Storytelling with data

There’s a growing need and desire to make sense out of all of this data. Visualizing it is one way of turning data into information, then telling stories with that information helps people understand and act upon it.

During my tenure at Uber working with Strategic Finance, there was a constant need in my team to automate things, to improve efficiency and performance of processes. Each time I ran insights on data, I realized that there is a need to answer questions like – How much revenue is being generated in various cities? What is the driver efficiency for pool trips? How is the efficiency related to market share? What is the customer and driver retention? Can you help us with cohort analysis of finance metrics?

To answer these questions, I certainly looked up to Edward Tufte and his books on data visualization and Stephen Few, especially Show Me The Numbers which helped me learn the art of generating insights.

How would you describe the difference between data visualization and what you would call storytelling with data? Because I feel like a lot of people will look at a chart and they’ll say when they’re generating a report, “Oh, I can generate a graph. It can’t be that complicated,” and then they copy and paste it and present it. Where are we going wrong with all of that?

Data visualization takes a lot of different forms. We often use data visualization as we’re exploring data to try to figure out what might be interesting, what can we learn from it, what might somebody else care about.

For me, data storytelling comes in when we’ve figured out those interesting things that somebody else may care about, and now want to explain it and really hone in on what actions we should take based on this and what we can learn from it. It’s easy to show data, and for an audience, it’s then easy for them to say, “Oh, that’s interesting,” and then move on to the next thing. If you’re telling a story with the data, instead, you’re engaging them. You’re asking for a specific action. Then, the audience has to respond to that.

I will break it down to 3 core lessons that I learned and that I practice:

1. Identify your target audience. For me, the best data visualizations have a story to tell and give the audience a clear understanding of what’s important, what they should pay attention to, and why.

2. Customize the data visualization. When presenting your result, visualization means a lot. A good figure is way better than a ton of words.

3. Link the data visualization to your strategy. Make sure to choose your graphics wisely. Color, the size of different elements, and words can all help create a visual hierarchy, or implicit cues for your audience to help them know the order in which to process the information that you’re giving them.