The application of HR analytics to enable data-driven decision-making (DDDM) in Human Resource Management

Abstract

The growing interest in big data and data-driven decision-making (DDDM) by business has led to a bit of pressure on HR professionals to start engaging with it and make data-driven decisions that add value to their organisations. This would also help HR practitioners to play the strategic business partnering role that they have always aimed to execute. The literature reviewed revealed that although there has been an increase in interest and the adoption of HR analytics in organisations, the maturity or growth level has remained stagnant at level 1 (descriptive analytics) of the HR analytics maturity model. In addition, there is a research gap in guiding practitioners on the implementation of HR analytics and DDDM. The aim of this study was to explore and gain insights on how HR practitioners were using HR analytics to make data-driven decisions in their organisations. This will enable those HR practitioners lagging behind, and those that are stuck at level 1 of the maturity model to understand what they need to do to successfully adopt and utilise HR analytics to enable DDDM in their organisations. The study was conducted through exploratory qualitative research design. Data was gathered through conducting virtual semi-structured interviews with fifteen HR practitioners from different South African organisations and industries. The findings highlighted those factors, such as good quality data, HR capability, and technological analytical tools or systems needed to be in place for HR practitioners to effectively use HR analytics to enable DDDM. It also gave an indication of the type data-driven decisions HR practitioners made, as well as the barriers to effective implementation of HR analytics and DDDM.