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’s path. In effect, the company learned to predict customer behavior through data.
This is a good example of how modern analytics works: businesses begin to see not only obvious indicators but also hidden patterns. That’s because most companies already have an overwhelming amount of data — 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.
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.
Excel is a great tool, but it was built for working with data — not for real-time management reporting. Here’s what happens in most companies:
Companies with advanced BI 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.
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.
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:
| Type | Horizon | Audience | Examples of KPIs |
| Operating | Today/Week | Line managers | Daily plan execution, number of calls, request processing time |
| Tactical | Month/quarter | Department heads | Budget execution, funnel conversion, NPS |
| Strategic | Quarter/year | CEO, CFO, owners | EBITDA (earnings before interest, taxes, depreciation and amortization), market share, CAC vs LTV, ROI by product |
Practical tip: connect data directly to the database or cloud storage. This way, the dashboard will update automatically without the need to manually upload files.
Power Query is Power BI’s built-in ETL editor. Here, you clean the data before building reports. The most common operations are:
Translator Note: Everything you do in Power Query is recorded as repeatable steps. Each time the data is refreshed, these transformations are applied automatically.
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.
Important: always create a separate date table. It allows you to correctly calculate metrics for any time period and use Time Intelligence functions in DAX.
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.
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.
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.
| Metrics | Example of logic | Why is it needed? |
| Total Sales | Sales amount | Basic revenue control |
| Plan % | Fact/plan | Fulfilling goals |
| Sales LY | Sales for the same period last year | Dynamics comparison |
| YoY % | Change from last year | Growth or decline assessment |
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.
The finished dashboard is published to Power BI Service (cloud version):
Trying to display everything at once is one of the most common mistakes when building dashboards. Let’s look at proven KPI sets to start with.
Sales
| KPI | Formula / source | Why |
| Revenue vs plan | Fact/plan × 100% | Basic performance control |
| Funnel conversion | Closed Deals/Leads × 100% | Quality of work with leads |
| Deal cycle (days) | Closing date − opening date | Sales process efficiency |
| Retention rate (customer retention) | (Clients at the end of the period − New clients) / Clients at the beginning of the period | Maintaining the customer base |
| KPI | Formula / source | Why |
|---|---|---|
| CAC (customer acquisition cost) | Marketing expenses/New customers | Customer acquisition cost |
| ROAS (return on advertising spend) | Advertising revenue/Advertising expenses | Effectiveness of advertising channels |
| Distribution of leads by channels | UTM tags + CRM | Budget allocation between channels |
| CPL (cost per lead) | Cost/Number of leads | Comparing campaign performance |
| Email open rate / CTR | Email platform data | Quality of content strategy |
| KPI | Formula / source | Why |
|---|---|---|
| Application execution time | Closing date − opening date | Speed of the operational process |
| Resource utilization | Actual hours/Available hours × 100% | Capacity planning |
| SLA (service level) fulfillment | Applications in the deadline/Total applications | Compliance with service standards |
| Number of defects | QC system or ERP data | Quality control |
| Cost of surgery | Total costs/Number of operations | Cost efficiency |
Free Power BI Templates for Download
The fastest way to get started is to use a ready-made template and adapt it to your data. Where to look:
Microsoft AppSource: The official library from Microsoft and its partners. Over 200 free templates by industry: retail, finance, manufacturing, HR.
PBIX Download: A community where developers share ready-made .pbix files with filtering by topic.
GitHub: Hundreds of open-source projects with source files — search for “power bi template”.
Microsoft Learn: Official training materials with ready-made sample files.
When using a template, pay attention to the version of Power BI Desktop: files created in a newer version may not open in an older one. We recommend keeping your Desktop updated at all times (updates are released monthly).
Therefore, templates are a good way to quickly test an approach or create an MVP. However, a serious BI system almost always requires a custom architecture.
Among IWIS’s data projects are management and analytical reporting systems for Planeta Kino, Helen Marlen, BAT, Swiss Krono, and other companies.
A typical situation in such projects looks like this: the business already has many digital systems but lacks a unified management picture. Sales are conducted in one system, finance in another, marketing looks at its own analytics, and some plans still live in Excel. Formally, the data exists, but management cannot quickly see what is happening with the company as a whole.
In such projects, the IWIS team starts by analyzing data sources and business logic. It is necessary to understand where the data resides, how it is updated, which KPIs management actually needs, and what decisions should be made based on them.
Next, a data model is built, integrations are configured, access levels are set up, and separate views are created for different roles. A director needs the big picture. A department head needs plan attainment, dynamics, and pain points. A manager needs their own KPIs and specific deviations.
The main value of Power BI for business is that companies begin to see their processes as a single system.
Learning Power BI on your own is entirely possible, but it takes time and requires deeper immersion if the goal is not just basic charts but a full-fledged management analytics system. Based on our experience, from the first launch of Power BI Desktop to a stable, working dashboard for a medium-sized business, it typically takes 2–4 months: learning, mistakes with the data model, restructuring, source integration, and aligning KPIs across departments.
IWIS’s BI dashboard development includes a full cycle: from data source audit to a completed dashboard with team training. We work both with companies that already have a CRM or ERP and with businesses where some processes still live in Excel. In both cases, the result is the same: a single source of truth for all management levels and a reporting system that does not depend on manually refreshing files.
If you want to understand how BI can work specifically for your company, you can now sign up for a free consultation with the IWIS team. We will help assess your current data structure, highlight potential growth points, and advise on which format of BI reporting will be most effective for your processes and tasks.
