Method and System for Discerning Learning Characteristics of Individual Knowledge Worker and Associated Team In Service Delivery

• US 20100002864A1
• Filed: 07/02/2008
• Published: 01/07/2010
• Est. Priority Date: 07/02/2008
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Saha, Debanjan, Ramakrishnan, Sreeram, Chang, Hung-Yang, Bose, Abhijit
• Application Number:
  US12/167,196
• Publication Number:
  US 20100002864A1
• Time in Patent Office: Days
• US Class Current: 379/265.06
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A method and system for measuring the learning ability and productivity of knowledge workers related to the delivery of services in service industry sectors, such as information technology (IT), healthcare and accounting. The method and system applies broadly to service domains that have a strong correlation between the learning ability and skill level of workers wherein the correlation affects the quality of service delivery. Utilizing data mining techniques, the method and system captures, analyzes and benchmarks individual knowledge worker'"'"'s skill(s) in order to normalize individual service agent proficiencies. The normalized service agent proficiencies allows the relative learning and skill indices of the individual service agents to be determined such that the skills and learning abilities of individual service agents to be determined. The method and system allows best practices and training thresholds to be determined.

Claims

1. A method, comprising:

capturing the activities of service agents;

analyzing said captured activities;

normalizing said captured activities; and

computing the relative learning and skill indices of said service agents.

2. The method according to claim 1, further comprising:

utilizing said relative learning and skill indices to evaluate the skills and learning abilities of said service agents.

3. The method according to claim 1, wherein analyzing said captured activities includes:

utilizing time metrics data associated with said captured activities.

4. The method according to claim 1, wherein analyzing said captured activities includes:

segmenting said activities based on service type;

selecting a time horizon; and

computing individual service agent proficiencies.

5. The method according to claim 4, wherein normalizing said captured activities includes:

normalizing said individual service agent proficiencies based on an associated team of service agents.

6. The method according to claim 5, further comprising:

utilizing said individual service agent proficiencies to identify best practices.

7. The method according to claim 5, further comprising:

utilizing said individual service agent proficiencies to identify thresholds for training.

8. The method according to claim 1, wherein said activities are captured by an activity capture agent and stored in a database.

9. A system, comprising:

an activity capture agent;

a database in communication with said activity capture agent;

a data miner in communication with said database; and

a learning agent in communication with said data miner.

10. The system according to claim 9, further comprising:

an administrator interface in communication with said data miner and said learning agent.

11. The system according to claim 9, wherein said activity capture agent captures activities performed by at least one service agent.

12. The system according to claim 11, wherein said database stores said captured activities.

13. The system according to claim 11, wherein said data miner extracts said captured activities based on user interest.

14. The system according to claim 11, wherein said learning agent normalizes said captured activities across multiple of said at least one service agent.

15. A system, comprising:

means for capturing the activities of service agents;

means for analyzing said captured activities;

means for normalizing said captured activities; and

means for computing the relative learning and skill indices of said service agents.

16. The system according to claim 15, further comprising:

means for utilizing said relative learning and skill indices to evaluate the skills and learning abilities of said service agents.

17. The system according to claim 16, wherein said means for analyzing said captured activities includes:

means for utilizing time metrics data associated with said captured activities.

18. The system according to claim 16, wherein said means for analyzing said captured activities includes:

means for segmenting said activities based on service type;

means for selecting a time horizon; and

means for computing individual service agent proficiencies.

19. The system according to claim 18, wherein said means for normalizing said captured activities further includes:

means for normalizing said individual service agent proficiencies based on a service team.

20. The system according to claim 19, further comprising:

means for utilizing said individual service agent proficiencies to identify best practices.

21. The system according to claim 19, further comprising:

means for utilizing said individual service agent proficiencies to identify training thresholds.

22. A computer program product comprising a computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to:

capture the activities of individual service agents;

analyze said captured activities;

normalize said captured activities; and

compute the relative learning and skill indices of said service agents.

23. A computer program product according to claim 22, wherein the computer readable program further causes the computer to:

evaluate the skills and learning abilities of said individual service agents based on said relative learning and skill indices.

24. A computer program product according to claim 22, wherein the computer readable program further causes the computer to:

utilize time metrics data associated with said captured activities;

segment said activities based on service type;

select a time horizon; and

compute individual service agent proficiencies.

25. A computer program product according to claim 24, wherein the computer readable program further causes the computer to:

normalize said individual service agent proficiencies based on an associated team of said individual service agents.