Workforce analytics
Five years of an organisation’s HR records rebuilt as a Power BI model: headcount, joiners and leavers, turnover, engagement and training. The HR system’s own status field disagrees with people’s start and exit dates more than a thousand times. The report believes the dates, and shows its working.
Headcount at each month-end
Turnover rose every year
Leavers over average headcount, annualised over the months each year actually holds — 2018 has five and 2023 seven, and dividing either by twelve would flatter it. Headcount is a stock, so it is read at month-ends and averaged, never summed.
| Year | Months | Joiners | Leavers | Headcount at year end | Average headcount | Turnover, annualised |
|---|
Rolling twelve-month turnover: leavers in the twelve months to each month-end, over the average headcount across the same months.
Nearly half leave in their first year
By department
Production is two thirds of the workforce, so it sets every company-wide rate. The small departments turn over faster, though at their size a handful of exits moves the rate.
| Department | Headcount | Leavers | Turnover | Left in year one |
|---|