Measuring HR analytics maturity: supporting the development of a roadmap for data-driven human resources management

• Published in: Management decision Vol. 62; no. 13; pp. 243 - 282
• Main Authors: Rigamonti, Elia, Gastaldi, Luca, Corso, Mariano
• Format: Journal Article
• Language: English
• Published: London Emerald Publishing Limited 2024; Emerald Group Publishing Limited
• Subjects: Business analytics; Business intelligence; Competitive advantage; Data analysis; Human resources; Development path; Decision-making; People analytics; Maturity model; Workforce analytics; Human capital analytics; Organisational capability; HR analytics
• DOI: 10.1108/MD-11-2023-2087
• ISSN: 0025-1747

PurposeToday, companies are struggling to develop their human resources analytics (HRA) capability, although interest in the subject is rapidly increasing. Furthermore, the academic literature on the subject is immature with limited practical guidance or comprehensive models that could support organisations in the development of their HRA capability. To address this issue, the aim of this paper is to provide a maturity model – i.e. HRAMM – and an interdependency matrix through which an organisation can (1) operationalise its HRA capability and assess its organisational maturity; (2) generate harmonious development roadmaps to improve its HRA capability; and (3) enable benchmarking and continuous improvement.Design/methodology/approachThe research described in this paper is based on the popular methodology proposed by Becker et al. (2009) and the procedure for maturity evaluation developed by Gastaldi et al. (2018). This method combines academic rigour and field experience in analytics, in a process spanning eight main phases that involves literature reviews and knowledge creation techniques.FindingsWe define HRA maturity through four areas and 14 dimensions, providing a comprehensive model to operationalise HRA capability. Additionally, we argue that HRA maturity develops through an evolutionary path described in four discrete stages of maturity that go beyond traditional analytics sophistication. Lastly, the interdependency matrix reveals specific enablers for the development of HRA.Practical implicationsThis paper provides practitioners with useful tools to monitor, evaluate and plan their HRA development path. Additionally, our research helps practitioners to prioritise their work and investment, generating an effective roadmap for developing and improving their HRA capability.Originality/valueTo the best of the authors’ knowledge, this study is the first to provide a model for evaluating the maturity of HRA capability plus an interdependency matrix to evaluate systematically the prerequisites and synergies among its constituting dimensions.