5 Steps Towards Compelling Storytelling With Data
Tags: Data Visualization, Storytelling, Data Science, Analytics, Xcelerator

5 Steps Towards Compelling Storytelling With Data

No, Great Analysis and Snappy Graphs Are Not The Whole Story

Muturi Njeri

Photo: Unsplash

Last month I listened to a Freakonomics Radio podcast — featuring David Coleman, the President of the College Board — which convinced me that our education system pulled off a fast one on us. Growing up, most of us proudly declared ourselves either Maths (Science-y) nerds or Humanities (Arts-y) nerds. If you were one, there was no way to be the other. You either turned a phrase or you solved an equation. In the old SAT, the college entrance exam ran by the College Board, you either excelled in the Verbal section with its convoluted passages and inscrutable vocabulary, or you cracked the code in the Maths section. When I did the SAT, I struggled with the Maths section, but I took comfort in my identity as a “Verbal” student. Yet a decade later, here was the President of the College Board saying, “You can no longer be perfectly verbal without being able to read and analyze data from charts, tables, and graphs…[it] was so silly that people call themselves highly verbal and wide readers, when in fact they’re illiterate when they reach science or the social sciences if they can’t evaluate numbers.” He was referring to the new SAT which integrates Maths and the Humanities skills across all sections.

Cole Nussbaumer Knaflic, a former Googler and author of Storytelling with Data, would appreciate this development. In the introduction to her book, she bemoans how schools, separately, teach us how to “make sense of numbers” in Maths classes then, in language classes, teach us how to “put words together into sentences and stories”. Rarely are those skills taught together; in other words, “no one teaches us how to tell stories with numbers.”

As (big) data proliferates and scholars and businesses scramble to make sense of (and value from) the data, we can no longer afford to treat stories and numbers as polar opposites. We must learn how to tell great stories with numbers.

The fact that we’re living in the age of big data needs no rehashing. 90% of the world’s data has been generated in the past two to three years. With this data influx comes an implicit promise to make better sense of our lives. For businesses around the world, the influx promises better understanding — and better value generation from — their markets, stakeholders, products and processes. However, for us to understand and communicate the insights the data generates, the insights must be coupled with another tool that has helped us make sense out of our realities for millenia: storytelling.

Evolutionary scholars and neuroscientists agree that were it not for stories, as a species, we would not have survived our hunting-and-gathering days in the jungles. Stories are how our ancestors learnt what was harmful or safe, what was right or wrong. As a result, our brains are literally wired for stories. A good story causes our brains to release dopamine, the “feel-good hormone” that affects, among other things, our heart rates, memory and motivation. Our love for stories cuts across time and space: from ancient Greece to 21st century China; from the parables of Jesus in Jerusalem two millennia ago to TED Talk stages today. In African contexts, stories like those of Anansi, the trickster spider, or of Shaka, the King of the Zulu, have captured our imagination for centuries.

In our age of data, insights and ideas, stories will humanize the numbers — allowing us to experience them, not as abstract, discrete and dry figures like machines would, but as specific, inter-connected and concrete shapers of our individual and collective experiences. Stories will connect us to the data, allowing us to not just understand it, but also relate to it and, consequently, take action.

But won’t slick data visualisation do the trick? A small yes and a massive no. Doug Rose, the author of Data Science: Create Teams That Ask the Right Questions and Deliver Real Value tells the story of a coworker who went on a trip to Mexico. The coworker made a 15-minute film about his trip and showed it to his peers. Rose talks about how the coworker had spectacular footage of the landscape and eye-catching graphics that could rival a blockbuster. But the video lacked the core component of every blockbuster: a narrative to weave the yarn together. Even after being wowed by the graphics, Rose could barely remember anything from the video just minutes after he had watched it. The coworker had lost an opportunity to tell the story of his own experiences in Mexico and what the trip had meant to him.

We have all had similar experiences where someone presented to us immaculate charts and figures but never helped us make sense of them. Ostensibly, the charts and numbers were meant to “speak for themselves.” While metrics and visuals can be great tools to understand our businesses, often, they’re not compelling communicators by themselves. However, combined with stories of what they tell us about where the organization has been, where it is, and where it is going — these tools possess the power to enthral and inspire us to act.

So, how do we move from decent visuals or interesting anecdotes to compelling narratives? Here’s a guide to get you started. (Note: the steps don’t always follow each other in this order; in fact, in most cases, you end up doing more than one step at a time.)

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1. Find the core of your story

You cannot tell a compelling story if you do not thoroughly understand its heart. As such, the first step towards compelling data storytelling is to find the crux of the story from your data. To do this, you (and your team) need to go through the knowledge discovery process: ask interesting questions, gather and clean data from a variety of sources to respond to the questions, analyse the data, and interpret the nuggets of insights from it. Often, this process surprises you as the data offers you unexpected findings — hence the need to keep an open mind.

For compelling storytelling, you need to go beyond identifying interesting patterns in the data, to connecting those patterns to significant themes that matter to people within — and outside — your organization. At McKinsey, they call this asking the “So What?” question. Ask yourself: what does this mean for our organization’s future? What might we, therefore, do differently? What does this imply for our product strategy? How does this affect our organization’s relationships with our clients? Why does it matter? The responses to these questions are the bedrock of your story.

2. Craft a vision to move your audience

Secondly, you must understand who you’re telling your story to and how you adapt it for them. Your subject might stay constant but the way you tell your story, or the details you emphasize, is bound to change with the audience. For instance, if you’re addressing a panel of potential investors you might emphasize your product’s return on investment while speaking to clients you might emphasize how the product saves them time and money. Ask yourself: who is my audience? What’s my relationship with them? How can I best connect with them? What questions might they have? How will I address these in my story? What do they already know? How can I connect what they already know with the new information I’ll be giving them?

Remember, when you tell a data story, this is not just another opportunity to impress. Instead, it’s an opportunity to move your audience: to move them to understand your subject better, to move them to change their perspective, to move them to act — to fund you, to buy your product, to approve a new hire, to vote for you, to join your team.

To move people, you need a powerful vision in your story. What are you asking your audience to sign up for and how does it change their world for the better? As a leader, your job as a storyteller, is to vividly and tantalizingly describe this vision to your audience.

3. Create an intriguing and meaningful narrative

The narrative is the irreplaceable axis of the story, without it — like in Doug Rose’s teammate’s film above — the whole affair falls flat. Narrative is what ties the threads (the characters, the events, the visuals, the significance) together.

By connecting your data insights to a narrative or a journey that your characters or your audience members take, your story, while specific, represents universal, timeless and meaningful values — like duty, love, identity, family, faith, community — that grip and move your audience.

Crucially, for a compelling narrative, you must sequence the events in your story such that they flow fluidly from one to the next, from the start to the end. You can use the same structure that scriptwriters use to keep us glued to our screens:

Beginning : where you set up the context (the characters, the time, the place) and hook the audience into the story. In The Lion King, for instance, this would be where we learn about Pride Rock and how Mufasa is the King of all animals — and Simba is his heir. In an episode of Hasan Minhaj’s Patriot Act, a Netflix show that excels at using data storytelling and humor to cover topical issues, at the beginning, Hasan will introduce his topic, key characters, as well as why he chose to talk about the topic.

: where you set up the context (the characters, the time, the place) and hook the audience into the story. In The Lion King, for instance, this would be where we learn about Pride Rock and how Mufasa is the King of all animals — and Simba is his heir. In an episode of Hasan Minhaj’s Patriot Act, a Netflix show that excels at using data storytelling and humor to cover topical issues, at the beginning, Hasan will introduce his topic, key characters, as well as why he chose to talk about the topic. Middle : where you introduce a conflict in your narrative — as well as why it matters. This is where you have most of the action related to the problem taking place. You can talk about how you’re solving the problem, the challenges there-in and how you’re confronting them. The conflict breeds intrigue that keeps the audience wanting to know what happens next. In The Lion King, conflict is stoked by Scar’s desire to disinherit Simba — and the subsequent murder of Mufasa and exiling of Simba. In Patriot Act, Hasan will introduce the key issues in the topic (bringing in the data and other forms of evidence to back up his arguments), the key barriers to progress on the issues and what is being done about them.

: where you introduce a conflict in your narrative — as well as why it matters. This is where you have most of the action related to the problem taking place. You can talk about how you’re solving the problem, the challenges there-in and how you’re confronting them. The conflict breeds intrigue that keeps the audience wanting to know what happens next. In The Lion King, conflict is stoked by Scar’s desire to disinherit Simba — and the subsequent murder of Mufasa and exiling of Simba. In Patriot Act, Hasan will introduce the key issues in the topic (bringing in the data and other forms of evidence to back up his arguments), the key barriers to progress on the issues and what is being done about them. Ending: where you resolve the conflicts, emphasize key points and/or call for action. In The Lion King, Simba returns to Pride Rock to reclaim the throne. In a Patriot Act episode, Hasan will wrap up with a summary of his key points and suggestions of actions the viewer can take to fix the issue.

4. Choose the right visuals to emphasize your core message

Cliché as it sounds, a good image is worth a thousand words (or even more). The right visual is not just the technically accurate or aesthetically pleasing one, but also the one that directly emphasizes your core message and vision (steps 1 & 2). You may use a technically accurate visual, but if it’s cluttered with unnecessary information, you risk distracting your audience. You may have a beautiful animation, but if it doesn’t hammer your point home, it is not good enough. Knaflic’s book, Storytelling with Data, offers principles and practical advice on how to design and choose the right visuals to tell data stories.

Two major principles from Knaflic’s work: 1) your visual needs to strategically focus the audience’s attention to the message you want them to take away using a designer’s tools like color contrast and relative text size; 2) clutter is your enemy! Eliminate every unnecessary element from the page (and story!).

Here is an example from Knaflic’s book: comparing a visual that simply presents data (Figure A) to one that tells a story using the same data (Figure B). Note how Figure B employs the two principles above.

Image source: Knaflic, Cole Nussbaumer. Storytelling with data: A data visualization guide for business professionals. John Wiley & Sons, 2015.

5. Use storytelling tools to make it engaging

Finally, to tell a compelling story, you need to tell it in an engaging style. There are a number of storytelling tools that you can employ to do so. The goal here is not to be extravagant, or even poetic, with language but rather to use language that appeals to the audience’s senses — thus connecting the abstractness of data and ideas to the concreteness of daily life. Examples, anecdotes, scenarios and metaphors are some of the tools that can allow you to do this.

Anecdotes are brief and personal accounts that relate to the topic which enable you to connect the ideas in your story to your own experiences. For example, the Freakonomics anecdote I started this article with. Scenarios (e.g. suppose a hacker took control of an in-house server containing your company’s most important data and demanded a ransom) challenge your audience to consider something by placing them in a hypothetical high risk situation.

Metaphors allow you to compare something new to something common to your audience’s experiences. A powerful metaphor can have the same — if not greater — impact as a great visual. For instance, imagine the impact that the metaphor “big data is the new oil” has had. It certainly has a better ring to it than “big data is a very valuable resource that is likely to significantly re-shape the global economy”. It captures the audience’s imagination and stays there longer.

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As a writer, I have spent the past decade honing my storytelling skills. In the past year, however, I have had to stretch myself harder to learn how to augment my storytelling with data. I came into my current role, as a learning design consultant for the Data Science Xcelerator (DSXL) program, from a Humanities background that emphasized qualitative skills. However, through rigorous research as we’ve developed the DSXL program, I have built up my quantitative muscle. Moreover, as our design team is diverse, with my peers better-versed in quantitative skills, we complement each other. Collectively, we can tell better stories in which language and data strengthen each other, in which metaphors and graphs sit side-by-side. This philosophy of complementarity is central to the DSXL program. We have built a program that believes in the interdependence of technical data science teams and business teams in times that demand tearing down the walls between them to create organizational value — a rare program that, in Knaflic’s words, teaches its participants to tell stories with numbers.

For more information about the Data Science Xcelerator program, please click here. We’d love to work with you to develop ‘storytelling with data’ skills for you and your team.

About the author: Muturi Njeri is a Data Science Design Consultant at Xcelerator. He is passionate about education, creative arts and African development. He loves to read and write on education, development, social justice, technology and the arts. You can read more thought pieces from him on his blog or follow him on LinkedIn.