Systems and methods for analyzing performance of an entity

• US 9,996,229 B2
• Filed: 12/15/2014
• Issued: 06/12/2018
• Est. Priority Date: 10/03/2013
• Status: Active Grant

• Current Assignee: Palantir Technologies Incorporated
• Original Assignee: Palantir Technologies Incorporated
• Inventors: Erenrich, Daniel, Mukherjee, Anirvan, Dwyer, William
• Primary Examiner(s): Lu, Hua
• Application Number:
  US14/571,060
• Publication Number:
  US 20150100907A1
• Time in Patent Office: 1,275 Days
• Field of Search: None
• CPC Class Codes: G06F 3/0484 for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• CPC Class Codes: G06F 40/143 Markup, e.g. Standard Generalized Markup Language [SGML] or Document Type Definition [DTD]
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/06395 Quality analysis or management

Abstract

Systems and methods are provided for analyzing entity performance. In accordance with one implementation, a method is provided that includes receiving data associated with a geographic region and transforming the received data into an object model. The method also includes analyzing the object model to associate the received data with a plurality of entities and to associate the received data with a plurality of sub-geographic regions of the geographic region. The method also includes applying a prediction model to the plurality of sub-geographic regions using the object model to determine a predicted performance for at least one entity of the plurality of entities. Further, the method includes determining actual performance for the at least one entity and providing a user interface that includes information associated with the predicted performance, the actual performance, or a combination of the predicted performance and the actual performance.

Claims

1. A system for analyzing organizational entity performance, the system comprising:

a memory device that stores a set of instructions;

one or more processors configured to execute the set of instructions that cause the one or more processors to;

receive data associated with a geographic region, the geographic region including a plurality of distinct merchant stores, wherein the received data is transformed into an object model using a schema map and an ontology, the object model comprising objects, properties and relationships;

analyze the object model to associate the received data with an organizational entity and to associate the received data with a plurality of sub-geographic regions of the geographic region;

apply a prediction model to the plurality of sub-geographic regions using the object model to determine a predicted performance associated with the organizational entity; and

provide a user interface that includes information associated with the predicted performance.

2. The system of claim 1 wherein the received data includes at least one of financial transaction data, consumer data associated with the geographic region, or entity data associated with the organizational entity.

3. The system of claim 1 wherein the user interface includes:

a representation of the geographic region;

a representation of locations of the organizational entity overlayed on the geographic region; and

a representation of the sub-geographic regions overlayed on the geographic region.

4. The system of claim 1 wherein the predicted performance includes determining the predicted spend amount associated with the organizational entity based on the object model.

5. The system of claim 4 wherein the user interface further includes:

a representation of the predicted spend amount for the sub-geographic regions associated with the organizational entity.

6. The system of claim 1 wherein the user interface further includes:

a representation of the predicted performance associated with the organizational entity.

7. The system of claim 1 wherein the one or more processors are further configured to receive a placement of a hypothetical entity location of the organizational entity wherein applying the prediction model further uses the placement of the hypothetical entity location to determine a predicted performance associated with the organizational entity.

8. The system of claim 7 wherein the one or more processors are further configured to determine the predicted performance for the hypothetical entity location.

9. The system of claim 1 wherein the one or more processors are further configured to determine a placement for a hypothetical entity location of the organizational entity based on the object model.

10. A method for analyzing organizational entity performance, the method being performed by one or more processors of one or more computers and comprising:

receiving data associated with a geographic region, the geographic region including a plurality of distinct merchant stores, wherein the received data is transformed into an object model using a schema map and an ontology, the object model comprising objects, properties and relationships;

analyzing the object model to associate the received data with an organizational entity and to associate the received data with a plurality of sub-geographic regions of the geographic region;

applying a prediction model to the plurality of sub-geographic regions using the object model to determine a predicted performance associated with the organizational entity; and

providing a user interface that includes information associated with the predicted performance.

11. The method of claim 10 wherein the received data includes at least one of financial transaction data, consumer data associated with the geographic region, or entity data associated with the at least one organizational entity.

12. The method of claim 10 wherein the user interface includes:

a representation of the geographic region;

a representation of locations of the organizational entity overlayed on the geographic region; and

a representation of the sub-geographic regions overlayed on the geographic region.

13. The method of claim 10 wherein predicted performance includes determining the predicted spend amount associated with the organizational entity based on the object model.

14. The method of claim 13 wherein the user interface further includes:

a representation of the predicted spend amount for the sub-geographic regions associated with the organizational entity location.

15. The method of claim 10 further including receiving a placement of a hypothetical entity location of the organizational entity and wherein applying the prediction model further uses the placement of the hypothetical entity location to determine a predicted performance associated with the organization entity.

16. The method of claim 15 further including determining the predicted performance for the hypothetical entity location.

17. The method of claim 10 further including determining a placement for a hypothetical entity location of an organizational entity based on the object model.

18. A non-transitory computer readable medium that stores a set of instructions that are executable by at least one processor of one or more computers to cause the one or more computers to analyze organizational entity performance, the set of instructions causing the one or more computers to:

receive data associated with a geographic region, the geographic region including a plurality of distinct merchant stores, wherein the received data is transformed into an object model using a schema map and an ontology, the object model comprising objects, properties and relationships;

analyze the object model to associate the received data with at least one organizational entity and to associate the received data with a plurality of sub-geographic regions of the geographic region;

apply a prediction model to the plurality of sub-geographic regions using the object model to determine a predicted performance associated with the organizational entity; and

provide a user interface that includes information associated with the predicted performance.

19. The non-transitory computer readable medium of claim 18 further comprising instructions executable for the at least one processor of the one or more computers to cause the one or more computers to perform:

receiving a placement of a hypothetical entity location of the organizational entity and wherein applying the prediction model further uses the placement of the hypothetical entity location to determine a predicted performance associated with the organization entity.

20. The non-transitory computer readable medium of claim 18 further comprising instructions executable for the at least one processor of the one or more computers to cause the one or more computers to perform:

determining the predicted performance for the hypothetical entity location.