data alone has no intrinsic value. It is neither good nor bad, neither positive nor negative, and cannot achieve anything on its own. Only by interpreting the data and constructing a story around it does the data become valuable.
I liken the role of a data scientist to that of a journalist. A great journalist must do the work (research) to gather the facts (data), then analyze and interpret the information, and finally package it in a way people can easily understand and remember. Their job is not just to report the facts, but to tell an enticing story.
The great screenwriter Nora Ephron was originally a journalist, and recounted a story (as told in the book Made to Stick) about an early journalism teacher who taught her the power and responsibility of journalists to not simply report facts, but synthesize knowledge and understanding.
Her class was given the task of writing the lede, or first sentence, of a story, the facts of which were, “Kenneth L. Peters, the principal of Beverly Hills High School, announced today that the entire high school faculty will travel to Sacramento next Thursday for a colloquium in new teaching methods. Among the speakers will be anthropologists Margaret Mead, college president Dr. Robert Maynard Hutchins, and California Governor Edmund Brown.”
Everyone in the class tried to work the facts into their sentence. And after reviewing their attempts, the professor said, “the story is: 'There will be no school next Thursday.’"
Like a great journalist, a data scientist must follow the same steps: gathering the data, analyzing and interpreting it, and finally — and perhaps most importantly — teasing out the story and presenting it in a way that everyone can understand.
But too many companies skip the final step. They rely on visualizations to try to make the data “user friendly.” While a graph can help tell the story, it isn’t the whole story — and isn’t enough on its own.
Why We Need Data Stories
Often, “data storytelling,” as it is frequently called is associated with data visualizations, infographics, dashboards, data presentations and the like, but that is only the beginning. We need someone to connect the dots to create a story.
Research is showing that our brains are stimulated by storytelling and that it even changes how we act and react in real life. The brain, it turns out, doesn’t make much of a distinction between reading about an experience and actually experiencing it.
The upshot of this for data scientists is that if we want our audience to truly understand what the data is telling us and then take action based on that understanding, we must communicate it in the form of a story.
Obviously, I’m not suggesting that we should start our reports with “It was a dark and stormy night,” or “Once upon a time,” but rather that we must construct our reports always with the greater story in mind, and there are some concrete actions you can take to improve your storytelling immediately.
Journalists may spend 50 percent of their writing time or more on crafting the headline for a piece because the headline is so important.
In the 1960s, advertising great David Ogilvy claimed that only 1 in 5 people read the copy that comes after a headline, and not much has changed today. Therefore, your headline must not only be positively magnetic to the reader, but also explain what the data story will be about in an easy to understand way.
Always aim for clarity over cleverness. And you can also strive to include the 4 U’s for the most compelling headlines.
