Data Storytelling -- What It Is, What It's Not, How To Do It

And How To Think About Data Storytelling So You Are More Influential

Here's a piece from Gartner that makes some good points about data storytelling.

James Richardson, is research director at Gartner. By some of his comments, my guess is that he is most likely not a trained business storyteller, but someone who has acquired skills in storytelling over the years. So some of his points need a bit more clarification.

First, data visualization is not data storytelling. On that we agree. Data visualization however, whether simple or complex, helps us make sense of data, but rarely generates insights that stimulate action. 

What insights can you gain from this data visualization? Or is your reaction, "Oh, I get it."

What insights can you gain from this data visualization? Or is your reaction, "Oh, I get it."

All business narratives are designed to help people to take action. Stories are always about experiences people have. Stories help listeners make an experience that's being shared personally meaningful. If designed in a certain way, those stories can inspire listeners to take action.

So data visualizations are terrific tools to use when telling the data story because they provide credibility and give weight to points being made in the story.

I do like the distinction Richardson makes about data visualizations being a point in time, but a data story is about a flow through time. It's a good way to think about both.

However, he then goes on to say this about data visualizations: "Arranged into a time or conceptual sequence, these visualizations can help reveal findings, trends or underlying patterns." You would hope so. But I'm here to tell you that laying out data in a sequence and then moving through that sequence is NOT a story. It's a series of events and it's the biggest mistake you'll make in trying to tell a data story. You will bomb.

Avoiding Endless Debates & Getting Nowhere

I can see right away that Richardson is probably delivering a series of events instead of a story when he says, “The goal of data storytelling is to encourage and energize critical thinking in exploring data insights for business decisions. By debating a data story collaboratively and subjecting it to critical thinking, organizations can make the story safe and useful in the decision-making process.”

Yes and no. What I experience again and again with the technology leaders and scientists I coach is that they generally activate the analytical mind when presenting. This is when they stimulate only 2 areas of the brain: the language centers named Boca’s Brain and Wernicke’s Area. They are not stimulating 5 other areas of the brain that have to do with images, sound, smell, movement, taste, etc.

Here’s what happens when you activate only the analytical brain: ongoing debates about the information, requests for more information, and no decision. Or a decision that takes a long time in coming. Emotional engagement is absent.

However, when emotions are shared and stimulated through the 5 senses, the limbic brain is activated and that is where decisions are made. Stories by their nature drive to resolution. We want to take action and know the end. A series of events or data leaves us flat. A well-told story gets us emotionally engaged. Which is why true data storytelling skills are so critically important.

Sure, discussions about your findings will still ensue, but at least you'll collapse the decision-making cycle.

How To Craft

So what do you do? You craft a story that with this basic pattern:

  1. Context/the current situation
  2. The people involved - your characters. 1, 2, or 3 people with real names so listeners can identify with them and the story
  3. The problem (build urgency)
  4. Actions taken to solve the problem
  5. The resolution
  6. Action steps to take and a time frame for those (more urgency)
  7. Insights, key message, Inspiring close

There are hundreds of ways to tell a data story. This is only 1 pattern. You could switch up the pattern start with the problem. Experiment with both and see which you like best. Training in advanced storytelling brings you many more patterns to play with.

You, you, you

In addition, what the best data storytellers do is weave in a few personal anecdotes, use a metaphor or two, use strong contrast to make a vivid point, and deliberately trigger the imaginations of those listening using sensory language. That means leaving out the business speak and avoiding too much jargon.

Telling an effective and influential data story (and why would you tell a data story unless you wanted to be effective an influential?) means you have to shift your thinking. You are not presenting material or information. You are instead giving people an experience. You have to share your experiences of grappling with the data, how you came to your insights, and what it all means. Yep, you. If you can share your experience, your audience members will experience the data. That creates emotional engagement. That is what you want.

That’s the next biggest mistake those telling data stories make: keeping themselves out of the equation.


Richardson also makes the point that some data narratives may be unreliable. He then makes a mistake by confusing bias with point of view.

The real danger with data storytelling is using data that is biased – because of faulty algorithms and unconscious built-in preconceptions that perpetuate biases about the world and its people. If the data is biased, the entire premise for your story is biased, and the story will perpetuate these biases.

All storytellers however, share a story from a particular point of view. Anytime you give a presentation, you are presenting your point of view. Yes, it’s supported by data. And you have a point of view about that data. Influence is about sharing your point of view and having people join you. So it’s better to weed out the biases in the data early so you can tell the story with a clean point of view.

So, to sum up: use data visualizations to help make sense of the data, tell a story to make the data meaningful, do so using a basic narrative structure, make sure you share your experiences with the data and insights, trigger emotional engagement by sharing your experiences, trigger the imagination using metaphors and words that stimulate the senses.

The result? Impact and influence. Now who wouldn’t want that?


Dr. Karen Dietz has 20 plus years working with Fortune 500 companies, startups, and nonprofits with her unique combination of organizational development, leadership, high performing teams, communication and storytelling expertise.

Karen is an original in the field of business narratives, the author of “Business Storytelling For Dummies” (Wiley), a TEDx and Vistage speaker, and has built the world’s largest library of the best business storytelling articles with over 17k followers at

Karen has recently turned her skills to developing a similar library for technology leaders on data insights, data storytelling, technology leadership, culture, and high performing teams at

She’s been around technology organizations for years and her favorite groups to work with are engineers and scientists.