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.