People Analytics
People analytics is the use of HR and workforce data to answer business questions about hiring, retention, engagement and performance, so that decisions about people rest on evidence as well as experience.
Definition
People analytics, also called HR analytics, brings together data on employees, such as headcount, hires, departures, absences, mobility and survey results, to understand what is happening in the workforce and why. It ranges from simple dashboards describing the situation to analyses that look for the factors behind turnover or hiring success.
It starts from a clear question, for example where do new hires leave in their first year, and then follows a few steps: gather reliable data from HR systems, define each indicator in the same way, analyse by team or group, and share findings with the managers who can act. Qualitative inputs such as interviews give the context that numbers miss.
It matters because HR decisions are expensive and often taken on impressions. The pitfalls are poor data quality, conclusions drawn from very small groups, and use of personal data without care. Employee data is personal data: respect the rules that apply, such as GDPR in the EU, be transparent, and keep humans in charge of decisions.
Key points
- It starts with a business question, not with the data available.
- Quality and shared definitions of indicators matter more than sophisticated tools.
- Numbers show what happens; conversations explain why.
- Avoid conclusions on very small groups and protect individuals' data.
- Analysis supports decisions made by people; it does not make them.
Example
An HR team of a 600-person company sees that departures peak in the first year. By comparing teams, it finds the peak is concentrated where onboarding is shortest. HR and managers redesign onboarding there and follow first-year departures over the next year.
Frequently asked questions
Do we need data scientists to start with people analytics?
No. Clear indicators on turnover, absences and hiring, reviewed regularly by team, already give useful insight. More advanced analysis can come later if there is a question that requires it.
Is people analytics compatible with data protection?
Yes, if done properly: collect only what is needed, tell employees what is used and why, limit access and report in aggregate. Check the data protection rules that apply in your country.
What should we measure first?
Start with the topics that concern leaders: turnover, time to hire, absenteeism and engagement. Pick a few indicators, define them precisely and track them over time.
Related terms
AI conversations, human decisions
Passisto holds structured voice conversations with candidates, employees, clients and students, and turns them into reports your team can act on.