Method and system of determining and evaluating a business relationship network for forming business relationships

• US 8,249,903 B2
• Filed: 10/10/2006
• Issued: 08/21/2012
• Est. Priority Date: 10/10/2006
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Pendergraft, David R., Miller, Michael P.
• Primary Examiner(s): PATS, JUSTIN
• Application Number:
  US11/545,753
• Publication Number:
  US 20080086343A1
• Time in Patent Office: 2,142 Days
• Field of Search: 705/7.11, 705/319
• US Class Current: 705/7.11
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A collective knowledge set of business relationship information from a plurality of sources is generated. The collective knowledge set is mapped as a plurality of navigable paths forming a business relationship network between a source and a target. One or more of the paths are identified as candidate paths most likely to lead to a business relationship between the source and the target based on evaluation criteria.

Claims

1. A method of automatically determining and evaluating a business relationship network for forming business relationships, the method comprising:

generating a collective knowledge set of business relationship information from a plurality of sources;

mapping the collective knowledge set as a plurality of navigable paths forming a business relationship network between a source and a target, each navigable path of the plurality of navigable paths comprising nodes and links between at least some of the nodes;

analyzing feedback including stored historical information of successes and failures in generating business relationships of prior navigable paths from previously-generated business relationship networks;

determining evaluation criteria from the feedback and the mapping, wherein the determining of evaluation criteria includes;

determining that a value of “

n”

for n-degrees of separation between the source and the target for each of the plurality of navigable paths is less than or equal to a predetermined threshold;

assigning, based on attributes of each node, a tier value for each link in each of the plurality of navigable paths, resulting in a plurality of tier values; and

assigning each of the plurality of navigable paths to one of the plurality of tier values representing a lowest tier valued link in the respective navigable path, wherein the lowest tier valued link is least likely of all links in the respective navigable path to lead to a business relationship between the source and the target; and

identifying, by a processor of a computer system, based on the determined evaluation criteria, a subset of the plurality of navigable paths as candidate paths mapped from the collective knowledge set to generate a business relationship between the source and the target.

2. The method of claim 1, where the plurality of navigable paths comprise paths between the source and the target and one or more of the plurality of navigable paths include multiple third party nodes.

3. The method of claim 1, further comprising:

determining business guidance points from the feedback; and

notifying a user of the business guidance points, such that the user is able to follow the business guidance points to further a business objective.

4. The method of claim 3, wherein the business guidance points comprise high target participation third party nodes or third party nodes that have been successful or unsuccessful for generating business relationships.

5. The method of claim 3, wherein the business guidance points comprise instructing the user that a predetermined number of navigable paths are to be followed to achieve at least a predetermined probability of success for generating a business relationship with the target.

6. The method of claim 1, further comprising:

determining a business objective; and

using the feedback to develop at least some of the evaluation criteria to achieve the business objective.

7. The method of claim 1,

wherein the tier of each candidate path is representative of an ability to satisfy a business objective using the candidate path.

8. The method of claim 1, further comprising:

updating the evaluation criteria based on analysis of new feedback.

9. The method of claim 1, further comprising:

using the feedback to determine types of data to be collected for the collective knowledge set, such that the collected data includes data most likely to lead to a business relationship between the source and the target.

10. The method of claim 1, further comprising:

using the feedback to determine whether to add or remove one or more of the plurality of sources for the collective knowledge set.

11. The method of claim 1, wherein mapping the collective knowledge set as a plurality of navigable paths forming a business relationship network between a source and a target further comprises:

identifying third party nodes associated with the source and the target from the collective data set; and

determining the plurality of navigable paths between the source and the target, such that at least some of the navigable paths include one or more of the third party nodes.

12. The method of claim 11, wherein determining the plurality of navigable paths between the source and the target further comprises:

determining link attributes for the source and the target, wherein the link attributes describe the source and the target;

searching the collective knowledge set for nodes having link attributes matching one or more of the link attributes of the source or the target, wherein the searched nodes having link attributes matching the one or more link attributes of the source or the target are the third party nodes;

creating links between the third party nodes and the source or the target based on the matching; and

forming the plurality of navigable paths from the created links.

13. The method of claim 1, further comprising:

generating a visualization of the business relationship network including the plurality of navigable paths.

14. The method of claim 13, wherein the visualization shows n-degrees of separation for the plurality of navigable paths representing indirect business relationships.

15. The method of claim 13, wherein the visualization shows profiles for at least one of the source, the third party node, and the destination in at least one of the plurality of navigable paths.

16. The method of claim 13, wherein the visualization comprises a plurality of visualizations representing the business relationship network, wherein each of the plurality of visualizations represents a layer of the business relationship network.

17. The method of claim 13, wherein the visualization shows high target participant third party nodes.

18. The method of claim 1, wherein the plurality of sources comprises at least one of internal structured data, internal unstructured data, external structured data, and external unstructured data.

19. A computer system to determine and evaluate a business relationship network for forming business relationships, the computer system comprising:

data storage to store a collective knowledge set of business relationship information gathered from a plurality of sources, including historical information on successes and failures of using previously-generated business relationship networks to develop a business relationship;

a processor; and

a business relationship prospector comprising;

a visualization module to map the collective knowledge set as a plurality of navigable paths forming the business relationship network between a source and a target, wherein at least one of the navigable paths includes a third party node and each of the plurality of navigable paths comprising nodes and links between at least some of the nodes;

a feedback module to generate and analyze feedback, the feedback including the stored historical information of successes and failures in generating business relationships of prior navigable paths from previously-generated business relationship networks; and

a relationship finder module to;

determine evaluation criteria from the feedback and the mapping, wherein the relationship finder module is to;

determine that a value of “

n”

for n-degrees of separation between the source and the target for each of the plurality of navigable paths is less than or equal to a predetermined threshold;

assign, based on attributes of each node, a tier value for each link in each of the plurality of navigable paths, resulting in a plurality of tier values; and

assign each of the plurality of navigable paths to one of the plurality of tier values representing a lowest tier valued link in the respective navigable path, wherein the lowest tier valued link is least likely of all links in the respective navigable path to lead to a business relationship between the source and the target; and

identify, based on the determined evaluation criteria, a subset of the plurality of navigable paths as candidate paths mapped from the collective knowledge set to generate a business relationship between the source and the target.

20. The computer system of claim 19, wherein the relationship finder module is further to guide a search tool for collecting the knowledge set and perform the mapping of the collective knowledge set as the plurality of navigable paths forming the business relationship network.

21. The computer system of claim 19, wherein the business relationship prospector is further to determine business guidance points from analysis of the feedback, and notify a user of the business guidance points, such that the user is operable to use the business guidance points to further a business objective.

22. The computer system of claim 19, wherein the tier of each candidate path is representative of an ability to satisfy a business objective using the candidate path.

23. The computer system of claim 19, wherein the visualization module is further to determine at least one visual representation of the business relationship network showing the navigable paths.

24. The computer system of claim 19, wherein the relationship finder module is further to determine the plurality of navigable paths by:

determining link attributes for the source and the target describing the source and the target;

searching the collective knowledge set for nodes having link attributes matching one or more of the link attributes of the source or the target, wherein the searched nodes having link attributes matching the one or more link attributes of the source or the target are third party nodes;

creating links between the third party nodes and the source or the target based on the matching; and

forming the plurality of navigable paths from the created links.

25. A computer program embedded on a non-transitory computer readable storage medium, the computer program including instructions that when executed by a processor implement a method comprising:

generating a collective knowledge set of business relationship information from a plurality of sources;

mapping the collective knowledge set as a plurality of navigable paths forming a business relationship network between a source and a target, each navigable path of the plurality of navigable paths comprising nodes and links between at least some of the nodes;

analyzing feedback including stored historical information of successes and failures in generating business relationships of prior navigable paths from previously-generated business relationship networks;

determining evaluation criteria from the feedback and the mapping, wherein the determining of evaluation criteria includes;

determining that a value of “

n”

for n-degrees of separation between the source and the target for each of the plurality of navigable paths is less than or equal to a predetermined threshold;

assigning, based on attributes of each node, a tier value for each link in each of the plurality of navigable paths, resulting in a plurality of tier values; and

assigning each of the plurality of navigable paths to one of the plurality of tier values representing a lowest tier valued link in the respective navigable path, wherein the lowest tier valued link is least likely of all links in the respective navigable path to lead to a business relationship between the source and the target; and

identifying, by a processor of a computer system, based on the determined evaluation criteria, a subset of the plurality of navigable paths as candidate paths mapped from the collective knowledge set to generate a business relationship between the source and the target.

26. The computer program embedded on a computer readable storage medium of claim 25, wherein the plurality of navigable paths comprise paths between the source and the target and one or more of the paths include multiple third party nodes.

27. The computer program embedded on a computer readable storage medium of claim 25, wherein the method further comprises:

determining business guidance points from the feedback; and

notifying a user of the business guidance points, such that the user is operable to follow the business guidance points to further a business objective.

28. The computer program embedded on a computer readable storage medium of claim 25, wherein the method further comprises:

using the feedback to develop at least some of the evaluation criteria to achieve a business objective.

29. The computer program embedded on a computer readable storage medium of claim 28,

wherein the tier of each candidate path is representative of an ability to satisfy a business objective using the candidate path.

30. The computer program embedded on a computer readable storage medium of claim 25, wherein mapping the collective knowledge set as a plurality of navigable further comprises:

determining link attributes for the source and the target, wherein the link attributes describe the source and the target;

searching the collective knowledge set for nodes having link attributes matching one or more of the link attributes of the source or the target, wherein the searched nodes having link attributes matching the one or more link attributes of the source or the target are third party nodes;

creating links between the third party nodes and the source or the target based on the matching; and

forming the plurality of navigable paths from the created links.