Communicating Scientific Data Effectively

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

There's nothing more painful than watching a data scientist stumble through a presentation without a framework. They dump data, show too many charts, forget to make a recommendation - and wonder why nothing happens. What they're missing is a proven structure that actually persuades. Here's the battle-tested structure that data scientist Russell E. Walker, PhD taught me from his experiences in competitive debate, that transforms technical presentations into persuasive business cases: 1. 𝗛𝗔𝗥𝗠 - 𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺? ✴️ Don't just state facts - frame the problem in terms your audience cares about For example: ✴️ For a medical audience: "Patient hospitalizations increased 20%"   ✴️ For a finance audience: "Hospitalization costs increased 20%" Same data, different framing 2. 𝗦𝗜𝗚𝗡𝗜𝗙𝗜𝗖𝗔𝗡𝗖𝗘 - 𝗛𝗼𝘄 𝗯𝗶𝗴 𝗶𝘀 𝘁𝗵𝗲 𝗶𝗺𝗽𝗮𝗰𝘁? ✴️ Quantify the harm in dollars, time, or other metrics that matter  ✴️ Put it in context (e.g. "This represents 15% of our annual profit") ✴️ Make it material to business goals 3. 𝗜𝗡𝗛𝗘𝗥𝗘𝗡𝗖𝗬 - 𝗪𝗵𝘆 𝘄𝗼𝗻'𝘁 𝘁𝗵𝗶𝘀 𝗳𝗶𝘅 𝗶𝘁𝘀𝗲𝗹𝗳? ✴️ Identify the root cause  ✴️ Show the problem is systemic, not temporary   ✴️ Prove intervention is necessary (e.g. "This trend has continued for 18 months despite normal business cycles"). 4. 𝗦𝗢𝗟𝗩𝗘𝗡𝗖𝗬 - 𝗛𝗼𝘄 𝗱𝗼𝗲𝘀 𝘆𝗼𝘂𝗿 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝘀𝗼𝗹𝘃𝗲 𝗶𝘁? ✴️ Present your plan or recommendation  ✴️ Connect the dots: show exactly how your solution addresses the root cause  ✴️ Loop back to the original harm (e.g. "This will reduce hospitalizations by X%, saving $Y annually") This works because you're taking your audience on a logical journey from problem to solution - each step builds on the previous one. And it works for any data science presentation - whether you're presenting a model, recommending process changes, or requesting resources. Try this structure in your next presentation. Start with the business problem your audience cares about, not with your methodology. Stop watching your brilliant insights get ignored because of poor presentation structure. How do you currently structure your data science presentations? #datascience #business #career --- 👋 If you enjoyed this, you'll enjoy my newsletter. Twice weekly, I share insights to help data scientists get noticed, promoted and valued. Click "Visit my website" under my name to join.

Everyone loves a good story. You should be using your data to tell one every chance you get. The importance of narrative in scientific communication cannot be understated. And that includes communication in traditionally technical environments! One thing that gets beaten into you in graduate school is that a scientific presentation is a technical affair. Communicating science is fact based, it's black and white, here's the data, this is the conclusion, do you have any questions? Actually, I do. Did you think about what story your data could tell before you put your slides together? I know this is a somewhat provocative question because a lot of scientists overlook the importance of telling a story when they present results. But if you want to keep your audience engaged and interested in what you have to say, you should think about your narrative! This is true for a presentation at 'The Mountain Lake Lodge Meeting on Post-Initiation Activities of RNA Polymerases,' the 'ACMG Annual Clinical Genetics Meeting,' or to a class of 16 year old AP Biology Students. The narrative doesn't need to be the same for all of those audiences, BUT IT SHOULD EXIST! There is nothing more frustrating to me than seeing someone give a presentation filled with killer data only to watch them blow it by putting the entire audience to sleep with an arcane technical overview of the scientific method. Please. Tell. A. Story. With. Your. Data. Here's how: 1. Plot - the series of events that drive the story forward to its resolution. What sets the scene, the hypothesis or initial observation? How can the data be arranged to create a beginning, middle, and end? 2. Theme - Good vs Evil, Human vs Virus, Day in the life of a microbe? Have fun with this (even just as a thought experiment) because it makes a big difference. 3. Character development - the team, the protein, gene, or model system 4. Conflict - What were the blockers and obstacles? Needed a new technique? Refuting a previous finding? 5. Climax - the height of the struggle. Use your data to build to a climax. How did one question lead to another and how were any problems overcome? 6. Resolution - What's the final overall conclusion and how was the conflict that was setup in the beginning resolved by what you found? By taking the time to work through what story you can tell, you can engage your entire audience and they'll actually remember what you had to say!

Be careful when you say this in a data presentation: "As you can see..." Because usually, I can't see. Not immediately. This phrase reveals a dangerous assumption: that what's obvious to the presenter is obvious to everyone. It rarely is. When you've spent days analyzing data, patterns become clear to you. Implications seem self-evident. Conclusions feel obvious. But your audience is seeing this for the first time. What's obvious to you is brand new to them. Instead of assuming understanding, build it deliberately: - "I'd like to draw your attention to..." - "What's significant about this is..." - "The pattern here suggests..." - "This matters because..." Don't expect your audience to instantly see what took you hours (or days or weeks) to discover. Guide their attention. Connect the dots explicitly. The goal isn't just to show data. It's to communicate. And create understanding.

I have some bad news for analysts. Especially those who are really good at their job. You’ve been cursed. More specifically, you have the curse of knowledge - the tendency to assume that others know what you know. (Google it - it’s real!) Not sure if you have the curse? Well, have you ever spent hours analyzing data, crafting what feels like a clear, thorough presentation… only to be met with a) blank stares, or b) questions with answers you thought were painfully obvious? This happens to all of us. And the more knowledgeable you are, the harder it is to put yourself in your audience’s shoes. The problem? If we can’t clearly communicate our insights or meet our audiences where they are, we’ll never change minds or inspire action. So what can you do? ➤ Zoom out before you zoom in Start with what your audience cares about, not what you analyzed. Frame the problem before the details. ➤ Design for clarity, not completeness Prioritize what matters. Simplify visuals, cut fluff, and really nail down your key message. ➤ Test your message with a non-expert Share your presentation with someone outside your domain. If they get it, your real audience will too. The goal isn’t to dumb it down. It’s to bridge the gap between what you know and what your audience needs to understand. —-— 👋🏼 I’m Morgan. I share my favorite data viz and data storytelling tips to help other analysts (and academics) better communicate their work.

Communicating complex data insights to stakeholders who may not have a technical background is crucial for the success of any data science project. Here are some personal tips that I've learned over the years while working in consulting: 1. Know Your Audience: Understand who your audience is and what they care about. Tailor your presentation to address their specific concerns and interests. Use language and examples that are relevant and easily understandable to them. 2. Simplify the Message: Distill your findings into clear, concise messages. Avoid jargon and technical terms that may confuse your audience. Focus on the key insights and their implications rather than the intricate details of your analysis. 3. Use Visuals Wisely: Leverage charts, graphs, and infographics to convey your data visually. Visuals can help illustrate trends and patterns more effectively than numbers alone. Ensure your visuals are simple, clean, and directly support your key points. 4. Tell a Story: Frame your data within a narrative that guides your audience through the insights. Start with the problem, present your analysis, and conclude with actionable recommendations. Storytelling helps make the data more relatable and memorable. 5. Highlight the Impact: Explain the real-world impact of your findings. How do they affect the business or the problem at hand? Stakeholders are more likely to engage with your presentation if they understand the tangible benefits of your insights. 6. Practice Active Listening: Encourage questions and feedback from your audience. Listen actively and be prepared to explain or reframe your points as needed. This shows respect for their perspective and helps ensure they fully grasp your message. Share your tips or experiences in presenting data science projects in the comments below! Let’s learn from each other. 🌟 #DataScience #PresentationSkills #EffectiveCommunication #TechToNonTech #StakeholderEngagement #DataVisualization

📍The importance of data storytelling cannot be emphasized enough. As a data scientist and educator, I have consistently emphasized to my students the significance of weaving a narrative into their exploratory data analysis, enabling non-technical individuals to grasp and comprehend the visualizations. 💡Here are seven rules for effective data storytelling: 1️⃣Know your audience: Tailor your data story to the specific needs and understanding of your audience. Consider their level of expertise and what information will resonate with them. 2️⃣Keep it simple: Focus on the most important insights and avoid overwhelming your audience with excessive data or complex visualizations. Simplify the message to make it easily digestible. 3️⃣Use compelling visuals: Utilize charts, graphs, and other visual aids to present data in a clear and engaging manner. Visualizations can help convey complex information more effectively than raw numbers. 4️⃣Structure your story: Organize your data story with a clear beginning, middle, and end. Establish a narrative flow that guides your audience through the data and its implications. 5️⃣Contextualize the data: Provide context and background information to help your audience understand the significance of the data. Explain why the data matters and how it relates to real-world situations. 6️⃣Make it relatable: Connect the data to relatable examples or stories that resonate with your audience. Humanizing the data can make it more impactful and memorable. 7️⃣Practice transparency: Be transparent about your data sources, methodologies, and any limitations or uncertainties in the data. Building trust through transparency is essential for effective data storytelling. 🚸By following these rules, you can create compelling and impactful data stories that resonate with your audience and drive meaningful insights. -------———————————------- 👉🏻Like, comment, and repost if you find it helpful. ⚠️Don't forget to connect with me Segun Umoru for another exciting content like this.✌️ ❗️Happy learning.

As sports scientists, how we communicate our findings is just as important as the data itself. Whether you’re delivering a keynote at a conference or speaking with athletes in a team meeting, the way we present our message is key to its impact. I recently explored the book "Talk Like TED: The 9 Public Speaking Secrets of the World's Top Minds", and it offered valuable lessons that can be applied to our work in sports science. Here are a few lessons to consider when crafting your next presentation: Speak from Passion: One of the most important things we can do as presenters is to speak from the heart. When we share our passion for our research or a topic, it resonates with our audience. Passion breeds engagement and can make even the most technical topics inspiring. Master the Art of Storytelling: Data and findings are powerful, but they’re even more impactful when tied to stories. Personal or relatable stories make the information more accessible and memorable. Think about how you can weave narratives into your presentations to give context to the numbers. Have a Conversation: You don’t need to sound like a robotic lecturer. The best presentations feel like a conversation. Practice your delivery until it feels natural and engaging. The more conversational you are, the easier it will be for your audience to connect with you. Offer Something New: Brains love novelty. Our audience has likely heard similar information before, but can we present it in a new light? Whether it’s a fresh perspective or a creative way of delivering the material, we should always look for ways to keep our audience engaged. Create a Jaw-Dropping Moment: Every talk should have that one moment that surprises and captivates the audience. It could be a surprising fact, a powerful visual, or an unforgettable soundbite. This moment can help drive home your message and keep it top-of-mind. Lighten Up with Humour: Science doesn’t always need to be serious. Using humour, when appropriate, can build rapport and make your message more relatable. A well-placed joke or light-hearted moment can engage your audience in ways that facts alone may not. Short and sweet: TED talks are famous for their brevity—18 minutes. The same can apply in our presentations. Keep it concise, focus on the most important points, and remember that sometimes less is more. Paint a Mental Picture: Humans are visual learners. When possible, use visuals to complement your presentation. Whether it's through images, videos, or diagrams, well-designed visuals can enhance retention and comprehension. Be Authentic: Don’t try to emulate someone else’s speaking style. Be yourself, share your experiences, and engage with your audience on a personal level. Authenticity helps to build trust, and your audience will appreciate your genuine approach. To see more on these principles, click here to read our full blog post: https://lnkd.in/eXRkuF3b

💡 𝗛𝗼𝘄 𝗣𝗶𝘅𝗮𝗿 𝗖𝗮𝗻 𝗧𝗲𝗮𝗰𝗵 𝗨𝘀 𝘁𝗼 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗲 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗶𝗻 𝗮 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗪𝗮𝘆? 🎬 Pixar has mastered the art of storytelling, creating narratives that engage audiences of all ages. So, why not apply their storytelling secrets to scientific communication? Here are 6 Pixar-inspired tips to make your scientific storytelling or medical strategies more engaging, memorable, and impactful: 1. 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗮 “𝗢𝗻𝗰𝗲 𝗨𝗽𝗼𝗻 𝗮 𝗧𝗶𝗺𝗲” – Frame your data as a journey, not a lecture. 2. 𝗘𝗺𝗼𝘁𝗶𝗼𝗻 𝗢𝘃𝗲𝗿 𝗗𝗮𝘁𝗮 – Start by showing why it matters before you dive into the details. 3. 𝗧𝗵𝗲 𝗛𝗲𝗿𝗼’𝘀 𝗝𝗼𝘂𝗿𝗻𝗲𝘆 – Identify your hero: the patient, the HCP, or the science itself. 4. 𝗥𝗲𝘃𝗲𝗮𝗹 𝗗𝗮𝘁𝗮 𝗟𝗶𝗸𝗲 𝗮 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 – Build suspense and curiosity before unveiling the results. 5. 𝗩𝗶𝘀𝘂𝗮𝗹𝘀 𝗧𝗵𝗮𝘁 𝗧𝗲𝗹𝗹 𝗮 𝗦𝘁𝗼𝗿𝘆 – Use before & after visuals, metaphors, and infographics to simplify complex data. 6. 𝗘𝗻𝗱 𝘄𝗶𝘁𝗵 𝗜𝗺𝗽𝗮𝗰𝘁 – Leave your audience with a sense of resolution and a "So What?" Pixar doesn’t just entertain—they create lasting emotional connections. If we could do the same with our clinical data, the understanding of data and its potential applications could be improved or enhanced. 🔗 Ready to turn your scientific storytelling into a blockbuster? Here are some thoughts on how: https://lnkd.in/eMTAeDvU

Being an MSL isn’t just about sharing data. It’s about telling stories that make science STICK... Because let’s face it: KOLs hear countless presentations. What makes yours stand out? It’s not the slides. It’s not the data overload. It’s how you tell the story. Here’s what effective scientific storytellers do: ➡️ They focus on the "why", not just the "what." Why does this data matter? ➡️ They simplify the complex. Science shouldn't be overwhelming—it has to be clear. ➡️ They connect emotionally. A story that resonates builds trust and engagement. ➡️ They adapt to their audience, whether it’s a seasoned KOL or a new HCP. Scientific storytelling is a skill—and like any skill, it takes practice. Through 1:1 coaching, you can: ▶️ Master techniques to turn data into compelling narratives. ▶️ Build confidence in presenting with clarity and impact. ▶️ Learn to engage your audience from start to finish. Ready to transform the way you communicate as an MSL? Let’s craft your story. 💜 #storytelling #msl #medicalscienceliaison #thrivemsl