How to Create Impactful Dashboards

🍱 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 ↓]

✈️ 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

Most analysts can make charts. Few can tell a story people actually care about. AI can generate a clean graph in seconds. But it can’t sit across from an executive and explain what the trend means, why it’s happening, and what they should do about it. That’s what companies pay for. It’s also what trips up most data analysts. I used to think that a clean, pretty dashboard was enough. But every time leadership asked, “Okay… so what do we do with this?”, I realized I was just displaying data, not providing insights. Everything changed when I started thinking in terms of storylines: ● What’s happening? ● Why is it happening? ● Which dimensions matter most? ● What should we investigate next? ● What’s the practical next action? Stakeholder meetings felt less intimidating. And my work finally made an impact. Here’s the real secret: Do you want to be the analyst who creates reports and dashboards or the analyst who helps influence decisions? If you want to stand out: ● Use titles that communicate the insight, not the chart type ● Pick visuals that prioritize clarity over aesthetics ● Use colors intentionally ● Focus on the big picture → drilldown → recommendations ● Keep visuals simple enough that the story shines on its own Data storytelling isn’t a “nice to have” anymore. Because flashy dashboards don’t get you promoted. Clear stories do. What’s the hardest part of data storytelling for you right now?  

Creating Dashboards Teams Actually Use Data visualization in healthcare performance management often creates pretty charts nobody looks at. Here's how to build dashboards that change behavior and improve outcomes. Focus on Actionable Metrics: Display information people can actually influence. Unit staffing effectiveness, patient satisfaction trends, safety incident patterns. Skip metrics that people can see but can't impact. Real-Time Updates: Weekly data updates, not monthly reports. People need to see the connection between their actions and results quickly enough to adjust their approach. Visual Clarity: Use simple graphs and clear colors. Green for meeting targets, yellow for approaching concerns, red for immediate attention needed. Avoid complex analytics that require interpretation. Accessibility Design: Make dashboards visible in common areas and accessible on mobile devices. If people have to search for the information, they won't look at it regularly. Team Ownership: Let teams help design their own dashboards. They know which metrics matter most for their daily work and how they prefer to see information displayed. The Implementation Test: If your dashboard doesn't change how people work within two weeks of implementation, it's not working. Adjust the metrics, the display, or the access points until it becomes a tool people actually use. What performance data would be most helpful if your team could see it in real-time? #PerformanceMetrics #DataVisualization #TeamDashboards #HealthcareAnalytics

👉 I’m sharing 16+ Inventory Dashboard design color combination Ideas today.  Yes, there are errors in the text and values in these AI-generated images. But this is a very initial phase of my research. I shared these images only to explain the layout ideas and color combinations.  to help you understand what an inventory dashboard actually looks like. Again, I repeat, I share these images only for a basic understanding of the Inventory dashboard Layout or designs. If you want a fully functional dashboard, then wait for my Upcomming Book - "Ultimate Dashboard Guide." Most people jump directly into: • Adding charts • Adding KPIs • Adding colors That’s the mistake. Before building an inventory dashboard, you must first train your eyes. Here’s how I recommend using these dashboards: Step 1 Do not try to learn everything at once. Pick one dashboard theme from the images and focus only on that. Step 2 Study the layout carefully. Where are the primary KPIs placed? How are trends separated from details? What information appears first, and what comes later? Step 3 Understand the intent. Is this dashboard built for executives, operations managers, or warehouse teams? Every good inventory dashboard answers one clear business role. Step 4 Observe what is missing. Good dashboards are powerful not because of what they show, but because of what they intentionally hide. Step 5 Rebuild one dashboard from scratch. Do not copy blindly. Recreate the structure, spacing, hierarchy, and logic. A strong inventory dashboard should always help answer questions like: • What stock is critical right now? • Where are delays happening? • Which items need attention today, not next week? Design comes before charts. Structure comes before colors. Clarity comes before creativity. If you want to master dashboard design, start by studying great dashboards, not tools. I’m sharing these images to help you build that mindset. #InventoryDashboard #DashboardDesign #DataAnalytics #BusinessIntelligence #PowerBI #Tableau #DataVisualization #BIDeveloper #AnalyticsDesign #SupplyChainAnalytics #OperationsAnalytics #DashboardBestPractices #DataDriven #AnalyticsLearning #DataProfessionals #Reporting #EnterpriseBI #InventoryManagement #DecisionSupport

Stop asking executives what they want in their dashboards. It's the fastest way to build something they'll never use. Here's what actually works for executive Power BI adoption: 1. Start With Decisions, Not Designs Wrong question: "What reports do you want?" Right question: "Which decisions need better data?" Focus on enabling better decisions, not prettier charts. 2. Build Trust Through Small Wins Perfect dashboards mean nothing if no one believes the numbers. What we've seen work well: • Week 1: Simple table visual (verify the numbers) • Week 1-2: Basic automation (show consistency) • Week 2-3: Added insights (demonstrate value) • Week 4+: New features (expand impact) Consistency builds confidence more than complexity. 3. Design for Quick Consumption Most-used reports follow these rules: • Readable in 90 seconds • Key metrics front and center • Clear visual flow and storytelling • Works on mobile If it takes too long to understand, it won't get used. 4. Start Small, Grow Smart Our most successful dashboards usually start with: • 3-5 must-have metrics • 1-2 clear visualizations • Daily refreshes • No complex features We evolved based on actual usage, not assumed needs. Success came when we stopped thinking like technical experts and started thinking like executive assistants. What's worked in your experience with executive dashboards? — ♻️ Repost if your network needs to see this, and follow Austin Levine for more.

Imagine you've performed an in-depth analysis and uncovered an incredible insight. You’re now excited to share your findings with an influential group of stakeholders. You’ve been meticulous, eliminating biases, double-checking your logic, and ensuring your conclusions are sound. But even with all this diligence, there’s one common pitfall that could diminish the impact of your insights: information overload. In our excitement, we sometimes flood stakeholders with excessive details, dense reports, cluttered dashboards, and long presentations filled with too much information. The result is confusion, disengagement, and inaction. Insights are not our children, we don’t have to love them equally. To truly drive action, we must isolate and emphasize the insights that matter most—those that directly address the problem statement and have the highest impact. Here’s how to present insights effectively to ensure clarity, engagement, and action: ✅ Start with the Problem – Frame your insights around the problem statement. If stakeholders don’t see the relevance, they won’t care about the data. ✅ Prioritize Key Insights – Not all insights are created equal. Share only the most impactful findings that directly influence decision-making. ✅ Tell a Story, Not Just Show Data– Structure your presentation as a narrative: What was the challenge? What did the data reveal? What should be done next? A well-crafted story is more memorable than a raw data dump. ✅ Use Clean, Intuitive Visuals – Data-heavy slides and cluttered dashboards overwhelm stakeholders. Use simple, insightful charts that highlight key takeaways at a glance. ✅ Make Your Recommendations Clear– Insights without action are meaningless. End with specific, actionable recommendations to guide decision-making. ✅ Encourage Dialogue, Not Just Presentation – Effective communication is a two-way street. Invite questions and discussions to ensure buy-in from stakeholders. ✅ Less is More– Sometimes, one well-presented insight can be more powerful than ten slides of analysis. Keep it concise, impactful, and decision-focused. Before presenting, ask yourself: Am I providing clarity or creating confusion? The best insights don’t just inform—they inspire action. What strategies do you use to make your insights more actionable? Let’s discuss! P.S: I've shared a dashboard I reviewed recently, and thought it was overloaded and not actionably created

Collecting insights is easy. Measuring their impact on strategy, clinicians, and patients? That’s the real challenge. Most teams are logging notes. Tagging KITs and KIQs. Tracking MSL activity. But if you asked, “What changed as a result of those insights?” The answer is often unclear. Here’s how we’re changing that 👇 Step 1: Start with a focused strategy Before you ask “What did we learn?” Define what you want to learn. That means: KITs = Key Insight Themes (ex: Safety vs. Competitors) KIQs = Key Insight Questions (ex: “Are HCPs confident in Drug A’s tolerability?”) Embed these into your CRM, onboarding, and field coaching so everyone’s aligned on what signals to capture. Step 2: Define what impact actually looks like You need metrics that move beyond volume: 1/ Business impact: Did we adjust content, launch a new IIT, improve cross-functional alignment? 2/ Clinician impact: Did HCP sentiment or behavior shift? 3/ Patient impact: Are more patients being identified or diagnosed earlier? The best teams track activity → sentiment → adoption, with dashboards, briefs, and executive decks tailored by audience. Step 3: Audit your data and sources Insights don’t only live in CRM. They’re hiding in med info, IME outcomes, ad board transcripts, and congress debriefs. Map what exists. Spot the gaps. Enable tagging and structure where it's missing. Step 4: Build a coaching loop around insight quality Most insights fall flat because they’re too vague. Example: ❌ “HCP had a question about safety.” ✅ “Dr. Smith expressed concern over neutropenia in older patients and asked for real-world data.” Start peer reviews. Create a simple rubric. Reward specificity and strategic alignment. Step 5: Operationalize it Make insights part of your team’s muscle memory. Dashboards that show KIT trends, sentiment shifts, and top themes Monthly briefs to highlight what's changing Quarterly reports that tie insights to business and clinical outcomes Every insight should be traceable to: → What was heard → What action was taken → What impact it had Bottom line: Insights aren’t valuable because they’re collected. They’re valuable when they drive action. And when that action changes strategy, improves HCP confidence, or accelerates patient care? That’s when insights stop being noise and start becoming leverage. If you want access to a more detailed version of this playbook with more examples and a plan for how to operationalize insights within your team, comment below or DM me!

Want to create impactful dashboards? Here’s what you need to keep in mind!  1. 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗣𝘂𝗿𝗽𝗼𝘀𝗲: Start with a clear objective. What questions should your dashboard answer? Align it with your business stakeholder's goals to ensure relevance and impact.       2. 𝗞𝗻𝗼𝘄 𝗬𝗼𝘂𝗿 𝗔𝘂𝗱𝗶𝗲𝗻𝗰𝗲: Tailor your dashboard to the needs of your end-users. Are they executives looking for high-level insights or operational managers needing detailed data?       3. 𝗞𝗲𝗲𝗽 𝗜𝘁 𝗦𝗶𝗺𝗽𝗹𝗲: Avoid overloading them. Focus on key metrics and visualizations that provide the most value. Simplicity will increase their clarity and usability.       4. 𝗖𝗵𝗼𝗼𝘀𝗲 𝘁𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗩𝗶𝘀𝘂𝗮𝗹𝘀: Use the appropriate chart types for your data like bar charts for comparisons, and line charts for trends. The right visuals make your data intuitive and engaging.       5. 𝗦𝗵𝗼𝘄 𝗞𝗣𝗜𝘀 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗹𝘆: Group related KPIs next to each other. Be aware of if they need to show a development over time or just the latest status. Always include indicators for what is a good or problematic value. Be transparent about units. Colors help, but don't go too crazy on them.       6. 𝗘𝗻𝘀𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆: Double-check your data sources and calculations. Inaccurate data undermines trust and can lead to poor decisions. Validate everything you use.       7. 𝗗𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆: Make your dashboard interactive. Allow users to drill down into details, filter data, and explore different views. Interactivity enhances user engagement and insight discovery.       8. 𝗧𝗲𝘀𝘁 𝗮𝗻𝗱 𝗜𝘁𝗲𝗿𝗮𝘁𝗲: Gather feedback from your users and iterate. Continuous improvement ensures your dashboard remains relevant and useful over time.       9. 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝘀𝘁𝗼𝗿𝘆𝘁𝗲𝗹𝗹𝗶𝗻𝗴: A great dashboard doesn’t just present data but it tells a compelling story that enables action.      10. 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗲 𝘁𝗵𝗲 𝗡𝗲𝗲𝗱: Check if the dashboard should be created at all. Building it might not be the best course of action if it's only needed for a single time. By keeping these tips in mind, you’ll create dashboards that not only look great but also deliver real business value. How do you balance simplicity and detail in your dashboards? ---------------- ♻️ Share if you find this post useful ➕ Follow for more daily insights on how to grow your career in the data field #dataanalytics #datascience #dashboards #datavisualization #careergrowth

📌 Dashboard Design Principles 101 (What Every Company Needs to Know) Dashboards are one of the most powerful tools we have to make data useful. When they are built right, they give leaders and teams: ⤷ A clear view of performance ⤷ Highlight where action is needed ⤷ And ultimately enable better decisions. But here’s the reality: most dashboards fail to deliver on this promise. And it’s not because the data is wrong or the tool is limited. They fail because of poor design choices that make them confusing, overwhelming, or simply irrelevant to the people who are supposed to use them. If you want to build dashboards that actually drive adoption and influence decisions, there are three design principles you need to follow 1️⃣ 𝐃𝐨 𝐘𝐨𝐮𝐫 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐁𝐞𝐟𝐨𝐫𝐞 𝐘𝐨𝐮 𝐃𝐞𝐬𝐢𝐠𝐧 Every dashboard starts with a purpose. Without it, you’re just arranging charts on a canvas. Ask yourself simple but critical questions: → Who exactly will use this dashboard? → What business decisions should it support? → Which insights and KPIs are truly essential? This is where most projects go wrong. Instead of focusing on the end user, dashboards get built around the data that happens to be "available" or the KPIs that someone thought might look good. The result? A nice-looking report that nobody actually uses. A strong dashboard is user-centric and decision-driven. It exists to answer questions and reduce uncertainty. Not to display every data point you’ve collected (a very common mistake). 2️⃣ 𝐆𝐮𝐢𝐝𝐞 𝐭𝐡𝐞 𝐔𝐬𝐞𝐫 𝐰𝐢𝐭𝐡 𝐚 𝐂𝐥𝐞𝐚𝐫 𝐅𝐥𝐨𝐰 Good design is invisible. A user should glance at the dashboard and instantly know where to focus. That means creating a logical flow of information that follows natural reading patterns (top left to bottom right) and keep the number of visuals under control (5 to 7 is usually the sweet spot) The goal is not to impress people with how much data you can show. It’s to guide them toward the insight that matters most. If you want to go deeper, I highly recommend exploring Nicholas Lea-Trengrouse’s work on UX/UI principles for dashboard design. 3️⃣ 𝐂𝐡𝐨𝐨𝐬𝐞 𝐭𝐡𝐞 𝐑𝐢𝐠𝐡𝐭 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐒𝐭𝐨𝐫𝐲 Data visualization is not decoration. It’s communication. The chart type you choose can completely change how your data is interpreted. The wrong choice creates confusion. The right choice makes the insight obvious, even for someone seeing it for the first time. Always think in terms of clarity: does this chart highlight the story I want the data to tell? At the end of the day, dashboards are about clarity, usability, and decision-making. If a dashboard doesn’t tell a story, guide the user, and present insights in a way that is easy to interpret, it will fail. No matter how advanced your tool or how clean your data. 📥 Save this framework. Share it with your team. And keep it in mind before your next build. #BusinessIntelligence #DashboardDesign