Computer-implemented system for human resources management

• US 20030200136A1
• Filed: 04/10/2003
• Published: 10/23/2003
• Est. Priority Date: 06/12/2000
• Status: Abandoned Application

• Current Assignee: ePredix, Inc. (SHL Group Limited)
• Original Assignee: ePredix, Inc. (SHL Group Limited)
• Inventors: Dewar, Katrina L.
• Application Number:
  US10/410,270
• Publication Number:
  US 20030200136A1
• Time in Patent Office: Days
• US Class Current: 705/11
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 10/1053 Employment or hiring
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G09B 7/02 of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student

Abstract

A system and method for testing and/or evaluating employees or potential employees is disclosed. A computer arranges a plurality of applicants in a stack ranked table. The table may rank or re-rank applicants against each other, from best to worst, after successive screening, selecting, and/or interviewing stages for a particular job. Performance evaluations of hired workers may be fed back to the computer for adjusting the system and method. Competencies shown to be predictive of successful performance of a given type of job are tested for at various stages in an online testing system.

Claims

146. A method of constructing a model generating one or more job performance criteria predictors based on input pre-hire information collected over the Internet, the method comprising:

from a plurality of applicants, collecting pre-hire information from the applicants, the collecting comprising administering application questions to the applicants, the application questions comprising;

validated questions designed to minimize adverse impact on minority groups and validated by correlating job performance ratings of a plurality of hired workers with previous responses given by the workers to the application questions before the workers were hired; and

requirements questions eliciting information on whether the applicants meet employment requirements;

collecting post-hire information for the applicants based on job performance ratings of the applicants after hire; and

from the pre-hire information and the post-hire information, generating a computer-based predictive model operable to generate one or more job performance criteria predictors and a turnover predictor based on newly input pre-hire information from new applicants, the newly input pre-hire information comprising;

responses from the new applicants to a short subset of the validated questions, the short subset being selected to serve as a fast job-related pre-screen; and

later responses collected from the new applicants at the employer'"'"'s premises after the applicants have come to the employer'"'"'s

premises and logged on, the later responses collected in response to a more in-depth assessment;

wherein the computer-based predictive model is operable in real time to generate from the job performance criteria predictors, the turnover predictor, and responses of the new applicants to the requirements questions a rank order of all the new applicants.

147. A method of constructing a model generating one or more job performance criteria predictors based on input pre-hire information collected electronically, the method comprising:

from a plurality of applicants, collecting pre-hire information from the applicants, the collecting comprising administering validated questions to the applicants, the validated questions designed to minimize adverse impact on minority groups and validated by correlating job performance ratings of a plurality of hired workers with previous responses given by the workers to the application questions before the workers were hired;

collecting post-hire information for the applicants based on performance of the applicants after hire; and

from the pre-hire information and the post-hire information, generating a computer-based predictive model operable to generate one or more job performance criteria predictors based on newly input pre-hire information from new applicants, the newly input pre-hire information comprising responses from the new applicants to a short subset of a large assessment, the short subset being selected to serve as a fast job-related pre-screen;

wherein the computer-based predictive model is operable to generate a rank order of the new applicants.

148. The method of claim 147 wherein the input pre-hire information is collected over the Internet.

149. The method of claim 147 wherein the input pre-hire information is collected over a telephone.

150. A method of constructing a model generating one or more job performance criteria predictors based on input pre-hire information collected electronically, the method comprising:

from a plurality of applicants, collecting pre-hire information from the applicants;

collecting post-hire information for the applicants based on job performance of the applicants after hire; and

from the pre-hire information and the post-hire information, generating an artificial intelligence-based predictive model operable to generate one or more job performance criteria predictors based on newly input pre-hire information from new applicants, the newly input pre-hire information comprising responses from the new applicants to a short set of validated questions numbering less than about sixty;

wherein the artificial intelligence-based predictive model is operable in real time and generates a rank order of the new applicants.