Over the last couple months, I’ve written several posts trying to help those designers create better visuals. However, I’ve realized that I’ve neglected those who are still somewhat skeptical and are unsure if data visualizations are worth it. So if you are a skeptic, this post is for you. I want to take a minute and explain why data visualizations matter.
Before I jump immediately into singing the graces of data visualization I want to take a minute and point out that not all data visualizations are created equal. As I have previously explained, when it comes to data visualization it really boils down to selecting the right visualization for the job. In an article from O’reilly Radar by Julie Steele, she writes that when it comes to data visualization they can be “at best confusing, and at worst misleading. But the good ones are an absolute revelation.”
According to Steele, “The best data visualizations are ones that expose something new about the underlying patters and relationships contained within the data” and I agree. The real power of data visualization is both interesting and engaging, so if you can help the reader easily understand the information, while still presenting it in an entertaining and engaging manner well then; you’ve got a real winner. This is always easier said than done of course, partially because data visualizations are like “a new set of languages you can use to communicate…the various kinds of data visualization are a kind of bidirectional encoding that lets ideas and information be transported from the database into your brain.” Given that visualizations can be complex and confusing, you need to select the right one for the job.
Explaining vs. Exploring
According to Steele, those designed for explaining include “infographics and other categories of hand-drawn or custom-made images”. She explains that this type of image is best when kept clean, pointing out the fact that the “ability to pare down the information to its simplest form – to strip away the noise entirely – will increase the efficiency with which a decision maker can understand it.” So, when designing “explaining” type visualizations, it’s good to remember less is more. This can only be successfully done once you “understand what the data is telling you, and you want to communicate that to someone else.” These are those visualizations you should see in power point presentations and reports.
“Exploring” visualizations can be more imprecise. Unlike “explaining” visualizations, “exploring” visualizations are “useful when you’re not exactly sure what the data has to tell you.” They are great for when you’re trying to get an understanding of the underlying patterns and relationships the data may have. Therefore Steele suggests that “visualization for exploring is best done in such a way that it can be iterated and experimented upon, so that you can find the signal within the nose. Software and automation are your friends here.”
Don’t forget about your customers
It’s important not to forget that your customers are out there making important decisions too. Every day, they are analyzing complex interactive or animated graphics that chart the differences between your company’s services versus the one your competitors provide. However, Steele rightfully points out that “so far the tide of popularity has risen more quickly than the tide of visual literacy, and mediocre efforts abound, in presentations and on the web.” But as people are exposed to more visualizations and as the general visual literacy rises, “data visualization will increasingly become a language your customers and collaborators expect you to speak – and speak well.”
Don’t leave it to chance, hire a designer
It’s well worth the investment of hiring an in-house designer. To make sure you get the most out of your visualizations, doesn’t it seem like a good idea to hire someone who speaks that language? Steele makes the analogy of using Google Translate. Sure Google Translate is great when you only want a general idea of what the message is about, but you wouldn’t trust it when writing an important letter. Instead, you hire a translator. Do the same when it comes to data visualizations and you’ll be much happier, the last thing you want to do is leave it to chance.
For those skeptics out there, I hope this post has helped turn you into a new born believer. Let me know in the comments below.