itsual HR Analytics
Overview
HR analytics turns people data into decisions. It requires clean definitions, appropriate methods, and ethical use of employee information.
When to Use
- Turnover and retention analysis
- Recruiting funnel diagnostics
- Diversity and pay equity analytics support
- Workforce planning inputs
- Predicting risk with appropriate caution
Core Practices
- Define metrics precisely (e.g., what counts as regrettable turnover)
- Build trusted data pipelines from HRIS and related systems
- Segment before prescribing global fixes
- Pair quantitative findings with qualitative context
- Protect privacy and avoid unfair automated decisions
- Present insight as decisions and actions, not only charts
Principles
- Bad definitions produce confident nonsense
- Correlation is not causation — especially in people data
- Transparency with employees about data use builds trust
- Analytics without operational owners changes nothing
Verification
- Metric dictionary exists for key measures
- Analyses lead to owned actions
- Privacy and ethics constraints are respected