Is Data Visualization a Joke?

Bill Franks, Chief Analytics Officer, International Institute for Analytics
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Bill Franks, Chief Analytics Officer, International Institute for Analytics

Bill Franks, Chief Analytics Officer, International Institute for Analytics

“Data visualizations are like jokes.”I initially heard this claim made by a speaker at a conference. While I’m certainly not suggesting data visualization shouldn’t be taken seriously, visualizations are very much like jokes in one important way. Namely, if you have to explain a chart or a graph then you’ve failed just as badly as if you have to explain the punch line to a joke. A good visual, like a good joke, explains itself.

Resist the Temptation to Get Fancy

In recent years, the availability of sophisticated visualization tools and their ease of use have both increased dramatically. Even MS Excel now has dozens of graphical options built-in so that there are myriad of options to help others see the information you want to share with just a few clicks. While the ability to make use of unusual or novel graphical approaches isn’t a bad thing, it is important to appropriately utilize those options.

You absolutely need to tell a story and get your key points across to your audience. However, as is true with many situations in life, the shorter and simpler the approach used to visualize the data, the better. Using novel graphics and complex visuals may make you feel like you’re taking your presentation to the next level. But, it can often have the opposite effect.

Focus on Impact, Not Aesthetics

A best practice is to start by thinking through how to utilize basic, classical charts to illustrate your points. If a simple bar chart gets the point across cleanly, stick with it. To the extent that you can identify a more complicated type of chart that gets information across more effectively, then it is okay to use it. But, only move up the complexity scale when it is required. More often than not, you’ll do best to stick with the basics.

 Creating visualizations that don’t require explanation is the path to success 

To illustrate how getting fancy can work against you, consider the two charts below that contain the exact same information. Chart 1 is basic but makes it easy to see the core facts present in the (totally fake!) data. Chart 2 uses “cool” 3D pyramids and fancy colorations. However, it is almost impossible to cleanly identify the core facts with any accuracy.

Chart 3 is an example of a more advanced visual called a Sankey diagram that is very useful when understanding patterns like how users navigate a website. A Sankey would be useless in most situations but is very powerful when needing to visualize time, volume, and sequencing. It is ok to use specialized visuals like this when relevant.

Chart 3: Sankey Diagram

Add Interactivity Too

One of the best features of modern visualization tools is the ability to make the charts interactive instead of static. In other words, it is possible to drill down to the underlying data by clicking on one of the components of the graph. In the prior examples, clicking on one of the bars related to cats might take the user to a table with the raw data, or to a chart that shows how cat popularity varies by region.

By adding interactivity, you enable your audience to explore the data further on their own so that the key findings are more firmly grasped. While people love to navigate data visually, the key is to enable only interactivity that adds value without overwhelming the user. Thinking through the follow-on questions a user might have after interacting with the data initially can provide ideas for value-added interactivity. In fact, the level of interactivity you provide might vary based on who you are delivering the information to.

For example, a high-level executive might be sent just the key views in a static format since he or she won’t realistically have time to explore the information further. Executives just need the key points. A lower level employee working for that executive might be given access to more detail so that he or she has what is needed to act and implement changes based on the findings.

Always Step Back to Ask the Key Question

Before you send out your latest visualizations, always ask yourself the very important question, “Will my audience understand these visuals without explanation?” If the answer is not a resounding “yes” then you should reconsider hitting “send”. In rare cases where the information just can’t be visualized without complexity, plan for some hand-holding and explanation face to face.

Just like comedians have failed miserably if they have to explain a joke to their audience, so will you fail if you have to explain your visualizations. Creating visualizations that don’t require explanation is the path to success.

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