User Interface Design for Support Dashboards

📌 Most Dashboards Fail Because of Bad UX Here’s the hard truth: You can have the cleanest data and the most advanced models… But if your dashboard is confusing, cluttered, or hard to navigate? Nobody will use it. BI isn’t just about data. It’s about experience. Dashboards are in fact UX products and should be treated that way. Great dashboards don’t just “show data.” They guide attention. Simplify decisions. Reduce friction. And just like any great product, they follow strong UX principles: → Clear layout → Logical flow → Minimal cognitive load → Built for the user, not the developer Let’s break down the 3 dashboard principles that make this possible 👇 1️⃣ 𝐃𝐞𝐬𝐢𝐠𝐧 𝐖𝐢𝐭𝐡 𝐭𝐡𝐞 𝐄𝐧𝐝 𝐔𝐬𝐞𝐫 𝐢𝐧 𝐌𝐢𝐧𝐝 This is where most dashboards go wrong. They’re built from a technical perspective and not a business one. Before touching a single chart, ask: → Who is this dashboard for? → What do they care about? → What action do they need to take from it? → What single question should this dashboard answer? If a dashboard tries to do everything for everyone, it ends up doing nothing for anyone. Treat your dashboard like a product. Build it around one user persona and one decision-making flow. 2️⃣ 𝐆𝐮𝐢𝐝𝐞 𝐭𝐡𝐞 𝐄𝐲𝐞 𝐰𝐢𝐭𝐡 𝐚 𝐂𝐥𝐞𝐚𝐫 𝐋𝐚𝐲𝐨𝐮𝐭 A great dashboard feels effortless to use. You don’t need to explain how to read it because it guides the user by design. Here’s how to do it: 1) Follow a natural reading pattern (top-left to bottom-right) 2) Use consistent spacing, alignment, and visual hierarchy 3) Group related charts and KPIs together 4) Avoid visual noise (limit to 5–7 key visuals per view) Think of your dashboard like a story It should unfold logically and lead the user to an insight without them having to look for it. 3️⃣ 𝐔𝐬𝐞 𝐭𝐡𝐞 𝐑𝐢𝐠𝐡𝐭 𝐕𝐢𝐬𝐮𝐚𝐥 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐉𝐨𝐛 Just because you can use a radar chart or sunburst doesn't mean you should. The best dashboards use simple, familiar visuals that communicate clearly. Here’s a cheat sheet I use: ⤷ To show progress or results → Use Scorecards or KPIs ⤷ To show trends over time → Line Charts or Area Charts ⤷ To compare parts of a whole → Pie Charts or Bar Charts ⤷ To analyze distributions → Histograms or Bell Curves ⤷ To show multivariate complexity → Heatmaps, Bubble Charts, or Pivot Tables Here what you need to remember is prioritizing clarity over creativity. Your dashboard isn’t a dribble a piece of art. It’s a decision tool. The bottom line is: Dashboards aren’t “data displays.” They’re interfaces for decision-making. And just like a product interface, design is everything. ☑ Good UX = Faster insights ☑ Good flow = Higher adoption ☑ Good visuals = Better decisions Build with purpose. Structure with clarity. Design for people. That’s how Business Intelligence becomes actual business impact. #DataStrategy #BusinessIntelligence #DataAnalytics

Power BI filter panels are often harder to use than they should be. Why does the one on the right work better? 𝐆𝐫𝐨𝐮𝐩𝐢𝐧𝐠  Slicers are broken into sections instead of one long block. Best if you can do it in a logical order or just space them out evenly. It makes the selection options easier to scan and less overwhelming. 𝐒𝐩𝐚𝐜𝐢𝐧𝐠 It’s hard to see which label belongs to which slicer when everything is cramped. Adjusted vertical gaps make it instantly clearer. 𝐇𝐮𝐦𝐚𝐧 𝐫𝐞𝐚𝐝𝐚𝐛𝐢𝐥𝐢𝐭𝐲 HasCreditCard and IsActiveMember are true/false fields with 0/1 values and the default field names. The viewers have to decode them in their head. Make them human-readable instead: • Credit Card Holders: Holding / Not Holding • Active Members: Active / Inactive Also why use dropdown just for two options? Show them directly. 𝐈𝐦𝐩𝐫𝐨𝐯𝐞 𝐮𝐬𝐚𝐛𝐢𝐥𝐢𝐭𝐲 The panel on the left closes only when you click the filter button again. There is zero indication for that. Add buttons to interact directly on the filter panel: • Two visible options to close the panel (top-right X and bottom Close button), so users can pick the shorter path. • As a third option you can also add a scrim (overlay behind the panel) with a close action. Users can close the panel clicking anywhere on the dashboard. This is often an expected behavior from other tools and apps. • A clear filter button to reset everything with one click. It makes the users’ life easier. 𝐓𝐲𝐩𝐨𝐠𝐫𝐚𝐩𝐡𝐲 • Replace pure black with softer grays to reduce visual contrast and give an easier feel. • Deemphasize slicer labels (lighter, smaller) so they don’t compete with the values. • Keep the selection values darker and larger so they stand out more. • The Clear button is red to indicate a “destructive” action. When you click it, you lose the filter selection. These are small changes but together they add up to a much better experience. If you want to build this in Power BI I shared the tutorial in the comments. 👇 #powerbi #dataviz #reportdesign #dashboarddesign #uidesign

𝗖𝗹𝗼𝘀𝗶𝗻𝗴 𝗼𝘂𝘁 𝘁𝗵𝗲 𝘄𝗲𝗲𝗸 𝘄𝗶𝘁𝗵 𝘀𝗼𝗺𝗲 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗱𝗲𝘀𝗶𝗴𝗻 𝗶𝗻𝘀𝗽𝗶𝗿𝗮𝘁𝗶𝗼𝗻 Dashboards don’t have to be walls of charts. You can use 𝘤𝘢𝘳𝘥𝘴 𝘢𝘯𝘥 𝘸𝘪𝘥𝘨𝘦𝘵𝘴 to create a modular, product-like experience that communicates faster. Looking at the example below, here are a few principles worth applying in your own builds: 𝗛𝗲𝗮𝗱𝗹𝗶𝗻𝗲 + 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗽𝗮𝗶𝗿𝗶𝗻𝗴 Each card leads with a single KPI (e.g. $34,914 𝘛𝘰𝘵𝘢𝘭 𝘚𝘢𝘭𝘦𝘴), immediately followed by a small trend statement (e.g. 𝘥𝘦𝘤𝘳𝘦𝘢𝘴𝘦𝘥 𝘣𝘺 –$4,266). This balances clarity with context. 𝗠𝗶𝗰𝗿𝗼-𝘁𝗿𝗲𝗻𝗱𝘀 𝗺𝗮𝘁𝘁𝗲𝗿 Small arrows and deltas (+356 / –273) give instant feedback without forcing users to compare multiple charts. These can be implemented in Power BI using measures with conditional formatting. 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗺𝗼𝗱𝘂𝗹𝗮𝗿 𝗹𝗮𝘆𝗼𝘂𝘁 Notice how every card has the same structure: KPI → supporting visual → legend/context. This consistency reduces cognitive load. In Power BI, use containers and grids to lock in spacing. 𝗠𝗶𝘅 𝗼𝗳 𝗰𝗵𝗮𝗿𝘁 𝘁𝘆𝗽𝗲𝘀, 𝗻𝗼𝘁 𝗰𝗵𝗮𝗿𝘁 𝗰𝗹𝘂𝘁𝘁𝗲𝗿 You see bar, donut, progress ring, and column charts - but each serves a clear role (composition, progress, forecast vs actual). The key is restraint: one message per widget. 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗵𝗶𝗲𝗿𝗮𝗿𝗰𝗵𝘆 From customer segmentation to country performance, each card answers a narrow question. Think of them as 𝘮𝘪𝘤𝘳𝘰-𝘢𝘱𝘱𝘴 inside the report. Users scan, not explore. 👉 𝗙𝗼𝗿 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀: build KPIs as reusable measures with calculation groups, field parameters etc so you can drop them into any card without rework - or, why not give the new UDF feature a go! 👉 𝗙𝗼𝗿 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝗻𝘁𝘀: push clients toward 𝘸𝘪𝘥𝘨𝘦𝘵-𝘴𝘵𝘺𝘭𝘦 𝘭𝘢𝘺𝘰𝘶𝘵𝘴 if they want reports that behave like products. 👉 𝗙𝗼𝗿 𝗮𝗻𝗮𝗹𝘆𝘀𝘁𝘀: focus each card on a question, not a dataset. When you design with this mindset, your reports feel less like static dashboards and more like interactive products. #PowerBI #UIUX #DataViz

The dashboard looked modern. But users were lost. I watched someone export a report: 7 clicks. 4 wrong turns. 3 minutes wasted. "Where is anything?" ↓ 𝐓𝐇𝐄 𝐂𝐇𝐀𝐎𝐒: Clean design. Total confusion. • Reports? Settings • Analytics? Top menu • Export? Three levels deep • Profile? Different spot each time Each team added their own menu. Nobody asked if it made sense. 𝐓𝐇𝐄 𝐅𝐈𝐗: We didn't redesign. We restructured. Modular Dashboard System: ✔ Grouped related actions (All reports together, not scattered) ✔ Unified layout logic (Same pattern every screen) ✔ Reusable UI patterns (Consistent everywhere) 𝟓 𝐖𝐄𝐄𝐊𝐒 𝐋𝐀𝐓𝐄𝐑: 📉 Support tickets: -35% 📈 NPS: +22 points ⚡ Tasks: 3x faster User feedback: "I can actually find things now." THE TRUTH: Dashboards don't need new paint. They need structure. Pretty doesn't fix lost. Logic does. Quick test: Find your main feature. Count clicks. More than 3? Users struggle daily. Dashboard feel like a maze? Comment "FLOW" 👇 Get my Dashboard Structure Framework. #DashboardDesign #ProductDesign #UXDesign #SaaS #UserExperience

✈️ Most dashboards are designed like airplane cockpits…when what you really need is a Control Tower. Too many BI dashboards try to show everything at once: KPIs, segments, raw data — all mashed together. It overwhelms users and kills decision speed. Instead, think about your dashboards as a Control Tower. The top of the tower offers a clear, panoramic view. You’re scanning for major movements and disruptions. When needed, you can zoom in with instrumentation or speak directly to pilots, but that's not your default. By managing your information hierarchy in layers, you can start simple and progressively reveal complexity. Here’s how it works: 📊 L1: The Tower View – high-level KPIs, trends, and alerts. What’s happening? 🔍 L2: Segment View – explore segments and categories. Where is it happening? 🧾 L3: Transaction View – detailed records and raw data. Why is it happening? Each level is built for a specific cognitive mode. Mixing them forces your brain to multitask and that’s where insight gets lost. 🧠 Rule of thumb: Dashboards should optimize for low cognitive load at entry. Users should never have to reconcile different zoom levels simultaneously. Control Tower dashboards allow users to scan, zoom, and act without overwhelming them. By designing dashboards to reflect human cognitive modes and information hierarchy, you create tools that are not just insightful but usable. #dataviz #dashboards #BI #uxdesign #analytics #productivity