Purpose-First Data Visualization

Looking at data visualization through a leadership and product lens not as “making charts,” but as designing clarity for decisions. Visualization works well when it is anchored in business and implementation context: what problem you’re solving, what action you’re enabling, or what understanding you’re trying to build.

And honestly, I’ve seen this happen in almost every team at some point, even strong teams. You’re under pressure, you have data, and you feel like the next logical step is to visualize it. But over the years, across projects, products, and business problems I’ve learnt that this is usually how you end up with data that look great but don’t help anyone make a decision.

Purpose first, charts later. Visualization should start with intent, not with available data. The chain: wisdom → knowledge → data → visualization.

First define what you’re trying to understand (wisdom), then what you need to know (knowledge), then what data supports it, and only then design the visual.

Visualization is a decision tool. A good data viz reduces ambiguity and makes the next step obvious (thresholds, alerts, ownership, drill-downs). Match the visual to the job. Different formats serve different needs, seeing direction, prioritizing, spotting issues early, or explaining drivers.

This approach comes from years of building products and solving business problems where “pretty dashboards” often failed because nobody knew what to do with them. The talk shares the practical lessons learned from real work, what consistently makes visualizations useful, and what makes them ignored.

Because visualization is never the end goal. It’s a tool with a purpose. And most of the time that purpose is one of three things: solve a problem, enable an action, or build understanding.

If you don’t know which of these you’re doing, you’ll end up visualizing everything and still not know what to do next.

How it connects to conversations in data visualization: A lot of data viz conversations focus on chart types, tools, aesthetics, or storytelling. This talk adds a complementary angle: data viz as product design and leadership craft where success is measured by decision quality, action clarity, and business outcomes, not by visual polish alone.

Talk overview:

1. Why “data → chart” is the most common trap
2. The wisdom → knowledge → data → visualization chain
3. Method: A repeatable checklist for purpose-first visualization
4. Examples: How the same thinking applies across different contexts (ecosystems, products, operations, experience design)
5. Close: A simple principle to remember + what to do differently starting tomorrow

Who is this relevant to: People working in products where multiple stakeholders rely on data to act. Product leaders, founders, design leaders, data teams, analysts, and anyone responsible for dashboards, reporting, or decision-making systems especially people working in products where multiple stakeholders rely on data to act.

Key takeaways A clear way to define why a visualization exists before designing it A repeatable framework to move from business context to the right data and the right visual Practical guidance on making data actionable (not just informative) A mindset shift: don’t visualize data, visualize decisions

So the big idea is simple, and it’s something I’ve come to believe because I’ve seen it play out repeatedly: Don’t visualize data. Visualize decisions.