Developing and Validating a Decision Analytics Maturity Model for Human Resource Management Using CFA and Machine Learning

This study proposes and validates the Decision Analytics Maturity Model for HRM (DAMM-HR). The five maturity stages of the model are reactive reporting, diagnostic insight, predictive foresight, prescriptive optimization, and autonomous decisioning. Firstly, it offers a theoretical contribution by establishing decision embeddedness as a key aspect of HR analytics maturity. Second, it does offer an empirical contribution by conducting multi-phase validation via confirmatory factor analysis, ordinal regression, and qualitative text analysis based on data from 217 HR analytics
practitioners. Third, it provides a practical diagnostic tool to help HR leaders assess their organizations’ maturity and identify areas for further development.