Job analysis and decomposed inferences improve selection decisions: Evidence from a computer paradigm for evaluating selection tools

Purpose: A computerized paradigm was created to allow for testing in the laboratory whether increasing systematicity helps the recruiter make better selection decisions. Design/methodology/approach: Participants were introduced to the job and the applicants on the computer screen and asked to select who they thought should be considered for the job and who should not. Level of systematicity was manipulated between subjects. Depending on experimental condition participants were helped by means of a tool for extracting judgment criteria (job analysis) and a tool for making judgments related to selected criteria (including calculation of a final score). Findings: The general prediction that increased systematicity leads to the selection of more qualified candidates was supported by the results, particularly when the motivation to put time and effort into the task was higher. Implications: The results support the claim from I/O psychologists that systematicity is a desirable characteristic in selection processes. The fact that increasing systematicity led to better selection decisions in a controlled laboratory experiment, along with process-related measures, suggests that this kind of paradigm could be useful when evaluating new tools for improving selection decisions, before they are tested in large (and costly) field studies of actual personnel selection. Originality/value: This study validates the causal link between level of systematicity and selection decision quality, which may be of value to researchers and practitioners alike. The computerized paradigm that was developed is flexible, novel and useful for testing the incremental effects of decision tools on decision quality.