When it comes to storytelling, Pixar is one of the best in the business at creating heartwarming movies with memorable characters and action-packed adventure. Back in 2011, story artist Emma Coats tweeted 22 storytelling tips she learned from working at Pixar and picking up a thing or two from her colleagues there (link here). Similar to movies, data visualizations tell stories in their own way, and applying some of Pixar’s storytelling principles can help us, as data visualizers, communicate more clearly and impactfully to our audience (more entertaining too!). Without further ado, here are 3 things we can learn from Pixar:

  1. “Come up with your ending before you figure out your middle. Seriously. Endings are hard, get yours working up front.” – What’s your message? It’s a little different for us when we work with data compared to writing the script for a movie because we often have to follow what the data tells us. However, when you start exploring your dataset, you often will spot several different patterns as well as jot down a few notable observations. Figuring out the key message you what to communicate to your audience out of all the possible things you can say about your data allows you to really get to the point and focus on making an impact with your visualization.  This might mean giving proper context to a visualization by adding a callout and caption or changing one bar in a bar chart to a color different from the rest in order to highlight that particular data point.

  2. “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.” – Sketch it! Nowadays computer-based, data visualization tools like Tableau and programming skills using R and Python have opened the doors to what is possible for data visualization. However, there is something unique that happens when you sketch out a visualization by hand. Giorgia Lupi, an information designer and founder of the data driven research-design and innovation firm Accurat, talks about the usefulness of this physical activity in the way it simplifies the process of data exploration by allowing you to take a birds eye view of the overall organization of information as well as nail down individual elements such as data points, without the complexities of doing so digitally.

  3. “You gotta keep in mind what’s interesting to you as an audience, not what’s fun to do as a writer. They can be v. different.” – Get feedback! When you’re mucking through the data and trying out different visualizations you often “can’t see the forest for the tree”. Taking a step back as the creator and designer of a visualization and asking for feedback is one way to get back to telling the story about your data and making clear communication of your data the focus. It’s important to remember to get feedback from your audience’s perspective since they are the ultimate end-users and consumers of your visualization. What’s important and interesting to you, might not be the same with them.

This post is a part of Love Data Week 2018. For an introduction to Love Data Week see Sharon’s blog post that includes information about the Library of Congress’ Congressional Data Challenge and The Zooniverse. GIS Specialist Josh Sadvari also penned a blog post for Love Data Week about telling stories with Esri’s Story Maps