How to Frame Data Insights

90% of data analysts show pretty charts. Only 10% know which chart tells the right story. But here's the brutal truth: They don't want to know what happened. They want to know what to do about it. 𝐓𝐡𝐢𝐬 𝐦𝐢𝐧𝐝𝐬𝐞𝐭 𝐬𝐡𝐢𝐟𝐭 𝐬𝐞𝐩𝐚𝐫𝐚𝐭𝐞𝐬 𝐠𝐫𝐞𝐚𝐭 𝐚𝐧𝐚𝐥𝐲𝐬𝐭𝐬 𝐟𝐫𝐨𝐦 𝐠𝐨𝐨𝐝 𝐨𝐧𝐞𝐬: Good analysts report: "Sales dropped 15% last quarter." Great analysts recommend: "Sales dropped 15% in Region A. Shift budget to Region B, where conversion is 3x higher." Good analysts show: "Customer churn increased"   Great analysts advise: "Churn spiked after the pricing change. Reverting would save $2M annually." 𝐓𝐡𝐞 𝐜𝐡𝐚𝐫𝐭 𝐭𝐲𝐩𝐞 𝐬𝐭𝐢𝐥𝐥 𝐦𝐚𝐭𝐭𝐞𝐫𝐬. 𝐁𝐮𝐭 𝐨𝐧𝐥𝐲 𝐢𝐟 𝐢𝐭 𝐝𝐫𝐢𝐯𝐞𝐬 𝐚𝐜𝐭𝐢𝐨𝐧: Bar Chart → Compare performance, identify winners to scale Line Chart → Spot trends early, predict what's coming Scatter Plot → Find correlations that unlock opportunities Heatmap → Highlight problem areas that need immediate attention 𝐇𝐞𝐫𝐞'𝐬 𝐭𝐡𝐞 𝐫𝐞𝐚𝐥𝐢𝐭𝐲: Your stakeholders have 50 dashboards already. They don't need another one. 𝐓𝐡𝐞𝐲 𝐧𝐞𝐞𝐝 𝐲𝐨𝐮 𝐭𝐨 𝐭𝐞𝐥𝐥 𝐭𝐡𝐞𝐦 𝐚 𝐬𝐭𝐨𝐫𝐲: - What's broken - Why it matters - What to do next Stop being a reporter. Start being an advisor. The best visualization isn't the prettiest one. It's the one that gets a decision made. ♻️ Share this with an analyst ready to level up 𝐏.𝐒. I share data storytelling insights and career tips in my free newsletter. Join 19,000+ readers → https://lnkd.in/dUfe4Ac6

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

If your HR data lives on dashboards, you owe it to your dashboard users to turn those numbers into stories that spark action. Here’s the key: Context, Clarity, and Connection I'm a founder of natural language AI for HR data insights, I talk to a lot of HR executives. Not every company is ready to hook AI up to their HRIS or dashboards for full cycle automation of custom reports. So here's how you can take action now: 🟩 Context: Don’t just say, “Our turnover rate is 15%.” Show why it matters: “Turnover has jumped from 10% to 15% since we cut back on flexible work policies. That’s costing us an extra $250K in rehiring and training.” 👉 By adding context—historic trends, external comparisons, or qualitative insights from exit interviews—you transform an isolated number into a relevant piece of intelligence. 🟩 Clarity: Skip buzzwords. Instead of burying leaders in pivot tables, highlight the core insight: “Our data shows that when managers engage in weekly check-ins, their teams stay 12% longer and report 20% higher job satisfaction.” 👉 Simplicity is crucial. Data can be daunting, so distill it into its most straightforward form. Describe what’s happening in plain language, highlight the key takeaway, and avoid excessive buzzwords. 🟩 Connection: Make the data human. Share a brief story about an employee’s journey—how they left due to inflexible hours, or how a new mentorship program increased retention. 👉 This personal angle sticks in leaders’ minds and moves them to act. When data is told as a story, it becomes memorable, persuasive, and actionable. That’s how you move from presenting numbers to driving real change. Storytelling is GREAT ⭐ 👍 Visualization: By combining that number with a narrative—like highlighting how three top performers left due to inflexible work policies—suddenly, you have context and emotion. Decision-makers can visualize the impact on projects, productivity, and team morale. 👍 It Captures Attention Leaders face a tidal wave of emails, reports, and dashboards every day. A compelling story cuts through the clutter. Instead of reading yet another data dump, they encounter a narrative that clearly connects metrics to outcomes (such as cost savings, product quality, or customer satisfaction). 👍 It Accelerates Buy-In Numbers can be debated or ignored, but when they’re woven into a story that resonates—especially one that ties to real pain points—leaders are far more likely to take action. A powerful story engages emotion and logic, making it easier for people to rally behind a solution. What's your Data storytelling tip? What works with your leaders ? #peopleanalytics #hrdata #peopledata #hr #dashboards #hrdashboards

As analysts, uncovering valuable insights is just the first step. The real magic happens when those insights drive action and results. Here’s how I approach turning analytics into decisions that matter: 1️⃣ Start with the End in Mind Always tie your analysis to a business objective. Whether it's increasing user retention, reducing churn, or improving operational efficiency, knowing the "why" behind your data ensures your insights are actionable. 2️⃣ Frame the Narrative Insights are only as powerful as the story behind them. Craft a narrative that’s: Clear - Avoid technical jargon; explain what’s happening and why. Concise - Highlight the key takeaways in a few bullet points or visuals. Compelling - Use data visualizations or analogies to make your insights memorable. 3️⃣ Collaborate Early and Often Actionable insights often require buy-in from multiple stakeholders. Engage key decision-makers, product managers, and engineers early in the process to align on priorities and understand constraints. 4️⃣ Provide Recommendations Data alone doesn’t drive action—recommendations do. Pair every insight with a clear next step, such as: A/B test this feature for higher engagement. Adjust pricing strategy to improve conversion rates. Focus marketing efforts on underpenetrated customer segments. 5️⃣ Quantify Impact Leverage forecasts or historical comparisons to show the potential upside of acting on your recommendations. For example, “Implementing X could increase revenue by 10% over the next quarter.” 6️⃣ Follow Through Action doesn’t end with delivering insights. Stay involved: Monitor implementation progress. Measure outcomes against your forecasts. Share success stories or lessons learned. 7️⃣ Build a Culture of Action Encourage data-driven decision-making across your organization. Host workshops, create dashboards, or share case studies of how analytics has driven impact. Insights are powerful, but actionable insights are transformative. What steps do you take to ensure your analytics drive real-world change? #data #dataanalytics #datainaction

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!

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

As I deliver #datastorytelling workshops to different organizations, I encounter a common misconception about how you should approach telling stories with data. To use a Lord of the Rings (LOTR) movie analogy, some #data professionals appear more focused on creating behind-the-scenes documentaries than actual narratives. They want to show the steps, methodologies, and approaches they used during their analysis rather than crafting a concise, compelling narrative. As a LOTR geek, I have watched many behind-the-scenes featurettes. However, I recognize that most people have only watched the LOTR movies and none of the documentaries. They're interested in compelling narratives--not the nitty-gritty of how the movies were made. When it comes to data stories, audiences are more interested in hearing an insightful narrative about a business problem or opportunity than an explanation of how you performed your analysis to assess the problem or opportunity. Taking a documentary approach with your data stories will introduce the following problems: ❌  Added complexity as you go into details that don’t matter to your audience (data collection/preparation, methodology, technical aspects, etc.). ❌  Loss of attention or interest as the audience waits to hear something meaningful. ❌  Less focused or clear communication as insights become buried in minutiae. ❌  Less time to discuss conclusions and determine next steps. ❌  Reduced actionability as extraneous details sidetrack the narrative and obscure the key takeaways. The only people who will get value from a behind-the-scenes documentary will be fellow data professionals. This is a much narrower audience than a broader business audience that is seeking insightful narratives about the business. I recommend delivering the narrative first and having your documentary ready in an appendix (if needed). Most of the time, no one will ask how you performed your analysis (unless they have questions about your numbers). With this approach, the audience will be focused on understanding your insight, implementing your recommendations, and taking action. That's a win-win. How do you avoid telling documentaries instead of narratives? 🔽 🔽 🔽 🔽 🔽 Craving more of my data storytelling, analytics, and data culture content? Sign up for my brand new newsletter today: https://lnkd.in/gRNMYJQ7

🚀 𝗠𝗮𝗸𝗲 𝗬𝗼𝘂𝗿 𝗘𝘅𝗰𝗲𝗹 𝗥𝗲𝗽𝗼𝗿𝘁𝘀 𝗦𝗽𝗲𝗮𝗸 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 💡 Data alone doesn’t guide decisions—𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗱𝗼𝗲𝘀. I see it all the time—teams spending hours compiling spreadsheets, yet decision-makers are still left asking, “𝘞𝘩𝘢𝘵 𝘥𝘰𝘦𝘴 𝘵𝘩𝘪𝘴 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘮𝘦𝘢𝘯 𝘧𝘰𝘳 𝘶𝘴?” The missing link? 𝗦𝘁𝗼𝗿𝘆𝘁𝗲𝗹𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗱𝗮𝘁𝗮. Raw numbers are powerful, but numbers paired with narrative drive action. Here’s how you can transform your Excel reports from static tables into compelling business stories: 1️⃣ 𝗩𝗶𝘀𝘂𝗮𝗹 𝗖𝗹𝗮𝗿𝗶𝘁𝘆: Use charts and conditional formatting to highlight trends, outliers, and key metrics. A single color-coded chart can communicate more than 100 rows of numbers. 2️⃣ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: Numbers without context are noise. Add commentary fields or notes explaining why a metric is moving, not just that it moved. 3️⃣ 𝗔𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗙𝗼𝗰𝘂𝘀: Frame insights around decisions. What should the business do based on this data? Every report should answer a question, not just present numbers. 4️⃣ 𝗡𝗮𝗿𝗿𝗮𝘁𝗶𝘃𝗲 𝗙𝗹𝗼𝘄: Organize your sheets and dashboards like a story—start with the headline metric, follow with supporting data, and close with a clear takeaway. 💬 𝘿𝙖𝙩𝙖 𝙞𝙨 𝙤𝙣𝙡𝙮 𝙖𝙨 𝙪𝙨𝙚𝙛𝙪𝙡 𝙖𝙨 𝙩𝙝𝙚 𝙨𝙩𝙤𝙧𝙮 𝙞𝙩 𝙩𝙚𝙡𝙡𝙨. 𝙒𝙝𝙖𝙩’𝙨 𝙮𝙤𝙪𝙧 𝙛𝙖𝙫𝙤𝙧𝙞𝙩𝙚 𝙬𝙖𝙮 𝙩𝙤 𝙢𝙖𝙠𝙚 𝙖 𝙙𝙖𝙩𝙖 𝙥𝙤𝙞𝙣𝙩 𝙩𝙚𝙡𝙡 𝙖 𝙨𝙩𝙤𝙧𝙮? #DataStorytelling #BusinessIntelligence #DataDrivenDecisionMaking #AnalyticsForBusiness

Most marketers don’t know what an insight is. And it shows. We’re drowning in data, trends, and decks of charts. But most of it is useless. Here’s the brutal truth: Data = Numbers on a page. (OK) Observation = “Oat milk sales are up.” (Yawn) Trend = “Plant-based is growing.” (Blind Freddy could see that) Insight = “Shoppers are switching to oat milk because it feels healthier and more sustainable than dairy.” That one sentence? That’s where growth comes from. An insight is not something you read in Nielsen. It’s the sharp “why” behind behaviour. It’s rare, valuable, and worth millions when you get it right. Most marketers confuse data with insight. That’s like confusing a shopping list with a three-course meal. One feeds you, the other doesn’t. And let’s be clear: if your “insight” could be copy-pasted from a LinkedIn carousel with pastel graphics, it’s not an insight. It’s marketing wallpaper. Examples of insights that built brands: Coke Zero Sugar: Saw “diet” was toxic, so reframed the offer. Now worth billions. Dove: Saw women were alienated by beauty ads. Built Real Beauty, and built category leadership. Red Bull: Saw people didn’t want a drink, they wanted an edge. Created a whole new category.   How to actually find a real insight (not the fluff most marketers call one): 👂 Get out of the office. Stop staring at dashboards and start talking to consumers. Go into homes, watch how people shop, sit at the dinner table or go into a few stores. You’ll learn more from one hour in front of a consumer than from 10 PowerPoint decks. 🔍 Look for contradictions. Insights usually hide in tension: “They say they want healthy, but they buy indulgent.” “They say they care about sustainability, but only if the price is right.” That gap is where opportunity lives. 📊 Stop worshipping data. Data tells you what is happening, never why. Treating data like insight is like mistaking the weather forecast for a holiday. 🧩 Connect across culture. Insights don’t come from a single dataset. They come when you combine consumer behaviour with wider cultural shifts. Example: plant-based eating didn’t explode because of soy milk — it rode the wave of climate anxiety + health + foodie culture colliding. 🚦 Test for action. A good “insight” is useless if it doesn’t drive different behaviour. If it doesn’t change your strategy, your comms, or your innovation pipeline, it isn’t an insight, it’s trivia. ✂️ Be ruthless. Kill weak insights. If it’s just “consumers like convenience,” bin it. That’s not an insight, that’s a horoscope. Most marketers stop at “interesting.” The best marketers push to the uncomfortable “why.” That’s where the money is. So let’s see it. 👉 Drop the best consumer or shopper insight you’ve seen in the comments. I’ll call BS on the weak ones.