Behavioral profiles in sourcing and recruiting as part of a hiring process

• US 8,204,778 B2
• Filed: 06/29/2007
• Issued: 06/19/2012
• Est. Priority Date: 06/29/2007
• Status: Active Grant

• Current Assignee: Infor Incorporated
• Original Assignee: PeopleAnswers, Inc. (Infor Incorporated)
• Inventors: Ellis, Mark, Taylor, Jason-Jno Engene
• Primary Examiner(s): Dixon, Thomas
• Assistant Examiner(s): VIZVARY, GERALD C
• Application Number:
  US11/771,704
• Publication Number:
  US 20090006178A1
• Time in Patent Office: 1,817 Days
• Field of Search: 1/1, 705/8, 705/11, 706/60
• US Class Current: 705/7.38
• CPC Class Codes: G06Q 10/063118 Staff planning in a project environment
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• 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 10/1053 Employment or hiring
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls

Abstract

A method of selecting potential hires for progression through a hiring process is provided. The method comprises selecting at least one performance indicator for a position, obtaining the at least one performance indicator for a plurality of incumbents in the position, and placing each incumbent in the plurality of incumbents along a performance continuum according to their performance indicator. The method also comprises surveying incumbents from at least both halves of the performance continuum, generating an ideal profile for the position based upon the incumbent survey and the at least one performance indicator of the incumbents, using a survey to generate a candidate profile of a potential hire, comparing the candidate profile of the potential hire with the ideal profile for the position to determine a result for the potential hire, and determining whether to progress the potential hire to a next stage in the hiring process based upon the result.

Claims

1. A computer-implemented method of selecting potential hires for progression through a hiring process, comprising:

selecting at least one measured performance indicator for a position;

obtaining the at least one measured performance indicator for a plurality of incumbents in the position;

placing each incumbent in the plurality of incumbents along a performance continuum according to their measured performance indicator;

surveying incumbents from at least a portion of a top half and a portion of a bottom half of the performance continuum;

generating, by a processor, an optimal profile for the position based upon a plurality of the incumbent surveys from the portion of the top half of the performance continuum, a plurality of the incumbent surveys from the portion of the bottom half of the performance continuum, and the at least one measured performance indicator of the incumbents, wherein the optimal profile increases a probability of success and reduces a probability of failure of potential hires by considering the plurality of the incumbent surveys from the portion of the top half of the performance continuum and the plurality of the incumbent surveys from the portion of the bottom half of the performance continuum in relationship to the measured performance indicators of the incumbents completing the plurality of the incumbent surveys;

generating, by a processor, a candidate profile of a potential hire based on a survey administered to the potential hire;

comparing, by a processor, the candidate profile of the potential hire with the optimal profile for the position to determine a result for the potential hire; and

determining whether to progress the potential hire to a next stage in the hiring process based upon the result.

2. The computer-implemented method of claim 1, wherein the measured performance indicator is selected from a group consisting of sales numbers, call center numbers, management numbers, individual contribution numbers, customer service numbers, and training numbers.

3. The computer-implemented method of claim 1, wherein the measured performance indicator is a direct performance indicator or an indirect performance indicator.

4. The computer-implemented method of claim 1, wherein the incumbents surveyed also include incumbents in a mid-range of the performance continuum.

5. The computer-implemented method of claim 1, wherein the survey used for the incumbents and the survey used for the potential hire are the same survey.

6. The computer-implemented method of claim 1, wherein the result is selected from a group consisting of an overall rating value, a fit index, a recommendation statement, and a rating symbol.

7. The computer-implemented method of claim 1, wherein the potential hire is selected to progress to an interview.

8. The computer-implemented method of claim 1, wherein the potential hire is selected to progress to a job offer.

9. A computer-implemented system for selecting potential hires for progression through a hiring process, comprising:

a non-transitory computer-readable medium comprising a set of instructions executable by a processor, the set of instructions executable to configure the processor to;

receive a survey completed by a potential hire for a position and a plurality of incumbents in the position, the plurality of incumbents including both high performers and low performers relative to an identified measured performance indicator;

generate a candidate profile of the potential hire by analyzing the survey completed by the potential hire;

generate an optimal profile for the position by analyzing a plurality of the incumbent surveys completed by the high performers and a plurality of the incumbent surveys completed by the low performers, wherein the optimal profile increases a probability of success and reduces a probability of failure of potential hires by considering the plurality of the incumbent surveys completed by the top performers and the plurality of the incumbent surveys completed by the bottom performers in relationship to the measured performance indicators of the incumbents completing the plurality of the incumbent surveys; and

generate a result for the potential hire by comparing the candidate profile of the potential hire with the optimal profile for the position;

wherein a determination of whether to progress the potential hire is made based upon the result.

10. The computer-implemented system of claim 9, wherein the measured performance indicator is selected from a group consisting of sales numbers, call center numbers, management numbers, individual contribution numbers, customer service numbers, and training numbers.

11. The computer-implemented system of claim 9, wherein the measured performance indicator is a direct performance indicator.

12. The computer-implemented system of claim 9, wherein the measured performance indicator is an indirect performance indicator.

13. The computer-implemented system of claim 9, wherein the incumbents surveyed also include incumbents in a mid-range of the performance continuum.

14. The computer-implemented system of claim 9, wherein the survey used for the incumbents and the survey used for the potential hire are the same survey.

15. The computer-implemented system of claim 9, wherein the result is selected from the group consisting of an overall rating value, a fit index, a recommendation statement, and a rating symbol.

16. The computer-implemented system of claim 9, wherein the potential hire is selected to progress to an interview.

17. The computer-implemented system of claim 9, wherein the potential hire is selected to progress to a job offer.

18. A computer-implemented method of determining an optimal range for a behavioral characteristic for a position at a company, comprising:

receiving a completed survey from each of a plurality of incumbents in a position,

the survey comprising a group of two or more items,

the group of items corresponding to the behavioral characteristic, and

the plurality of incumbents including both high performers and low performers relative to an identified measured performance indicator;

plotting results of a plurality of the incumbent surveys from the high performers and a plurality of the incumbent surveys from the low performers on a continuum;

determining, by a processor, an optimal range for the behavioral characteristic for the position based upon the results of the plurality of the incumbent surveys from the high performers and the results of the plurality of the incumbent surveys from the low performers, wherein the optimal range increases a probability of success and reduces a probability of failure of potential hires by considering the plurality of the incumbent surveys from the top performers and the plurality of the incumbent surveys from the bottom performers in relationship to the measured performance indicators of the incumbents completing the plurality of incumbent surveys; and

determining, by a processor, where the optimal range falls on the continuum;

wherein the optimal range is between but not inclusive of the endpoints of the continuum.

19. The computer-implemented method of claim 18, further comprising:

having the survey comprise a plurality of groups of items, each group corresponding to a different behavioral characteristic; and

determining the optimal range for each behavioral characteristic.

20. The computer-implemented method of claim 19, further comprising:

administering the survey to a potential hire; and

providing to a survey reader the results for each behavioral characteristic.

21. The computer-implemented method of claim 19, further comprising assigning varying weights of importance to each group of items.

22. A computer-implemented method of determining the more effective source for sourcing candidates, comprising:

receiving a first group of candidates for a position from a first source;

receiving a second group of candidates for the position from a second source;

generating, by a processor, an optimal profile for the position based upon a first survey of a group of incumbents in the position and an at least one measured performance indicator of the incumbents;

generating, by a processor, a candidate profile based upon a candidate survey for each candidate in both groups;

determining, by a processor, a result for each candidate in both groups based upon the comparison of the candidate survey with the optimal profile;

tracking, by a processor, a measurement of candidates from each group that receive results over a threshold result;

determining whether the first or the second source is the more effective source for sourcing candidates based on the measurement of candidates from each group that receive results over the threshold result; and

selecting the more effective source for sourcing candidates based on the measurement of candidates.

23. The computer-implemented method of claim 22, wherein the first source is selected from the group consisting of an employment agency, an Internet posting, and a newspaper advertising.

24. The computer-implemented method of claim 22, wherein the second source is selected from the group consisting of an employment agency, an Internet posting, and a newspaper advertising.

25. The computer-implemented method of claim 22, wherein the first and second sources are from the same provider.

26. The computer-implemented method of claim 22, further comprising providing an organization associated with the position with an assessment of the sources.

27. The computer-implemented method of claim 26, wherein the assessment is selected from the group consisting of a cost per candidate over the threshold result, a cost per hire, a candidate flow by position, a candidate over the threshold result by source, and a candidate over the threshold result by position.

28. The computer-implemented method of claim 26, wherein the determination of whether the first or the second source is the more effective source for sourcing candidates is made by also considering a secondary factor.

29. The computer-implemented method of claim 28, wherein the secondary factor is selected from the group consisting of education, work experience, skill level, and training.

30. The computer-implemented method of claim 28, wherein the threshold result is an average of the results for all of the candidates.