Dashboard Design Principles

🍱 How To Design Effective Dashboard UX (+ Figma Kits). With practical techniques to drive accurate decisions with the right data. 🤔 Business decisions need reliable insights to support them. ✅ Good dashboards deliver relevant and unbiased insights. ✅ They require clean, well-organized, well-formatted data. ✅ Often packed in a tight grid, with little whitespace (if any). 🚫 Scrolling is inefficient in dashboards: makes comparing hard. ✅ Start with the audience and decisions they need to make. ✅ Study where, when and how the dashboard will be used. ✅ Study what metrics/data would support user’s decisions. ✅ Explore how to aggregate, organize and filter this data. ✅ More data → more filters/views, less data → single values. 🚫 Simpler ≠ better: match user expertise when choosing charts. ✅ Prioritize metrics: key insights → top left, rest → bottom right. ✅ Then set layout density: open, table, grouped or schematic. ✅ Add customizable presets, layouts, views + guides, videos. ✅ Next, sketch dashboards on paper, get feedback, iterate. When designing dashboards, the most damaging thing we can do is to oversimplify a complex domain, or mislead the audience. Our data must be complete and unbiased, our insights accurate and up-to-date, and our UI must match users’ varying levels of data literacy. Dashboard value is measured by useful actions it prompts. So invest most of the design time scrutinizing metrics needed to drive relevant insights. Bring data owners and developers early in the process. You will need their support to find sources, but also clean, verify, aggregate, organize and filter data. Good questions to ask: 🧭 What decisions do you want to be more informed on? (Purpose) 😤 What’s the hardest thing about these decisions? (Frustrations) 📊 Describe how you are making these decisions? (Sources) 🗃️ What data helps you make these decisions? (Metrics) 🧠 How much detail is needed for each metric? (Data literacy) 🚀 How often will you be using this dashboard? (Value) 🎲 What constraints should we know about? (Risks) And, most importantly, test dashboards repeatedly with actual users. Choose key tasks and see how successful users are. It won’t be right at first, but once you get beyond 80% success rate, your users might never leave your dashboard again. ✤ Dashboard Patterns + Figma Kits: Data Dashboards UX: https://lnkd.in/eticxU-N 👍 dYdX: https://lnkd.in/eUBScaHp 👍 Ethr: https://lnkd.in/eSTzcN7V Orange: https://lnkd.in/ewBJZcgC 👍 Semrush: https://lnkd.in/dUgWtwnu 👍 UKO: https://lnkd.in/eNFv2p_a 👍 Wireframing Kit: https://lnkd.in/esqRdDyi 👍 [continues in comments ↓]

Reporting is NOT delivering insights. Unfortunately, many data & analytics professionals think it is. Reporting dashboards show WHAT's happening and enable basic slicing and dicing, but fail to deliver WHY. Example - "Performance is down 15% WoW" This is just stating the obvious. It's not a real insight. It's not actionable. This leaves many business leaders frustrated. When business stakeholders ask for more dashboards, what they are ultimately trying to achieve is "I need to know what's impacting my key business metrics and what I should do to improve it". Adding 15 more charts/views/slices won't help much to understand what's impacting the key business metrics and which actions should be taken. The key to REAL INSIGHTS that can move the needle? ROOT-CAUSE ANALYSIS to find the WHY (i.e., DIAGNOSTIC analytics) This is the most effective way to drive change with data & analytics. This can make the data & analytics team a TRUSTED ADVISOR and get a seat at the leadership and decision-making table. Insights need to be: 🟢SPEEDY: business stakeholders need quick insights into performance changes to make decisions before it's too late 🟢PROACTIVE: don't wait for business stakeholders to ask. Monitor key metrics and proactively share insights to become that trusted advisor 🟢IMPACT-ORIENTED: focus on the key drivers that drove most of the change and communicate accordingly 🟢EFFECTIVELY COMMUNICATED to drive the right action #data #analytics #impact #diagnosticanalytics

👀 This dashboard is not flashy. Quite the opposite. It is clean, simple, and helps the reader find the most important information quickly. That comes from a few small but intentional design choices: 1️⃣ Dynamic slicer label “Data shown as on Jan-19 ending” tells the user that the dashboard shows the position up to the selected month, not just the numbers for January. 2️⃣ Red dot alert 🔴 The red dot beside the customer name immediately shows that this customer still has unpaid invoices. 3️⃣ Title used as a legend Billing is written in red and Receipts in blue, matching the chart lines. No separate legend needed. 4️⃣ A header that gives context Instead of simply saying “Invoices”, the header tells you there are 40 invoices, 5 are unpaid, and the outstanding balance is 7,825. 5️⃣ Subtle checkmarks ✔ The checkmarks make it easy to identify which invoices have been fully paid without adding another text column. 6️⃣ Thin green indicators 🟩 The green lines beside the Receipts column quickly show the months in which payments were received. 7️⃣ Plenty of white space Probably the most important design choice. It keeps the report readable and allows the numbers that matter to stand out. None of these things is impressive on its own. But together, they reduce cognitive load, improve clarity, and make the dashboard much easier to use. That is good dashboard design. Not adding colours, boxes, and shadows everywhere, but making every element useful. If you’re building dashboards, this is the kind of polish that sets your work apart.

Most people don’t need more charts. They need the right chart. This graphic shows 50 ways to visualize data — and that’s exactly why many dashboards are confusing. Too many choices, not enough thinking. Here’s how I’d use this: Start with the question, not the chart. Comparison? Use column/bar. Trend? Line, area, or sparkline. Distribution? Histogram or box/violin (not 12 pie charts…). Choose by relationship, not aesthetics. Correlation → scatter, correlogram. Composition → stacked bar/area, not donut overload. Flow or structure → Sankey, org chart, network. One insight per visual. If your audience can’t say, “This chart shows X,” in 5 seconds, it’s decoration, not communication. Reduce cognitive load. Fewer colors. Clear labels. No 3D anything. Ever. Build your “go-to 10.” From these 50, pick 10 charts you’ll master. Use them 90% of the time. The pros look “simple” because they obsess over clarity, not complexity. Save this as a checklist for your next report or dashboard. And if you want to go deeper into data storytelling and visualization, Corporate Finance Institute® (CFI)'s resources are a great place to start.

Why do some dashboards make executives nod in approval while others get ignored? https://lnkd.in/e8bnfzQS It comes down to 3 mistakes most people don't even know they're making. I made all of them when I started my accounting firm six years ago. And they killed my credibility until I figured out what actually makes dashboards work. Mistake number one is sending raw exports from your accounting software. A profit and loss with 200 line items isn't a dashboard. It's just data overwhelm. Most founders don't even know how to read a P&L, let alone a balance sheet or cash flow statement. You're not guiding them to what matters or what actions they need to take. The fix is grouping everything into 5 to 8 summary categories so the story becomes obvious. Now you can analyze at a macro level first and only drill deeper when something looks off. Mistake number two is missing context. Numbers without comparison are meaningless. That's why budget vs actuals is the most powerful report you can show. It proves you actually planned for something instead of just reacting. Good variances show as positive, bad variances show as negative. And when you miss your targets, you have a story ready that makes leadership sleep better at night. Mistake number three is static dashboards. If someone wants to see a different time period or metric, they shouldn't need to ask you for a new report. Dynamic dashboards let viewers toggle between months, quarters, years, budget comparisons, all in real time. One dashboard becomes ten different views depending on what they need to see. Here's what changes when you fix these three mistakes. Your dashboards go from data dumps to actual insights. Leadership starts trusting your analysis. You spend less time answering questions because the answers are already visible.

9 out of 10 dashboards never get used. At least, it feels that way. The reason is not because the charts are wrong, but because nobody asked the right questions first. 10 to ask before you build your next one: 𝟭. 𝗪𝗵𝗼 𝗶𝘀 𝘁𝗵𝗶𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗳𝗼𝗿? A dashboard for "the team" is a dashboard for no one. 𝟮. 𝗪𝗵𝗮𝘁 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝘀𝗵𝗼𝘂𝗹𝗱 𝗶𝘁 𝗱𝗿𝗶𝘃𝗲? If it doesn't change a decision, it's a report, not a tool. 𝟯. 𝗪𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝘄𝗵𝗲𝗻 𝗮 𝗻𝘂𝗺𝗯𝗲𝗿 𝗹𝗼𝗼𝗸𝘀 𝗯𝗮𝗱? If no one acts on it, you're building wallpaper. 𝟰. 𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗼𝗻𝗲 𝗺𝗲𝘁𝗿𝗶𝗰 𝘁𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗺𝗼𝘀𝘁? Everything else supports it or distracts from it. 𝟱. 𝗛𝗼𝘄 𝗳𝗿𝗲𝘀𝗵 𝗱𝗼𝗲𝘀 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗿𝗲𝗮𝗹𝗹𝘆 𝗻𝗲𝗲𝗱 𝘁𝗼 𝗯𝗲? Real-time is expensive and almost never necessary. 𝟲. 𝗪𝗵𝗲𝗿𝗲 𝘄𝗶𝗹𝗹 𝘁𝗵𝗲𝘆 𝗼𝗽𝗲𝗻 𝗶𝘁? A phone and a wall monitor are not the same design. 𝟳. 𝗗𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗲𝘅𝗶𝘀𝘁 𝘀𝗼𝗺𝗲𝘄𝗵𝗲𝗿𝗲? Two sources of truth means zero sources of truth. 𝟴. 𝗪𝗵𝗼 𝗮𝗴𝗿𝗲𝗲𝘀 𝗼𝗻 𝘁𝗵𝗲 𝗺𝗲𝘁𝗿𝗶𝗰 𝗱𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻𝘀? "Revenue" means three different things to three teams. 𝟵. 𝗪𝗵𝗮𝘁 𝘀𝗵𝗼𝘂𝗹𝗱 𝘁𝗵𝗲𝘆 𝗯𝗲 𝗮𝗯𝗹𝗲 𝘁𝗼 𝗶𝗴𝗻𝗼𝗿𝗲? A dashboard that shows everything helps with nothing. 𝟭𝟬. 𝗛𝗼𝘄 𝘄𝗶𝗹𝗹 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝗶𝘁'𝘀 𝗯𝗲𝗶𝗻𝗴 𝘂𝘀𝗲𝗱? If you can't tell, you can't improve it. Answer these before you open the BI tool, and the dashboard almost designs itself. Anything you'd add to this list?

Most teams polish visuals. Few design the thinking. That’s why dashboards often look fine — but explain nothing. Try this flow instead: 1) Structure metrics – map relationships, drivers, and shared definitions. 2) Define purpose – clarify what decisions it supports. 3) Build & format – choose charts that mirror logic. 4) Add context – if-then prompts, comparisons, slices, thresholds. 5) Maintain & evolve – track usage, prune, update. Pretty dashboards inform. Logical dashboards explain. Save this for your next redesign.

The dashboard is not a reporting tool. It’s a leadership system. When operations rely on scattered Excel sheets, updates over calls, and manual follow-ups, leaders don’t lack effort—they lack real-time control. A well-designed dashboard changes that. It answers the questions leaders actually need clarity on: * What needs attention now? * Where is execution stuck? * What’s moving—and what’s not? * Where should leadership intervene? One dashboard becomes the operating system for the business. It brings: * Clarity — priorities are visible, not assumed * Ownership — responsibility is built into the system * Discipline — deadlines are tracked, not chased * Visibility — leaders see reality, not reports We’ve integrated this into our core systems so operations run on one source of truth. No duplicate data entry. No rework. No confusion. Teams focus on execution and sales. Leaders focus on decisions and growth. That’s operational excellence not by pushing people harder, but by building systems that work smarter. Pawel B Suresh Kumar P Swastika Pathak

Most billing dashboards show numbers. This one shows structure. Instead of forcing users to read through tables or guess proportions, the design answers two questions instantly: What’s the total billing? Where is it coming from? Here are the intentional design decisions that make this work: 1. Total anchored at the center: The total sits in the middle- exactly where the eye goes first. Users don’t need to calculate anything. The main KPI is established before the breakdown even begins. 2. Visual hierarchy shows contribution instantly Example: Surgery has the largest arc, followed by Consultation, then Diagnostics. Even without numbers, the ranking is obvious. That’s good hierarchy doing its job. 3. Color builds association, not decoration: Each category has one clear color repeated across icon and segment. No gradients. No unnecessary accents. Color helps recognition, not distraction. 4. Legend acts like a precision layer: The right panel doesn’t just name categories- it shows exact dollar values. Executives get a quick scan. Finance teams get accurate numbers. One layout serves both. This KPI focuses on distribution- not trends, not comparisons, not growth. Because the scope is clear, the message stays strong. Love this? Follow #TheVisualBreakdown and hit the bell so you don’t miss the next one

Day 1 of #BusinessIntelligence Ever wondered why some dashboards make an impact while others confuse users? Here are 5 essential principles that I always follow when building dashboards: • Know Your Audience: Understand the decisions they need to make. • Prioritize KPIs: Focus on the most critical metrics. • Simplicity is Key: Clutter can distract, so aim for clarity. • Consistent Design: Maintain a consistent format, color scheme, and chart types. • Iterate and Improve: Gather feedback and continually refine your dashboard. I’ve applied these principles to a recent project where simplifying a complex dashboard led to higher user engagement and clearer insights. By understanding user needs and removing non-essential data, I turned it into an actionable tool. What’s the one principle you never skip when building dashboards? #BusinessIntelligence #DashboardDesign #DataVisualization #PowerBI #Tableau #DataAnalysis