Here’s the audio version:
Russian novelists are among the finest in the world. That’s why literature professors and self-styled intellectuals enjoy assigning them for papers or quoting from Tolstoy, Solzhenitsyn or Dostoevsky. Because their novels are nearly always 957+ pages long, most American students rely on the Cliff Notes version (I’m sure you NEVER did that!) Sadly, Cliff Notes and the movie leave out so much. Russian names and intricate plots force them to design charts to keep relationships straight without the pleasure of really getting into the story.
For example, if you are a refugee from Anna Karenina, you had to keep in mind that Countess Vronskaya is Count Alexi Vronsky’s mother, not wife. And at least two different women fall in love with him: Anna Karenina (married), Katerina “Kitty” Alexandrovna Shcherbatsky (single). Alexi and Anna fall in love, repent, follow each other around Russia, become objects of gossip, marry, and have two children. #itscomplicated
But they never achieve the happiness together that they ardently desired. In the end, Anna suspecting the love between them has died, throws herself under a fast moving train. Which is sometimes what I’m tempted to while listening to some “data-driven” presentation.
That particular Russian novel is an excellent metaphor for this love affair between US businesses and Data. It has appeared promising, but like the tormented relationship between Vronsky and Anna, the love affair between business and data doesn’t always end well. For all the talk of “data-driven decisions,” having data is not the same as presenting an accurate and compelling narrative from that data.
A collection of data doesn’t mean anything in itself because numbers can’t explain anything without a story. Your lovely data may hold tremendous potential value, but no real value results until or unless insights are translated into actions and outcomes.
Throwing down a report full of pie charts from your dashboard is not much different from reading off a list of dehydrated statistics.
The point of transforming data into a story isn’t to compete with Limony Snicket in the young adult fiction category. It’s not about becoming a youtube storyteller with a bazillion views. The point is using your data to tell a compelling (and truthful) story that influences people.
The trouble with compelling data-based stories is that they don’t create themselves. Good storytelling is never included in technical training programs. In fact, technical professionals often labor under the false assumption that people only need clear data points to make rational decisions. (A dirty secret: that’s not true even for themselves, if they’re honest about it.)
Decisions are made at the emotional level and justified at the rational. People who sell already know this.
Research from professor Antonio Damasio found that patients, who had brain damage in an area that helps process emotions (the prefrontal cortex), struggled to make basic decisions when choosing among alternatives. Even simple decisions like where to eat or when to schedule an appointment turned into lengthy cost-benefit debates for them. Turns out these patients’ decision-making skills were damaged by the lack of emotional judgment. Emotion helps our brains navigate the many alternatives for making decisions.
When transforming your insights into a data story, you need to connect the data to the influential, emotional part of the brain. When someone is absorbed in a story, more areas of their brains are stimulated compared to when they’re listening to a list of facts or statistics. That difference determines how your audience relates in terms of memorability, persuasion and engagement.
3 tips for crafting a Compelling Data Story (CDS):
Audiences tend to fall into these categories but they all want to know one thing: What’s in it for me. WIIFM
- Newbie: it’s the first exposure to the topic: a great opportunity to win them over to your cause. Attitudes may be completely open, or not.
- Regular Joe (or Josefa) : is aware of the topic but interested in an overview and major themes that relate to their work.
- Immediate Boss: wants in-depth, actionable understanding of intricacies and interrelationships with access to detail.
- C-Suite: only has time for the significance and conclusions of weighted probabilities.
- SME (subject matter expert): wants details and explorations of the topic— stories are not as important for this audience, or in any case, not the same stories as for the less-informed.
So before you decide what to present, consider what is appropriate for your purpose for this specific audience. A good art dealer will talk about the same painting differently, depending on the prospect. She may emphasize investment value, the decorative impact or the kind of people who are buying this artist’s work.
2. Details are darling.
If you found a way to move results from point A to point B, don’t just say that. What gave you the idea? What were you thinking at the time? How did people react when you suggested the change? What did people say? How were you feeling?
We want the scoop. Inquiring minds want to know.
Go into any good art gallery and you’ll hear detailed stories of why the artist chose this subject, this kind of paint, this size of canvas and so forth. Whether it’s concerning how long a patient stays in the hospital or why one painting is more attractive than another, the details of the story lead to action.
3. Show don’t tell.
Take this line from Tolstoy, “He stepped down, trying not to look long at her, as if she were the sun, yet he saw her, like the sun, even without looking.” (Anna Karenina)
Wowza. Don’t feel inadequate and don’t just say it. Share your point through an example or comparison.
Now if you can craft statements like this one, you’re clearly ahead of the storytelling game. If not, just ask yourself, is there a better way to get this point across? Is there a way to show what is going on?
In the above quotation, Tolstoy is showing, not telling. He could have written, “He thought she was really hot” in whatever way 19th-century Russians of his social class would say that. But then we wouldn’t be reading his stories 100+ years later.
How can you make your Compelling Data Story so clear your audience can “see” it?