DECISION SUPPORT SYSTEM AND METHOD FOR DISTRIBUTED DECISION MAKING FOR OPTIMAL HUMAN RESOURCE DEPLOYMENT

• US 20110106711A1
• Filed: 10/30/2009
• Published: 05/05/2011
• Est. Priority Date: 10/30/2009
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Roy, Sambuddha, Kulkarni, Shivaram, Soni, Soujanya, Thomas, Simon, Krishnan, Pavithra, Kambhatla, Nandakishore, Vaidya, Milind V., Goyal, Munish, Parija, Gyana R., Lotlikar, Rohit Manohar, Majumdar, Debapriyo
• Granted Patent: US 8,818,832 B2
• Time in Patent Office: Days
• US Class Current: 705/80
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: G06Q 50/188 Electronic negotiation

Abstract

A decision support tool which takes a high-level view of supply and demand in the realm of labor resources and produces globally-optimal recommendations for assignment of practitioners to open seats. These assignments preferably optimize a utility function composed of different business metrics and can be customizable for different organizations and priorities.

Claims

1. A system comprising:

a decision support tool comprising one or more processors and one or more modules executable by the one or more processors, the one or more modules comprising;

computer code configured to assimilate open seat data and practitioner data;

computer code configured to transform the open seat data and practitioner data into seat attributes and practitioner attributes;

computer code configured to assess viability of matching practitioners with seats based on predetermined matching criteria;

computer code configured determine preferred matches based on assessed viability; and

computer code configured to deliver the preferred matches to a user interface.

2. The system according to claim 1, wherein the one or more modules further comprise computer code configured for assessing viability of matching practitioners with seats based on fitness scores.

3. The system according to claim 2, wherein the one or more modules further comprise computer code configured for assessing viability of matching practitioners with seats based on text matching, the text matching contributing to the fitness scores.

4. The system according to claim 3, wherein the text matching comprises comparing text related to practitioners and seats, respectively, and yielding a result corresponding to a degree of text matching.

5. The system according to claim 4, wherein the text matching further comprises comparing text related to distinct categories relating to practitioners and seats, and assigning a comparative weight to each category.

6. The system according to claim 3, further comprising computer code configured for employing a substitutability matrix, the substitutability matrix indicating prescribed equivalencies between pairs of differing text vectors.

7. The system according to claim 2, further comprising computer code configured for assigning a lower threshold for fitness scores and discarding results not meeting the lower threshold.

8. The system according to claim 1, wherein the one or more modules further comprise computer code configured for determining preferred matches via integer programming.

9. The system according to claim 8, wherein the one or more modules further comprise computer code configured for determining preferred matches via optimization of business metrics.

10. The system according to claim 9, wherein the seat attributes include a prescribed timescale for effecting a match, and the business metrics are configured to assert a preference for overdue seats with respect to the prescribed timescale.

11. A system comprising:

a user interface comprising one or more processors and one or more modules executable by the one or more processors, the one or more modules comprising;

computer code configured to receive data relating to preferred matches of practitioners and open seats; and

computer code configured to display at least one optimal match corresponding to a practitioner and a seat and, adjacent thereto, cross-match information corresponding to at least one other viable seat corresponding to a practitioner.

12. The system according to claim 11, the one or more modules further comprising computer code configured to display, based on a fitness score rank, matches corresponding to a plurality of practitioners and seats.

13. A method comprising:

assimilating open seat data and practitioner data;

transforming the open seat data and practitioner data into seat attributes and practitioner attributes;

assessing viability of matching practitioners with seats based on predetermined matching criteria;

determining preferred matches based on said assessing; and

delivering the preferred matches to a user interface.

14. The method according to claim 13, wherein said assessing comprises assessing viability based on fitness scores.

15. The method according to claim 14, wherein said assessing based on fitness scores comprises text matching.

16. The method according to claim 15, wherein said text matching comprises comparing text related to practitioners and seats, respectively, and yielding a result corresponding to a degree of text matching.

17. The method according to claim 16, wherein said text matching further comprises comparing text related to distinct categories relating to practitioners and seats, and assigning a comparative weight to each category.

18. The method according to claim 15, further comprising computer code configured for employing a substitutability matrix, the substitutability matrix indicating prescribed equivalencies between pairs of differing text vectors.

19. The method according to claim 14, further comprising assigning a lower threshold for fitness scores and discarding results not meeting the lower threshold.

20. The method according to claim 13, wherein said determining comprises determining preferred matches via integer programming.

21. The method according to claim 20, wherein said determining further comprises determining preferred matches via optimization of business metrics.

22. The method according to claim 21, wherein the seat attributes include a prescribed timescale for effecting a match, and the business metrics are configured to assert a preference for overdue seats with respect to the prescribed timescale.

23. A method comprising:

receiving data relating to preferred matches of practitioners and open seats; and

displaying at least one optimal match corresponding to a practitioner and a seat and, adjacent thereto, cross-match information corresponding to at least one other viable seat corresponding to a practitioner.

24. The method according to claim 23, wherein said displaying comprises displaying, based on a fitness score rank, matches corresponding to a plurality of practitioners and seats.

25. A computer program product comprising:

a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising;

computer code configured to assimilate open seat data and practitioner data;

computer code configured to transform the open seat data and practitioner data into seat attributes and practitioner attributes;

computer code configured to assess viability of matching practitioners with seats based on predetermined matching criteria;

computer code configured determine preferred matches based on assessed viability; and

computer code configured to deliver the preferred matches to a user interface.