The first step in creating data stories that engage and educate is to identify the basic elements of your data story. This is our first post in a series on data storytelling — look for additional posts coming twice a month to learn how to effectively incorporate data into a compelling story.
The Basic Elements of a Data Story
Before you can begin crafting a story that incorporates data, you need to set some goals. Telling stories with data isn’t quite the same as composing a work of fiction. You can’t just let your story run wild — so setting some guidelines that help identify the basic elements of your data story is important.
The easiest way to develop data story guidelines is to ensure you can ensure these five questions.
What is the “Big Idea”?
What are you trying to say in your data story? The “big idea” (or theme, or hypothesis) is the starting point when crafting a data story. After all, if you don’t know what you intend to say, the odds of your audience getting the message are pretty low.
Are you trying to tell a story of change that’s occurred (or occurring)? Maybe you’re highlighting a case of injustice or marginalization. Or are you using your data to make a case for political or social change? Make sure you have a clear idea of the story that your data is telling before you begin crafting a narrative.
What is Most Interesting to You?
Is there a key bit of data in your story that you feel is particularly important? A statistic that you feel deserves extra attention? Maybe you’ve uncovered data that is especially relevant to the work you or your team are doing or a stat that contradicts a popular misconception related to your field.
In addition to having a clear understanding of what your “big picture” story is, you should be clear on which pieces of information you want to highlight in your data story.
What is Most Interesting to Them?
We’d all like to focus on the stories that we think are most interesting. But a big part of effectively telling data stories is audience engagement. If your readers (or listeners) don’t think the data you’ve chosen to highlight is interesting, it’s unlikely you’ll convince them to read your data story.
Is there some data that you think would have broad appeal? Something that would attract attention and draw readers into your data story. While you obviously shouldn’t overlook parts of your data story you deem important, be careful not to dismiss data your audience will care about either.
What Do You Need Your Audience to Understand?
Chances are, you’re going to know more about the subject matter in your data story than your audience. (If you didn’t, there wouldn’t be much point in writing it, would there?) And not every person who engages with your story is going to understand every piece of information you have to present.
To ensure your story is a) accessible and b) doesn’t unintentionally lead audiences to the wrong conclusion, you should define the bare minimum you need readers to understand. Often, our research yields more data than our audience is really prepared for. This step will help you prune back extraneous data that might overcomplicate your story.
What Would You Like Your Audience to Understand?
The last question was about defining the concepts your audience needs to understand in your data story. But that’s not to say that you can only present them with the bare minimum of information.
This question should help you strike a happy medium between the absolute basics and an overly-complicated data story that will overwhelm many readers. After you’ve defined what you need them to understand, think about other points that you’d like to make in your data story.
Need Help Crafting Data Stories?
There are still six posts yet to come in our series on data storytelling, so stay tuned! Of course, if you have a specific question about telling stories with data, you don’t have to wait. The experts at Datassist are always ready to help. Get in touch now!