Change does not happen in straight line. And we do a disservice when we thinking about “data driven decisions” as a simple sequence of events:
gather data —> do analysis —> find insights —> present insights —> action

We know that ChatGPT is remarkable at generating text. It is also a powerful tool for summarizing text. It can compress a long article down to the CliffsNotes version in an instant.

There’s obviously a lot of value hidden in this data, so we pointed Juicebox at it to discover (and share) some of those hidden insights. The interactive report we built is embedded below, but here are some things we captured during our exploration:

Data storytelling is quickly becoming a popular mode for presenting data. It combines text and graphics with data visualizations to guide an audience. Traditionally, people have used tools like PowerPoint and Excel, as well as traditional dashboard and business intelligence platforms, to communicate in this way. But these solutions are limited in their ability to balance the explanatory and exploratory elements of an effective data story.

Maslow’s Hierarchy of Human Needs provides a useful framework for understanding the drivers of behaviors. He recognized that basic needs must be met before higher level functions can happen. He also identified that once a need is met, it becomes an expectation.

I used to spend a fair amount of time criticizing pie charts. And I wasn’t alone — everyone who cares about visualizations has spent time shaking their fists at ineffectual pie charts (take this article for example: “The Worst Chart in the World”).

Data Storytelling is the evolution beyond data visualizations. It is a recognition that well-designed charts aren’t enough to move people to action. We need to use the tools and techniques of narrative stories to engage audiences with data. While the term has been around for a while, we are still early in the discussion about what Data Storytelling means and how it should be practiced.