People Analytics, also known as HR analytics or workforce analytics, is the practice of collecting, analyzing, and applying data about employees to improve HR decision-making and business outcomes. It uses statistical methods, predictive modeling, and data visualization to uncover patterns in employee behavior, performance, engagement, and retention.
HR decisions have traditionally relied on intuition and experience. People analytics introduces a data-driven approach, enabling leaders to make informed choices about hiring, development, performance, and retention. By leveraging analytics, organizations can identify trends, predict risks (such as turnover), and design strategies that improve both employee experience and business performance.
People analytics sits within the analytics and insights layer of the HR stack. It pulls data from core systems like HRIS, ATS, LMS, engagement platforms, and payroll systems to generate insights. Increasingly, people analytics is being embedded into all HR tech tools, rather than existing as a stand-alone function.
HR reporting provides descriptive data (e.g., headcount, turnover rates), while People Analytics uses advanced techniques like predictive modeling and machine learning to forecast trends and recommend actions.
Common sources include HRIS, payroll, ATS, engagement surveys, LMS, and performance management tools. External data, such as labor market trends, can also be integrated.
No. While it started in large organizations, many SaaS-based tools now make People Analytics accessible to small and mid-sized businesses.
Data privacy, employee consent, and the potential for biased algorithms are key concerns. Companies must ensure transparency and comply with data protection regulations (e.g., GDPR).
HR teams need skills in data analysis, statistics, and storytelling. Increasingly, companies also hire data scientists or business analysts to support People Analytics initiatives.