Track your key HR metrics, and add the ones specific to your business

Every report ships connected to an Excel file, the simplest setup when you don't have a data infrastructure. You can swap that file for your own Excel files, and, more importantly, connect the report directly to your sources.

• Power BI Desktop file (.pbix), ready to publish to the Power BI service.
• Five pages: Headcount (headcount, % women, salaried employees, and % managers vs. prior year, detail by department), Demographics (age and gender balance), Turnover (leavers, hires, turnover and churn rates vs. prior year, by department, age, and tenure), Compensation (average and median pay, annual payroll, P90/P10 ratio, raises YTD, spread by department), and Pay Equity (women's and men's average hourly rate by department); Year, Department, Pay type, Gender, Marital status, and Job title filters, depending on the page.
• Data loaded by Power Query from five sheets of an Excel workbook, the anonymized dataset, which you replace with your data: Employees, Assignments, Pay History, Departments, and Shifts, linked by employee ID and by department and shift codes; a single query points to the file to read.
• As-of date: the later of your export date (optional "Extract" sheet) and the workbook's latest event. Headcount, age, tenure, and pay are calculated at that date; leavers and hires over the selected period, vs. the same months of the previous year.
• Leavers counted on the exit date, whatever the reason, and assigned to the department of the last assignment. Turnover rate = leavers / average headcount, the US definition; churn rate = (leavers + hires) / 2 / average headcount; not annualized.
• Pay: each current employee's hourly rate in effect. Annual salary = rate × 2,080 hours, a 40-hour full-time week (AnnualHours parameter, to adjust to your standard working hours); annual payroll in full-time equivalent, excluding bonuses, overtime, and employer payroll taxes.
• Gender pay gap = (women's average hourly rate - men's average hourly rate) / men's average hourly rate: an unadjusted gap, not controlled for job, level, or age, and not a regulatory pay gap report.
• Model: employees linked to the history of their assignments and hourly rates, to departments, to shifts, and to a calendar rebuilt at every refresh.
• DAX measures: headcount at a date and average headcount, leavers and hires vs. prior year, turnover and churn rates, ages and tenures, average and median pay, percentiles (P10 to P90), raises YTD, gender pay gap.