Computer-implemented system for human resources management

• US 20030191680A1
• Filed: 04/10/2003
• Published: 10/09/2003
• 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:
  US10/410,307
• Publication Number:
  US 20030191680A1
• Time in Patent Office: Days
• US Class Current: 706/45
• 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

14. An electronic assessment system for assessing an individual applicant for employment by an employer, the system comprising:

an electronic applicant terminal operable to present a plurality of questions to the applicant and to receive electronically the applicant'"'"'s responses to the questions;

an applicant screening computer configured to provide applicant results automatically in response to receiving the electronically received responses; and

an electronic report viewer operable to present to the employer a viewable report containing the applicant results,

characterized in that the computer is configured to compare automatically the electronically received responses with electronically stored rating correlation data, the rating correlation data being indicative of calculated correlations between actual job duty performance ratings of a plurality of hired individuals and previous responses given by the hired individuals.

15. The system of claim 14, the previous responses characterized by having been collected from the individuals before the individuals were hired into the job for which the actual job duty performance ratings were collected.

16. The system of claim 14, the previous responses characterized by having been collected from the individuals in response to the plurality of questions.

17. An electronic prediction system for assessing an individual applicant for employment by an employer, the system comprising:

an electronic applicant terminal operable to present a plurality of questions to the applicant and to receive electronically the applicant'"'"'s responses to the questions;

an applicant screening computer responsive to the electronically received responses and operable to predict expected performance for a candidate if the candidate were to be employed by the employer, the computer providing applicant results indicative of expected performance based upon correlations of the electronically received answers with answers to questions by other individuals for which job duty performance information has been collected; and

an electronic report viewer operable to present to the employer a viewable report containing the applicant results.

18. The apparatus of claim 17 wherein the job duty performance information has been collected electronically.

19. The apparatus of claim 17 wherein the job duty performance information has been stored electronically.

20. The apparatus of claim 17 characterized in that the applicant terminal is configured to communicate with the applicant screening computer over the Internet.

21. An electronic assessment system for assessing an individual for a potential human resources action by an employer, the system comprising:

an electronic terminal operable to present a plurality of questions to the individual and to receive electronically the individual'"'"'s responses to the questions;

a computer configured to provide results automatically in response to receiving the electronically received responses; and

an electronic report viewer operable to present to the employer a viewable report containing the results,

characterized in that the computer is configured to compare automatically the electronically received responses with electronically stored rating correlation data, the rating correlation data being indicative of calculated correlations between actual job duty performance ratings of a plurality of hired individuals and previous responses given by the hired individuals.

22. The electronic assessment system of claim 21, characterized in that the potential human resources action is hiring the individual for a job.

23. The electronic assessment system of claim 21, characterized in that the potential human resources action is promoting the individual.

24. An apparatus for assisting in determining the suitability of an individual for employment by an employer, the apparatus comprising:

an electronic data interrogator operable to present a first set of a plurality of questions to the individual;

an electronic answer capturer operable to electronically store the individual'"'"'s responses to at least a selected plurality of the first set of questions presented to the individual;

an electronic predictor responsive to the stored answers and operable to predict at least one post-hire outcome if the individual were to be employed by the employer, the predictor providing a prediction of the outcome based upon correlations of the stored answers with answers to sets of questions by other individuals for which post-hire information has been collected; and

an electronic results provider providing an output indicative of the outcome to assist in determining the suitability of the individual for employment by the employer.

25. An apparatus according to claim 24 wherein the post-hire outcome indicates whether the individual is predicted to be eligible for re-hire after termination.

26. An apparatus according to claim 24 wherein the post-hire outcomes indicate whether the individual is predicted to be involuntarily terminated and whether the individual is predicted to be eligible for re-hire after termination.

27. An apparatus according to claim 24 wherein at least one of the predicted outcomes is a predicted value for a continuous variable.

28. An apparatus according to claim 24 wherein the predicted outcome indicates whether the individual will belong to a particular group.

29. An apparatus according to claim 24 wherein at least one of the predicted outcomes is a predicted ranking of the individual for the outcome.

30. An apparatus according to claim 24 wherein at least one of the predicted outcomes indicates a predicted employment tenure for the individual.

31. An apparatus according to claim 24 wherein at least one of the predicted outcomes indicates a predicted number of accidents for the individual.

32. An apparatus according to claim 24 wherein at least one of the predicted outcomes indicates a predicted sales level for the individual.

33. An apparatus according to claim 24 wherein the predictor comprises an artificial intelligence-based prediction system.

34. An apparatus according to claim 24 wherein the data interrogator is located at a first location and the predictor is located at a second location which is remote from the first location.

35. An apparatus according to claim 34 wherein the data interrogator and the predictor are selectively electronically interconnected through a network.

36. An apparatus according to claim 35 wherein the network is the worldwide web.

37. An apparatus according to claim 35 wherein the network is a telephone network.

38. An apparatus according to claim 35 wherein the network is an electronic network.

39. An apparatus according to claim 24 wherein the first set of questions may be varied.

40. An apparatus according to claim 39 wherein the predictor is operable to determine and indicate a lack of a correlation between one or more questions of the first set of questions and at least one of the predicted outcomes, whereby questions which lack the correlation may be discarded or modified.

41. An apparatus according to claim 24 wherein at least one of the predicted outcomes is longevity with an employer and the answers to sets of questions by other individuals comprise answers by employees of the employer for whom longevity has been determined.

42. An apparatus according to claim 24 in which the predictor comprises at least one model which provides a predictor of the probability of the individual exhibiting at least one of the predicted outcomes, the model being based on correlations between the at least one of the predicted outcomes and the answers to questions by the other individuals, including answers by at least some employees of the employer, the model taking at least selected answers of the stored answers as inputs to the model, a probability of the individual exhibiting the at least one of the predicted outcomes being provided as an output of the model.

43. An apparatus according to claim 33 wherein the model comprises at least one expert system.

44. An apparatus according to claim 24 wherein the predictor is responsive to the stored answers and operable to predict plural outcomes if the individual were to be employed by the employer.

45. A method for assessing suitability of persons for employment based on information for hired employees, the method comprising:

collecting pre-hire applicant information for hired employees before they are hired;

collecting post-hire measures of the job effectiveness of hired employees;

constructing an artificial intelligence model identifying associations of patterns within the pre-hire data associated with patterns of job effectiveness in the post-hire data;

collecting pre-hire information for a new applicant; and

applying the artificial intelligence model to the pre-hire information for the new applicant to provide a prediction of the new applicant'"'"'s suitability for employment.

46. The method of claim 45 further comprising:

collecting post-hire information for the new applicant; and

using at least the pre-hire and post-hire information for the new applicant to refine the artificial intelligence model.

47. The method of claim 45 further comprising:

constructing at least one other artificial intelligence model of a different type; and

assessing the relative effectiveness of the artificial intelligence models at predicting suitability of employees for employment based on actual employment effectiveness of employees hired based on the models.

48. An apparatus for assisting in determining the suitability of an individual for employment by an employer, the apparatus comprising:

means for electronically presenting a first set of a plurality of questions to the individual;

means for electronically storing the individual'"'"'s responses to at least a selected plurality of the first set of questions presented to the individual;

responsive to the stored answers, means for predicting at least one post-hire outcome if the individual were to be employed by the employer, the means for predicting providing a prediction of the outcome based upon correlations of the at least one characteristic with answers to sets of questions by other individuals and the closeness of the stored answers to such correlations; and

means for providing an output indicative of the outcome to assist in determining the suitability of the individual for employment by the employer.

49. An artificial intelligence-based system for predicting employee behaviors based on pre-hire information collected for the employee, the system comprising:

an electronic device for presenting an employment application comprising a set of questions to an employment candidate, wherein the electronic device is operable to transmit answers of the employment candidate to a central store of employee information, wherein the central store of employee information comprises information collected for a plurality of candidate employees and a plurality of hired employees;

an artificial intelligence-based model constructed from information collected from the hired employees based on answers provided by the hired employees and employment behaviors observed for the hired employees;

a software system for supplying the answers of the employment candidate to the artificial intelligence-based model to produce predicted employment behaviors for the employment candidate; and

a report generator to produce a hiring recommendation report for the employment candidate based on the predicted employment behaviors of the employment candidate.

50. A computer-implemented method of predicting employment performance characteristics for a candidate employee based on pre-hire information collected for hired employees, the method comprising:

collecting data indicating pre-hire information for a plurality of the hired employees;

collecting data indicating post-hire outcomes for the hired employees;

constructing an artificial intelligence-based model from the pre-hire information and the post-hire outcomes for the employees;

from the candidate employee, electronically collecting data indicating pre-hire information of the candidate employee; and

applying the model to the collected pre-hire information of the candidate employee to generate one or more predicted post-hire outcomes for the candidate employee.

51. The method of claim 50 wherein collecting data from the candidate employee comprises electronically presenting a set of questions at an electronic device and electronically collecting answers to the questions at the electronic device.

52. The method of claim 50 wherein the pre-hire information comprises one or more pre-hire characteristics and constructing the model comprises:

identifying one or more pre-hire characteristics as ineffective predictors; and

responsive to identifying the pre-hire characteristics as ineffective predictors, omitting the ineffective predictors from the model.

53. The method of claim 50 further comprising:

providing a report indicating applicant flow.

54. The method of claim 50 wherein constructing the model comprises:

constructing a plurality of proposed models, wherein at least two of the models are of different types; and

selecting a superior proposed model as the model to be used.

55. The method of claim 54 wherein at least two of the proposed models are different expert models.

56. The method of claim 50 further comprising using the one or more predicted post-hire outcomes to influence a hiring decision.

57. The method of claim 50 further comprising using the one or more predicted post-hire outcomes to influence a promotion decision.

58. The method of claim 50 wherein at least one of the predicted post-hire outcomes is denoted as a probability that a particular value range of a job effective measure will be observed for a candidate employee.

59. The method of claim 50 wherein at least one of the predicted post-hire outcomes is denoted as a value for a continuous variable.

60. The method of claim 50 wherein at least one of the predicted post-hire outcomes is denoted as a relative ranking for an outcome.

61. The method of claim 60 wherein the ranking is relative to other employment candidates.

62. The method of claim 60 wherein the ranking is relative to the hired employees.

63. The method of claim 50 further comprising:

storing a relative importance of one or more particular post-hire outcomes; and

generating automated hiring recommendations based on the predicted post-hire outcomes for the candidate employees and the importance of the post-hire outcomes.

64. The method of claim 50 further comprising:

refining the model based on newly-observed post-hire outcomes.

65. The method of claim 50 wherein the pre-hire information comprises answers to questions on a job application, the method further comprising:

identifying one or more questions as ineffective predictors;

responsive to identifying the questions as ineffective predictors, modifying the job application by removing the questions;

collecting new pre-hire information for additional candidate employees based on the modified job application;

collecting new post-hire information for the additional candidate employees; and

constructing a refined artificial-intelligence model based on the additional pre-hire and post-hire information for the additional candidate employees.

66. The method of claim 65 further comprising:

responsive to determining pre-hire and post-hire information has been collected for a sufficient number of additional employees, providing an indication that a refined model can be constructed.

67. The method of claim 65 further comprising:

providing a report indicating the identified questions are ineffective predictors.

68. The method of claim 65 further comprising:

adding one or more new questions to the modified job application before collecting additional pre-hire information.

69. The method of claim 68 wherein the new questions are composed based on job skills appropriate for a particular job related to the job application.

70. The method of claim 68 further comprising:

evaluating the effectiveness of the new questions.

71. An artificial intelligence-based employee performance prediction system comprising:

a set of pre-hire characteristic identifiers;

a set of post-hire outcome identifiers;

a collection of data for employees, wherein the data includes values associated with the pre-hire identifiers and the post-hire identifiers; and

an artificial intelligence-based model chosen from a set of candidate models, the artificial intelligence-based model exhibiting superior ability at predicting values associated with the post-hire outcome identifiers based on values associated with the pre-hire characteristic identifiers in comparison to the other candidate models.

72. A computer-readable medium having a collection of employment-related data, the data comprising:

pre-hire information for a plurality of employees, wherein the pre-hire information comprises information electronically-collected from an applicant, wherein the information comprises a plurality of pre-hire characteristics;

post-hire information for at least some of the plurality of employees, wherein the information comprises a plurality of post-hire outcomes; and

a data structure identifying which of the pre-hire characteristics are effective in predicting a set of one or more of the post-hire outcomes for a job applicant.

73. A method for providing an automated hiring recommendation for a new potential employee, the method comprising:

collecting pre-hire information for potential employees;

storing the pre-hire information for the potential employees in a database;

after hiring a plurality of the potential employees, collecting employment performance information for at least some of the hired employees;

storing the employment performance information collected from the hired employees;

constructing an artificial intelligence-based model based on correlations between the pre-hire information and the employment performance information collected from one or more of the hired employees;

collecting pre-hire information for a new potential employee;

based on the artificial intelligence-based model, providing an automated hiring recommendation for the new potential employee;

after hiring the new potential employee, collecting employment performance information for the new potential employee;

adding the employment performance information for the new potential employee to the database; and

modifying the artificial intelligence-based model based on the pre-hire and employment performance information for the new potential employee.

74. A method for providing an automated hiring recommendation service for an employer, the method comprising:

stationing a plurality of electronic devices at a plurality of employer sites, wherein the electronic devices are operable to accept directly from one or more job applicants answers to questions presented at the electronic devices;

sending the answers of at least one of the job applicants to a remote site for analysis;

applying an artificial intelligence-based predictive model to the answers of the least one of the job applicant to generate an automated hiring recommendation; and

automatically sending the hiring recommendation to the employer.

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

from a plurality of applicants, electronically 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 input pre-hire information from new applicants.

76. A computer-readable medium comprising computer-executable instructions for performing the method of claim 75.

77. The method of claim 75 further comprising:

limiting the applicants for the model to those providing a certain answer to a knock-out question.

78. The method of claim 75 further comprising:

limiting the applicants for the model to those not providing a certain answer to a knock-out question.

79. The method of claim 75 further comprising:

limiting the applicants for the model to those with a particular occupation; and

constructing the model as an occupationally-specialized model.

80. The method of claim 75 wherein the model accepts one or more inputs, the method further comprising:

identifying in the pre-hire information one or more characteristics that are ineffective predictors; and

omitting the ineffective predictors as inputs to the model.

81. The method of claim 75 wherein the pre-hire information comprises one or more characteristics, the method further comprising:

identifying in the pre-hire information one or more characteristics that are ineffective predictors; and

providing an indication that the characteristics no longer need to be collected.

82. The method of claim 75 wherein job performance criteria predictors comprise a predictor indicating whether a job candidate will be voluntarily terminated.

83. The method of claim 75 wherein job performance criteria predictors comprise a predictor indicating whether a job candidate will be eligible for rehire after termination.

84. The method of claim 75 wherein the pre-hire information comprises one or more characteristics, the method further comprising:

identifying in the pre-hire information one or more characteristics that are ineffective predictors; and

responsive to identifying the ineffective predictors, collecting new pre-hire information not including the ineffective predictors; and

building a refined model based on the new pre-hire information.

85. The method of claim 84 further comprising:

adding one or more new characteristics to be collected when collecting the new pre-hire information.

86. The method of claim 85 further comprising:

evaluating the effectiveness of the new characteristics.

87. An electronic assessment system for assessing an individual for a potential human resources action by an employer, the system comprising:

an electronic terminal operable to present a plurality of questions to the individual and to receive electronically the individual'"'"'s responses to the questions;

a computer configured to provide results automatically in response to receiving the electronically received responses; and

an electronic report viewer operable to present to the employer a viewable report containing the results,

characterized in that the computer is configured to rate automatically the electronically received responses to provide a rating for the individual and to rank automatically the individual in order against other individuals based on the rating.

88. An electronic assessment system for assessing an individual for a potential human resources action by an employer, the system comprising:

an electronic terminal operable to present a plurality of questions to the individual and to receive electronically the individual'"'"'s responses to the questions;

a computer configured to rate automatically the electronically received responses to provide a rating for the individual and to rank automatically the individual in order against other individuals based on the rating; and

an electronic report viewer operable to present to the employer a viewable report containing the individual'"'"'s rating and the individual'"'"'s rank order.

89. An electronic assessment system for assessing an individual for a potential human resources action by an employer comprising:

an electronic terminal operable to present an abbreviated set of questions to the individual and to receive electronically the individual'"'"'s responses to the questions;

a computer configured to provide results automatically in response to receiving the electronically received responses; and

an electronic report viewer operable to present to the employer a viewable report containing the results,

characterized in that the computer is configured to compare automatically the electronically received responses with electronically stored rating correlation data, the rating correlation data being indicative of calculated correlations between actual job duty performance ratings of a plurality of hired individuals and previous responses given by the hired individuals to a full set of questions, the abbreviated set of questions being selected from the full set of questions.

90. The system of claim 89, further characterized in that the abbreviated set of questions are selected from the full set of questions based on validated correlations between the abbreviated set and the actual job duty performance ratings.

91. A computer-readable medium substantially as shown and described.

92. A method substantially as shown and described.

93. An apparatus substantially as shown and described.

94. A method for constructing an artificial intelligence-based employment selection process based on pre-hire information comprising personal employee characteristics and post-hire information comprising employee job performance observation information, the method comprising:

generating a plurality of predictive artificial intelligence models based on the pre-hire and post-hire information, wherein at least two of the artificial intelligence models are of different types;

testing effectiveness of the models to select an effective model; and

applying the effective model to predict post-hire information not yet observed.

95. The method of claim 94 characterized in that at least one of the models is an expert system.

96. The method of claim 94 further comprising:

identifying at least one of the models as exhibiting impermissible bias; and

avoiding use of the models exhibiting impermissible bias.

97. The method of claim 96 wherein the impermissible bias is against a protected group of persons.

138. The method of claim 94 wherein the different types of artificial intelligence models are at least two of the following four different types of artificial intelligence models:

application questions;

customer service inventory;

working with information test; and

sales potential inventory.

98. A computer-implemented method of refining an artificial-intelligence based employee performance selection system, the method comprising:

collecting information via an electronic device presenting a set of questions to employment candidates, wherein the questions are stored in a computer-readable medium;

testing effectiveness of at least one of the questions in predicting the post-hire information; and

responsive to determining the question is ineffective, deleting the question from the computer-readable medium.

99. A computer-readable medium comprising a predictive model, the model comprising:

inputs for accepting one or more characteristics based on pre-hire information for a job applicant;

one or more predictive outputs indicating one or more predicted job effectiveness criteria based on the inputs, wherein the predictive model is an artificial intelligence-based model constructed from pre-hire data electronically collected from a plurality of employees and post-hire data, and the model generates its predictive outputs based on the similarity of the inputs to pre-hire data collected for the plurality of employees and their respective post-hire data.

100. The computer-readable medium of claim 99 wherein the predictive model comprises a predictive output indicating a rank for the job applicant.

101. The computer-readable medium of claim 100 wherein the rank is relative to other applicants.

102. The computer-readable medium of claim 100 wherein the rank is relative to the plurality of employees.

103. The computer-readable medium of claim 99 wherein the predictive model comprises a predictive output indicating probability of group membership for the job applicant.

104. The computer-readable medium of claim 99 wherein the predictive model comprises a predictive output indicating predicted tenure for the job applicant.

105. The computer-readable medium of claim 99 wherein the predictive model comprises a predictive output indicating predicted tenure for the job applicant.

106. The computer-readable medium of claim 99 wherein the predictive model comprises a predictive output indicating predicted number of accidents for the job applicant.

107. The computer-readable medium of claim 99 wherein the predictive model comprises a predictive output indicating whether the applicant will be involuntarily terminated.

108. The computer-readable medium of claim 99 wherein the predictive model comprises a predictive output indicating whether the applicant will be eligible for rehire after termination.

109. A computer-readable medium comprising a refined predictive model, the model comprising:

inputs for accepting one or more characteristics based on pre-hire information for a job applicant;

one or more predictive outputs indicating one or more predicted job effectiveness criteria based on the inputs, wherein the predictive model is constructed from pre-hire data electronically collected from a plurality of employees and post-hire data, wherein the pre-hire data is based on a question set refined by having identified and removed one or more questions as ineffective.

110. The computer-readable medium of claim 109 wherein the ineffective questions are identified via an information transfer technique.

111. The computer-readable medium of claim 109 wherein the model is an artificial intelligence-based model.

112. A system for assessing an individual applicant for employment by an employer, the system comprising:

an electronic applicant terminal logged on to a website and operable to present a plurality of questions to the applicant and to receive electronically the applicant'"'"'s responses to the questions;

an applicant screening computer associated with the website and configured to provide applicant results automatically in response to receiving the electronically received responses;

an electronic network connecting the electronic applicant terminal to the applicant screening computer in accordance with a uniform resource locator associated with website, the uniform resource locator having been entered by the applicant into the electronic applicant terminal; and

an electronic report viewer operable to present to the employer a viewable report containing the applicant results,

wherein the applicant screening computer is configured to compare automatically the electronically received responses with electronically stored rating correlation data, the rating correlation data being indicative of calculated correlations between actual job duty performance ratings of a plurality of hired individuals and previous responses given by the hired individuals.

113. A method for assessing an individual applicant for employment by an employer, the method comprising:

hosting an employer website identified by a uniform resource locator;

providing via the uniform resource locator access to the website by the applicant at an applicant terminal;

transmitting questions from an applicant screening computer to the applicant terminal;

receiving at the applicant screening computer responses from the applicant to the questions transmitted over the Internet;

comparing automatically the received responses with electronically stored rating correlation data, the rating correlation data being indicative of calculated correlations between actual job duty performance ratings of a plurality of hired individuals and previous responses given by the hired individuals.

114. A method for assessing an individual applicant for employment by an employer, the method comprising:

making a connection over a network between a job applicant telephone and a computer;

transmitting questions from the computer to the job applicant telephone;

receiving at the computer responses from the applicant to the questions transmitted, the responses having been transmitted over the network from the job applicant telephone;

comparing automatically the received responses with electronically stored rating correlation data, the rating correlation data being indicative of calculated correlations between actual job duty performance ratings of a plurality of hired individuals and previous responses given by the hired individuals.

115. A method of assessing the suitability of an individual for a job action, the method comprising:

making a connection between a computer and a terminal;

receiving at the computer responses entered at the terminal by the individual in response to questions;

scoring the received responses according to correlations between job duty performance ratings of a plurality of workers and previous responses given by the workers.

116. The method of claim 115, wherein making the connection comprises logging the individual on to a website.

117. The method of claim 115, wherein the scoring is performed automatically.

118. The method of claim 115, wherein the scoring is performed in real time.

119. The method of claim 115, further comprising displaying a rank order of the individual.

120. The method of claim 115, wherein the previous responses were given by the workers in response to said questions.

121. The method of claim 115, wherein the scoring predicts the turnover potential.

122. The method of claim 115, wherein the scoring provides information on a probability of not terminating early.

123. The method of claim 115, wherein the scoring is indicative of a probability of successful job duty performance.

124. The method of claim 115, wherein the individual is a job applicant and the job action is employment.

125. The method of claim 115, wherein the correlations are made before the responses are received.

126. An apparatus for assessing the suitability of an individual for a job action, the apparatus comprising:

means for making a connection between a computer and a terminal;

means for receiving at the computer responses entered at the terminal by the individual in response to questions;

means for scoring the received responses according to correlations between job duty performance ratings of a plurality of workers and previous responses given by the workers.

127. The apparatus of claim 126, wherein the means for making a connection comprises a website.

128. The apparatus of claim 126, wherein the previous responses were given by the workers in response to said questions.

129. The apparatus of claim 126, wherein the terminal comprises a telephone.

130. The apparatus of claim 126, wherein the means for making a connection comprises an Internet and the responses are entered at the terminal by pointing and clicking.

131. The apparatus of claim 126, wherein the computer comprises a testing program.

132. The apparatus of claim 126, further comprising a scoring database.

133. The apparatus of claim 126, wherein the correlations are made before the responses are received.

134. A computer program capable of causing a computer to perform the functions of:

making a connection between a terminal and a computer;

receiving at the computer responses entered at the terminal by an individual in response to questions;

scoring the received responses according to correlations between job duty performance ratings of a plurality of workers and previous responses given by the workers.

135. A method of constructing a computer model useful for deciding whether a new job applicant would be suitable for employment, the method comprising:

collecting complete pre-hire information from a plurality of original applicants in response to a complete set of pre-hire information items;

hiring the original applicants;

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

comparing the complete pre-hire information to the post-hire information;

responsive to the comparing, selecting a sub-set of the complete pre-hire information items, the sub-set being selected for a high correlation to the post-hire information;

generating from the pre-hire information and the post-hire information a computerized predictive model operable to generate an applicant suitability indication based on newly input pre-hire information electronically collected from a new applicant,

the suitability indication indicating whether the new applicant would be suitable for employment and the newly input pre-hire information being limited to the new applicant'"'"'s responses to the selected subset of the complete pre-hire information items.

136. The method of claim 135 wherein the computerized predictive model reflects input from job incumbent experts.

137. The method of claim 135 further comprising:

designing and testing the pre-hire information to comply with EEOC guidelines and to not be dependent on any group membership.

139. An electronic prediction system for assessing the suitability of job applicants for an employer, the electronic prediction system comprising:

a plurality of applicant terminals connected to the Internet;

an applicant screening server connected through the Internet to the applicant terminals, the applicant screening server having a testing computer program and storing test meta-data;

an employer website configured to present questions to the applicants at the applicant terminals and to receive applicant responses entered at the applicant terminals in response to presentation of the questions, the questions having been validated by correlating job duty performance ratings of a plurality of hired workers with previous responses given by the workers to the questions;

a scoring system for automatically scoring the applicant responses, the scoring system being validated to predict both performance and turnover potential;

a scoring database connected to the applicant screening server;

an applicant input system located on the employer'"'"'s premises and configured electronically to receive input from an applicant at the employer'"'"'s premises after the candidate has come to the employer'"'"'s premises and logged on; and

a viewing system for permitting the employer to view applicant results from the electronic prediction system and the applicant'"'"'s rank order.

140. A method of constructing a computer model generating one or more job performance criteria predictors based on input pre-hire information, 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

responsive to the pre-hire information and the post-hire information, forming a computer model operable to generate a plurality of job performance criteria predictors based on input pre-hire information electronically collected from new applicants.

141. An electronic prediction system for assessing the suitability of job applicants for an employer, the electronic prediction system comprising:

an applicant screening server storing a testing computer program and test data, the testing computer program configured to present questions to the applicants over a network, the questions having been validated by correlating job duty performance ratings of a plurality of hired workers with responses given by the workers; and

means for receiving input from an applicant at the employer'"'"'s premises after the candidate has come to the employer'"'"'s premises and logged on.

142. A method of deciding whether a new job applicant would be suitable for employment, the method comprising:

collecting complete pre-hire information from a plurality of original applicants in response to a complete set of pre-hire information items;

hiring the original applicants;

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

comparing the complete pre-hire information to the post-hire information;

responsive to the comparing, selecting a sub-set of the complete pre-hire information items, the sub-set being selected for a correlation to the post-hire information;

preparing from the pre-hire information and the post-hire information a computerized predictive model operable to generate automatically an applicant suitability indication based on newly input pre-hire information electronically collected from a new applicant,

the suitability indication indicating whether the new applicant would be suitable for employment and the newly input pre-hire information being limited to the new applicant'"'"'s responses to the selected subset of the complete pre-hire information items.