Editor's note: This Storytelling Month guest blog post was written by Cole Nussbaumer of Storytelling With Data, originally posted on her site here. The illustrative example Cole uses in this post was also published to Tableau Public using the new Story Points feature here.

When asked to write a guest blog post for this month’s focus on storytelling, I spent some time reflecting: if I had just a single lesson to share, what’s the #1 piece of advice I’d give in this space? I’d boil it down to three simple words: lead with story.

It may sound counterintuitive, but success in data visualization does not start or end with data visualization. To resonate with your audience, you need to do more than simply show data. Attention and time should be paid to the context for the need to communicate: what does your audience need to know? What do they need to do? How can you make the data you want to share meaningful and memorable? Part of the answer is story. Stories resonate and stick with us in ways that data alone cannot. Purposeful story can bridge the gap between showing data and imparting information.

Now, if you’re an analyst by training (like me), “leading with story” might strike you as a little off-putting. This can be an uncomfortable space for many. Often, this seems to be driven by the belief that the audience knows better and therefore should choose whether and how to act upon the information presented. In other words, that they should be the ones creating the story. I would argue this is rarely (if ever) the case: if you are the one analyzing and communicating the data, you likely know it best, you are a subject matter expert. This puts you in a unique position to interpret the data and lead people to understanding and action. So, while it may feel more comfortable to lead with data, I recommend you fight this urge when it comes to explanatory analysis and lead with story.

To ensure your story comes across clearly, there are two lessons to keep in mind: 1) don’t make your audience wait for it, and 2) don’t make your audience work for it. Let’s discuss each in a little more detail and then look at an example of these lessons in action.

Don’t make your audience wait for story

Don’t bury your story: lead with it! Too often, I see situations where the communicator of the information wants to take the audience through the same chronological path they took to reach their conclusion. In most cases, this is unnecessary. Rather, lead with the “so what” and then back up into the path you took to get there only if absolutely necessary. This way, you don’t leave your audience wondering when you’re going to get to the point and run the risk of losing their attention before you do.

When it comes to crafting the narrative arc, I recommend storyboarding. Storyboarding is perhaps the single most important thing you can do up front to ensure the communication you’re crafting is on point: it establishes a structure for your communication. Write each of the main points you want to make on a post-it note. Then you can play with different arrangements to get the right flow that makes sense given your audience and what you want to communicate. Once you get the flow how you want it using this low-tech method, you can leverage Tableau’s Story Points feature to create this same narrative arc with your data visualizations. For more on storyboarding, check out this blog post.

Don’t make your audience work for story

Spend time making the story you’re telling impossible to miss in your data visualization by leveraging visual cues to help direct your audience where to look. Without these visual cues, our audience has to do work to figure out where they are meant to pay attention. When we ask our audience to do work, we run the risk of them deciding they don’t want to and moving on to something else, at which point we’ve lost our opportunity to communicate. Preattentive attributes like size, color, and placement on page/screen can be used strategically to signal to your audience where to look in the visual for evidence of the story you are telling. For more on preattentive attributes, check out this blog post.

Lessons in action

Let’s look at a simple example applying these lessons. Imagine you work for a car manufacturer. You’re interested in sharing insight around the top design concerns for a particular make and model. Your initial visual might look something like the following:

While the preceding view may work as part of your exploratory analysis (where you’re looking at the data to understand what might be interesting or noteworthy), it can be improved when it comes to explanatory analysis (where you want to communicate those interesting or noteworthy observations to someone else) by applying the lessons we’ve discussed.

First, let’s think about what story we want to tell and make that clear with words:

In the above, we’ve made clear the point we want to make via the statement above the graph. However, our audience has to do some work to see the evidence of those words in the data. Let’s reduce that work by employing some visual cues to help direct their attention:

In the above iteration, it’s clear where our audience is meant to look through the strategic use of color. We can even take this a step further, continuing the narration and use of color to tell a story with the data we are showing:

In this example, annotation and strategic use of color are combined to turn a simple graph into something more. Lead with story: don’t make your audience wait for it or work for it.

Leverage these lessons and Tableau’s Story Points feature to turn your data visualizations into compelling stories!