Dashboard Design Principles

👀 This dashboard is not flashy but quite the opposite. It's clean, sleek and helps the reader find their most valuable information FAST! It's because of some small, intentional design choices that improve clarity, and add real value. 1️⃣ Dynamic slicer label - The top right clearly says “Data shown as on Jan-19 ending” – so users know this is an 'as on' dashboard, not a summary for the selected month. 2️⃣ Red dot alert 🔴 - A simple red dot next to the customer name instantly signals that they haven’t cleared all invoices. 3️⃣ Title as legend - No need for extra legends. The chart title itself is colour-coded (Billing in red, Receipts in blue), making it easy to read at a glance. 4️⃣ Descriptive table header - Instead of a generic “Invoices Table”, it says exactly what it shows: total invoices, paid count, and balance. Clear and straight to the point. 5️⃣ Subtle checkmark ✔- A clean visual cue to mark paid invoices. It’s not loud, but does the job efficiently. 6️⃣ Thin green pipe 🟩 - Placed next to the receipts column, it’s a quick indicator of incoming cash for the month, without adding any clutter. 7️⃣ White space - is the real hero. Makes everything feel breathable and readable. Helps the important things stand out without boxing or borders. These small visual cues may seem minor, but they make a big difference. 👉🏼 They reduce cognitive load. 👉🏼 They make the dashboard feel smoother. 👉🏼 And they actually help people use it better. This is real design. Not just splashing colours and shadows, but adding meaning with every element. If you’re building dashboards, this is the kind of polish that sets your work apart. #PowerBI #Excel #Dashboards

Today, I want to highlight the challenge that brand colors can present in #datastorytelling, #dashboards, and other forms of data communication. 🟩 🟨 🟥 🟦 🟧 🟪 ⬛️ In my career, I’ve worked with several large companies with strong brand identities. I come from a marketing background, so I understand and appreciate the importance of adhering to brand guidelines. However, I draw a line when it comes to data communication. Brand colors should never interfere with your ability to communicate your key messages clearly and effectively. They shouldn't make your text or charts harder to read or interpret. Clear communication trumps brand identity. In the examples, I’ve used brand colors for three past companies I’ve worked for. Brand A and B present challenges in data communication because green and red already have strong associations (green = positive, red = negative) that can interfere with your messaging and the audience's interpretation. Brand C offers a different challenge because the brand color lacks adequate contrast. Without sufficient contrast, using the brand color in corporate dashboards makes the information difficult to read. It also can’t be used for highlighting in data stories. In these situations, I’m reminded of Gary Larson's Far Side comic, where two deer face each other upright in a forest. One deer comments to the other, “Bummer of a birthmark, Hal.” The other deer has a bull’s eye birthmark on his chest. If your company has a poor brand color for data communication, you're Hal. The brand cops at your organization aren’t going to like this post, but you must override brand guidelines when it comes to information sharing. You must communicate key points clearly without interference from poor brand colors. If your current company’s brand color has good contrast and has no associations, you’re in luck. However, you’re also not off the hook. I’ve still seen people overuse a particular brand color when leveraging different colors more strategically in their charts would have worked better. By all means, please respect your organization’s brand color(s), but don’t let them interfere with your ability to convey your key messages. What has been your experience with using brand colors in your data communications?

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

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

Why this attendance KPI works better than most “% present” dashboards I see? Not because it uses icons. Not because it looks like a calendar. But because every single design choice removes ambiguity. There are 7 intentional decisions here. Let me break them down. 1. The insight is IN the sentence, not hidden in a chart: Before you look at a single icon, you already know: - Who this is about - What happened (attendance) - The outcome vs opportunity (13 out of 21) 2. Personalization turns reporting into responsibility: Student selector (David). This KPI isn’t about averages. It’s about a person. 3. Time is shown the way humans actually think: Calendar-style layout with Sun → Sat. Attendance is a daily behavior, not a trend line. By aligning days of the week, Users immediately recall patterns (“He missed Wednesdays”). This isn’t decoration. It’s cognitive alignment. 4. Status is scannable in under 3 seconds: Green checks, red Xs, muted circles. You can instantly read this as: “Mostly good… then a rough patch… then recovery.” No legend needed. Shape + color reinforce each other. Patterns emerge before numbers are processed. That’s intentional. 5. Non-working days are shown- but de-emphasized: Yellow circles for weekends and holidays. These days exist on the calendar, but they don’t compete for attention. Why this matters: - Users don’t ask “Why wasn’t the student present on Sunday?” - Performance is judged only on valid days - Visual noise is reduced without hiding information What you mute is as important as what you highlight. 6. Summary and detail live in the same space: Top: 13/21 days | Bottom: daily breakdown. Leaders can stop at the number. Counselors can look at specific days. No drill-through. No extra pages. This is a mini storytelling arc. 7. Context is available exactly when needed: Info tooltip explaining holidays and exclusions. Instead of cluttering the KPI, the main view stays clean. This is progressive disclosure done right. The Lesson: This KPI works because someone asked: - What question is this answering? (How consistently is this student attending?) - What’s the fastest takeaway? (13 of 21 days attended) - What confusion can I remove? (Calendar rules, weekends, holidays) Love this? #TheVisualBreakdown series drops every other day with a new chart deconstruction. Follow + hit the bell icon so you don't miss the next one.

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

Don’t Lose Your RAG: How to Use Red, Amber & Green Responsibly in Dashboards As data professionals, we’ve all heard it: “Don’t use red and green in your dashboards - people with colour vision deficiency won’t be able to tell the difference.” Wrong. The truth is, you can use red, amber, and green - as long as you do it properly. What do I mean, and why should you care? 🧐 Why RAG Still Matters Whether you like it or not, RAG status indicators are embedded in business culture - especially in executive reports and performance dashboards. 📌 Executives love a quick-glance signal. 📌 Red = urgent. Green = all good. Amber = needs attention. 📌 It’s familiar. And familiarity drives faster decisions. So rather than throwing RAG out entirely, we need to be smarter about how we use it. 🧐 The Accessibility Issue Roughly 1 in 12 men and 1 in 200 women have some form of colour vision deficiency (CVD) - commonly referred to as colour blindness. The most common type, deuteranopia, affects red-green perception. So yes - your standard green-to-red gradient is a mess for a sizeable chunk of your audience. Especially when: ❌ You're using continuous colour scales (e.g. red to green heatmaps) ❌ The colours are just slightly different hues with no other visual cue ❌ There's no text, label or tooltip to clarify meaning 🧐 What Works Better? ✅ Use discrete colours instead of gradients When you’re working with Red, Amber, and Green KPIs, use clearly separated blocks of colour, not a continuous scale. This removes the visual ambiguity. ✅ Choose a colour-safe palette For example, the IBCS colour palette provides Red and Green colours that remain distinguishable even with CVD filters applied. ✅ Add labels or tooltips Text clarifies what colour alone might not. A simple “Red: Critical”, “Amber: At Risk”, “Green: On Track” label or hover tooltip can make your dashboard instantly more accessible. ✅ Give users control Where appropriate, consider letting users switch views or toggle labels to meet their accessibility needs. 🧐 A Real Example I recently tested two RAG designs (see in the attached video): 1) A standard green-to-red diverging palette (looked fine at first - but ran into problems under a CVD filter) 2) A discrete IBCS-style palette with clearly separated colour blocks (remained readable even with filters applied) The difference was clear - literally. And yet, the RAG meaning remained intact for all users. 🧐 Final Thoughts Stop treating red and green as the villains of dashboard design. Used well, they’re clear, powerful, and intuitive. Just make sure you’re thinking about everyone who uses your dashboards - not just those with perfect vision. 🎯 Want to try this yourself? Test your colour palettes with ColorOracle.org and build with confidence. And as I always say…give your stakeholders what they WANT, and a little bit more of what they NEED, each and every time… #DashboardDesign #ColourAccessibility #TableauTips #KPIReporting

Most internal audit reports are thorough, detailed… and underutilized. Why? Because decision-makers don’t need more pages. They need clarity. This is where a high-level audit dashboard changes the game. A powerful one-page dashboard can: ✔ Highlight critical risks instantly ✔ Show what truly matters to the business ✔ Drive faster, better decisions ✔ Strengthen Audit Committee engagement ✔ Create accountability for action Frameworks like the Institute of Internal Auditors emphasize effective communication as a core pillar of Internal Audit. And in today’s fast-moving business environment, visual storytelling is no longer optional. From my experience, the real value of Internal Audit is not in identifying issues, it’s in ensuring they are understood, prioritized, and acted upon. A well-designed dashboard typically answers: 🔹 Where are the biggest risks? 🔹 What needs immediate attention? 🔹 Are issues recurring? 🔹 Who is accountable? 🔹 What is the business impact? When done right, it transforms Internal Audit from "a reporting function" to "a strategic decision enabler". One page. Clear insights. Real impact. #InternalAudit #RiskManagement #CorporateGovernance #AuditCommittee #DataVisualization #Leadership

📌 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

After designing hundreds of business dashboards, I keep coming back to these four patterns: Tall + Scrolly Stack everything vertically, organized by metric family, and let people scroll to their level of depth. Best for mobile viewing and email delivery with basic chart types that doesn't require instructions. Where I've seen this work: New product/feature introductions where audiences are different levels (executive to operators) and functions. BANs + Decomp Big numbers that focus attention and breakdowns that show differences. For when you've identified the important metrics, but want to show segment granularity. Switch group-by dimension while maintaining familiar layout. Where I've seen this work: Operational monitoring for teams that have ownership of metric outcomes. Sankey + Wide Table Flow diagram establishes a map of the whole system and reference tables show details. For diagnosing conversion and retention patterns across nodes and segments to know where to optimize. Where I've seen this work: Growth teams figuring out behavior across complex funnels and overlapping segments. Potential Show what you could be delivering versus what you're actually delivering. Makes the gap between current performance and available capacity visible. Where I've seen this work: Operational teams that have a clear action to take, but limited time. What each of these have in common: - Establish big picture awareness, but direct small picture action (think global, act local) - Strengthened by KPI ownership - Act as a prioritization mechanism Organizations often start with one dashboard trying to serve everyone, then evolve into multiple dashboards with different patterns for different groups. The more established the business, the more discrete the problems being solved are. That means early on, you go from optic oriented communications to more optimization oriented direction. I've found that organizations lack a portfolio strategy for their analytics interfaces, they take templates from one context and try to apply them to another OR they try to combine use cases together into a singular dashboard because they only have budget for one but multiple stakeholders with different needs, so they get a flying-boat-car of compromises. Some data work and analytics are going to be a cost of doing business, like reporting that just keeps everyone informed. While other data work is a strategic bet. The challenge is that some analytics deliver hard value you can measure in dollars, while others provide soft value like better collaboration and shared understanding that's difficult to quantify. Most organizations don't think about this mix deliberately. #dataAnalytics