Diagnostic Analytics

Diagnostic Analytics examines historical data to identify causes of past events and performance. Diagnostic Analytics in HR helps explain why turnover rose, why time-to-hire increased, or why engagement scores fell.

What is Diagnostic Analytics

Diagnostic Analytics goes beyond descriptive reporting to determine why something happened. It uses methods such as drill-downs, segmentation, correlation, and root cause analysis to reveal relationships between HR metrics and underlying factors.

How does it work

It combines HRIS, applicant tracking, payroll, performance, and engagement data. Analysts compare cohorts, run statistical tests, analyze timelines, and examine contextual factors. Insights link outcomes to causes so leaders can design targeted interventions.

Practical usage and examples

Where and why it is used: organisations use diagnostic analytics to investigate problems, meet compliance needs, and improve workforce planning. Common HR scenarios include

• Investigating a sudden spike in voluntary turnover to identify departments or managers with higher exits
• Diagnosing recruitment bottlenecks by analysing time-in-stage, source quality, and interview feedback
• Explaining pay disparities for compliance and remediation planning

Related HR concepts include descriptive analytics, predictive analytics, people analytics, HR metrics, and root cause analysis. These terms are closely connected and often used together in workforce decision making.