A Comparison of Factor Weighting Methods in Job Evaluation: Implications for Compensation Systems

Abstract

Job evaluation has received a great deal of attention recently, in part because of its potential role in the gender-related pay equity issue. Investigators have been particularly interested in such psychometric characteristics of job evaluation instruments and plans such as reliability, gender bias, construct validity, and predictive accuracy. One aspect of job evaluation methodology that could directly affect compensation systems is the weighting of factors in scoring jobs. However, very little information exists in the compensation literature about the differential effects of alternative weighting methods or the psychometric parameters that may contribute to such differences.The present article reviews past psychometric research related to weighting, and presents evidence of the salary effects of four different weighting methods examined in an applied job evaluation setting. The study sample consisted of 52 jobs in a municipal government. The four weighting methods were: (1) an unweighted raw score composite, (2) equal unit weights, (3) committee-judgmental weights, and (4) multiple regression weights. Results indicated high agreement among the 4 methods in terms of ordinal rankings of the pay rates for the 52 jobs. However, when jobs were classified into pay grades using the alternative weighting models, distinct differences occurred. Particularly relevant was a finding that the weighting models differed in their relative impact on male and female dominated jobs. The article discusses generalizability issues and recommendations to practitioners concerning weighting methodology in job evaluation projects.