Join Doug Rose for an in-depth discussion in this video Define a story, part of Learning Data Science: Tell Stories With Data.
- A friend of mine recently bought a video camera and created a short movie about his trip to Mexico. The editing software made the video look spectacular. The opening credits looked like a movie you'd see in a theater. There was music, voiceover, and even some special effects. We sat down together and watched his 15 minute movie. After about five minutes of watching, I was reminded of the difference between storytelling and just looking at videos. He made no effort to draw me into his trip.
It was just great footage of a beautiful place. It didn't connect me to his experience. The 15 minutes went by pretty slowly. Two minutes after it was over, I couldn't remember what I had just seen. Many data science teams think about storytelling the same way. They believe in an old phrase, a picture is worth a thousand words. That's fine, but you don't need a thousand words. You just need a few words that tell a great story. Some teams feel that if you just have beautiful visualizations, then the story will tell itself.
If I put up a graph that's easy to read, then the viewer will understand the meaning. That's not reality. Just like my friend's video, making something beautiful doesn't make it interesting. Beauty can enhance the experience, but it doesn't replace the story. A lot of data visualization focuses on the skill of creating charts. A data science team needs to remember that data visualization and storytelling are not the same thing. In fact, they're very different.
A beautiful data visualization is like a well designed movie set. It might stage the context, but it doesn't give you any of the meaning. That's why you don't watch two hour movies of beautiful movie sets. What makes a story engaging is not easy to define. There's structural definitions. These lay out characters, struggles, and reaching an important goal. The Greek philosopher, Aristotle, laid out six important elements of a story. These include plot, mythos, and spectacle.
These elements are a fine place to start, but they only give you a sense of the parts of the story. They won't help you connect with an audience. It's a little bit like trying to learn sculpture by focusing on chisels or brushes. The tools of storytelling are not the same as the art of storytelling. The art is being able to have your audience make a real connection to what you're telling. Try to think of a story as a way to use language and visualizations to help your audience understand and connect the tale to some larger meaning.
That's one of the first things you'll need to think about in storytelling. How are you going to create a connection? How will you help your audience find the larger meaning? There's a few things to keep in mind with this definition. The first is that you're using language and visualizations to make connections. What you say and what you show are not in itself the story. Often the visualizations will get in between you and your audience. Think about the best presentation that you've ever seen.
Did you come away from it saying, "I didn't really understand what was said, "but the chart was spectacular,"? It's more likely that you said the opposite. You probably thought of the misunderstood child or the overworked parent. These might have been the characters in this story. The dozen or so PowerPoint slides probably faded out into your distant memory. The second part of the definition is helping the audience. Remember that a good story is for the benefit of the audience.
There's nothing more boring than watching a data science team talk about their accomplishments. You're telling a story to help the audience connect with the material. Everything you say should be there for their benefit. That means you shouldn't talk about the process or share the credit. Get right into connecting with your audience. Finally, remember that it's all about creating this connection to help your audience find some meaning. When you've done a good job, then the audience will have found some of the meaning that you were trying to communicate.
Maybe they only found part of the meaning. That may have been the part where they found the closest connection. That's fine and you can use that to build on your next story. It's important to see that the beauty and production value of your data visualization is not the same as a good story. I would have gotten a lot more out of that video if my friend had spent less time on special effects and more time making a connection. Mexico's a beautiful country, filled with colorful history and terrific stories.
If he'd only started there, then I would have felt like we had a shared experience. I would share the larger meaning of his trip and not just look at the pictures.
- Structuring a data science story
- Defining plot, conflict, and details
- Going beyond reporting
- Knowing your audience
- Working with data
- Introducing visuals
- Eliminating distractions
- Incorporating metaphors
- Motivating the audience
- Avoiding pitfalls