Designing a Human Resource Analytics System for Predictive Workforce Planning

The first contribution of this study is the analysis of the role of HR analytics tools for the predictive workforce planning and the effect on the organizational performance. The first objective is to develop an HR analytics system to facilitate data driven decision making and the second objective is to evaluate the impact of HR analytics system on workforce optimization, employee retention, and cost efficiency. Quantitative research approach was adopted with a structured questionnaire which was used to collect data from 100 respondents. In order to determine the relationship between HR analytics system performance and performance of key factors like workforce planning effectiveness, decision making quality, employee retention, organisational productivity, and cost efficiency, the study used regression analysis and ANOVA. This model is validated by the results which show that workforce planning effectiveness, decision making quality and organizational productivity have a significant effect on the performance of HR analytics system. Despite this, the impact of employee retention and cost efficiency was not very strong and it is possible that there are other factors contributing to these. As later validated by the ANOVA findings, the model also statistically relates HR analytics to workforce management. Based on this, the study suggests that incorporating the HR analytics into the workforce planning can improve predictive abilities, improve decisions, and allocate resources more efficiently. HR analytics is effective when organizations are able to implement HR analytics effectively, which will help organizations become more efficient, adaptable and sustainable in the long term for workforce management.