The concept of storytelling has become a popular tool for business users. Combine it with the word ‘data’, and it becomes even more appealing. The problem, like many buzz words, is the term has reached a tipping point of use, where it no longer holds value.
We’re all familiar with what it means to tell a story – we hear stories every day in our conversations with each other. A story is essentially a series of events (however small). To tell a story, is to communicate this series of events in some way.
Digital platforms play a role in modern storytelling – Facebook, Instagram and Snapchat all give users the opportunity to create and share their own story. The events captured by this media may not always be interesting, but then we don’t always tell interesting stories…
So what is storytelling, in a data context?
Data storytelling, uses data to help support the communication of a series of events.
Businesses are good at using data to describe a single event, usually because the data in question is a tracked metric. Where businesses need help, is joining the dots between events, to create a series of events – or a story.
Focusing on why an event happens, helps connect it with other events. Using data to support the occurrence of these events, creates a data story.
A good data story always has a point, or an audience take away - you've connected a series of events and supported these using data... so what? What do you want your audience to do or know? Data stories should start here!
If you aren't clear on a key take away, you will fail in telling your story well.
Storytelling is a skill. Storytellers who include too many irrelevant details, generally lose their audience before getting to their point (if they’re even aware of what this is).
Good data storytellers have identified their key message, include only event data to help convey this, and understand the best way to communicate with their specific audience.