METHODS AND SYSTEMS FOR PROVIDING PREDICTIVE METRICS IN A TALENT MANAGEMENT APPLICATION

• US 20140074738A1
• Filed: 09/10/2013
• Published: 03/13/2014
• Est. Priority Date: 09/11/2012
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Lotia, Samar, Thankappan, Sharad, Pandey, Saurabh, Shuster, Irvin
• Granted Patent: US 9,818,086 B2
• Time in Patent Office: Days
• US Class Current: 705/321
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 10/1053 Employment or hiring

Abstract

Techniques for providing predictive metrics relating to employment positions are provided. A method may include receiving, by a computing device, data relating to a plurality of employment positions, wherein the data is received from a plurality of customers. The computing device may aggregate the data received from the plurality of customers and may determine statistics using the aggregated data, which are based on each of the plurality of employment positions. The computing device may generate one or more predictive metrics relating to the plurality of employment positions using one or more of the statistics.

Claims

1. A computer-implemented method, comprising:

receiving, by a computing device, data relating to a plurality of employment positions, wherein the data is received from a plurality of customers;

aggregating, by the computing device, the data received from the plurality of customers;

determining, by the computing device, statistics using the aggregated data, wherein the statistics are based on each of the plurality of employment positions; and

generating, by the computing device, one or more predictive metrics relating to the plurality of employment positions using one or more of the statistics.

2. The method of claim 1, wherein the statistics include one or more of a time at which each of the plurality of employment positions is posted, a time period indicating how long was required to fill each of the plurality of employment positions, a number of candidates that applied to each of the plurality of employment positions, a salary of each of the plurality of employment positions, or a source that was successful in locating a candidate that filled the position.

3. The method of claim 1, wherein the one or more predictive metrics includes a source effectiveness value of one or more employment position sources, wherein the source effectiveness value indicates a predicted effectiveness of each of the one or more employment position sources.

4. The method of claim 3, further comprising:

receiving, by the computing device, input corresponding to an indication of a particular employment position;

determining a source effectiveness value for each of the one or more employment position sources for the particular employment position; and

ranking the one or more employment position sources based on the source effectiveness value of each employment position source for the particular employment position.

5. The method of claim 1, wherein the one or more predictive metrics includes an effectiveness value of one or more employment position source types, wherein the effectiveness value indicates a predicted effectiveness of each of the one or more employment position source types.

6. The method of claim 1, wherein the one or more predictive metrics includes a position difficulty metric indicating a difficulty of filling an employment position.

7. The method of claim 6, wherein the position difficulty metric indicating the difficulty of filling the employment position is determined based on one or more of a time period indicating how long was required to fill the employment position, a time period indicating how long was required to hire a candidate for the employment position, a hiring rate for the employment position, or an offer acceptance rate for the employment position.

8. The method of claim 1, wherein the one or more predictive metrics includes a hiring process effectiveness value of one or more hiring processes, wherein the hiring effectiveness value indicates a predicted effectiveness of each of the one or more hiring processes.

9. The method of claim 1, wherein the one or more predictive metrics includes a candidate difficulty metric indicating a difficulty of finding an employment position candidate with one or more particular attributes.

10. A talent recruiting system, comprising:

a memory storing a plurality of instructions; and

one or more processors configured to access the memory, wherein the one or more processors are further configured to execute the plurality of instructions to;

receive data relating to a plurality of employment positions, wherein the data is received from a plurality of customers;

aggregate the data received from the plurality of customers;

determine statistics using the aggregated data, wherein the statistics are based on each of the plurality of employment positions; and

generate one or more predictive metrics relating to the plurality of employment positions using one or more of the statistics.

11. The system of claim 10, wherein the one or more predictive metrics includes a source effectiveness value of one or more employment position sources, wherein the source effectiveness value indicates a predicted effectiveness of each of the one or more employment position sources.

12. The system of claim 11, wherein the one or more processors are further configured to execute the plurality of instructions to:

receive, by the computing device, input corresponding to an indication of a particular employment position;

determine a source effectiveness value for each of the one or more employment position sources for the particular employment position; and

rank the one or more employment position sources based on the source effectiveness value of each employment position source for the particular employment position.

13. The system of claim 10, wherein the one or more predictive metrics includes a position difficulty metric indicating a difficulty of filling an employment position.

14. The system of claim 10, wherein the one or more predictive metrics includes a hiring process effectiveness value of one or more hiring processes, wherein the hiring effectiveness value indicates a predicted effectiveness of each of the one or more hiring processes.

15. The system of claim 10, wherein the one or more predictive metrics includes a candidate difficulty metric indicating a difficulty of finding an employment position candidate with one or more particular attributes.

16. A computer-readable memory storing a plurality of instructions executable by one or more processors, the plurality of instructions comprising:

instructions that cause the one or more processors to receive data relating to a plurality of employment positions, wherein the data is received from a plurality of customers;

instructions that cause the one or more processors to aggregate the data received from the plurality of customers;

instructions that cause the one or more processors to determine statistics using the aggregated data, wherein the statistics are based on each of the plurality of employment positions; and

instructions that cause the one or more processors to generate one or more predictive metrics relating to the plurality of employment positions using one or more of the statistics.

17. The computer-readable memory of claim 16, wherein the one or more predictive metrics includes a source effectiveness value of one or more employment position sources, wherein the source effectiveness value indicates a predicted effectiveness of each of the one or more employment position sources.

18. The computer-readable memory of claim 16, wherein the one or more predictive metrics includes a position difficulty metric indicating a difficulty of filling an employment position.

19. The computer-readable memory of claim 16, wherein the one or more predictive metrics includes a hiring process effectiveness value of one or more hiring processes, wherein the hiring effectiveness value indicates a predicted effectiveness of each of the one or more hiring processes.

20. The computer-readable memory of claim 16, wherein the one or more predictive metrics includes a candidate difficulty metric indicating a difficulty of finding an employment position candidate with one or more particular attributes.