Hiebing Book Club: Data Storytelling

August 22, 2023by Hiebing

In today’s day and age, data surrounds us. It’s necessary to be able to share an insight effectively and inspire action. During this month’s book club, we explored becoming effective communicators by infusing the possibilities of storytelling with data to back it up in “Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals” by Brent Dykes.

The author dives into the essential skills needed to craft persuasive, memorable data stories. Data storytelling is the difference between a problem being resolved or overlooked; an opportunity being taken or missed; or a risk being mitigated or exacerbated. If you are interested in becoming a master data storyteller, you can pick up a copy here.  But if you’re pressed for time, here are our top three takeaways.  

Stories beat statistics.  

We hear facts, but we feel stories. Humans are storytellers by nature, so connecting with an audience through a story opens a pathway to shared comprehension. In fact, our brains are wired to respond differently when we hear stories versus when we hear facts. When hearing a fact, just two areas of the brain are triggered – the language comprehension and the language processing areas. But when we hear a story, the areas of the brain that process colors, language, movement, sounds and scents are all triggered, making the story come to life for us.

By turning an insight into a story, we can reframe the circumstance with a stronger narrative that our audience will easily understand. You’ll catch and hold the audience’s attention, help them to understand the insight, create a scenario for them to remember and inspire them to act.  

Every data story has six essential elements

To craft a compelling story, the storyteller must invest the time and effort to do it right. And just like any good piece of literature, there are several elements to include.

  • The story needs to be rooted in data. You can use some creativity with the storyline but be careful not to stray too far off-base – it could result in creating unnecessary, distracting noise.  
  • The main point should guide the whole story. Keeping the focus on the central insight will help convey the clear purpose of the story.  
  • It’s important to go a step further than descriptive and be explanatory. Clearly explain the insight and context surrounding it instead of just describing the circumstances.  
  • Your story should follow a linear sequence. The events should build on each other to unfold a series of supporting data points leading to the central point. By exposing the data in stages, you won’t overwhelm the audience.  
  • Back in middle school literature class, we all learned about the elements to a dramatic story. The same goes for a data story – it’s important to establish the setting, have a plot and introduce characters. Each event introduced should be purposeful to advance the story or develop a character.  
  • Lastly, the story needs visual anchors. This will help your audience to see patterns, trends and anomalies. In the words of Mark Twain, “Don’t say the old lady screamed, bring her on and let her scream.” 

A powerful data story combines both narrative and visuals.

The next phase is the narrative. Your story should follow a storytelling arc. Start by introducing the setting to give background on the current situation and characters, as well as presenting the problem/opportunity (hook). Next, rising insights peel back the layers of the problem or opportunity in a directed manner. This leads to the “Aha” moment, sometimes referred to as the climax of the story, that shares the central insight. And finally, you should conclude with the solution and next steps to tell the audience how they can leverage the new insight.  

And the final piece is to add visuals. As humans, we’re visual creatures – we need to see, not just hear or read. All visuals used in the story should support the narrative. Just like with the data, anything that doesn’t support the main point is unnecessary. Remove any unnecessary noise, use tools like annotations and color contrasting to focus the attention on what’s important, make the data approachable, and instill trust by avoiding simple errors or using misleading charts. 

So, why is it important to use storytelling when it comes to data? In the words of the author, “The companies that are best able to turn their data into insights, and their insights into knowledge, will outsmart and outperform their competition.”  

 Searching for a partner that can help your brand craft a meaningful story rooted in data? Email Nate Tredinnick at ntredinnick@hiebing.com to set up a call.

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