{"id":6978,"date":"2026-06-08T11:54:42","date_gmt":"2026-06-08T11:54:42","guid":{"rendered":"https:\/\/iwis.io\/?p=6978"},"modified":"2026-05-30T20:44:10","modified_gmt":"2026-05-30T20:44:10","slug":"kpi-dashboards-in-power-bi","status":"publish","type":"post","link":"https:\/\/iwis.io\/en\/blog\/kpi-dashboards-in-power-bi\/","title":{"rendered":"KPI dashboards in Power BI: how to build a reporting system that every manager understands"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":6977,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[355,350],"tags":[],"class_list":["post-6978","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics","category-business-intelligence"],"acf":{"blog_custom_title":"KPI dashboards in Power BI: how to build a reporting system that every manager understands","blog_featured_image":6977,"blog_custom_excerpt":"","blog_external_url":"","blog_categories":[350,355],"blog_tags":false,"blog_featured_post":false,"blog_content_blocks":[{"acf_fc_layout":"text_block","text_content":"

In 2004, Walmart began analyzing how customer behavior changed before hurricanes. The company expected to see increased sales of water, batteries, and canned goods. However, one of the top-selling items that surged before storms turned out to be quite unusual: strawberry Pop-Tarts (a popular quick-toast snack in the U.S. that can be eaten straight from the package, even cold). Before hurricanes, sales of Pop-Tarts rose approximately sevenfold. After this discovery, Walmart started proactively increasing shipments of such items to regions in the storm\u2019s path. In effect, the company learned to predict customer behavior through data.<\/span><\/p>\r\n

This is a good example of how modern analytics works: businesses begin to see not only obvious indicators but also hidden patterns. That\u2019s because most companies already have an overwhelming amount of data \u2014 from CRM, ERP, ad platforms, Excel files, financial systems, and warehouse analytics. But without a proper reporting system, it all remains a jumble of disconnected numbers.<\/span><\/p>\r\n

This is why Power BI dashboards have also become a way for businesses in Ukraine to bring these fragments together into a unified management picture.<\/span><\/p>\r\n\r\n

Why Excel-Based Management Reporting No Longer Works<\/span><\/strong><\/h2>\r\n

Excel is a great tool, but it was built for working with data \u2014 not for real-time management reporting. Here\u2019s what happens in most companies:<\/span><\/p>"},{"acf_fc_layout":"list_block","list_title":"","list_type":"ul","list_items":[{"item_text":"The analyst spends 2-3 days every month compiling the report, and even if it is perfect, it may be out of date by the time it is sent."},{"item_text":"Each department keeps its own file, the data diverges, and no one knows which version to believe."},{"item_text":"Formulas break: someone deleted a row, someone changed the structure. The report starts showing nonsense, and it takes a while to notice."},{"item_text":"Scaling is impossible: as the business grows, the Excel model turns into a monster with thousands of rows, intimidating new employees and starting to run slowly even on basic operations."}]},{"acf_fc_layout":"text_block","text_content":"Companies with advanced BI<\/strong> reporting usually make management decisions faster because they work with centralized and up-to-date data. The difference between Excel and Power BI is that the data is updated automatically and the manager sees the state of the business right now."},{"acf_fc_layout":"text_block","text_content":"

What a KPI Dashboard Is and What It Should Be Like<\/span><\/strong><\/h2>\r\n

A KPI dashboard is an interactive visual report that aggregates key performance indicators from various sources and displays them in a single interface. It is a decision-making tool that shows what is going wrong and where deviations from the plan exist.<\/span><\/p>\r\n\r\n

Principles of Good Visualization<\/span><\/strong><\/h3>\r\n

A good dashboard follows the \"three-second rule\": within three seconds, a manager should be able to grasp the main insights. The key principles of data visualization are:<\/span><\/p>"},{"acf_fc_layout":"list_block","list_title":"","list_type":"ul","list_items":[{"item_text":"Information hierarchy. The most important KPIs in large font at the top, details below."},{"item_text":"Minimum colors. Two or three: one for the norm, one for deviation, one for accent. Too many colors usually make the dashboard difficult to understand."},{"item_text":"The correct type of graph. Dynamics - linear. Comparison - bar. It is usually more convenient to show shares with a doughnut chart, rather than a classic pie chart. Geography - map."},{"item_text":"Context. For example, the number 5000 by itself doesn\u2019t say anything. But \u201c5000 vs plan 6000 (-17%)\u201d says a lot."},{"item_text":"Filters and drill-down. The manager can drill down into details: from the general region to a specific manager or SKU (product line item)."}]},{"acf_fc_layout":"text_block","text_content":"

Dashboard types: operational, strategic, tactical<\/strong><\/h3>"},{"acf_fc_layout":"table_block","table_header":null,"table_rows":[{"row_cells":[{"cell_content":"Type"},{"cell_content":"Horizon"},{"cell_content":"Audience"},{"cell_content":"Examples of KPIs"}]},{"row_cells":[{"cell_content":"Operating"},{"cell_content":"Today\/Week"},{"cell_content":"Line managers"},{"cell_content":"Daily plan execution, number of calls, request processing time"}]},{"row_cells":[{"cell_content":"Tactical"},{"cell_content":"Month\/quarter"},{"cell_content":"Department heads"},{"cell_content":"Budget execution, funnel conversion, NPS"}]},{"row_cells":[{"cell_content":"Strategic"},{"cell_content":"Quarter\/year"},{"cell_content":"CEO, CFO, owners"},{"cell_content":"EBITDA (earnings before interest, taxes, depreciation and amortization), market share, CAC vs LTV, ROI by product"}]}]},{"acf_fc_layout":"text_block","text_content":"
\r\n
\r\n

Step-by-Step Guide to Creating a Dashboard<\/span><\/strong><\/h2>\r\n

Power BI Desktop is Microsoft's main free application for creating BI reports. Below, we'll go through a step-by-step guide on setting up Power BI from scratch to a finished dashboard.<\/span><\/p>\r\n\r\n

Step 1: Connecting Data Sources<\/span><\/strong><\/h3>\r\n

Power BI connects to hundreds of data sources: Excel, Google Sheets, SQL databases, CRM systems, cloud services, web APIs.<\/span><\/p>\r\n\r\n<\/div>\r\n<\/div>"},{"acf_fc_layout":"list_block","list_title":"CRM systems, cloud services, web APIs. Algorithm:","list_type":"ul","list_items":[{"item_text":"Click \u201cGet Data\u201d on the main panel."},{"item_text":"Select the source type: Excel, SQL Server, SharePoint, or Other for non-standard connections."},{"item_text":"Enter the connection parameters (file path or database connection string)."},{"item_text":"Preview the tables and select the ones you need."}]},{"acf_fc_layout":"text_block","text_content":"

Practical tip:<\/span><\/strong> connect data directly to the database or cloud storage. This way, the dashboard will update automatically without the need to manually upload files.<\/span><\/p>\r\n\r\n

Step 2: Transformation in Power Query<\/span><\/strong><\/h3>\r\n

Power Query is Power BI's built-in ETL editor. Here, you clean the data before building reports. The most common operations are:<\/span><\/p>"},{"acf_fc_layout":"list_block","list_title":"","list_type":"ul","list_items":[{"item_text":"Removing empty rows and duplicates."},{"item_text":"Changing data types (text \u2192 date, text \u2192 number)."},{"item_text":"Column breakdown (\u201cLast Name\u201d \u2192 \u201cFirst Name\u201d + \u201cLast Name\u201d)."},{"item_text":"Merging tables from different sources (Merge\/Append)."}]},{"acf_fc_layout":"text_block","text_content":"

Translator Note:<\/span><\/strong> Everything you do in Power Query is recorded as repeatable steps. Each time the data is refreshed, these transformations are applied automatically.<\/span><\/p>\r\n\r\n

Step 3: Data Model and Relationships<\/span><\/strong><\/h3>\r\n

Go to the \"Model\" tab. Here you can see all the tables and the relationships between them. The most common architecture is the \"star schema\": a fact table (sales, transactions) in the center, with dimension tables (customers, products, dates, managers) around it.<\/span><\/p>\r\n

Important:<\/span><\/strong> always create a separate date table. It allows you to correctly calculate metrics for any time period and use Time Intelligence functions in DAX.<\/span><\/p>\r\n\r\n

Step 4: Basic DAX Metrics<\/span><\/strong><\/h3>\r\n

DAX (Data Analysis Expressions) is the formula language in Power BI used to calculate management reports. This is where raw data is transformed into metrics that managers actually use in their daily work: revenue, margin, conversion rate, plan attainment, year-over-year dynamics, average check, CAC, ROI.<\/span><\/p>\r\n

At first glance, this seems like just a technical step. But in reality, it often reveals a deeper problem: different departments may interpret the same metric in different ways.<\/span><\/p>\r\n

For example, sales might calculate revenue based on signed deals, finance based on actual payments received, and operations based on fulfilled orders. Everyone uses the term \"revenue,\" but they mean different things. This is why DAX is a way to establish a single, unified logic for management metrics.<\/span><\/p>\r\n\r\n

Here are the simplest examples of basic metrics:<\/span><\/strong><\/h3>"},{"acf_fc_layout":"table_block","table_header":null,"table_rows":[{"row_cells":[{"cell_content":"Metrics"},{"cell_content":"Example of logic"},{"cell_content":"Why is it needed?"}]},{"row_cells":[{"cell_content":"Total Sales"},{"cell_content":"Sales amount"},{"cell_content":"Basic revenue control"}]},{"row_cells":[{"cell_content":"Plan %"},{"cell_content":"Fact\/plan"},{"cell_content":"Fulfilling goals"}]},{"row_cells":[{"cell_content":"Sales LY"},{"cell_content":"Sales for the same period last year"},{"cell_content":"Dynamics comparison"}]},{"row_cells":[{"cell_content":"YoY %"},{"cell_content":"Change from last year"},{"cell_content":"Growth or decline assessment"}]}]},{"acf_fc_layout":"text_block","text_content":"The table here is useful as a way to show that even basic KPIs need to be formalized. If the formula is not described, everyone will interpret it in their own way.\r\n

Step 5: Visuals and Filters<\/strong><\/h3>"},{"acf_fc_layout":"list_block","list_title":"Go to the \u201cReport\u201d tab. Here are some practical recommendations:","list_type":"ul","list_items":[{"item_text":"Start with the KPI cards at the top: they show the most important numbers with a comparison to the plan or the previous period."},{"item_text":"Add a line graph for dynamics over time. This is the most readable way to show a trend."},{"item_text":"Use slicers to filter by region, manager, product category. Place them on the left or on top."},{"item_text":"Enable interaction between visuals: click on a column and all other elements are filtered."},{"item_text":"Do not overload one page: maximum 5-7 elements, detailing \u2013 on separate tabs."}]},{"acf_fc_layout":"text_block","text_content":"

Step 6: Publish and Access<\/strong><\/h3>\r\nThe finished dashboard is published to Power BI Service (cloud version):"},{"acf_fc_layout":"list_block","list_title":"","list_type":"ol","list_items":[{"item_text":"Click \u201cPublish\u201d in Power BI Desktop."},{"item_text":"Select a workspace in Power BI Service."},{"item_text":"Configure automatic data refresh (the number of refreshes depends on the Power BI license type)."},{"item_text":"Give colleagues access via a link or set up Row Level Security: everyone sees only their own data."},{"item_text":"If necessary, embed the dashboard into a corporate portal or SharePoint."}]},{"acf_fc_layout":"text_block","text_content":"

Top 5 KPIs for Different Departments<\/strong><\/h3>\r\nTrying to display everything at once is one of the most common mistakes when building dashboards. Let\u2019s look at proven KPI sets to start with.\r\n\r\nSales<\/strong>"},{"acf_fc_layout":"table_block","table_header":null,"table_rows":[{"row_cells":[{"cell_content":"KPI"},{"cell_content":"Formula \/ source"},{"cell_content":"Why"}]},{"row_cells":[{"cell_content":"Revenue vs plan"},{"cell_content":"Fact\/plan \u00d7 100%"},{"cell_content":"Basic performance control"}]},{"row_cells":[{"cell_content":"Funnel conversion"},{"cell_content":"Closed Deals\/Leads \u00d7 100%"},{"cell_content":"Quality of work with leads"}]},{"row_cells":[{"cell_content":"Deal cycle (days)"},{"cell_content":"Closing date \u2212 opening date"},{"cell_content":"Sales process efficiency"}]},{"row_cells":[{"cell_content":"Retention rate (customer retention)"},{"cell_content":"(Clients at the end of the period \u2212 New clients) \/ Clients at the beginning of the period"},{"cell_content":"Maintaining the customer base"}]}]},{"acf_fc_layout":"text_block","text_content":"

Marketing<\/h3>"},{"acf_fc_layout":"table_block","table_header":[{"header_text":"KPI"},{"header_text":"Formula \/ source"},{"header_text":"Why"}],"table_rows":[{"row_cells":[{"cell_content":"CAC (customer acquisition cost)"},{"cell_content":"Marketing expenses\/New customers"},{"cell_content":"Customer acquisition cost"}]},{"row_cells":[{"cell_content":"ROAS (return on advertising spend)"},{"cell_content":"Advertising revenue\/Advertising expenses"},{"cell_content":"Effectiveness of advertising channels"}]},{"row_cells":[{"cell_content":"Distribution of leads by channels"},{"cell_content":"UTM tags + CRM"},{"cell_content":"Budget allocation between channels"}]},{"row_cells":[{"cell_content":"CPL (cost per lead)"},{"cell_content":"Cost\/Number of leads"},{"cell_content":"Comparing campaign performance"}]},{"row_cells":[{"cell_content":"Email open rate \/ CTR"},{"cell_content":"Email platform data"},{"cell_content":"Quality of content strategy"}]}]},{"acf_fc_layout":"text_block","text_content":"

Operations<\/h3>"},{"acf_fc_layout":"table_block","table_header":[{"header_text":"KPI"},{"header_text":"Formula \/ source"},{"header_text":"Why"}],"table_rows":[{"row_cells":[{"cell_content":"Application execution time"},{"cell_content":"Closing date \u2212 opening date"},{"cell_content":"Speed \u200b\u200bof the operational process"}]},{"row_cells":[{"cell_content":"Resource utilization"},{"cell_content":"Actual hours\/Available hours \u00d7 100%"},{"cell_content":"Capacity planning"}]},{"row_cells":[{"cell_content":"SLA (service level) fulfillment"},{"cell_content":"Applications in the deadline\/Total applications"},{"cell_content":"Compliance with service standards"}]},{"row_cells":[{"cell_content":"Number of defects"},{"cell_content":"QC system or ERP data"},{"cell_content":"Quality control"}]},{"row_cells":[{"cell_content":"Cost of surgery"},{"cell_content":"Total costs\/Number of operations"},{"cell_content":"Cost efficiency"}]}]},{"acf_fc_layout":"text_block","text_content":"

Free Power BI Templates for Download<\/span><\/strong><\/p>\r\n

The fastest way to get started is to use a ready-made template and adapt it to your data. Where to look:<\/span><\/p>\r\n\r\n