Systems and methods for recommending business decisions influenced by weather elements

• US 20050096947A1
• Filed: 10/29/2003
• Published: 05/05/2005
• 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
• Granted Patent: US 7,184,965 B2
• Time in Patent Office: Days
• 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 for assigning a confidence level to data within the set of weather driven demand data;

an opportunity matrix filter coupled to said confidence level filter for assigning an opportunity level to data within the set of weather driven demand data;

a weather decision point generator coupled to said opportunity matrix filter for generating weather decision points;

a business rule recommendation engine coupled to said weather decision point generator for providing a business recommendation; and

a business rules knowledge database coupled to said business rule recommendation engine that contains business rules.

2. The weather-based decision system of claim 1, further comprising a graphical user interface for displaying weather driven data, weather decision points and business recommendations generated by said business rule recommendation engine.

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

4. The weather-based decision system of claim 1, wherein said confidence level filter assigns a confidence level to weather driven demand data based on a probability that a weather element forecast is accurate.

5. The weather-based decision system of claim 1, wherein said confidence level filter assigns a confidence level to weather driven demand data based on the strength of the correlation between a product being considered and one or more weather elements.

6. The weather-based decision system of claim 1, wherein said weather decision point generator generates weather decision points by examining a weather element forecast confidence level, a weather element forecast and opportunity level for a weather driven demand data point.

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

(a) receiving a weather element relationship for a business activity;

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

(c) assigning opportunity measures to each of the data points within the weather driven demand data;

(d) identifying weather decision points based on opportunity measures associated with a weather driven demand data point; and

(e) applying business weather rules to the weather decision points identified in step (d), thereby generating the business recommendation.

8. The method of claim 7, further comprising:

(f) assigning weather element relationship confidence levels for weather driven demand data, wherein step (d) further comprises using the weather element relationship confidence levels to identify weather decision points.

9. The method of claim 7, further comprising:

(f) assigning a weather element forecast confidence level, wherein step (d) further comprises using the weather element forecast confidence levels to identify weather decision points.