{"id":10876,"date":"2026-01-08T10:04:09","date_gmt":"2026-01-08T09:04:09","guid":{"rendered":"https:\/\/powerbi.pl\/blog\/news\/power-bi-in-hr-analytics-of-turnover-absenteeism-and-labor-costs"},"modified":"2026-01-27T10:42:40","modified_gmt":"2026-01-27T09:42:40","slug":"power-bi-in-hr-analytics-of-turnover-absenteeism-and-labor-costs","status":"publish","type":"post","link":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/power-bi-in-hr-analytics-of-turnover-absenteeism-and-labor-costs","title":{"rendered":"Power BI in HR: analytics of turnover, absenteeism, and labor costs"},"content":{"rendered":"<h2>What business questions are worth \u201ctranslating\u201d into KPIs in Power BI?<\/h2>\n<p>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: <\/p>\n<ul>\n<li>turnover (who is leaving and why),<\/li>\n<li>absence (when and in which teams it increases),<\/li>\n<li>labor costs (how the cost of a full-time position and the cost of production change).<\/li>\n<\/ul>\n<p>It is worth defining KPIs in the \u201cHR \u00d7 finance\u201d logic right away, because then the same measure is useful for both HRBP and controlling.<\/p>\n<p>Example: \u201cturnover costs\u201d include not only recruitment, but also lost productivity and training time \u2013 <a href=\"https:\/\/www.gallup.com\/workplace\/247391\/fixable-problem-costs-businesses-trillion.aspx\">Gallup <\/a>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 <a href=\"https:\/\/www.zus.pl\/documents\/10182\/39590\/Raport_Absencja%2Bchorobowa%2Bw%2B2024%2Broku.pdf\/a4947e09-3b9c-41c6-1de6-83563006fd49?t=1744352901435\">(ZUS)<\/a> 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. <\/p>\n<p>A practical set of KPIs (good for starters):<\/p>\n<ul>\n<li><strong>Rotation:<\/strong> voluntary vs involuntary, 0\u20133 \/ 3\u20136 \/ 6\u201312 months of service, rotation of top performers, rotation in key roles. <\/li>\n<li><strong>Absenteeism:<\/strong> absenteeism rate (%), average number of days per FTE, short-term absenteeism (e.g., 1\u20133 days) vs. long-term absenteeism, seasonality.<\/li>\n<li><strong>Labor costs: <\/strong>FTE cost (total), overtime cost, replacement cost, absence cost, turnover cost, vacancy recruitment cost.<\/li>\n<li><strong>Effectiveness of actions: <\/strong>time-to-fill, time-to-productivity, retention after onboarding.<\/li>\n<\/ul>\n<h2>Data: how to build a model that \u201cconnects\u201d HR with personnel finance<\/h2>\n<p>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\u2014without 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 \u201ctwo-headed,\u201d 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 \u2192 increase in overtime \u2192 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 \u201cthis is not an incident, but a trend that needs to be managed.\u201d      <\/p>\n<p>What should usually be included in the data?<\/p>\n<ul>\n<li><strong>Human resources:<\/strong> date of hire\/departure, contract type, position, job title, manager, department, location, grade\/seniority.<\/li>\n<li><strong>Absences:<\/strong> date from\u2013to, type (illness\/care\/other), length, planned\/unplanned (if applicable).<\/li>\n<li><strong>Salaries and costs: <\/strong>gross salary + surcharges, bonuses, overtime, recruitment costs (invoices), training\/onboarding costs (if applicable).<\/li>\n<li><strong>Productivity\/operations (optional): <\/strong>sales per FTE, output per hour, requests handled per full-time position \u2013 this allows you to calculate productivity costs.<\/li>\n<\/ul>\n<h2>Rotacja w Power BI: od \u201eile\u201d do \u201edlaczego\u201d i \u201eco zrobi\u0119 jutro\u201d<\/h2>\n<p>Counting turnover is just the beginning \u2013 the real value lies in segmentation and early warning. The rotation dashboard works well with the following layout: a 12\u201324-month trend broken down into voluntary\/involuntary, then a drill-down to teams and risk groups (e.g., 0\u20136 months of service). In many organizations, turnover is most costly not because it is high, but because it affects key roles or top performers \u2013 Power BI allows you to show this without \u201cslide stories.\u201d<\/p>\n<p>It is also worth adding the recruitment dimension \u2013 the source of candidate acquisition, time-to-fill, quality of fit after 3\/6\/12 months \u2013 then we can see whether the problem lies with onboarding, the market, or selection. In financial communication, turnover is best measured by the \u201ccost of turnover\u201d metric because management makes decisions more quickly when they see the impact on the bottom line. <\/p>\n<h2>Absenteeism: seasonality, risk signals, and the \u201ctrue cost\u201d in payroll<\/h2>\n<p>In many companies, absenteeism is reported separately from costs \u2013 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). <\/p>\n<p>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 \u201crepeaters\u201d (recurring patterns) \u2013 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). <\/p>\n<h2>Labor costs: controlling, budgeting, and \u201cwhat-if\u201d scenarios<\/h2>\n<p>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: \u201cfixed costs\u201d (salaries and surcharges) and \u201cvariable costs\u201d (overtime, bonuses, replacements, recruitment, training). <\/p>\n<p>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: \u201cwhat if we increase the rate by 5% in critical roles vs. what if we increase staffing by 1 FTE per shift.\u201d This \u201cwhat-if\u201d model makes the HR-finance conversation more realistic: instead of discussing feelings, you compare options and their budgetary impacts.  <\/p>\n<h2>Painless implementation: governance, privacy, and quick wins in 30 days<\/h2>\n<p>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, \u201csafe\u201d summaries\u2014for 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 \u2013 without manually sending \u201ccut-out\u201d files or risking errors.   <\/p>\n<p><strong>The best results are achieved by making three simple cockpits at the beginning:<\/strong><\/p>\n<ol>\n<li>Turnover and retention \u2013 who leaves, when people most often leave (e.g., in the first 3\u20136 months), and where this occurs.<\/li>\n<li>Absenteeism \u2013 when does it increase, in which teams is it highest, and is there any seasonality (e.g., in winter)<\/li>\n<li>Labor costs \u2013 how much does it cost to hire someone, how does the actual work compare to the plan, and what \u201cincreases the bill\u201d (e.g., overtime, substitutes).<\/li>\n<\/ol>\n<p>In practice, after just a few weeks, you can have your first meaningful \u201cmanagement panel\u201d that organizes communication within the company. And then, step by step, you can add more data sources\u2014e.g., from recruitment, training, or time records\u2014without 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.  <\/p>\n<h2>Microsoft Power BI in HR \u2013 is it worth it?<\/h2>\n<p>Power BI allows you to combine turnover, absenteeism, and labor costs into a single, clear picture of the situation\u2014without 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 \u2013 so that it really supports HR and personnel controlling in managing people and budgets. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>In many companies, HR and finance departments look at people from two perspectives: HR looks for causes and patterns (why people leave, where absenteeism is growing, what is happening with engagement), while payroll keeps an eye on costs (how much it really costs and how it affects the bottom line). Power BI allows you to combine these worlds into a single, consistent data model and turn scattered HR and payroll reports into decision-making dashboards. This is particularly important because turnover is rarely \u201cjust an HR problem\u201d \u2013 the cost of replacing an employee is estimated at between 50% and 200% of their annual salary, depending on their role and seniority. In turn, sick leave in Poland is on a scale that cannot be ignored: in 2024, 27.4 million medical certificates were registered, totaling 290 million days of absence. When we compare this data with the cost of man-hours, overtime, and replacements, we get a picture that is ideal for weekly or monthly management \u2013 not \u201cafter the fact\u201d at the end of the quarter.     <\/p>\n","protected":false},"author":2,"featured_media":10873,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[30],"tags":[489],"class_list":["post-10876","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-microsoft-power-bi-en","tag-power-bi-in-hr"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Power BI in HR: analytics of turnover, absenteeism, and labor costs | EBIS - Microsoft Power BI Partner<\/title>\n<meta name=\"description\" content=\"Power BI allows you to combine turnover, absenteeism, and labor costs into a single, clear picture of the situation\u2014without guesswork or manually piecing together reports.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/power-bi-in-hr-analytics-of-turnover-absenteeism-and-labor-costs\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Power BI in HR: analytics of turnover, absenteeism, and labor costs | EBIS - 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