Bringing Data to Life! The Art of Data Storytelling

HOW TO GET ANYONE EXCITED ABOUT YOUR DATA

Humans communicate using language: we talk, write and sign, developing shared systems of meaning. Data, while using familiar symbols, is often presented to us in complex ways—graphs, charts and numbers. Understanding data requires having context and previous knowledge to interpret it accurately. Interpretation and meaning making is subjective and audiences develop their own conclusions based on relevant (or irrelevant) information. The misinterpretation of data can have unintentional consequences, and this is where data storytelling can help.

Woman describing visual data

Data storytelling can help you craft a compelling narrative that tells the story of the data you have collected. It puts you in control of how others will view your data and allows you to outline a clear message without the need for audience interpretation. By removing all the guesswork and presenting data in compelling ways through art, story and visualization, you can communicate insights in a more engaging and clear way.

Data narratives—or data storytelling—is a relatively new concept, though the science of storytelling is widely recognized. Simply put, our brains remember and process information more effectively when presented to us in a story. In his book, Actual Minds, Possible Worlds (1987), the late cognitive psychologist Jerome Bruner found that people are 22 times more likely to remember facts if delivered to them within a story!

The Power of Storytelling

The Untapped Power of Imagination in the Workplace, by Grant (2017), reveals how storytelling is a powerful tool that calls to a primal, emotional core that makes us human. She highlights the Hero’s Journey and identifies four major strengths of storytelling in the context of business management, though these strengths of storytelling are universal.

1

It facilitates the connection between emotional and personal values as part of the management decision-making process. It provides context that builds personal investment. An effective story takes the information and presents it in a way that’s relatable and elicits an emotional response.

2

Storytelling simplifies complex situations and deconstructs them in a way that enhances the audience’s understanding. Again, context is important, and we don’t retain anything if we are overburdened by complex information that is difficult to understand. Breaking complexity down to simple, universally understood words communicates the important points.

3

Effective storytelling can establish, maintain, and express the values held by an organization. It gives an audience a reason to invest in a narrative that resonates with them. Moving you through an effective story with strong messaging can help you shape your own experiences.

4

Storytelling can harness the emotion and energy of an organization by moving its members to action. Eliciting a specific emotion can transform a story from something that people passively absorb to an effective call to action. It builds the motivation to spark change.

Now that we know some of storytelling’s strengths, how can we create a data narrative?

Building a Good Data Story

Think back to high school English class, where you may have learned about the different elements of a story. The characters. The setting. The plot and conflict. The narrative arc that builds up to the climax, and the aftermath of that final big moment. In a good story, everything is intentional. There are no elements that don’t help drive the story. No details that don’t build the atmosphere or the characters. Similarly, consider the five “W’s” of journalism—who, what, where, when, why (and how!). A good data story includes these core components, expressing them through both language and visual representations.

With this in mind, consider the following elements when crafting your data story:

Keep It Relevant

Who is your audience? Who do you want to impact, to drive to action, to enact change based on your data findings? Keeping your target audience in mind helps determine which data are most important for your story, and how best to translate them. Think about what terms are too complicated, why the data you’re presenting is important to them, and which data you can omit to keep your narrative clear and impactful. Keeping your target audience in mind will help you figure out the components you need to craft the most effective story. Data gathered from one study or research project may have many stories to tell.

Analyze Good Data

While this may seem straightforward, it is essential that the data used to tell the story is good. The methodology used will inform the validity of the final data, but you also need to identify where and why the data may be incorrect or incomplete. Recognizing the limitations of your research in the story itself will build credibility with your audience. Think of questions you expect your audience to ask and build a strategy to address those questions within your narrative. This is why knowing your audience is so important! If you need to, collect data points you feel are missing but your audience would want to know from external research and include them into your narrative.

Develop a Clear Narrative

Think about the message you want to convey through the data you’ve collected. You conducted your research for a reason, so draw from that reason! Write out your journey collecting the data through clear narrative points and organize those points in a way you feel best represents your greater narrative arc. This is your chance to contextualize your data in a way that is interesting and

understandable to your target audience. Looking for patterns and outlining why those patterns occur can be a great way of outlining your story. You don’t want your audience to walk away more confused than before, so make sure to end on a strong conclusion—even if your conclusion is that further research is needed!

Use Visuals Visuals Visuals

Adding a well-constructed visual component to your data storytelling will add to its credibility. As with many things, when designing, less is more. Don’t overload your audience with too much colour and information; stick to one colour palette and break down your points as simple as you can make them. Write up clear titles for each visual, and make sure each point reinforces the title. Nothing kills a data story more than mismatched graphics! Make sure you have a lot of negative (or white) space, as it prevents cognitive overload and helps your audience better retain the information presented.

Conclusion

At its core, good data storytelling is simply communicating data in the right way to the people who need it most. How do you know if your story has worked? If your audience can retell your story without losing any important information, you know you have succeeded. You want your data to spark a conversation that moves past the numbers and drives meaningful action. If your data isn’t saying anything, what’s the point of collecting it?

References

Bruner, J. (1987). Actual Minds, Possible Worlds. Harvard University Press.

Grant G. (2017) The Untapped Power of Imagination in the Workplace. In Neal J. (Ed.), Handbook of Personal and Organizational Transformation. Springer, Cham. https:// doi.org/10.1007/978-3-319-29587-9_14-1

Further Reading

8 fantastic examples of data storytelling (https://www.import.io/post/8-fantastic-examples-ofdata-storytelling/)

Data storytelling: The essential data science skill everyone needs (https://www.import.io/post/8fantastic-examples-of-data-storytelling/)

The next chapter in analytics: Data storytelling (https://mitsloan.mit.edu/ideas-made-to-matter/nextchapter-analytics-data-storytelling)

What is data storytelling and why should you care? (https://narrativescience.com/data-storytelling)