Storytelling with Data: A Data Visualization Guide for Business Professionals

by Cole Nussbaumer Knaflic

We’ll cover content to help you learn and be comfortable employing six key lessons: Understand the context Choose an appropriate visual display Eliminate clutter Focus attention where you want it Think like a designer Tell a story

Who: The budget committee that can approve funding for continuation of the summer learning program. What: The summer learning program on science was a success; please approve budget of $X to continue. How: Illustrate success with data collected through the survey conducted before and after the pilot program.

The 3-minute story is exactly that: if you had only three minutes to tell your audience what they need to know, what would you say? This is a great way to ensure you are clear on and can articulate the story you want to tell. Being able to do this removes you from dependence on your slides or visuals for a presentation. This is useful in the situation where your boss asks you what you’re working on or if you find yourself in an elevator with one of your stakeholders and want to give her the quick rundown. Or if your half-hour on the agenda gets shortened to ten minutes, or to five.

The Big Idea boils the so-what down even further: to a single sentence. This is a concept that Nancy Duarte discusses in her book, Resonate (2010). She says the Big Idea has three components: It must articulate your unique point of view; It must convey what’s at stake; and It must be a complete sentence.

When you have just a number or two that you want to communicate: use the numbers directly.

One thing to keep in mind with a table is that you want the design to fade into the background, letting the data take center stage. Don’t let heavy borders or shading compete for attention. Instead, think of using light borders or simply white space to set apart elements of the table.

To reduce this mental processing, we can use color saturation to provide visual cues, helping our eyes and brains more quickly target the potential points of interest.

storytellingwithdata.com/slopegraph-template.

Sometimes bar charts are avoided because they are common. This is a mistake. Rather, bar charts should be leveraged because they are common, as this means less of a learning curve for your audience. Instead of using their brain power to try to understand how to read the graph, your audience spends it figuring out what information to take away from the visual.

Note that, because of how our eyes compare the relative end points of the bars, it is important that bar charts always have a zero baseline (where the x-axis crosses the y-axis at zero), otherwise you get a false visual comparison.

When graphing data, a common decision to make is whether to preserve the axis labels or eliminate the axis and instead label the data points directly. In making this decision, consider the level of specificity needed.

Highlighting one aspect can make other things harder to see One word of warning in using preattentive attributes: when you highlight one point in your story, it can actually make other points harder to see. When you’re doing exploratory analysis, you should mostly avoid the use of preattentive attributes for this reason. When it comes to explanatory analysis, however, you should have a specific story you are communicating to your audience. Leverage preattentive attributes to help make that story visually clear.

We can leverage visual affordances to indicate to our audience how to use and interact with our visualizations. We’ll discuss three specific lessons to this end: (1) highlight the important stuff, (2) eliminate distractions, and (3) create a clear hierarchy of information.

Bold, italics, and underlining: Use for titles, labels, captions, and short word sequences to differentiate elements. Bolding is generally preferred over italics and underlining because it adds minimal noise to the design while clearly highlighting chosen elements. Italics add minimal noise, but also don’t stand out as much and are less legible. Underlining adds noise and compromises legibility, so should be used sparingly (if at all).

By highlighting the important stuff and eliminating distractions, we’ve markedly improved this visual.

Translation for data visualization: the more complicated it looks, the more time your audience perceives it will take to understand and the less likely they are to spend time to understand it.

Here are some additional tips to keep your visuals and communications from appearing overly complicated: Make it legible: use a consistent, easy-to-read font (consider both typeface and size). Keep it clean: make your data visualization approachable by leveraging visual affordances. Use straightforward language: choose simple language over complex, choose fewer words over more words, define any specialized language with which your audience may not be familiar, and spell out acronyms (at minimum, the first time you use them or in a footnote). Remove unnecessary complexity: when making a choice between simple and complicated, favor simple.

Beyond annoying our audience by trying to sound smart, we run the risk of making our audience feel dumb. In either case, this is not a good user experience for our audience. Avoid this. If you find it hard to determine whether you are overcomplicating things, seek input or feedback from a friend or colleague.

There are a few types of text that absolutely must be present. Assume that every chart needs a title and every axis needs a title (exceptions to this rule will be extremely rare). The absence of these titles—no matter how clear you think it may be from context—causes your audience to stop and question what they are looking at. Instead, label explicitly so they can use their brainpower to understand the information, rather than spend it trying to figure out how to read the visual. Don’t assume that two different people looking at the same data visualization will draw the same conclusion. If there is a conclusion you want your audience to reach, state it in words.

The title bar at the top of your PowerPoint slide is precious real estate: use it wisely! This is the first thing your audience encounters on the page or screen and yet so often it gets used for redundant descriptive titles (for example, “2015 Budget”). Instead use this space for an action title. If you have a recommendation or something you want your audience to know or do, put it here (for example, “Estimated 2015 spending is above budget”). It means your audience won’t miss it and also works to set expectations for what will follow on the rest of the page or screen.

Be smart with color. The use of color should always be an intentional decision; use color sparingly and strategically to highlight the important parts of your visual. Pay attention to alignment. Organize elements on the page to create clean vertical and horizontal lines to establish a sense of unity and cohesion. Leverage white space. Preserve margins; don’t stretch your graphics to fill the space, or add things simply because you have extra space.

We can leverage visual cues to draw a distinction between the actual and forecast data, easing the interpretation of the information. In Figure 6.2, the solid line represents actual data and a thinner dotted line (which carries some connotation of less certainty than a solid, bold line) represents the forecast data. Clear labeling of Actual and Forecast under the x-axis helps reinforce this (written in all caps for easy scanning), with the forecast portion set apart visually ever so slightly via light background shading.