity level.

14. The method of claim 7, wherein step (c) further comprises using a relationship between a weather element forecast and at least one weather element prediction to determine the second confidence level.

15. The method of claim 14, wherein step (c) further comprises using trends in weather element measurements to determine the at least one weather element prediction.