What business questions are worth “translating” into KPIs in Power BI?
The most valuable dashboards are those that answer specific questions: where to raise salaries, where to strengthen onboarding, and where to change the organization of work. In practice, three areas are key:
- turnover (who is leaving and why),
- absence (when and in which teams it increases),
- labor costs (how the cost of a full-time position and the cost of production change).
It is worth defining KPIs in the “HR × finance” logic right away, because then the same measure is useful for both HRBP and controlling.
Example: “turnover costs” include not only recruitment, but also lost productivity and training time – Gallup indicates that the cost of replacing an employee can range from half to even twice their annual salary. The same applies to absenteeism: Social Insurance Institution (ZUS) data allows us to place the issue in the context of market realities (number of days), and the company then adds its own rates and replacement mechanism.
A practical set of KPIs (good for starters):
- Rotation: voluntary vs involuntary, 0–3 / 3–6 / 6–12 months of service, rotation of top performers, rotation in key roles.
- Absenteeism: absenteeism rate (%), average number of days per FTE, short-term absenteeism (e.g., 1–3 days) vs. long-term absenteeism, seasonality.
- Labor costs: FTE cost (total), overtime cost, replacement cost, absence cost, turnover cost, vacancy recruitment cost.
- Effectiveness of actions: time-to-fill, time-to-productivity, retention after onboarding.
Data: how to build a model that “connects” HR with personnel finance
In Power BI, the star model yields the best results: one fact table (e.g., employment/HR events) and several dimensions (employee, position, department, location, time). This layout allows you to quickly filter turnover and absenteeism by managers, job types, shifts, locations, or recruitment sources—without manually creating Excel files. The key rule is that HR dimensions (e.g., department, position, manager) must be consistent with financial dimensions (MPK, cost center, contract/project), the report will be “two-headed,” and everyone will calculate something different. For absenteeism and labor costs, it is worth keeping separate data (e.g., daily absenteeism facts, payroll facts), but linked to the same time and organization dimensions. This gives you the ability to perform cause-and-effect analysis: e.g., increase in absenteeism → increase in overtime → increase in unit cost. And because the Social Insurance Institution reports, among other things, the total number of days of absenteeism in Poland on an annual basis, it is easier to show in internal communication that “this is not an incident, but a trend that needs to be managed.”
What should usually be included in the data?
- Human resources: date of hire/departure, contract type, position, job title, manager, department, location, grade/seniority.
- Absences: date from–to, type (illness/care/other), length, planned/unplanned (if applicable).
- Salaries and costs: gross salary + surcharges, bonuses, overtime, recruitment costs (invoices), training/onboarding costs (if applicable).
- Productivity/operations (optional): sales per FTE, output per hour, requests handled per full-time position – this allows you to calculate productivity costs.
Rotacja w Power BI: od „ile” do „dlaczego” i „co zrobię jutro”
Counting turnover is just the beginning – the real value lies in segmentation and early warning. The rotation dashboard works well with the following layout: a 12–24-month trend broken down into voluntary/involuntary, then a drill-down to teams and risk groups (e.g., 0–6 months of service). In many organizations, turnover is most costly not because it is high, but because it affects key roles or top performers – Power BI allows you to show this without “slide stories.”
It is also worth adding the recruitment dimension – the source of candidate acquisition, time-to-fill, quality of fit after 3/6/12 months – then we can see whether the problem lies with onboarding, the market, or selection. In financial communication, turnover is best measured by the “cost of turnover” metric because management makes decisions more quickly when they see the impact on the bottom line.
Absenteeism: seasonality, risk signals, and the “true cost” in payroll
In many companies, absenteeism is reported separately from costs – and this is a mistake, because absenteeism has a direct impact on overtime, replacements, and timely delivery. Microsoft Power BI is great at showing seasonality (months, weeks, even days of the week), as well as differences between locations and types of work (shift work vs. office work, physical work vs. knowledge work).
In company practice, it is worth distinguishing between short-term absences (often the most painful in operational terms) and long-term absences (often significant in terms of cost) and analyzing “repeaters” (recurring patterns) – but with respect for privacy rules. The biggest breakthrough comes when vacation time is linked to payroll: the cost of absenteeism (salary + surcharges), the cost of replacements, the cost of lost productivity, and the cost of quality (e.g., complaints, delays).
Labor costs: controlling, budgeting, and “what-if” scenarios
If Power BI is to truly support personal finance, we need a consistent view of labor costs: per FTE, per department, per MPK/project, and over time (M/M, YTD, rolling 12). It is good practice to show costs in two layers: “fixed costs” (salaries and surcharges) and “variable costs” (overtime, bonuses, replacements, recruitment, training).
In this context, it is easy to identify whether the increase in labor costs is due to wage decisions or operational problems (e.g., absenteeism leading to overtime). Scenarios in Power BI (e.g., parameters/what-if) allow controlling to quickly calculate the consequences: “what if we increase the rate by 5% in critical roles vs. what if we increase staffing by 1 FTE per shift.” This “what-if” model makes the HR-finance conversation more realistic: instead of discussing feelings, you compare options and their budgetary impacts.
Painless implementation: governance, privacy, and quick wins in 30 days
In HR analytics projects, the problem is usually not a lack of tools, but two things: whether we can trust the data and whether we will violate employee privacy. That is why it is best to start with simple, “safe” summaries—for example, at the department, location, or position level, without going into details about specific individuals. Only when the access rules are clearly established can you go deeper and analyze the data in more detail, which makes real business sense. Power BI also lets you set up views so everyone sees only what they need: managers see their teams, and controllers see costs across cost centers – without manually sending “cut-out” files or risking errors.
The best results are achieved by making three simple cockpits at the beginning:
- Turnover and retention – who leaves, when people most often leave (e.g., in the first 3–6 months), and where this occurs.
- Absenteeism – when does it increase, in which teams is it highest, and is there any seasonality (e.g., in winter)
- Labor costs – how much does it cost to hire someone, how does the actual work compare to the plan, and what “increases the bill” (e.g., overtime, substitutes).
In practice, after just a few weeks, you can have your first meaningful “management panel” that organizes communication within the company. And then, step by step, you can add more data sources—e.g., from recruitment, training, or time records—without causing a revolution. The most important thing is that the report does not end with nice charts, but leads to specifics: what we are doing, who is responsible for it, and how we will know in a month that the situation is improving.
Microsoft Power BI in HR – is it worth it?
Power BI allows you to combine turnover, absenteeism, and labor costs into a single, clear picture of the situation—without guesswork or manually piecing together reports. It provides the greatest value when it does not end with charts, but leads to decisions: where we operate, who is responsible, and how we measure the effect. It is worth starting with a few key indicators and simple dashboards, and then developing analytics step by step – so that it really supports HR and personnel controlling in managing people and budgets.