Classification Utility: Measuring and Improving Benefits in Matching Personnel to Jobs

Over a period of two decades, the content of both test composites and the operational test battery, the Armed Services Vocational Battery (ASVAB), have been selected to maximize predictive validity with little attention given to improving the classification efficiency of the total set of test compos...

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Bibliographic Details
Main Authors: Johnson, Cecil D, Zeidner, Joseph
Format: Report
Language:English
Subjects:
APTITUDE TESTS
CLASSIFICATION
CLASSIFICATION UTILITY
FISCAL YEAR 1991
JOB ANALYSIS
LPN-IDA-T-D2-435
MANPOWER UTILIZATION
MILITARY PERSONNEL
MILITARY TRAINING
PERFORMANCE TESTS
PERFORMANCE(HUMAN)
Personnel Management and Labor Relations
PERSONNEL SELECTION
RESOURCE MANAGEMENT
SBI1
UTILITY ANALYSIS
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Summary:Over a period of two decades, the content of both test composites and the operational test battery, the Armed Services Vocational Battery (ASVAB), have been selected to maximize predictive validity with little attention given to improving the classification efficiency of the total set of test composites in a multi-job, optimal assignment situation. This emphasis on predictive validity and its operational simplicity can be shown to be fundamentally erroneous with respect to both empirical results and psychometric theory. Although the present composites are of marginal value, considerable classification efficiency is potentially obtainable from the existing ASVAB if it is used in accordance with differential assignment principles. The primary objective of this report is to describe the principles underlying selection and classification for multiple jobs identified through reliance on the measurement of mean predicted performance. The report includes descriptions of: (1) a new taxonomy for the total personnel utilization decision process that embraces selection, classification, and placement; (2) methods of measuring potential classification efficiency and its components; (3) techniques for improving classification efficiency through selecting predictors or structuring job families and associated full least squares composites; (4) a means of identifying rotations of principal component factors that maximize the differential efficiency of a battery; and (5) a practical and flexible model sampling and simulation approach as a tool for measuring selectional and classification utility.