5 Power BI Layout Myths That Hurt Dashboard Usability

Everyone knows what makes a good dashboard. More charts equal more insight. Visuals should fill the space. Filters help users explore.

Except much of what "everyone knows" is wrong. These layout myths persist because they sound reasonable — but they sabotage usability and undermine trust.

Myth 1: "More Charts = More Insight"

The belief: A comprehensive dashboard shows everything. The more visuals you include, the more complete the picture.

The reality: More visuals mean more cognitive load. When users see 15 charts, they don't synthesize them into a unified understanding — they get overwhelmed and disengage.

Research on dashboard effectiveness consistently shows that fewer, well-chosen visuals outperform comprehensive data dumps. The goal isn't to show everything — it's to show the right things clearly.

What to do instead: Limit pages to 5-7 visuals maximum. Every visual should answer a specific question. If it doesn't support a decision, cut it or move it to a drill-through. See our article on KPI prioritization for a framework.

Myth 2: "All Visuals Should Be the Same Size"

The belief: Uniform sizing looks clean and professional. Making all charts the same size creates visual harmony.

The reality: Same-size visuals create flat hierarchy. When everything is equal, nothing is important. Users don't know where to focus, so they don't focus anywhere.

Visual hierarchy guides attention. The most important information should be the most prominent. Secondary details should be visually subordinate.

What to do instead: Size visuals by importance. KPIs at the top, larger. Primary charts in the middle, prominent. Supporting details smaller or in secondary positions. Let size communicate priority.

Myth 3: "Filters Belong Everywhere"

The belief: Filters empower users. The more filter options, the more users can explore. Put slicers on every page for flexibility.

The reality: Filters create cognitive overhead. Every slicer is a decision users have to make. Too many filters lead to confusion, inconsistent states, and "I don't know what I'm looking at" syndrome.

Filter overload is especially problematic for executives and casual users who want answers, not exploration tools.

What to do instead: Match filter complexity to audience. Executive summaries need few or no visible filters — pre-filter to the most relevant view. Analytical pages can have more filter options, but organize them deliberately. Consider a filter panel pattern that can collapse to hide complexity.

Myth 4: "Fill All Available Space"

The belief: Empty space is wasted space. A professional dashboard uses the entire canvas. Whitespace looks like a mistake.

The reality: Whitespace is a design tool. It groups related content, separates distinct sections, and gives users visual breathing room. Dashboards crammed edge-to-edge feel cluttered and overwhelming.

Studies on visual perception show that whitespace improves comprehension and recall. Users process information better when it's not fighting for attention.

What to do instead: Use whitespace intentionally. Add margins around visuals. Create clear visual groupings with space between sections. When in doubt, add more whitespace, not more content.

Myth 5: "Users Will Figure It Out"

The belief: Users understand how to use Power BI. They'll find the drill-throughs, discover the tooltips, figure out the filters. Building for power users is fine.

The reality: Most users won't explore. They'll look at the first thing they see, fail to find what they need, and give up. Then they'll email you asking questions the dashboard should answer.

Dashboard design isn't about what's possible — it's about what's discoverable. If users don't know a feature exists, it doesn't exist.

What to do instead: Design for the least technical user. Make navigation explicit. Add visual cues for interactivity. Test with real users and watch them struggle. The features they don't find are the features you need to surface.

The Bottom Line

Layout myths persist because they feel logical in isolation. But effective dashboard design requires questioning assumptions and prioritizing user outcomes over theoretical completeness.

Less is more. Hierarchy matters. Whitespace helps. And users need more guidance than you think.

Want a faster way to apply these patterns? Download the free BI Blueprint starter template.