Andy Kriebel

Recently, I was discussing the benefits of data storytelling with a client. Most people see narrative as something that benefits the audience. It makes your data communications: ✅ 𝐄𝐧𝐠𝐚𝐠𝐢𝐧𝐠 – captures attention and holds it. ✅ 𝐏𝐞𝐫𝐬𝐮𝐚𝐬𝐢𝐯𝐞 – adds emotive pull so your evidence resonates. ✅ 𝐀𝐜𝐭𝐢𝐨𝐧𝐚𝐛𝐥𝐞 – clarifies the “so what” and “now what.” But what often gets overlooked is how much narrative also helps the presenter. It helps you stay: ✅ 𝐅𝐨𝐜𝐮𝐬𝐞𝐝 – you know the key insight you’re driving toward. ✅ 𝐒𝐭𝐫𝐞𝐚𝐦𝐥𝐢𝐧𝐞𝐝 – you filter out noise and avoid overwhelming detail. ✅ 𝐂𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐭 – you know what matters and speak with conviction. We often think of narrative as a way to guide others through the numbers. But in reality, it’s also guiding you, refining what you share. That’s the hidden win. Narrative doesn’t just make your audience’s experience better. It makes your data communications cleaner and sharper. How have you seen data storytelling benefit you as the presenter? 🔽 🔽 🔽 🔽 🔽 Craving more of my data storytelling, analytics, AI, and data culture content? Sign up for my newsletter today: https://lnkd.in/gRNMYJQ7 Check out my comprehensive data storytelling masterclass: https://lnkd.in/gy5Mr5ky Need a virtual or onsite data storytelling workshop? Let's talk. https://lnkd.in/gNpR9g_K

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AI is moving faster than most teams can handle. Data Management and literacy is now a vital skill for ALL your teams This week inside CTRL//SHIFT AI, here’s what we unpack for our members: 🚨 $364B projected AI spend from Big Tech in 2025 🧠 The predicted 10,000+ jobs lost to AI in July globally, and where the new demand is growing 💸 $2B raised by Thinking Machines to push autonomous agent AI ⚔ Amazon vs Walmart: The AI supply chain battle is heating up 📈 Governments are mandating upskilling — and why soft skills now drive hiring But here’s the thing no one’s saying loud enough: 74% of AI initiatives fail. Not because of tech, but because of poor data management and understanding, lack of AI strategy, poor to no training for their teams and no human context. That’s why we built CTRL//SHIFT: A space for founders, operators, professionals, and teams to not just “learn AI”… But to build confidence, clarity, and systems that work, without burning out. ✨ Data Fundamentals ✨ Strategy ✨ Mindset ✨ Automation ✨ Real human support 👀 Want in? Join the free tier of CTRL//SHIFT AI now and get weekly drops like this, real-time insights, and a smarter way to stay ahead of the shift. https://lnkd.in/e4PMb3BP

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Lessons learned from 100 data assessments - There are a lot of funky filters out there! The most common funkiness I see is duplicate values. I once say Aluminum in a filter 5 times (Aluminum, Alumimun, Alum, ALUMINUM, Aluminum[space]). This is a big headache to the user experience, especially if you can't select multiple filter values. The fix: Style Guidelines & PIM Business Rules -Make sure you have a style guideline to establish formatting rules -Build these rules into your PIM or use LOVs to help ensure you data is clean -Cyclical data audits to clean up data

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