People Analytics – Using Data and Algorithms to shape the Employee Experience

Abstract

People Analytics (PA) is the name for a growing approach to talent management that has the potential to re-shape the employee experience. Making use of new computational techniques to leverage large amounts of digital data about employee behaviour, this approach promises to introduce evidence-based management to the talent function. Main drivers of PA include advances in data collection and analytics (big data), as well as new approaches to algorithmic management based on machine learning techniques (AI). In this study, we spell out promises, challenges and limitations of People Analytics. We have undertaken a comprehensive market overview of PA software solutions. We found that most PA systems originate from established HR and talent management solutions, while a number of interesting and innovative new players are solving particular pertinent issues in a focused way. Our market analysis classified systems according to detailed criteria derived from the talent management wheel. We identified five main archetypes of PA systems. Moreover, we present three Capgemini client case studies with various learnings around PA implementation challenges. We conclude the report with recommendations on how to kick-off people analytics projects. We argue that the Employee Experience (EX) will always take centre stage, as PA is never an end in itself, but a means to achieving more effective talent management with a view to improve employee experience, satisfaction, productivity and retention.