Data leadership and culture with Laszlo Mucsi

A CDO Who Doesn’t Influence Strategy Is Just an Expensive Data Scientist In today’s AI-driven world, CDOs can’t hide behind data pipelines and cleansing. If your role doesn’t shape business direction, you risk being boxed into operations rather than strategy. “A CDO Who Doesn’t Influence Strategy Is Just an Expensive Data Scientist” 🔗 https://lnkd.in/g73yU8gA Questions for CDOs / Data Leaders: How often do you sit at the strategy table — not just the data ops table? What’s one move you’re making to shift from infrastructure custodian → business driver? Where are you pushing other CXOs to see value in data-led transformation? Drop your thoughts below. Let’s reset the CDO narrative together. #CDO #DataStrategy #Leadership #AI #DigitalTransformation #CXOTV #BusinessStrategy

🚨 The biggest myth in modern leadership: Having data = using data. Data doesn’t drive change, people who understand it do. That’s where Data Phonics comes in. We’re building a culture where data isn’t just seen, it’s heard, felt, and acted on. From dashboards to decisions. From numbers to narratives. From noise to truth. If that’s the kind of data world you want to live in, 👉 Follow Data Phonics. Because data is only powerful when it speaks clearly.

Is "data-driven" becoming a misleading buzzword? A thought I can't shake recently: We all strive to be "data-driven." It’s the gold standard we chase, and we rightly invest heavily in the talent and technology to get there. But here's the challenge: Data, in its raw form, has no intrinsic value. It’s an enabler. A powerful one, but still a means to an end. The true goal isn't to have data; it's to make better, faster, and more confident business decisions. This leads me to wonder if we should shift our language and our focus. Instead of being data-driven, should our ambition be to become decision-driven? It’s a subtle but powerful distinction: - A data-driven approach often starts with the data: "What insights can we find in this dataset?" This can sometimes lead to analysis paralysis or interesting-but-not-actionable findings. - A decision-driven approach starts with the outcome: "What is the most critical decision we need to make this quarter, and what is the minimum viable data we need to make it effectively?" This isn't to diminish the role of data. You absolutely cannot be decision-driven without a rock-solid data-driven culture and infrastructure. Data is the fuel, and decisions are the destination. One is useless without the other. But language shapes culture. Focusing on "decisions" anchors our work in business outcomes, pushes for clarity, and ensures our analytical efforts are always tied to tangible action. So, my question to you is: Is this just a matter of semantics, or does reframing our goal from "data-driven" to "decision-driven" fundamentally change how we approach strategy and analytics? Would love to hear your perspectives. #DataDriven #DecisionDriven #DataStrategy #BusinessIntelligence #Analytics #Leadership #DataCulture

Great discussion at the Eden Smith Group Executive Data Lounge on line about Data Value; a chance to get under the skin of what real data value looks like in practice, and how bold cultures make it happen. Kate Sargent, CDO at the Financial Times, who knows a thing or two about value creation has given us a vision of why measuring matters going beyond the buzzwords — into how data genuinely delivers measurable impact. Building a value-first mindset where data work directly ties to business goals. Tracking what truly works (and what doesn’t) so data earns its seat at the decision table. Doubling down on the wins — scaling repeatable successes while letting go of low-value distractions. And then there’s Eddie Short “Reinventing, Not Realigning: Lessons from Bold Data Cultures.” Too often data strategy becomes a risk-averse exercise in governance rather than a catalyst for reinvention. I have always preferred "data informed" v “data-driven" and the latter has become a tired phrase as Eddie explains and just when AI demands the best data foundations we’ve ever built.  Ask me about it! :) "Data is the new oil" - My response to that has been that oil still needs to be refined into a myriad of useful products! If data is to be used to power transformation, we need to measure what matters, act on what we learn, and sometimes, have the courage to start again. Thanks Jez Clark, Dan Harris, Christa Swain and everyone in the team for organising again!

How Do You Really Measure Data Value? Data isn’t valuable because it exists — it’s valuable because it changes decisions. At the Eden Smith Group Exec Leaders Data Lounge, we’re diving into how to make that happen in practice. Featuring Kate Sargent, CDO at The Financial Times, on “Measuring What Matters: Embedding Data Value in Decision-Making”, and Eddie Short on “Reinventing, Not Realigning: Lessons from Bold Data Cultures.” #DataStrategy #AI #Leadership #DigitalTransformation #ExecLeaders

🔥 Winning the Data Trust War: How DataOps Delivers Quality at Scale Today’s leaders are under pressure to make faster, smarter decisions—yet data trust is at an all-time low. Duplicate records. Conflicting metrics. Silent pipeline failures. These aren’t small issues—they’re multimillion-dollar problems. In fact, Gartner estimates poor data quality costs organizations $12.9M per year on average. 💡 Enter DataOps—a modern discipline built to restore trust in data at scale. By combining automation, continuous testing, and real-time observability, DataOps ensures that every dataset, pipeline, and dashboard is reliable and business-ready. It’s not just about speed—it’s about confidence. ✅ Automated testing catches issues early ✅ Real-time monitoring ensures reliability ✅ Collaboration aligns IT, data, and business teams The result: decisions backed by trusted data—not guesswork. DataOps doesn’t just improve pipelines—it scales trust across the enterprise. #DataOps #DataQuality #DataManagement #Analytics #DataEngineering #DataGovernance #DigitalTransformation #AI #DataTrust #BusinessIntelligence https://lnkd.in/egNixz6r

🚨 80% of the world’s data is unstructured. Its accuracy? Often questionable. Yet entire industries, governments, and strategies are now being built on “Big Data insights.” Here’s the uncomfortable question: 👉 If the foundation itself is messy and uncertain, should we really trust machine-driven insights more than human intuition? Or… have we simply replaced one kind of bias (human instinct) with another kind of blind spot (overconfidence in data)? We celebrate data-driven decision-making as if it’s unquestionable progress. But what if our obsession with data is quietly narrowing our vision instead of expanding it? 🔥 What do you trust more when the stakes are high — Big Data or human judgment? And what are we risking by choosing wrong? 💡 This reflection came after a mentorship session with Sebastian Obeta, and it left me rethinking the balance between data and intuition.

If you haven't already, check out Issue 11 of the Data & AI Magazine! It includes my write-up on these four excellent data-related books released in 2025. ‘UNLINKED’ by Meenu Howland, CPBI, CSM, CDMP highlights frequently overlooked disconnects that impede performance. She offers a framework for better aligning organizational strategy with enterprise architecture. Meenu is an awesome person and a true systems thinker – go read her book!! Malcolm Hawker’s ‘The Data Hero Playbook’ provides pragmatic guidance for building essential data leadership skills, enabling readers to drive transformation and deliver measurable value. If you ever get the chance to see Malcolm speak, don't sleep through his conference session!! Also, don't miss his excellent CDO Matters podcast. In ‘Non-Invasive Data Governance Unleashed’, Robert S. Seiner elaborates on his established methodology, extending its application to artificial intelligence, with a strong emphasis on practical, people-centred governance. Bob Seiner is one of my favorite people in data. His writing is so lyrical and engaging, you'll have a new understanding of Data Governance after engaging with his work. Serena H. Huang, Ph.D. ‘The Inclusion Equation’ integrates themes of data, artificial intelligence, and well-being, proposing a timely model to promote diversity through evidence-based decision-making. I had the chance to see Serena speak once (at the sadly defunct Data Universe), and she's not to be missed! Have you read any of these titles? What did you think? #DataGovernance #DataStrategy #DataManagement #ChangeManagement #DataEthics #DataLeaders #DataLeadership

💥 𝐃𝐚𝐭𝐚 𝐝𝐨𝐞𝐬𝐧’𝐭 𝐢𝐧𝐬𝐩𝐢𝐫𝐞 𝐚𝐜𝐭𝐢𝐨𝐧, 💥 𝐒𝐭𝐨𝐫𝐢𝐞𝐬 𝐛𝐮𝐢𝐥𝐭 𝐟𝐫𝐨𝐦 𝐝𝐚𝐭𝐚 𝐝𝐨... 🎯 Most organizations are sitting on a goldmine of insights… but they’re too busy counting the gold to use it. 🔍 We live in the “Age of Information,” yet most of it goes unused. According to Google Cloud (2024), 66% of companies leave more than half their data untouched. That’s like owning a warehouse full of Lego bricks, and never building anything with them. As a journalist turned storyteller, I’ve learned one truth that applies from newsrooms to boardrooms: Numbers don’t move people. Stories do. 🧩 𝐅𝐫𝐨𝐦 𝐃𝐚𝐭𝐚 𝐭𝐨 𝐒𝐭𝐨𝐫𝐲: 𝐓𝐡𝐞 𝟑 𝐒𝐡𝐢𝐟𝐭𝐬 𝐭𝐡𝐚𝐭 𝐔𝐧𝐥𝐨𝐜𝐤 𝐈𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞 1️⃣ 𝐒𝐨𝐫𝐭 𝐢𝐭 → 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐀𝐩𝐩𝐞𝐚𝐫 Find what stands out. Not all data points matter — only those that reveal a shift, an anomaly, or a human truth. 2️⃣ 𝐀𝐫𝐫𝐚𝐧𝐠𝐞 𝐢𝐭 → 𝐓𝐫𝐞𝐧𝐝𝐬 𝐓𝐚𝐤𝐞 𝐒𝐡𝐚𝐩𝐞 Order your insights like a storyline. Every metric should lead the audience from “What’s happening?” to “Why it matters.” 3️⃣ 𝐀𝐝𝐝 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 → 𝐈𝐭 𝐁𝐞𝐜𝐨𝐦𝐞𝐬 𝐚 𝐒𝐭𝐨𝐫𝐲 Data without narrative is noise. When you connect it to impact, on customers, operations, or society, it gains meaning. 🚀 The real power of data lies in transformation, not presentation. A great dashboard informs. A great story inspires change. So next time you’re building a report, ask: 👉 “What changes because of this?” That single question turns analytics into action. Because the difference isn’t in the numbers, It’s in what they make possible. 📊 Data → Insight → Story → Impact That’s the new literacy of leadership. 🔁 Share this to help others tell better stories with data. ➕ Follow me 🧲 for more on turning analytics into influence.

📊 The Hidden Art Behind Reliable Data Everyone talks about data as if it’s objective, clean, logical, always right. But anyone who has built a data pipeline knows the truth: data is emotional. It carries the assumptions, shortcuts, and biases of the humans who built it. Every SQL query has a story. Every dashboard hides a decision someone once made under pressure. Good engineering isn’t just about automation or performance. It’s about empathy, understanding why something was built that way before deciding how to fix it. As analytics evolves, the real challenge isn’t collecting more information, it’s teaching systems (and teams) how to interpret it with clarity and care. #DataEngineering #Analytics #Leadership #DataCulture