How to Build Data Dashboards

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

Most dashboards don’t measure what actually drives performance. And that’s why many companies make decisions too late. If your finance dashboard isn’t driving real-time action, your team is probably drowning in data, but not necessarily moving the business forward. Here’s how to build KPIs and dashboards that actually drive results. 1. Identify the Right KPI Categories Great finance dashboards don’t drown in data, they focus on what matters across five key dimensions: - Financial performance: Revenue growth, EBITDA margin, CCC - Operational efficiency: Gross margin, inventory turnover, AR/AP turnover - Risk & liquidity: Current ratio, working capital, debt-to-equity - Strategic performance: ROI, market share, customer retention - Sustainability: Energy efficiency, waste reduction, carbon footprint This structure ensures visibility across short-term liquidity, operational throughput, and long-term value creation. 2. Align KPIs with Strategy Every metric should connect directly to a business goal. - A SaaS CFO tracks MRR and churn. - A manufacturing CFO tracks throughput yield and supply chain cost. Strategic alignment turns dashboards from reports into decision systems. 3. Design a Multi-Layered Dashboard - Executive view: Profit trend, cash flow, liquidity - Operational view: Efficiency, cost, utilization - Analytical view: Variance and root cause analysis Each layer should show what happened, why it happened, and what could happen next. 4. Integrate Your Data Systems Centralize your data through ERP, accounting, CRM, HR, and supply chain. Use platforms like Power BI, Tableau, or Looker for real-time visibility. - Key principles: APIs, automation, role-based access, and audit trails. - Trust in the data = confidence in boardroom discussions. 5. Build, Visualize, and Communicate. Control the financial narrative. Dashboards should tell a story. - Waterfall charts → cash flow trends - Treemaps → expense or revenue breakdown - Tiles & traffic lights → performance vs. thresholds Every visualization should connect results to action. 6. Continuously Evolve Treat your dashboard as a living management system. - Review. Benchmark. Refine. - Involve your finance and strategy teams to keep KPIs aligned This framework blends financial precision with operational insight. Bottom line: A great finance dashboard doesn’t just measure performance, it drives it. How does your finance dashboard drive performance?

“Dashboards are dead”? Only the context-free ones. Most teams start with definitions. They write a KPI dictionary, argue about formulas, then stack charts. Start with relationships. Map what drives what. Use metric maps and driver trees to sketch causality. ↳ Then define formulas. ↳ Then design screens. ↳ Then pick visuals. Here’s the 4-layer model we use: 1) Maps & Drivers: – metrics maps – driver trees 2) Definitions: – cohorts – formulas – granularity – attribution model – validation checks 3) Information Architecture – filters – page flow – drill paths – segments – comparisons 4) Visuals & UX – chart patterns – color semantics – legends & labels – responsive layout – conditional formatting Why this order? Because “what moved?” is useless without “why.” Common traps this avoids: ✕ Glossary-first thinking. Clean formulas ≠ causal logic. ✕ Chart sprawl. More graphs ≠ more clarity. ✕ Mixed levels. Result, diagnostic, actionable in one pot. If your dashboard doesn’t explain change, it’s reporting, not analytics. Build the logic first. Then display it. #dashboards

Claude Design is genuinely terrfifying… A year ago I would've paid thousands for an analyst to mock these up. Instead… I built these custom market research dashboards in an afternoon. And all I did was show it a screenshot of a coding interface I liked, mono typeface, dark background, terminal feel, and asked it to reproduce that style. Then I had it conduct real market research for each dashboard separately. I ended up with: (1) A cross-channel performance report covers spend, CPM, conversions, and ROAS across CTV, Display, Mobile Apps, Native, Audio, and DOOH with line-item detail per campaign. (2) A channel mesh topology view shows how signals, identity graphs, and suppression lists flow between channels in a cross-channel setup. (3) A workflow monitor tracks deployment and release status across the stack. All three used the same terminal-style visual language, populated with real-looking data from the research it pulled. A few things stood out. • The research was ACTUALLY specific. It pulled REAL numbers and competitive detail I could use to optimize our client’s performance • The visual consistency held across every dashboard. I gave it one style brief, threw three different topics at it, and got the same design language across all of them. • The edit mode is incredible Generation gets you 80% of the way there, and being able to tweak specific elements after the fact is what turns it from a cool demo into a real deliverable. The thing I keep thinking about is what this does to the cost of custom internal tools. Dashboards and research docs used to be a budget item. You'd either pay a vendor for a generic template, or you'd pay a designer and an analyst to build something bespoke. That whole layer of work can now be collapsed into a SINGLE session with a chat interface. If it would be useful, I can record a Loom walking through exactly how I set these up: • prompting • the visual reference • my edit mode workflow All of it. That way you can build your own dashboards for your ad accounts. Comment “DASHBOARD” and I’ll do it.

There are so many ways to build dashboards in Excel. Turning those dashboards into web apps gives users a live window into data without exposing the underlying workbook. Many professionals build dashboards in Excel to monitor KPIs, performance, or team activity. The spreadsheet layer is powerful: charts, formulas, formatting, and filters all work together to provide real-time insight. But sharing those dashboards often means emailing files, managing version chaos, or exposing data you’d rather keep hidden. Here’s how to build a focused dashboard in Excel — and how Sheetcast can help turn that dashboard into a secure web app without rework. In Excel: Build a responsive dashboard layout. ·    1. Design your workbook with a dedicated Dashboard sheet. Use formulas like =SUMIFS() or =AVERAGEIFS() to summarize key metrics from your data. ·    2. Add Excel charts (e.g., column, line, pie) linked to summary cells. Use slicers or dropdowns for filters. ·    3. Use named ranges (via Formulas > Name Manager) to create reusable metrics like SalesLastMonth or OpenTickets. ·    4. Apply conditional formatting to visually flag trends — for example, highlight cells with =B2>B1 to indicate improvement. ·    5. Add Pivot Tables and Charts to provide a more interactive and flexible view of the data. ·    6. Protect the dashboard sheet to prevent accidental edits while allowing dynamic updates. ·    7. Use =NOW() or =TODAY() to timestamp the dashboard. ·    8. Export and share snapshots as a view-only PDF and charts manually for reporting. This method works — but manual sharing and version control are ongoing burdens, and user-specific filters or permissions require duplicating the file. With Sheetcast: Turn your Excel dashboard into a live web app. Start with your existing workbook, then: ·    1. Upload your file to Sheetcast and create a Layout Container Page for your dashboard. Add the different pages/views to this as you create them. ·    2. Use Filter and Slicer Pages to allow real-time filtering of the dashboard by region, status, or timeframe. ·    3. Create List Pages and add Item Templates to cleanly present summaries of records. ·    4. Combine Solo Forms and Report Pages to create dynamic projection tools. ·    5. Transform your Pivot Tables and Charts with the Pivot Explorer Page to make them interactable from the web and choose the level of data security you’d like to apply. ·    6. Add a Tabs Container to group multiple dashboard views (e.g., Overview, Department, History) into a single interface. ·    7. Apply permissions when you share pages, so users only see the data and charts they’re authorized to view. No need to split files. ·    8. Embed the dashboard in your intranet or portal using the HTML code created for you when you share the app. The result: dashboards that stay live, secure, and personalized — all powered by Excel, without file sprawl.

📌 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

Dashboards should be designed for action, not data. Most dashboards contain plenty of data. Dozens of metrics and pretty charts. We've been taught that data drives action, but in practice, it rarely does. As you build your dashboards & and reports, consider the question: What is the user's "next best action"? Then, build solutions to prompt (or enable) that action. Some examples of "next best action": 1.) More Data Sometimes, the user will have more questions. That's ok! We build in self-service filters, segments, and drill-downs to dive in deeper. Self-service > fewer questions for the data team > faster time to action. 2.) Related Data Most businesses will have dozens of reports, often fragmented and disjointed. We can build links to bridge between the reports. Additionally, those links can be dynamic to carry through important filters (date ranges, segments applied) and help users keep their contextual flow. Less time hunting for reports > faster action. 3.) Sharing the data Once users find interesting data, they want to save it or send it to a coworker or client. Enable sharing via email, slack, raw export, etc. Sharing > More distribution > more action. 4.) Actions in another platform (Shopify, Meta, Salesforce, etc) Based on the data, users will need to make a change in another tool. Take someone in merchandising. They see product reports showing that certain products have low conversion rates, likely due to dwindling inventory levels. We can build a link in the dashboard that takes them DIRECTLY to the Shopify admin portal to the product setup and re-merchandise their collection. With one click, they've gone from data > to action. Fewer clicks > faster action. 5.) Alerts Users may see a number and wish they knew about it sooner. For this we setup alerts (email, slack, sms, webhook, etc.) Faster alerts > faster action. Our goal is to transform data-heavy dashboards into tools for action. Consider: - Can we make them more self-service? - Can users set up alerts? - Can they export and share the data easily? - Can we link tools and reports together to avoid context switching? - Can we automate the data to drive action? Are there any tricks you're using to make your dashboards more actionable? #businessintelligence #looker #ecommerceanalytics #measure

From 5 Pages of a Dashboard to 1: Simplifying Insights Without Losing Depth Most dashboards tell a story in pages. Mine tells it in one. When I designed this one-page dynamic Power BI dashboard, the goal was simple: Make data interaction intuitive, fast, and insightful. So instead of switching between five different pages for Sales, Profit, Profit Margin, Discounts, and Quantity, I created a single, fully interactive dashboard. Here is how it works: - Each KPI card isn't just a number. It's a button. - When you click on a metric, the entire dashboard transforms to show detailed visuals and information related to that specific metric. No page reloads. No clutter. Just pure insights in one glance. What it took to build it: - Used the Button Slicer for the KPIs. - Used the New Card visual to add YoY Metrics. - Created a Field parameter with all the KPI metrics. - DAX measures to keep metrics accurate and flexible. - A clean, consistent color theme to enhance readability. - A focus on user experience, not just on data visualization. The result? - A dashboard that saves time, reduces complexity, and keeps decision-makers focused on what truly matters, the story behind the data. 👉🏽 Check the short clip attached to see the functionality. If you have ever designed dashboards, you know how challenging it is to make simplicity powerful. P.S. Have you tried turning a multiple-page dashboard into a single dynamic view before? I would love to hear how you approached it.

Every reliable dashboard begins long before a single chart is built. It starts in the quiet, invisible layers of Google Tag Manager - where precision, not design, determines the accuracy of every number your team will see. Because the truth is this: dashboards don’t create clarity. Implementation does. Here’s how I build data foundations that hold up - not just for this quarter, but for the next five years of growth. 1- Tag Architecture That Scales: A strong structure beats a large one. I use modular event naming and trigger templates that grow with your website - not against it. This ensures every new campaign, page, or platform addition fits seamlessly without breaking your tracking logic. 2- Context-Aware Tagging: Data without context is noise. By using Lookup Tables and conditional triggers, I ensure events only fire when they should, no duplication, no irrelevant noise, just clean intent-driven signals. 3- Ongoing Tag Validation: Every setup is alive. That’s why I implement automated tag tests using GA4 DebugView and regular audits to catch silent breakages before they erode decision-making trust. ➞ The Result? Dashboards that don’t just look good - they are good, because they’re built on truth. ↷ I’m Neil Shapiro, Founder of Zen Digital Analytics. ↷ I help Marketing Directors turn complex tracking setups into scalable, reliable measurement systems. ➡️ What’s the one area of your analytics setup you’re least confident in right now? A) Tag structure B) Trigger accuracy C) Ongoing validation

Most dashboards don’t fail because of bad data or bad charts. They fail because they were built too early. Someone asks for “a dashboard.” The team opens the BI tool. SQL gets written. Charts get polished. And only at the end does anyone ask the uncomfortable question: “Wait… what decision is this supposed to support?” That’s why prototyping is non-negotiable if you want dashboards that actually get used. Prototyping forces the hard thinking before the build: → What questions are we really trying to answer? → Who is this for, and what do they need to decide? → Which metrics matter, and which ones are just noise? → What level of detail is useful vs overwhelming? A simple low-fidelity prototype (even boxes and labels) does two critical things: 1 — It exposes vague thinking immediately. 2 — It lets stakeholders react to structure and logic, not colors and charts. By the time you open your BI tool, 80% of the decisions should already be made. That’s exactly why I put together this practical, no-nonsense cheatsheet for dashboard discovery and prototyping. It’s a repeatable framework to gather clean, complete dashboard requirements — without endless meetings, vague requests, or dashboards that get ignored. The guide walks you through: – Running focused user interviews – Defining business questions first – Aligning on metrics and breakdowns – Mapping data sources – Translating all of that into a clear, stakeholder-friendly layout If your dashboards aren’t getting used, don’t add more charts. Prototype better → https://lnkd.in/dxyFYdUy