Work Experience and Employee Selection

Abstract

Experience is one of the most frequently invoked yet least precisely measured constructs in personnel selection. Organizations routinely seek candidates with relevant experience, but the tools used to assess experience vary widely in their theoretical grounding, psychometric quality, and fairness implications. This chapter reviews and integrates major approaches to experience-based selection, focusing on how different assessment methods capture work-related experience and translate it into predictions of job performance and other important organizational outcomes. Drawing on performance models that emphasize job knowledge and motivation as proximal determinants of effectiveness, the chapter argues that experience influences performance primarily through these mechanisms rather than as a direct predictor. It examines multiple methods for assessing experience (e.g., structured biodata, work samples, structured interviews), highlighting the strengths, limitations, validity evidence, and subgroup differences associated with each method. In addition, the chapter contrasts experience-based tools with general mental ability tests, clarifying how ability and experience interact over time and why combining methods often yields superior outcomes. The importance of structure, job relevance, and thoughtful design in enhancing both predictive accuracy and fairness is emphasized. The chapter concludes by offering integrative guidance for researchers and practitioners on selecting, combining, and implementing experience-based assessment tools in ways that balance validity, equity, and practical constraints.