Data storytelling can change the world.
And no, we’re not just talking about the power of big data or about the billions of gigabytes that are stored on machines. Data storytelling is the art of transforming quantitative information into a compelling narrative in order to engage your audience and prompt them to take action. In this article, you’ll find out why it’s so important.
But can a diagram really do all of that? With all due respects to bar charts, you’ve used enough of them in PowerPoint presentations to know they’re not all that powerful. Change the world? Isn’t this claim a bit too much?
The thing is: data storytelling is about way more than turning raw data into visuals. Translating data into graphics is called data visualization. And while data visualization is an important part of data stories, there are differences between the two and we’ll go over them and much more in this article. You’ll learn :
- Why the skill of data storytelling is becoming so important now
- 4 principles to keep in mind to tell a good data story
- 5 reasons why businesses need data stories, too
- What’s a data storytelling tool
- 7 criteria to pick the right data storytelling tool for you
But before that, it’s only fair that I start this article about data storytelling with a good story.
The doctor who used data storytelling to fight cholera
The year is 1854. Doctors are unable to curb the cholera outbreak raging in the London district of Soho: in three days alone, 127 people on Broad Street died, with a mortality rate of 12% in the city. At the time, most scientists didn’t know how the disease was really transmitted: they believed in the theory of miasma and thought that cholera was caused by particles carried in the air. A young doctor by the name of John Snow decides to take action. He’s skeptical of the dominant miasma theory and sets out to save the day by proving that cholera is transmitted through contaminated water.
Even though history ended up proving him right, the medical establishment of his time refused to take him seriously. But his observations led him to believe that a public water pump, the Broad Street pump, was supplying contaminated water to nearby residents. There was one problem: his microscopic and chemical analysis of the water was inconclusive. So he relied on the power of data instead: he collected statistical information about the incidence of cholera in the neighborhood and mapped it on a chart, proving that houses that get their water from the broad street pump have 14 times higher cholera mortality rates. His exposé was so convincing that local authorities agreed to disable the pump that same day.
The map used by John Snow to persuade local authorities that the cholera epidemic originated in the water pump.
Not only was John Snow a good enough scientist to detect the true cause of the cholera outbreak, he also had an acute understanding of human communication. He presented the right data in order to achieve his goal of disabling the water pump and saving lives. Storytelling with data can allow you to convince similarly skeptical crowds.
Once upon a time, a data scientist needed to persuade a crowd
We live in a time where data reigns supreme. Every company strives to be more data driven, and data scientists have been on the Glassdoor top-3 podium for jobs in highest demand during 5 consecutive years. But it’s not just businesses: with our connected watches and our fitness trackers, we’re all trying to use data to make better decisions and lead better lives. And since we’re gathering data that is more voluminous and accurate than ever, this should be pretty easy.
There’s only one problem: we’re not naturally wired to make our decisions according to data. There’s a much more powerful force at play behind most of our decisions: emotions. Neuroscientists now agree that most of the things we do are influenced by how we feel. Data science alone is not enough to change our behaviors.
The hard truth is, we’re not the rational agents we’d like to think we are. Stories are the way humans understand the world, feel emotions, and decide how to act. Before science was able to explain most of the natural phenomenons around us, we used myths to make sense of what we see. Even in a world that strives towards data, stories are still our main source of entertainment, hope, and inspiration.
We tend to see the worlds of data and stories as fundamentally separate. On one side, data scientists with their spreadsheets, on the other, writers and communicators with their carefully spun discourses. Data storytelling is where these two worlds collide. When you pair data knowledge with stories, you can effectively persuade crowds and sway opinions in the right direction. This can help end public health crises (just like Dr John Snow found out) or tackle pressing issues such as global warming: a challenge that data journalism is taking on.
How to tell good data story
This sounds very promising, but where do you begin? Can you do it at the scale of your own organization, or is it a skill that only the best New York Times and National Geographic data journalists possess?
Here at Toucan, we believe everyone can tell a good data story if they have the right data storytelling tools. They also must understand some basic storytelling principles. Think back to the story you’ve read in the beginning of this article: I could’ve simply given you facts and figures about data storytelling. Instead, I’ve told you the story of a brilliant doctor fighting against the scientific establishment of his time to save innocent people from an imminent death. It’s much more engaging, no? You root for John Snow and you’re much more prone to believe that data storytelling can indeed, fix problems.
Here’s how to do it.
1 - Know your audience
Every good story is tailored to its audience. Knowing the context of the people listening to you can help you fill their knowledge gaps. I might not know who exactly will read this article, but we’ve all lived through a pandemic of almost 2 years, so it’s safe to bet that my reader would be interested in hearing a story about a doctor stopping an epidemic. Conversely, most people don’t know what the theory of miasma is, so I had to give this information.
2 - Make them care
There are key rules to storytelling that apply to every narrative. Any writer would tell you a good story needs a beginning, a middle and an end. If you can, add a human element by introducing characters that the audience can root for and build an emotional bond with. They must have a clear goal, and you should give your audience a way to help them reach it: remember, your aim with your data storytelling is for people around you to want to take action.
3 - Prove your point
This is where the “data” part of data storytelling comes in: you have numbers, use them! When your audience is sufficiently engaged with your narrative, give them the data that proves the efficiency of the solution you’re advocating for.
4 - Show them
We’ve already said data visualization is an important part of data storytelling. Humans are wired to interpret visual information way quicker than numbers: integrating graphs and visuals to your narrative will make it more potent. You can read more about data visualization here.
Businesses need stories too
We tend to wrongly assume that the world of business is one of numbers and rationality. This is not true, or every publicist and communicator would be out of a job. And it doesn’t only apply to consumers: even at the higher level of companies, decisions are made emotionally. This is why storytelling with data has successful use cases in business. Unfortunately, this “last mile” of data often tends to be ignored: companies invest heavily in data science, analytics and exploration and do not think enough about how to package and present them. Here’s what data storytelling can help you achieve:
1- Make better decisions
We sometimes misinterpret numbers when we don’t have the full picture. This is particularly true when you’re managing your company’s branches from afar, or when the size of your organization is too big for you to be on the ground. For instance, let’s say you notice the results for a branch of your restaurant have been dropping over the past month. If you don’t know that the weather conditions have been particularly bad in that region, prompting your customer base to stay home, you might wrongly interpret this as a management problem. Data storytelling can provide context and promote better decision-making.
2- Convince stakeholders
Convincing members of the board or comex to undertake a certain strategy or adopt a new solution is a big part of any executive or manager’s life. It is often thought that sheer numbers are enough to prove the efficiency of a certain solution, but anyone who’s ever been to a board meeting knows it isn’t true: you need to back up your data with a story to get decision makers on board with you.
3- Assess past strategies
Conversely, when a decision has already been made, it’s important to draw accurate conclusions about its efficiency and rectify potential mistakes. Being able to tell the full story around a strategic decision is important: you need to know the context in which it was taken, its initial goal, and how it was implemented. In hindsight, these important factors can often be overlooked.
4- Involve your whole workforce
The thing about data: it’s being generated more intensively than ever within companies, but only a small fraction of the workforce can understand and leverage it. Most employees don’t have the data literacy skills required to make data-driven decisions, which can influence the way your business is run. Data storytelling can help everyone understand data, no matter their data literacy skills, which leads to better results.
5- Market your product
Data storytelling is important for marketing: numbers alone are not sufficient to market your product to the general public. But if you do have numbers that prove the efficiency of your product or solution, then turning them into a compelling, engaging story can make or break your marketing strategy. Give them the facts and the inspiration that goes with it!
What’s a data storytelling tool and how to pick one
While all of this is interesting in theory, you need concrete ways to implement data storytelling in your company or organization. What we have explained might be easy to do manually once or twice, but you need to scale: it’s only if you have an infallible method for data storytelling that it becomes a habit for your teams to tell stories with data. This is where data storytelling tools come in: they’re way more than just data visualization dashboards. They prioritize design and allow you to integrate text or visual media to provide context to your data.
Here are some criteria that you can look at while trying to decide what data visualization tool better fits your needs:
1- User Experience
A data storytelling platform should be first and foremost user friendly, allowing users to understand your data in a glance.
2- Integration
Whether you keep your data on the cloud or on-premise, your data storytelling solution should be able to retrieve it through built-in connectors to minimize integration time.
3- Accessibility
The point of data storytelling is to understand data everywhere, even when you’re on the go. Your data storytelling platform should be accessible on every device.
4- Security
Ask your data storytelling provider about their authentication methods and how they keep the data they handle safe and secure.
5- Price
From free solutions to premium tools, the price grids of your provider should match your needs and budget.
6- Customer Service
As with any software or platform you use, make sure your provider has a team of customer service specialists that can help you navigate their solution.
7- Shareability
A good data story must be shared: whether through pdf, email or by granting viewing accesses, you should be able to share insights through your organization.
At Toucan, we’ve worked hard to make sure our data storytelling tool ranks high on these 7 criteria. But you don’t have to take it from us: read what our users think about our product on G2.
