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Rethinking Data Visualisation: A UX Approach To Dashboards That Actually Drives Decisions

hello@smashingmagazine.com (Meriem Benhabiles) 2026年08月26日 21:00 1 次阅读 来源:Smashing Magazine

Data visualisation sits at the intersection of two disciplines that rarely talk to each other: data and design. Meriem Benhabiles explores what changes when you bring structured UX thinking to dashboards and data presentations, from the questions you ask before opening any tool to the decisions that determine whether an insight actually lands.

In organisations today, data has never been more available. Dashboards and performance decks exist for almost every function — sales, product, marketing, operations — and the tools to build them have never been more accessible. And yet, in weekly standups and quarterly reviews, the same thing happens constantly: someone shares the numbers, the room nods, and the meeting ends without a decision or clear direction . When that happens, the data usually takes the blame. The numbers weren’t granular enough, the dataset wasn’t complete, we need more information before we can act. But the data is almost never the problem. The reality is that nobody designed it to deliver insights. The chart was built from what was available, not from the question that needed answering. The audience was assumed rather than understood, and what should actually change as a result of seeing this data — that question — was never asked at all. Data visualisation and UX are solving the same underlying problem: both are trying to move the right information to the right person in a way that changes something. The vocabulary is different, but the underlying challenge is identical, and the moment you start treating them as complementary disciplines is the moment dashboards stop being a passive collection of charts and start doing something functional . For designers who work with data, analysts who present to non-technical audiences, and marketers who need their numbers to do more than sit in a slide, this read is for you. The Chart Was Never The Whole Story In 1973, the statistician Francis Anscombe (PDF) published a paper that made a quiet but clarifying point. He constructed four datasets that are statistically identical: same mean, same variance, same correlation coefficient, and same regression line. Run the numbers on any of them, and they are identical. Plot them, and they could not be more different. Anscombe’s lesson to statisticians was about diagnosis: visualisation reveals the operational
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