HR analytics is working with data about people: what hiring costs, where turnover is rising, how overtime relates to absenteeism. It is not reporting for the board but a way of answering questions that would otherwise be answered by intuition.
Where it actually starts
Not with dashboards but with trustworthy source data. A timesheet filled in from the schedule yields zero absenteeism and even overtime — and any analysis on top of it describes the plan rather than reality. So the first step is always the same: actual time records and personnel events captured when they happened.
The second condition is comparability. A metric with no breakdown and no history yields no decision: 12% turnover means nothing, while 12% against 7% last quarter and 30% at two sites out of twenty is a specific conversation about specific branches.
The metrics worth starting with
It pays to start not with a full suite but with a few measures that are connected and explain one another.
- Turnover, broken out for new hires and by unit — together with the cost of replacement.
- Absenteeism and overtime by site: usually two sides of the same scheduling problem.
- Time to hire and funnel conversion: the price of an open vacancy is counted through the overtime that covers it.
- Payroll as a share of a site's revenue — the measure that connects HR data to the economics of the business.
How this works in Verifix
In Verifix analytics is not a separate module but a consequence of keeping records in one system: time records, timesheets, accruals, personnel events, KPIs and training results sit in one loop and are already linked.
So breakdowns by site, department and period come out without consolidating spreadsheets, and the measures can be read together: rising overtime at a branch is visible next to its turnover and absenteeism for the same month.
In short
HR analytics starts with a trustworthy timesheet, not with a dashboard. On data entered from the schedule, any analysis describes the plan rather than reality.