Data Visualization Tips

Many accountants email the balance sheet and income statement to their CEOs and think,   “Job done.”  But here’s the problem: Your CEO is not necessarily trained in reading financial statements. Even if they were, you've just given them an assignment to "figure it out" If your boss doesn’t understand the numbers, then you haven’t communicated. You’ve just forwarded a report.  🚨 A financial statement without context is just data.   📊 Your job is to turn that data into insights.  How to Present Financials the Right Way  📌 1️⃣ Give a One-Page Summary 🔹 Highlight key figures—Revenue, Profit, Cash Flow, and Key Ratios.   🔹 Include clear takeaways (e.g., “Revenue grew 10%, but margins dropped due to rising costs.”).   🔹 Avoid technical jargon—simplify complex metrics.  📌 2️⃣ Answer the Big Questions   Your CEO doesn’t want numbers—they want meaning. Help them understand:   🔹 What changed? (“Profit dropped 5% due to higher shipping costs.”)   🔹 Why did it happen? (“Fuel prices increased 20% this quarter.”)   🔹 What should we do next? (“We should renegotiate supplier contracts.”)  📌 3️⃣ Use Visuals   🔹 Graphs > Tables—a well-designed chart can explain in seconds.   🔹 Use color-coded trends (e.g., 🔴 Negative, 🟢 Positive).   🔹 Keep it clean—no clutter, no distractions. 📌 4️⃣ Speak the CEO’s Language   🔹 Skip the accounting terminology—focus on impact.   🔹 Tie financials to business goals:     - Sales grew 15% → “We’re expanding market share.”     - Cash flow dipped → “We need to tighten collections.” ✅ Financial statements don’t speak for themselves—you do.   ✅ Numbers are useless without insights.  If your CEO isn’t making better decisions because of your reports, then your job isn’t done.  💡 Don’t just report numbers—explain them. That's how you add value and impact.

In #datastorytelling, you often want a specific point to stand out or “POP” in each data scene in your data stories. I’ve developed a 💥POP💥 method that you can apply to these situations: 💥 P: Prioritize – Establish which data point is most important. 💥 O: Overstate – Use visual emphasis like color and size as a contrast.   💥 P: Point – Guide the audience to the focal point of your chart. The accompanying illustration shows the progressive steps I’ve taken to make Product A’s Q3 $6M sales bump stand out. Step 1️⃣: Add headline. One of the first things the audience will attempt to do is read the title. A descriptive chart title like “Products by quarterly sales” is too general and offers no focal point. I replaced it with an explanatory headline emphasizing the increase in Product A sales in Q3. The audience is now directed to find this data point in the chart. Step 2️⃣: Adjust color/thickness I want the audience to focus on Product A, not Product B or Product C. The other products are still useful for context but are not the main emphasis. I kept Product A’s original bold color but thickened its line. I lightened the colors of the two other products to reduce their prominence. Step 3️⃣: Add label/marker I added a marker highlighting the $6M and bolded the label font. You’ll notice I added a marker and label for the proceeding quarter. I wanted to make it easy for the audience to note the dramatic shift between the two quarters. Step 4️⃣: Add annotation You don’t always need to add annotations to every key data point, but it can be a great way to draw more attention to particular points. It also allows you to provide more context to help explain the ‘why’ or ‘so what’ behind different results. Step 5️⃣: Add graphical cue (arrow) I added a graphical cue (arrow) to emphasize the massive increase in sales between the two quarters. You can use other objects, such as reference lines, circles, or boxes, to draw attention to key features of the chart. In terms of the POP method, these steps align in the following way: 💥 Prioritize – Step 1 💥 Overstate – Step 2-3 💥 Point – Step 4-5 Because data stories are explanatory rather than exploratory, you need to be more directive with your visuals. If you don’t design your data scenes to guide the audience through your key points, they may not follow your conclusions and become confused. Using the POP method, you ensure that your key points stand out and resonate with your audience, making your data stories more than just informative but memorable, engaging, and persuasive. So next time you craft a data story, ensure your data scenes POP—and watch your insights take center stage! What other techniques do you use to make your key data points POP? 🔽 🔽 🔽 🔽 🔽 Craving more of my data storytelling, analytics, and data culture content? Sign up for my newsletter today: https://lnkd.in/gRNMYJQ7

Many amazing presenters fall into the trap of believing their data will speak for itself. But it never does… Our brains aren't spreadsheets, they're story processors. You may understand the importance of your data, but don't assume others do too. The truth is, data alone doesn't persuade…but the impact it has on your audience's lives does. Your job is to tell that story in your presentation. Here are a few steps to help transform your data into a story: 1. Formulate your Data Point of View. Your "DataPOV" is the big idea that all your data supports. It's not a finding; it's a clear recommendation based on what the data is telling you. Instead of "Our turnover rate increased 15% this quarter," your DataPOV might be "We need to invest $200K in management training because exit interviews show poor leadership is causing $1.2M in turnover costs." This becomes the north star for every slide, chart, and talking point. 2. Turn your DataPOV into a narrative arc. Build a complete story structure that moves from "what is" to "what could be." Open with current reality (supported by your data), build tension by showing what's at stake if nothing changes, then resolve with your recommended action. Every data point should advance this narrative, not just exist as isolated information. 3. Know your audience's decision-making role. Tailor your story based on whether your audience is a decision-maker, influencer, or implementer. Executives want clear implications and next steps. Match your storytelling pattern to their role and what you need from them. 4. Humanize your data. Behind every data point is a person with hopes, challenges, and aspirations. Instead of saying "60% of users requested this feature," share how specific individuals are struggling without it. The difference between being heard and being remembered comes down to this simple shift from stats to stories. Next time you're preparing to present data, ask yourself: "Is this just a data dump, or am I guiding my audience toward a new way of thinking?" #DataStorytelling #LeadershipCommunication #CommunicationSkills

Master the art of Financial Storytelling 🧑🏫 Your numbers tell a story, but are you telling it right? 👇 Numbers without context are just digits on a page. The real power comes from transforming those numbers into insights that drive action. ➡️ COMMON MISTAKES IN FINANCIAL REPORTING Let's start with what NOT to do when presenting financials: 1️⃣ Dropping raw numbers without context Raw data overwhelms your audience. When you say "Revenue grew to $100K," what does that mean for the business? 2️⃣ Reading slide content word-for-word Your presentation should add value beyond what's written. Share insights that aren't visible in the numbers. 3️⃣ Rushing through without pausing for questions Financial data needs time to digest. Create moments for discussion and clarification. ➡️ BUILDING A COMPELLING FINANCIAL STORY Here's how to transform your financial presentations: 1️⃣ Start with the fundamentals Always begin by establishing context. What's normal? What's exceptional? What benchmarks matter? 2️⃣ Connect data points to strategy Show how financial results link to business decisions. If working capital improved, explain which specific actions drove that improvement. 3️⃣ Use comparisons effectively - Period over period changes - Budget vs actuals - Year over year trends - Industry benchmarks 4️⃣ Structure your narrative - What happened? - Why did it happen? - What does it mean for the future? - What actions should we take? ➡️ COMPONENTS OF GREAT FINANCIAL STORYTELLING 1️⃣ Clear Dashboards Start with a clean, focused view of KPIs that matter most. Don't overwhelm with data. 2️⃣ Strategic Context Show how financial results connect to company goals and market conditions. 3️⃣ Forward-Looking Analysis Use current data to paint a picture of future opportunities and challenges. 4️⃣ Action Items End every presentation with clear next steps and decision points. ➡️ PRACTICAL TIPS FOR IMPLEMENTATION 1️⃣ Know your audience CFO needs different details than the marketing team. Adjust your depth accordingly. 2️⃣ Use visual aids Graphs and charts can illustrate trends better than tables of numbers. 3️⃣ Practice active listening Watch for confusion or disengagement. Adjust your presentation based on real-time feedback. 4️⃣ Create discussion points Plan specific moments to pause and engage with your audience. === Remember: Financial storytelling isn't about making numbers sound good. It's about helping stakeholders make informed decisions. What techniques do you use to make financial data more engaging? Share your thoughts in the comments below 👇

When a chart raises more questions than it answers, it's bad dataviz. A well-designed chart doesn’t just present data. It guides the audience effortlessly to the insight. But when a chart lacks clear meaning, it forces viewers to work too hard to interpret the data, leading to misinterpretation and disengagement. Take this chart, “Gold in 2020.” Everything about its design make it harder — not easier — for the audience to understand what it means. 1. Vague Title, No Headline, No Clear Message - “Gold in 2020” is too broad — does it track price, supply, or investment? - Does it cover the full year as the given title implies or just a segment? - A missing headline leaves viewers guessing at what the chart means. Fix: Be precise and include the chart's story in writing. • Instead of “Gold in 2020,” use a more accurate title like “Gold Prices in Early 2020.” • Add a clear headline that states the main message your chart is trying to deliver. 2. Missing Labels Create Unnecessary Cognitive Load - The y-axis lacks a unit — are these prices in USD? - The x-axis doesn’t define if the data is daily, weekly, or monthly. Fix: Labels should eliminate guesswork: • “Gold Price per Ounce (USD)” on the y-axis • “Daily Closing Prices (Jan–Feb 2020)” on the x-axis 3. No Annotations to Explain Key Trends - A sharp price spike in February is left unexplained — was it due to COVID-19 fears? Market speculation? - Without context, the audience is forced to speculate. Fix: Strategically add annotations to provide clarity -- a few simple Google searches reveal these important contextual datapoints around the times of price surges: • Jan 4: WHO reports mysterious pneumonia cases in Wuhan. • Mid-Jan: First COVID-19 case confirmed in Thailand. • Jan 21: First U.S. COVID-19 case announced in Washington. • Late Feb: Markets crash; gold surges amid economic turmoil. 4. No Visual Cues to Guide Attention - All data points look equally important, even though the February spike is the real story. - No reference points to show how these prices compare historically. Fix: Use design intentionally: • Bold or darken the February spike to emphasize its significance. • Add a horizontal benchmark line for comparison to 2019 prices. • Shade key periods to highlight market shifts. The Takeaway A chart should remove ambiguity, not create it. Better data visualization means: • Writing precise titles and headlines that frame the insight. • Using labels that eliminate guesswork. • Adding annotations that tell the story behind the data. • Applying visual cues that direct attention to key insights. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

Most plots fail before they even leave the notebook. Too much clutter. Too many colors. Too little context. I have a stack of visualization books that teach theory, but none of them walk through the tools. In Effective Visualizations, I aim to fix that. I introduce the CLEAR framework—a simple checklist to rescue your charts from confusion and make them resonate: Color: Use color sparingly and intentionally. Highlight what matters. Avoid rainbow palettes that dilute your message. Limit plot type: Just because you can make a 3D exploding donut chart doesn’t mean you should. The simplest plot that answers your question is usually the best. Explain plot: Add clear labels, titles. Remove legends! If you need a decoder ring to read it, you’re not done. Audience: Know who you’re talking to. Executives care about different details than data scientists. Tailor your visuals accordingly. References: Show your sources. Data without provenance erodes trust. All done in the most popular language data folks use today, Python! When you build visuals with CLEAR in mind, your plots stop being decorations and start being arguments—concise, credible, and persuasive.

Data without a story is just a spreadsheet. A story without data is just an opinion. Ever wondered why some presentations leave you stunned while others put you to sleep? The answer might be simpler than you think: It's all about how you present your data. Let's dive into a masterclass on data visualization, courtesy of Hans Rosling's iconic TED talk. Rosling starts with a bombshell: Swedish top students know statistically significantly less about the world than chimpanzees. Wait, what? He goes on… Rosling used a simple quiz: → 5 pairs of countries → Each pair: one country has twice the child mortality of the other → The task: Identify which country in each pair has higher mortality The results from his students were…shockingly bad. Why this story works: Simplicity: The test is easy to understand Contrast: Humans vs. Chimpanzees (unexpected comparison) Personal connection: We all think we're smarter than chimps Just like startups need to solve high-intensity problems, your data needs to address high-intensity curiosities. Rosling didn't pick random facts. Instead, he chose a topic that matters (child mortality), a comparison that shocks (educated humans vs. random guessing), and results that challenge assumptions (We're not as informed as we think). This is the "Intensity Imperative" of data storytelling. How to Apply This: 1/ Find the Unexpected What data point in your industry would surprise even the experts? Where do common assumptions fall apart when faced with real numbers? 2/ Make It Personal How can you frame data so your audience sees themselves in the story? What universal human experiences can you tap into? 3/ Simplify, Then Simplify Again Can you explain your key data point in one sentence? If not, keep refining until you can. 4/ Use Vivid Comparisons Instead of abstract numbers, how can you relate your data to everyday concepts? Example: "This much carbon dioxide would fill 1 million Olympic-sized swimming pools" 5/ Build Tension, Then Release Start with a question or premise. then let the data reveal the answer dramatically.

Here's a data visualization tip: Start with a white slide. Not with Excel. Not with Tableau. Not with PowerPoint templates. A blank white page. Then write in the center: "When someone sees this, I want them to understand _______." This forces us to clarify the core message before diving into visualization details. Only then should we ask: - What's the minimum data needed to convey this message? - What's the simplest way to show this relationship? - What context is essential for understanding? - What can I remove without losing meaning? Great data visualization isn't about showing everything you know. It's about making one thing impossible to miss. Next time you're creating a chart or dashboard, start with that blank page. Define your message first. Visualization second. Your clarity of purpose will create clarity of design.

The no-bullsh*t playbook for building a winning MBB-style PPT When a client tells me: “Can you make this deck prettier?”. What they mean is: “I don’t understand a damn thing; help me.” Because if the presentation were clear, no one would care about the design. If MBB was about aesthetics, we’d hire cartoonists and museum curators, not top-tier analysts, economists, and engineers. Yet, people struggle with decks because no one teaches you how to structure a presentation that drives decisions. So here’s your no-BS playbook. Save it. Use it EVERY-SINGLE-TIME. 1. Every great deck starts with the storyline Your presentation is a narrative, not a collection of slides. • Start with the problem → “Why are we even discussing this?” • Support with evidence → “What do we know for sure?” • Lay out the options → “What choices do we have?” • Land the recommendation → “What’s the best move forward?” Start always with the main takeaway and then build the flow. Before jumping into slides, summarize your whole deck in five to ten bullet points; otherwise, you won’t have a deck; you will have a mess. 2. Your slide titles should tell the full story A classic MBB rule: You should be able to read just the slide titles and get the full story. • “Market trends” says nothing. • “The market is growing 15%, but only 3 players capture 80% of the upside” makes the insight obvious. If your audience has to read graphs and footnotes to understand the key message, your slide has failed. 3. Use visuals for impact, not decoration Consultants don’t add charts because they “look nice.” We add them because they clarify the story. A giant data dump with no clear takeaway is useless. A bar chart showing a clear comparison, with the key insight highlighted, adds value. Use the right tool for the job: • Bar charts → For comparisons • Line charts → For trends over time • Scatter plots → For correlations • Heatmaps → To emphasize intensity and distribution • Tables → Only if they’re digestible in seconds Your visuals exist to reduce cognitive load, not increase it. 4. Prioritize signal over noise A simple test: If your boss came and said, “Cut this to 10 slides,” could you do it while keeping all the critical insights? If yes, your deck is well structured. If not, you’re adding noise. Every 100-page deck should be distillable into 10 critical pages if needed. Every slide should add new critical insight. If it doesn’t, move it to backup. 5. Make decisions easy The best decks don’t just inform. They drive decisions. Your final slide should answer: So what? What do we do next? A deck that doesn’t lead to action is just another PowerPoint, not a decision-making tool. Bottom line: A great deck isn’t about aesthetics. It’s about clarity, structure, and impact.