Data Storytelling: Appealing to Logic and Perspective
By: Kristi Pelzel
Tags: Entrepreneurship, Marketing, Data Science, Data Visualization, Storytelling

Data Visualization — Part 7

Data Storytelling: Appealing to Logic and Perspective

Data Storytelling provides a presenter with the ability to appeal to logic and perspective at the same time.

Leveraging storytelling concepts helps to communicate effectively with data because data (numbers and non-emotional information) connect an audience to logic, and stories connect people to reason or perspective.

Presenting information that bridges logic and perspective can help an audience recall the information they’ve seen and, also, trust it. If an audience cannot remember what they’ve just seen and heard, the story didn’t work, and you won’t meet your goals. If an audience doesn’t trust the information, they’ll either ignore it or work counter to it — a failure either way you look at it.

To tell a good story that people remember, you first need their attention. What Shahram Heshmat Ph.D. says in an article in Psychology Today is, “Emotional intensity acts to narrow the scope of attention so that a few objects are emphasized at the expense of many others.” This idea works for data storytelling because it’s intended to take a broad set of information and drill into a smaller or single point.

If I look at a data story for 12-seconds and then look away, what will I recall from the text and visuals?

Take a look at the story above.

Beginning, Middle, and End

At its most basic structure, a story is what storytellers have learned to describe as a beginning, middle, and end. One way to structure and link these three parts is by using plot points. Plot points flush out things such as motivations, desires, or setbacks.

Beginning: Regional exports in Chicago are strong, more robust than other big cities. Chicago’s job market is diverse, but overall economic growth has slowed. Why?

Plot point: Define the setback that connects us to the middle. Looking at the story example above, I assume that the “extensive assets” might be one reason a setback has persisted.

Middle: Using what the audience knows about the good and bad background of the situation, how did the “setback” align with opportunity or failure. Maybe it could go either way depending on the future actions of the intended audience reviewing this story.

Plot point: The plot point that connects the middle to the end might be the motivation to reduce debt or find unique resources.

End: The end is a forecast of the future, showing what the data would look like if everyone “does the right thing” and maybe a simulation of data if they choose the “wrong path.”

The three-act structure can be an outline or model to weave the story through. Conflict or tension (drama) is an essential part of a story because a feeling will trigger a memory, helping to link ideas with urgency.

In the example above, it seems that all was going well. The data was moving in favor of Chicago’s economic strength, but then … a setback. Those damn “extensive assets.” What will we do?

Building the Story

The beginning helps the audience understand the context of what the situation or point is. This should spark interest by answering the questions, “Why do I care?” and “What’s in it for me?”

The middle moves people from context to the implications of the context. Because the situation is “x,” it’s lead us to a state of “x,” and it’s even more substantial when implications of the context can connect to the audience as the key to the future of “x.”

The end of a story should lead people to understand why you brought them through this journey. Will you close with a call to action, something subtle that suggests a behavior change? Does the presentation’s goal call for a direct request, asking for time, money, or resources?

If you are presenting a data story for fun that you want to spend 40-hours building, which everyone will forget in 4-seconds, post to Tableau Public, or have fun in a MakeoverMonday Challenge. If you’re going to create something that has a return on investment and moves a goal forward, there should be a clear message at the end.

Facts are not Interesting

Suppose you reduce the Chicago example, above, to facts. It’s not engaging, visual, or memorable. It might be unclear if presented in a 30-page excel file.

And despite what you might think, turning a 30-page excel file into a story is not the easiest route either. Storytelling takes creativity, and it can even be harder to create than outlining rows of information.

Still, if the data you have requires a data story to digest and transform from information into action, it will be worth the effort.

Reviewing Your Story Before Presenting to Others

Try outlining a set of questions based on your goal, which you want the audience to answer after being presented with your data story. These questions will help you understand what’s missing because if, for example, you cannot walk away knowing what the issue is, the story fell apart somewhere.

After your presentation or reviewing your data story dashboard, will they be able to answer:

What was the problem?

Why did the problem occur?

What can be done to fix the issue or restore balance?

If I (audience) ignore this data, what will happen to me or those close to me?

What did the designer/presenter want me to care about the most?

Do I believe this information?

Do I need more information to decide to act, which will take time and resources that will delay my action or even change my mind?

A standard set of rules does not define a narrative structure for data storytelling. Narrative flow depends on your audience, the purpose of the presentation, and the data you have, or do not have, access to.

How much time will you have with your audience, and do they already trust you, or will it need to be established? Are they familiar with the topic, or will you need to layout a more extensive background and context? The narrative flow will align with answers to the questions above.

Facts presented alone do not always stick, and they rarely compel audiences into doing anything, but facts do help people logically believe a point. Stories lend structure to facts, leveraging the potential to give information meaning and actionable purpose. Data Storytelling provides a presenter with the ability to appeal to logic and perspective at the same time.

Part 1 — Context and Pre-Data Visualization Planning

Part 2 — Selecting Effective Visuals for Data Visualizations

Part 3- Identifying and Eliminating Design Clutter From Data Visualizations

Part 4 — Data Visualization: Designing for Attention

Part 5 — Fundamentals of Good Design for Data Storytelling

Part 6 — Good Data Visualization Examples