Data Storytelling: Using Pixar's Formula to Build Narrative in Your Data Analysis
Humans are storytellers. It's an innate feature of being human. Margaret Atwood, Canada's most celebrated storyteller and author of The Handmaids Tale, once said, “You’re never going to kill storytelling because it’s built in the human plan. We come with it.” Stories help us make sense of the world, communicate important information, and pass along cultural knowledge from one generation to the next.
In data analysis, storytelling is non-negotiable. It’s how we make sense of our datasets and communicate our findings to others. Data storytelling is a skill that takes time to develop and strengthen, and we can look to the best storytellers in the world for tips on how to do it well. Lucky for us, Pixar Animation Studios, renowned for its storytelling, has documented and shared its storytelling principles. Let's look and see if we can apply some of these principles to improve our data storytelling.
Principle 1: You admire a character for trying more than for their success.
In Pixar films, it's normal to see characters fail at a task several times before succeeding. In data analysis, it's normal to run into problems along the way. Often, discovering a data insight is a journey full of ups and downs. Don't just highlight the results; take your audience on the journey. Show them how the problem got solved and the steps you took to get there. It will make your data more compelling.
Principle 2 - You've got to keep in mind what’s interesting to you as an audience, not what’s fun to do as a writer. They can be very different.
When presenting and communicating data analysis, focus on your audience. You need them to be engaged. What is informative to them? Why should they care what you have to say? How does this data analysis impact their goals and objectives? Don't just showcase what you think is interesting.
Principle 3 - Trying for a theme is important. But you won’t see what the story is actually about til you’re at the end of it. Now rewrite.
Your data story must have a clear message or theme. This theme may not become clear until all the data has been analyzed. Part of thinking critically about data is challenging your assumptions as you progress through the process. Sometimes your data story will change as more information becomes available. It's ok to start again.
Principle 4 - Use the story spine structure.
Once upon a time, there was…
Every day…
One day…
Because of that…
Because of that…
Until finally…
That is the 'story spine structure.' The principle for data storytelling is to pick a story structure. It makes it easier for your audience to follow your story and better understand your message. It's a good idea to choose a structure that creates some tension. I like Ben Sykes's five elements of data storytelling:
- Set up and hook: What is the status quo? What unexpectedly changed?
- Rising insight 1: What influenced or contributed to the change?
- Rising insight 2: What other supporting evidence is needed or helpful?
- Aha moment: What is the impact if nothing changes?
- Solutions and next steps: What are the options? What is the best course of action?
Principle 5 - Simplify. Focus. Combine characters. Hop over detours. You’ll feel like you’re losing valuable stuff. But it sets you free.
Keep the data presentation simple, focus on the most important points and combine similar data. Avoid getting bogged down in unnecessary details. Research shows that people have better recall when learning things in groups of 3 or 4, and you only have 10 minutes of an audience's attention before they start tuning out. Keep things simple, and you will become a more effective data storyteller.
Principle 6 - Come up with your ending before you figure out your middle. Seriously. Endings are hard; get yours working up front.
Identify the key message you want to communicate before crafting the narrative around your data analysis. This will make it easier to choose the most relevant data to highlight. Think about what the audience will remember the most and what will be of most value to your organization.
Principle 7 - Finish your story; let go even if it’s not perfect. In an ideal world, you have both. But move on. Do better next time.
It’s important to have a sense of closure in data storytelling, even if it’s not exactly how you thought the analysis would play out. Perhaps you didn't get to complete a portion of the analysis, or you had trouble collecting some valuable data. Move on, use what you have, and strive to improve in the next project.
Principle 8 - Putting it on paper lets you start fixing it. If it stays in your head, a perfect idea, you’ll never share it with anyone.
Script out your narrative and storyboard your visuals. Yes, write/type out a script of what you want to say to your audience. Use storyboarding to sketch out slide designs, data visualizations, and dashboards. Putting your data story into a visual format allows for easier identification of any issues with your narrative. For example, you may notice that your narrative jumps around a lot, which makes it hard for the audience to follow the story.
Principle 9 - If you were your character in this situation, how would you feel? Honesty lends credibility to unbelievable situations.
Take time to understand your audience’s perspective and tailor your story to fit their perspective. What are their goals? What problems are they facing? Use empathy and understanding of your audience’s perspective to present the data in a way that will be believable and relatable to them.
Principle 10 - What are the stakes? Give us a reason to root for the character. What happens if they fail? Stack the odds against.
Highlighting the potential consequences or impact of the data will make it more engaging and make the audience more invested in the outcome. It's all about building up tension with your audience. They need to feel like the characters have potential dangers they could face and, ideally, that they will be able to overcome them.
Principle 11 - No work is ever wasted. If it is not working, let go and move on. It'll come back around and be useful later.
Don’t get too attached to specific data or visualizations. If they don’t effectively convey the message, move on and find something that works better. Whenever I'm building presentations, there are a few slides that I like but don't fit the narrative. I never delete them and add them to a repository of good slides that may help future presentations, and they often do.
Principle 12 - What’s the essence of your story? Most economical telling of it? If you know that, you can build out from there.
Identify the core message or takeaway of the data. Take time to present and communicate this message using data clearly and efficiently. The message should be simple and direct for your audience. Don't make them work to understand the message.
Some good data storytelling and data visualization examples:
- Digital journalism stories from The Pudding. I apologize in advance for the rabbit hole I'm sending you down.
- One of the authorities on data storytelling put together a series of makeovers here. A masterclass on how important data visualization is to tell your story.