Assessing the Analytic Competency Gap for HR Professionals: Providing HR a Roadmap to Data-Driven Decision-Making

Abstract

Human Resource (HR) professionals have fallen behind their peers in utilizing and leveraging analytics to enhance performance. Research indicates that HR professionals need a more prescriptive understanding of competencies required for analytics and the influence on job performance. This study utilizes a novel method to map a newly demanded skill set or competency cluster to a profession, filling a gap in the competency modeling literature for future state occupational needs. The developed and supported HR analytic competency cluster is logic, numeracy, and critical evaluation with special considerations for persuasion. This study utilized a structural equation model (SEM) to test the effect of these competencies on job performance. The HR analytic competencies predict increased job performance except for persuasion. Contrary to expectations, the analytic cluster of logic, numeracy, and critical evaluation mediated the impact of persuasion. Self-efficacy mediated competency impact on performance. The research increased our understanding of analytics on performance. Further, the study increased our knowledge of competencies in the behavioral model of job performance. The results have practical contributions, providing HR professionals with relevant information to inform their personal development.