Four Types of People Analytics

People analytics, the collection and analysis of data to drive better business and talent outcomes by informing better decisions about individuals, teams, and organizations, is a rapidly evolving discipline, driven by the availability of more data, advances in technology, and the influence of diverse disciplines.

I-O psychology has been foundational in shaping people analytics, and continues to be a connector and leader in the field, touching all four types of people analytics:

• Descriptive analytics
• Diagnostic analytics
• Predictive analytics
• Prescriptive analytics

Perhaps the most common type of people analytics, descriptive analytics, uses data to look at what happened. Diagnostic analytics goes a step further, exploring why something happened.

Predictive analytics uses data and models to predict what will or might happen in the future, while prescriptive analytics uses that information to make decisions that will improve business outcomes and the employee experience.

Although each of these types of people analytics offer valuable insight into employee performance, demographics, and engagement, using them together provides a comprehensive look at the workforce.

“These four types of analyses are sometimes portrayed as sequential in the sense of an analytics maturity progression, where you have to start with descriptive analytics and progress toward prescriptive analytics. However, they are complementary and overlapping; nothing stops you from jumping straight into predictive analytics,” said 2025 SIOP Leading Edge Consortium Speaker and Planning Committee Member Amit Mohindra. “As an example, a descriptive analysis of the impact of training on promotability via a two-by-two matrix showing participation (yes/no) and promotion (yes/no) is also predictive, since you can extract the odds of promotion given participation from the four numbers in the matrix. After all, you forecast or predict the future based on the past.”

In action, descriptive analytics might show that fewer employees participated in professional development in the past calendar year. Diagnostic analytics might suggest that fewer employees are participating in professional development because they are struggling with work-life balance. Predictive analytics might suggest that without intervention, even fewer employees will participate in professional development in the current calendar year. By using prescriptive analytics, a team may decide to offer new or additional group professional development opportunities during typical working hours so that employees do not have to choose between professional development and personal time over lunch, in the evenings, or on weekends.

For more information about people analytics and how I-O psychology can advance the field, read on about the 2025 SIOP Leading Edge Consortium: Advancing People Analytics.