Why Visualization Alone Isn’t Storytelling

It never fails—whenever I tell an audience “visualization isn’t storytelling,” I’m met with looks of surprise and doubt. But then I explain the role each plays in connecting with decision makers, and I can almost hear the click as everything falls into place. That’s when I know a data storyteller is born.

It may be hard to believe, but the phrase “data storytelling” really only entered our lexicon during the last five to seven years. Before that, you were much more likely to hear the still-used phrase “actionable insights.”

Unfortunately, data storytelling seems to have become synonymous with data visualization—a feature of technology. That’s a shame, and, said even more plainly, a mistake.

But, visualization makes conclusions from data obvious. Don’t we need it?

We do, but visualization on its own is not storytelling.

Let me briefly pause here and be clear: I think visualization plays an important role in the data storytelling process. Visualization does a brilliant job of bringing order to chaos, and it can help those uninitiated in data to understand what it means. It can demystify and democratize the data, so to speak.

But visualization is only part of the process. It’s not a story by itself.

Today we recognize there are three areas of expertise at play in the creation of a data story: analytics, communication (narrative) and visualization. Analytics informs narrative, narrative informs visualization, and visualization supports the analytic narrative.

Or, in simpler terms, what you learn drives what you say. What you say needs to be backed up by what you show.

What does storytelling bring to the table?

Even though “learn-say-show” is fairly straightforward, the path to get there—and the number of ways we can optimize decision making—is complex. That puts a general strain on what can be understood, as we can’t be masters of everything. Which means we rely on the expertise of others to give data the voice it needs to inspire action.

Enter the need for a storyteller.

The most inspiring storytellers are those who can take observations and translate them into actions that benefit the reader or listener. Their messaging can motivate a change in behaviour.

Now put “data” in that same definition, and you’ll get a better understanding of what data storytelling brings to the table. The most compelling data storytellers are those who can take what is observed in the data and translate it into actions that benefit the business.

Why isn’t visualization storytelling if it’s the final step?

Think about the movies: Films come after scripts. Scenes are shot to support an established narrative and create an engaging experience for audiences. Compelling data stories are supported by visuals designed around the analytic narrative. But the narrative comes first.

Here’s the bottom line: Storytelling is about connecting the dots and translating that into action. Visualization alone doesn’t close the loop. While it may bring clarity to information, next steps are open to interpretation. It is only the narrative that brings alignment and inspires action.

So let’s reframe our thinking. Recognize what visualization brings and put the analytic narrative first. That’s where you’ll really make an impact.


I attended the Data Storytelling Workshop you hosted a few months ago. Since that time, I find myself constantly going back to the POET Technique to tell compelling data stories.

–MMA’21 Candidate


If you’re not sure you’re nailing the narrative, or want to know if your visuals are really telling a compelling story, let’s talk. Drop me an email at laura.warren@storylytics.ca.

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