ENTERPRISE SKILLS DEVELOPMENT USING COGNITIVE COMPUTING

• US 20170061353A1
• Filed: 08/28/2015
• Published: 03/02/2017
• Est. Priority Date: 08/28/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: RAJAN, Upendra
• Granted Patent: US 11,068,826 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• 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: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 10/105 Human resources

Abstract

Various embodiments for enterprise skill development using cognitive computing, by a processor device, are provided. In one embodiment, a method comprises applying cognitive computing to analyze user data from an information system to identify a user'"'"'s Enterprise Skills Index (ESI) of enterprise skills and skill-gaps by inputting and analyzing a plurality of indices for average achievement within the enterprise.

Claims

1. A method for enterprise skill development using cognitive computing, by a processor device, comprising:

applying cognitive computing to analyze user data from an information system to identify a user'"'"'s Enterprise Skills Index (ESI) of enterprise skills and skill-gaps by inputting and analyzing a plurality of indices for average achievement within the enterprise.

2. The method of claim 1, wherein the plurality of indices comprises a plurality of pillars, and further including analyzing a geometric mean of the plurality of pillars.

3. The method of claim 2, wherein the user'"'"'s ESI is the geometric mean of average achievement of the user based upon information gathered using the plurality of pillars.

4. The method of claim 2, wherein the plurality of pillars each comprise one of:

an indication of an estimate of years of experience remaining

an indication of a current knowledge or skill set

an indication of a desired skill set; and

an indication of a desire for skill growth.

5. The method of claim 1, further including training the information system using a knowledge database, the knowledge database containing a collaborative input of user data.

6. The method of claim 5, further including generating a synthesis of hypotheses regarding the plurality of pillars based upon information gathered using the knowledge database.

7. The method of claim 1, further including presenting the ESI as a percentage score.

8. A system for enterprise skill development using cognitive computing, comprising:

a processor device, wherein the processor device;

applies cognitive computing to analyze user data from an information system to identify a user'"'"'s Enterprise Skills Index (ESI) of enterprise skills and skill-gaps by inputting and analyzing a geometric mean of a plurality of indices for average achievement within the enterprise.

9. The system of claim 8, wherein the plurality of indices comprises a plurality of pillars, and wherein the processor device analyzes a geometric mean of the plurality of pillars.

10. The system of claim 9, wherein the user'"'"'s ESI is the geometric mean of average achievement of the user based upon information gathered using the plurality of pillars.

11. The system of claim 9, wherein the plurality of pillars each comprise one of:

an indication of an estimate of years of experience remaining

an indication of a current knowledge or skill set

an indication of a desired skill set; and

an indication of a desire for skill growth.

12. The system of claim 8, wherein the processor device trains the information system using a knowledge database, the knowledge database containing a collaborative input of user data.

13. The system of claim 12, wherein the processor device generates a synthesis of hypotheses regarding the plurality of pillars based upon information gathered using the knowledge database.

14. The system of claim 8, wherein the processor device presents the ESI as a percentage score.

15. A computer program product for enterprise skill development using cognitive computing, by a processor device, the computer program product embodied on a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:

a first executable portion that applies cognitive computing to analyze user data from an information system to identify a user'"'"'s Enterprise Skills Index (ESI) of enterprise skills and skill-gaps by inputting and analyzing a geometric mean of a plurality of indices for average achievement within the enterprise.

16. The computer program product of claim 15, wherein the plurality of indices comprises a plurality of pillars, and further including a second executable portion that analyzes a geometric mean of the plurality of pillars.

17. The computer program product of claim 16, wherein the user'"'"'s ESI is the geometric mean of average achievement of the user based upon information gathered using the plurality of pillars.

18. The computer program product of claim 16, wherein the plurality of pillars each comprise one of:

an indication of an estimate of years of experience remaining

an indication of a current knowledge or skill set

an indication of a desired skill set; and

an indication of a desire for skill growth.

19. The computer program product of claim 15, further including a second executable portion that trains the information system using a knowledge database, the knowledge database containing a collaborative input of user data.

20. The computer program product of claim 19, further including a third executable portion that generates a synthesis of hypotheses regarding the plurality of pillars based upon information gathered using the knowledge database.

21. The computer program product of claim 15, further including a second executable portion that presents the ESI as a percentage score.