What is data storytelling and why is it important?
Data storytelling is all about clear communication on the insights derived from data. What is de story behind the numbers that mathematics or statistics professionals unlock? If people within an organization do not understand the insights and the visualization through standard BI-tooling is not compelling, no employee will take action, so nothing will change.
Data storytelling is usually interpreted as just visualizing data effectively, however, it is much more than just creating visually-appealing data charts. Remarkable storytelling leads to comprehension and firm decision-making, because it simultaneously addresses both emotions and logic. There are multiple neuroscientific researches that show decisions are often based on emotion, not on logic.
About data storytelling
Data storytelling is a structured approach for data insights communication; an approach that holds three key pillars: data, visuals, and narrative. The increasing amount of data that is too overwhelming to grasp at first sight, turns into context everybody understands with data visualization. These three pillars are the foundation for a successful data storytelling strategy that answers the following questions:
► Who is my audience?
► What is the right data and visualization that will support my story?
► How do you lead your audience to the information that matters?
► What is the narrative that will drive engagement and inspire action?
► How will you engage with the audience for them to see the bigger picture?
It is simply how our brain works
Good stories engage people emotionally. When we see or hear a story, the neurons in our brain trigger the same patterns as the storyteller, a process known as “mirroring.” According to a research by Greg J. Stephens, Lauren J. Silbert, and Uri Hasson, mirroring involves processes across many different areas of the brain, with the ability to incite a shared contextual definition of the situation. The motor and sensory cortices, as well as the frontal cortex are shaped and nurtured by feelings of anticipation of the story’s resolution. It is the dopamine that is set free that takes care of the rewarding part afterwards. The thing with dopamine is that when we experience an emotionally-charged event or hear a story of that impacts us, certain parts of our brain release dopamine, making it easier to remember something with greater accuracy.
Data storytelling nudges people into action
To get everybody in the organization on par with the strategy or desired actions, building a bridge to close the gap between logic and emotions is crucial. Statistics will not link the insights to daily actions. Simply because organizations have to deal with the fact that not everybody is (equally) data literate.
Data literacy is something that has been addressed more and more. Still, not every employee is able to understand, interpret, process and communicate data insights at the same level. Data storytelling is important, because the data insights you want to compel employees with to act or change, needs to be suitable for the audience, needs to highlight the key information they need to be able to deal with the requirements. So not ‘what are the numbers?’, but ‘what is the story?’ should be the center piece here.
To address the emotional part of humans, it is crucial to tell a story that people understand, embrace and makes them act. Numbers will not get that done. Reports used for making decisions or taking action do not need a static reporting dashboard, they need a data story as a communication approach. Static reports show data that’s relevant to a specific time period. In numbers. They share a moment in the past, but don’t tell you what it means for the business and its activities. Dynamic, visualized dashboards offer data analysts the pathway to tell the story based on an organization’s strategy.
With the current rise of BI tooling and the increasing possibilities, many organizations do apply visualization. But if the visualization through dashboards with data graphs and charts does not get the right call-to-action out, it will not create change. Meaning, the insight-to-value conversion remains low because insights are not translated into actions or business outcomes. Why do you expect something from the audience and what does it mean for them?
Reports and dashboards are mainly focused on providing information instead of insights. What are insights for mathematical or statistical people, is static information for others. You need an audience-centric approach – a story.
The how-to of data storytelling
How do you display and explain data and insights in such way that will nudge people into action?
In the next part about data storytelling, I will elaborate more on the how-to, providing some guidelines and examples with the help of Microsoft tooling.