An Introduction to Data Storytelling

It’s unclear who first uttered the words “lies, damned lies, and statistics”, but the meaning of the phrase is clear. Statistics, even those derived from trustworthy and reliable data, are easily manipulated to support any argument. Abuse of data allows untrustworthy parties to mislead their audience, particularly if that audience isn’t data-literate.

We see it all the time. The graph on a news program that purposefully removes context to support a political position. The sleazy investment pitch that focuses entirely on the upside while downplaying the risks. We’re all familiar with the ways that unscrupulous people sell us bad intel.

Although there is such a thing as bad data — small samples, bad collection methodology — typically, the data itself is blameless. Data doesn’t care to tell one story or another. It just is. Humans, however, require a narrative to wrap their heads around complex data. Our brains are wired for narratives. It’s how we organize and preserve knowledge — how we’ve done so since the earliest days of human civilization.

This is the role data analysis plays within an organization. Data analysts are the storytellers who present insights in a digestible way. Their power is the ability to influence critical business decisions by pointing leaders in the right direction. Their responsibility is to do so honestly, accurately, and without undue bias.

Let’s take a look at the role of storytelling in business: why it matters, how it works, and what can go wrong if it’s done poorly.

What is business storytelling?

First, let’s define what we’re talking about. Business storytelling is the practice of turning facts and figures into a narrative for yourself, your team, or your clients. It matters because humans learn through stories better than they do by looking at a spreadsheet.

To be clear, business storytelling should be non-fiction. It’s not about making up a story that doesn’t reflect reality in order to appease a client or ignore a problem. The storyteller’s goal is to uncover truth, then present that truth in a compelling way.

While business storytelling shouldn’t be frivolous or overwrought, it can be entertaining, funny, eclectic, stylish… whatever it needs to be in order to engage its audience and successfully confer its message. Basic business memos and lengthy text-based reports have a place in the working world, but they tend not to tell a very good story.

When we talk about business storytelling, we’re often referring specifically to data storytelling. There are other kinds of business storytelling as well. How do you present your training materials to new staff? What does your quarterly strategy meeting look like? These business units can also benefit from good storytelling.

Why does data storytelling matter?

You may not yet be convinced of the importance of a good story when presenting information. The facts and figures are already available in a spreadsheet. Why spend more time (sometimes much more time) to make it look pretty?

Stories are how people communicate ideas. Imagine if history class consisted only of list of names, dates, and statistics. We might be able to conceive of the scale of WWII’s Ardennes Offensive, where a month of fighting combined for 200,000 casualties. But would we remember those names, facts, and figures without the first-hand accounts from servicemen? Can we fully appreciate the devastation of war without primary sources from reporters and civilians? Film footage and photography?

A story is more than a list of events or a summary table of data. Stories provide intellectual and emotional context that make the information presented memorable. They allow us to do more than merely report information — analysis itself is storytelling.

Ultimately, a good story should help a decision-maker make smart choices. It should facilitate access to information without requiring the kind of data literacy or specialization that a raw data dump might. It provides an artifact that can be stored, shared, and reflected upon by team members of many disciplines with different levels of data sophistication.

The do’s and don’ts of data storytelling

There is a wide range of acceptable practice in business storytelling, but there some definite do’s and don’ts to consider.

Do’s

• Ensure the story you’re telling is valuable. Before you embark on a storytelling journey, plan out how this story will deliver value to you, your team, or your customers. It can be easy to get in the weeds and lose sight of the objective if we aren’t deliberate.
• Verify the quality of your supporting data. If the information you’re presenting is inaccurate, your story will be too.
• Empathize with your audience. Craft your story with a specific audience in mind. Don’t be too general, or develop a story that resonates with you. You already know what’s up.

Don’ts

• Don’t overreach your grasp. Keep stories short, direct, and digestible. Ensure you have the time and resources to do justice to your subject matter.
• Don’t fight the data. Sometimes the picture we hoped to paint just isn’t supported by the facts. Honesty is our responsibility as analysts. Interpret and contextualize, but never hide or misrepresent facts.
• Don’t take things at face value. When we develop business stories, we’re doing the leg work to understand a challenge, then communicate our understanding to others. If things don’t add up, look into it. If the data suggests something shocking or unusual, verify it.

Getting started with story-based analysis

Telling a story with data is a lot more work than simply generating a report or exporting a spreadsheet. There are many formats in which we can tell a story, ranging from powerful data visualization tools like Tableau and Google Data Studio to slideshows, custom infographics, or even microsites. Regardless of the tool we choose to use, the initial process is the same.

Setting an agenda and collecting your data

The first thing we do is set the agenda. If we try to tell a story without having a sense of the beginning, middle, and end, we’re going to get lost in the plot immediately. Communicate with the intended audience for the report: what questions do they have? What business metrics do they wish they could understand at-a-glance?

Starting with a question or two sets the plot for our story. A good report should be concise and answer one question or a set of related questions. Don’t try to broadly explain everything at once. The narrower the scope of the story, the better crafted it will be.

Once we have a question, we pursue answers. Start by planning out where the answers may be. Often, we’ll need to compare information from multiple data sources. Figure out which tools you’ll need to do so — how do you export, combine, and clean up your data? In many cases, Excel or Google Sheets will do. If your needs are more complex, there are hundreds of tools that can help you connect and combine data sources. Google Data Studio is a good (and free) place to start.

Check yourself before you wreck yourself

Before we dig into the data, carefully consider the potential pitfalls and challenges posed by the questions you’re trying to answer. Where might your biases mislead you? What gaps can you identify in the data set? Critically, how can you address those gaps and mitigate those biases? Write down a framework of considerations to guide you through the process. Once we’re neck-deep in data, it can be hard to maintain an unbiased and rigorous process.

Find the right answers

You’ve surely heard the phrase “there are no stupid questions”. That may be true, but there are stupid answers. As an analyst, arguably our greatest concern is truth. We know that statistics can be manipulated to say almost anything. We can’t succumb to the temptation to deliver the easiest answer, or the one that makes our department look best. This will feel like delivering value for everyone involved — at first. But if our reports are used to make business decisions, and our reports are flawed, the decisions will be equally flawed. Eventually, those shortcuts and boastful claims come home to roost. Stay humble, and be committed to truth.

Write for your audience

When reporting information, there is no single right way to best reach an audience. Just as small children enjoy picture books while adults prefer novels, our tone and format must adapt to the one receiving the report. Everybody has different abilities, strengths, and weaknesses. Great analysis involves empathy and emotional intelligence as well as rigorous data skills. Do your best to present your findings in a format that is both digestible and enjoyable for your primary audience. If they are visual learners, emphasize graphs and include colours and imagery. If you know their hobbies and interests, you could even include references or design elements that mirror said interests.

Don’t get too cute with it, but be willing to play. It makes the job more fun, and may make your end user more receptive to the insights you’re sharing.

Plan for a sequel

Often, when we present one report it will pave the way for another. By answering one burning question, we help our team identify more questions — hopefully, better questions. It’s good to consider where a report may lead you. You may end up taking note of other metrics that may support the topic of your initial report, or set aside useful views and data blends anticipated to be used in the future. While you’re digging through the data, it makes sense to plan for eventualities.

In conclusion

They say data is the new oil, an infinitely valuable resource waiting to be tapped. If so, analysts are the refineries that turn it from black sludge into useful material. We’re the pipelines that distribute information throughout a business so that it can be used effectively.

From solopreneurs to industry titans, data is central to the operations of a modern business. By telling the right stories, we ensure that data is useful, accurate, and honest.