A powerful chart tells a story

A powerful chart has a clear message. It should be short and meaningful, and obvious in the blink of an eye. If there’s only one thing our audience remembers at the end of the day, this should be it.

Answering the ‘so what’ question

A visual without a clear key message might show the data, but it doesn’t show what’s interesting, surprising or noteworthy about the data. It leaves our audience guessing, they have to do all of the thinking work. Ideally, we want to create a visual that helps them to quickly see what’s important. A visual that not only answers the ‘what’ question, but more importantly also the ‘so what’ question.

Here’s one of my favourite examples to illustrate the importance of visual storytelling. This chart shows the evolution of meat consumption in the US since the 1960s. By itself, this chart is pretty clear. It shows us the data, in a way that is easy to understand. It answers the ‘what’ question. The design is satisfactory, with pleasing colours and good readability. But can it be improved?

US per capita consumption of poultry and livestock

Here is an attempt at a rework. Even though we’re looking at exactly the same data – we wouldn’t want to lie to our audience! – the message in this new visual is loud and clear. It’s right there in the title: Americans are eating more chicken than ever before!

Americans are eating more chicken than ever before

The power of data visualization at work

Two simple changes turned the original ‘what’ visual into this super-clear ‘so what’ visual.

  • First of all, clever colour choices: the line that interests us – the one for chicken consumption – gets a bright orange colour, the other two become grey. They’re still there, but pushed a bit to the background.
  • Secondly, clever text: the original title was very factual – ‘US per capita consumption of poultry and livestock’. All the thinking work is left for the reader. But what if we simply tell them the interesting part? The new title ‘Americans are eating more chicken than ever before’ is still 100% true, but now it tells us why this visual is actually quite surprising.

These two small but impactful changes turned the original visual, which simply shows the data, into a great visual that actually tells a story. For me, that’s the real power of data visualization at work.

If you want to know more about visualizing data in the right way, you can check out the other videos in this series. Or I invite you to read my book, Powerful Charts, that will give you actionable insights and practical guidelines to create data visuals that truly engage and inspire your audience.

Read more:

Side-by-side comparison of two bar chart versions showing the number of inhabitants per paid political mandate across EU27 countries, ranked from lowest to highest. The left version labels countries with two-letter abbreviations (FR, CZ, SI, etc.), while the right version uses full country names (France, Czechia, Slovenia, etc.). Both show identical data: France has the lowest ratio at 134 inhabitants per mandate, rising through the EU27 average of 385 (highlighted in dark blue), up to Latvia with the highest ratio at 2,570. Source: European Committee of the Regions and VRT NWS.

Avoiding abbreviations

People are lazy. Make it as easy as possible for them to see what you are trying to show. There are tons of ways to reduce mental noise in your charts, but one of the easiest is avoiding abbreviations.

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Three-panel spread: the Nature magazine cover for 23 July 2026, featuring a detailed pencil-and-ink illustration of a rhinoceros beetle alongside drafting tools; a magazine page for the article 'Three Tips to Avoid AI Image Mistakes in Science' with an abstract red-and-blue line illustration of a hand and pencil; and a painted illustration of a hornbill's head with two circular inset diagrams showing colorful cross-sections of its skull anatomy.

The uncomfortable relationship between scientific illustrations and AI

Scientific journal Nature devoted the headline of its 23 July 2026 issue to “the human art of scientific illustration in the age of artificial intelligence”. Of course, that sparked my attention.

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Review: Info We Trust

Info We Trust is an ambitious, visually stunning book that sits somewhere between philosophy, information design, and a collection of visual essays.

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Gridlines are better than axes

Almost always, gridlines are better than axes. Vertical axes are the default option, and they have been around for centuries, so they are very well known. But they also have downsides. My biggest problem with vertical axes is that they’re often so far away from where the action is really happening.

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Review: A History of Data Visualization and Graphic Communication

Michael Friendly and Howard Wainer clearly love graphs. But A History of Data Visualization and Graphic Communication isn’t just about graphs — it’s about the stories behind them: the context, the people, the new measurements that made them necessary, and the discoveries they enabled.

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Report visuals don’t have to suck

Discover how CREG, Belgium’s electricity regulator, turns complex data into clear and engaging visuals. From smart annotations to small multiples and uncommon chart types, their Monitoring Report shows how thoughtful data visualization makes technical reports easier to read and understand.

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