ABSTRACT
People analytics results in attaining new skills and experiences to survive and thrive in this digital era in the human resources processes, from hiring to the last day of employment. It’s a disruptive technology to earmark high-performing organizations. Various machine learning (ML) and Internet of Things (IoT) solutions and their characteristics, trends, and general uses across sectors have been widely researched, however, specific studies on their effects and concerns in people analytics (PA) are still inadequate. Therefore, this chapter discusses the impact analysis of ML and IoT application in PA to bridge this limited scholarship on workforce diagnosis through ML and IoT systems. This book chapter proposes a research-based agenda for use of IoT and ML in PA. The research is based solely on literature review from the major databases, namely, Google Scholar; Elsevier; SAGE Publications, and Emerald Insight. Generally, the use of PA (technology-based) is its infancy. Organizational-based models need to be developed and implemented in relation to sector and organizational experiences. The implemented models will need evaluation and benchmarking for success.
