Jan Meskens

You poured weeks into building the perfect solution. The data platform is live, the reports are polished, the AI model is ready. And then nothing happens. Your end-users keep copy-pasting numbers into the same Excel workbook they've been nursing since 2017. As data and AI professionals, few things are more frustrating than watching your hard work being ignored. This talk is about understanding why that happens and what you can do about it. The answer lies in the Dead Horse theory: when you realize you're riding a dead horse, the best strategy is to dismount. Simple advice, yet incredibly hard to follow. People raised those horses. They know every quirk and every shortcut by heart. No amount of better technology will convince them to let go if they have no reason to change. The real challenge is almost never technical. It's about people, habits, and the absence of a shared vision. Drawing from my own experience in data and AI transformation programs, I walk you through the Dead Horse theory in action. You'll recognize the workarounds teams invent to avoid new ways of working, understand why each one fails, and learn how combining a clear future vision with practical change management turns resistance into momentum. To make sure this survival guide sticks, I use a structured visual framework built around horses, unicorns, ponies, and foals. Each character represents a recognizable stage in the change journey, giving you a memorable model you can apply immediately. You'll leave with clear anti-patterns you can spot on Monday morning, a practical framework for navigating resistance, and the confidence to help your team finally dismount.

Wouldn't it be fantastic to reach more people with your message? To spark creativity—not just in what you say, but in how you say it? Here’s the good news: you don’t need more slides or software—you need to start drawing. Because when you draw, you think differently. You uncover fresh angles and sharper ideas. The simple act of sketching engages your brain in ways no digital brainstorming session ever could. But the power of drawing doesn’t stop with you—it helps your audience too. Visuals make your message easier to grasp, remember, and respond to. A well-placed sketch draws attention, invites the right questions, and turns passive listeners into active participants. I’ve experienced this firsthand. For the past four years, I’ve drawn nearly every day—on LinkedIn, in articles, in keynotes, and in internal workshops. And there’s one question I keep getting: “How do you create these drawings?” In this session, I’ll share the practical side of visual storytelling: ✅ What makes a drawing resonate (and what falls flat) ✅ Tips to draw even if you think you "can’t draw" ✅ My favorite tools, workflows, and formats No art degree required. Just a pen, some paper, and a willingness to think in lines.

A well-designed and well-managed data platform can significantly amplify an organization's ability to transform data into business value. However, substantial technological investments are no magic solution for bureaucratic data processes, an inefficient data team structure, or the lack of data knowledge and appetite within your organization. This is why even the most advanced data platforms are often underutilized. This talk explores how you can break this pattern and shift towards a "Data Nirvana" where people, processes, and data tools live in harmony. The secret to getting there? A robust data strategy! I will introduce a data strategy framework that can empower individuals within your organization (the "who") to become more data literate by aligning your company’s goals (the "why") with "the what"—whether it be technological components like artificial intelligence or data platforms, as well as process and people-driven data management initiatives. But describing and defining your "Data Nirvana" is only the beginning. You also need to convey your data strategy to organization-wide stakeholders, ensuring broad understanding and support. I will show how storytelling techniques can accelerate the adoption of your data strategy.