Power BI dashboard design: 5 key features for effective data communication

With the UK business intelligence market projected to reach £1.57 billion in 2025 and 58% of UK organisations actively expanding their Power BI usage, it's clear that data-driven decision making has become essential for British businesses. But here's the thing - having Power BI isn't enough. The difference between a dashboard that gathers dust and one that transforms how your team works comes down to design.

Power BI has become the dominant business intelligence platform in the UK, with British organisations representing the largest European market for Microsoft's analytics tool. And there's good reason for this popularity - 58% of organisations report that Power BI pays for itself within the first year of implementation. That's a pretty compelling return on investment.

Yet despite 77% of UK businesses handling digital data, only 21% actually analyse that data to generate insights. That's a massive gap between data collection and data-driven action - and it's often down to poorly designed dashboards that fail to communicate information effectively.

So what separates a dashboard that drives real business value from one that just looks pretty? In this guide, we'll explore the five key features that make Power BI dashboards truly effective at communicating data to users: interactive visuals, drill-through functionality, smart filtering, KPI tracking, and data storytelling. Whether you're building your first dashboard or looking to improve existing ones, understanding these features will help you create dashboards that your team actually wants to use.

1. Interactive visuals for user engagement

Static reports are yesterday's news. Modern Power BI dashboards invite users to explore data actively, transforming passive viewers into engaged analysts. This interactivity is what turns a nice-looking chart into a genuinely useful business tool.

Cross-filtering and cross-highlighting

When you click on a data point in one visual, something interesting happens to the other visuals on your page. This behaviour comes in two flavours, and understanding the difference matters for your dashboard design.

Cross-filtering removes unrelated data entirely from other visuals. Click on "London" in a regional bar chart, and your product table updates to show only London sales. This is brilliant for focused, scenario-based analysis where you want to eliminate noise and concentrate on a specific segment.

Cross-highlighting keeps all data visible but dims the unrelated portions. The same click on "London" would highlight London's contribution while greying out other regions, letting you see both the specific data and its context within the whole. This works well when understanding proportions and relationships matters more than drilling into specifics.

Power BI applies sensible defaults (cross-filtering for line charts and maps, cross-highlighting for bar and column charts), but you can customise these through the Edit Interactions feature in the Format menu. The key is matching the interaction type to how your users actually analyse data.

Tooltips that add genuine value

Tooltips are the hover-over information boxes that appear when users point at data points. Done well, they provide context exactly when it's needed without cluttering your visual design.

Power BI offers three levels of tooltip sophistication. Default tooltips show the basic value and category automatically. Custom field tooltips let you add additional measures to the tooltip, perhaps showing percentage of total alongside the actual figure. Report page tooltips are where things get really interesting, allowing you to create entire mini-dashboards that appear on hover, complete with charts, images, and multiple metrics.

The principle of progressive disclosure applies here: show essential information by default, with more detail available through the tooltip. A well-designed tooltip answers the follow-up questions users are likely to ask when they see a data point, without requiring them to navigate away from the current view.

2. Drill-through for deeper insights

When users spot something interesting in your dashboard, what happens next? Drill-through functionality answers this question by providing a clear path from summary views to detailed analysis pages. It's one of the most powerful features for enabling genuine data exploration.

Drill-through versus drill-down: what's the difference?

These terms often cause confusion, but they serve fundamentally different purposes.

Drill-down operates within a single visual, moving through hierarchy levels. Think Year to Quarter to Month to Day. You're seeing the same data at different levels of granularity, staying within the same chart. It requires pre-defined hierarchies in your data model.

Drill-through navigates between report pages, taking you from a summary to a completely different page designed to show detailed information about your selected item. Click on a customer name in a summary table, and you land on a dedicated customer profile page showing their complete transaction history, contact details, and engagement metrics.

The distinction matters because each serves different analytical workflows. Drill-down answers "what are the component parts of this number?" while drill-through answers "tell me everything about this specific entity."

Designing effective drill-through pages

A common mistake is creating drill-through destination pages that simply dump raw data into a table. That's a missed opportunity. Effective drill-through pages should provide genuine analytical value with multiple visualisations offering different perspectives on the selected entity.

For a customer drill-through page, you might include a summary card with key metrics, a timeline of their purchasing behaviour, a breakdown of products purchased, and recent support interactions. This gives users a comprehensive view without requiring them to navigate to multiple places.

Setting up drill-through requires creating a destination page, adding a field to the Drillthrough filters well, and ensuring your visuals respond appropriately to that filter. A back button helps users return to their starting point, and maintaining consistent styling with your source pages creates a cohesive experience.

Recent Power BI updates have made drill-through more discoverable through modern visual tooltips, which now surface drill options directly in the tooltip rather than requiring users to right-click. This small change significantly improves adoption because users no longer need to know the feature exists to find it.

3. Filters and slicers to tailor the user experience

Filters are how users narrow down dashboards to show exactly what matters to them. Power BI offers multiple filtering mechanisms, and choosing the right approach significantly impacts usability.

Understanding the filter hierarchy

Power BI operates with three levels of filters that work together. Visual-level filters apply to a single chart or table. Page-level filters affect everything on the current page. Report-level filters apply across all pages in the entire report. These levels combine through intersection logic, so if you set a report-level filter for 2024, a page-level filter for the North region, and a visual-level filter for Electronics, that visual shows only 2024 North region Electronics data.

This hierarchy enables powerful dashboard design patterns. You might set fiscal year selection at the report level so it persists across all pages, apply department filtering at the page level for focused analysis, and use visual-level filters to highlight specific product categories in individual charts.

Slicers versus the Filter pane

The choice between using slicers (visible controls on the canvas) and the Filter pane (a separate panel) comes down to importance and space. Slicers work brilliantly for filters users need constantly because they're immediately visible and encourage interaction. The Filter pane works better for secondary filters that users apply occasionally, keeping your canvas uncluttered.

A good rule of thumb: limit slicers to five to eight per page. If you find yourself needing more, consider whether some filters could move to the Filter pane, or whether you need multiple focused pages rather than one overloaded page.

Slicer formatting matters more than you might think. For large value lists with dozens or hundreds of options, dropdown slicers with search functionality prevent overwhelming users. Hierarchy slicers that let users drill through levels like Region to Territory to District consolidate what would otherwise require multiple separate slicers. The goal is always to make filtering intuitive, not a chore.

Synchronised slicers across pages

Multi-page reports often need certain filters to persist as users navigate between pages. If someone selects "2024" on your summary page, they probably want that selection maintained when they move to the detail page. Power BI's Sync Slicers feature handles this automatically, linking slicers across pages so selections propagate without users needing to reselect on every page.

4. Success metrics with KPIs

A well-designed KPI should communicate performance status within three to six seconds. If users need to study a metric to understand whether it's good or bad, the design isn't working hard enough.

KPI visual versus card visual

Power BI offers two main approaches for displaying key metrics. The KPI visual is purpose-built for tracking progress toward specific goals, combining a current value with a target and an optional trend line. It's ideal for executive scorecards where you want to show whether you're hitting targets.

The newer Card visual provides more flexibility, allowing multiple metrics within a single visual and richer formatting options. Cards work well when you need contextual metrics together, like showing current sales alongside last year's figure and the budget, all in one compact display.

The choice depends on your emphasis. For goal tracking with clear targets, the KPI visual's built-in features make sense. For presenting multiple related metrics with sophisticated formatting, cards offer more design freedom.

Conditional formatting for instant comprehension

Conditional formatting transforms KPIs from passive numbers into active indicators. The classic traffic light pattern uses green for good performance, amber for caution, and red for concern. When implemented effectively, users can scan a dashboard and instantly identify which areas need attention.

Power BI supports three approaches: value-based formatting where the data itself contains colour information, rule-based formatting where you define ranges (under 80% equals red, 80-100% equals amber, over 100% equals green), and measure-based formatting where DAX formulas calculate colours dynamically based on complex business rules.

When placing KPIs on your dashboard, position them in the top-left area where users naturally look first. Limit yourself to three or four key metrics per section because exceeding this dilutes their impact. Surround your KPIs with breakdown visuals that explain what's driving performance, helping users understand not just what the number is, but why it's at that level.

Our Software Engineering team specialises in creating custom KPI dashboards tailored to your business objectives. We work with UK organisations across sectors to build dashboards that track the metrics that actually matter for your operations.

5. Tell a story with your data

The best dashboards don't just display data. They guide users through a narrative, leading them from headline insight to supporting detail to actionable conclusion. This storytelling approach transforms scattered metrics into coherent understanding.

Visual hierarchy and layout patterns

Eye-tracking research has identified two dominant patterns people use when scanning visual information. The F-pattern applies to information-dense pages: users read across the top, drop down, read a shorter second line, then scan down the left edge. The Z-pattern works for simpler layouts: users move from top-left to top-right, then diagonally to bottom-left, and across to bottom-right.

Both patterns converge on the same principle: your most important insight belongs in the top-left corner. That's where every user looks first. Place secondary information along the left margin and supporting details in the remaining space. Size and colour reinforce this hierarchy; larger, brighter visuals signal importance, while smaller, neutral elements provide context without competing for attention.

Annotations that add meaning

A spike in your sales chart means nothing without context. Was it a seasonal effect? A successful campaign? An anomaly? Annotations bridge the gap between what the visual shows and what it means. A simple text box explaining "20% increase driven by Black Friday promotion" transforms raw data into business understanding.

Power BI's Smart Narrative feature takes this further by using AI to automatically generate text summaries of your visualisations. These narratives update dynamically as filters change, providing running commentary that helps users interpret what they're seeing. Research suggests smart narratives can reduce interpretation time by up to 60%.

Bookmarks for guided analysis

For stakeholders who need guided journeys through your data, bookmarks capture specific dashboard states that you can string together into a narrative sequence. Create bookmarks for "Executive Summary," "Regional Breakdown," "Problem Areas," and "Recommendations," then link them to navigation buttons. Users can click through your story like a presentation while retaining the ability to explore further when questions arise.

This approach particularly suits board presentations and stakeholder reviews where you need to control the narrative flow while keeping the underlying data accessible for questions.

Designing for everyone

Approximately 8% of men experience some form of colour vision deficiency, which means dashboards that rely on red and green to signal good and bad performance exclude a significant portion of your audience. Effective dashboard design uses colour to reinforce meaning rather than convey it alone, adding shapes, labels, or icons alongside colour coding.

Accessibility extends beyond colour. Ensure your dashboards work with keyboard navigation for users who can't use a mouse. Add descriptive alt text to visualisations for screen reader users. Test colour contrast ratios to ensure text remains readable. Microsoft provides accessible colour themes specifically designed to meet these requirements without sacrificing visual appeal.

How UK organisations are getting it right

These dashboard design principles aren't theoretical. UK organisations across sectors are using them to drive real business value.

NHS trusts: better patient outcomes through better dashboards

The NHS has become a significant Power BI adopter, with trusts using dashboards to improve patient care and operational efficiency. Maidstone and Tunbridge Wells NHS Trust migrated from static monthly Excel reports to interactive Power BI dashboards, giving clinical staff the ability to drill into performance data from any device. The result was faster identification of operational issues and quicker corrective action.

NHS CCGs have implemented real-time bed management dashboards that map bed availability across their network. Staff can see at a glance which facilities have capacity, enabling better patient placement decisions. Research from comparable healthcare implementations shows potential for 30% reductions in patient wait times and significant cost savings through readmission reduction analytics.

Sainsbury's: democratising data for 12,000 colleagues

Sainsbury's approach to Power BI demonstrates the value of dashboard design done right. Rather than concentrating analytics in specialist teams, they made dashboards accessible to over 12,000 colleagues across stores and corporate functions. Store managers across 1,400+ stores now access real-time KPIs on sales, waste, and shrink, enabling immediate action rather than waiting for weekly reports.

The payoff? The organisation saves an estimated 150,000 labour hours annually and generates over 650,000 weekly report views. That's not dashboards gathering dust; that's dashboards driving decisions.

Metro Bank: a bank in your pocket

Metro Bank's CEO famously described their Power BI implementation as providing "a bank in his pocket." The bank now runs over 100 reports in production, tracking everything from call centre performance to customer satisfaction metrics. Dashboards monitor call volumes, service levels, and resolution timeframes in real-time, enabling rapid response to emerging issues.

Isle of Wight Council: transparent performance management

Local government has embraced Power BI for both internal performance management and public transparency. The Isle of Wight Council publishes performance dashboards integrating data from the Office for National Statistics alongside internal metrics. Their balanced scorecard approach lets councillors and the public track progress against strategic objectives through interactive, accessible dashboards.

Common mistakes to avoid

For every success story, there are dashboards that fail to deliver value. Understanding the common pitfalls helps you avoid them.

Building without a decision strategy tops the list. If you can't articulate what specific decision your dashboard supports, stop and answer that question first. Dashboards built around available data rather than business questions often look impressive but don't change behaviour.

Assuming Power BI fixes data quality is equally damaging. When your underlying data contains inconsistencies, your dashboards will contradict each other. Sales figures that differ between reports erode trust in the entire analytics infrastructure. Fix data quality at the source, not in the visualisation layer.

Overcomplicating your design creates cognitive overload rather than clarity. Dashboards crammed with filters, dozens of charts, and every possible KPI leave users uncertain where to look. Start with one or two KPIs per page, designed around how people actually make decisions.

Publishing without an adoption strategy virtually guarantees your dashboards will be ignored. Training, promotion of successful use cases, and monitoring of adoption metrics are as important as the technical build itself.

Putting it all together

These five features work together to create dashboards that genuinely serve your organisation. Interactive visuals invite exploration. Drill-through enables deep investigation. Filters let users focus on what matters to them. KPIs communicate performance at a glance. And thoughtful storytelling guides users toward the insights that drive action.

The difference between a dashboard that gets used and one that gathers dust often comes down to design decisions that seem small but compound into significant usability differences. Placing your most critical metric in the top-left corner. Limiting your KPIs to the essential few. Providing context through annotations. These choices determine whether your investment in Power BI translates into better decisions.

Our friendly, knowledgeable team at Red Eagle Tech are here to help you with Power BI dashboards and reports, whatever your requirements. Our Business Intelligence solutions can transform your raw data into actionable insights that drive growth. Whether you're building your first dashboard or looking to improve existing ones, we can help you create dashboards that your team actually wants to use.

Frequently asked questions