So far this year, we’ve challenged you to improve your storytelling skills, equipped you with strategies for handling audience questions like a pro, and introduced you to three crucial tests for preparing your data visualizations for Prime Time. In this post, I aim to provide some insight into a fundamental concept that ties together all of these ideas: the key principles behind effective data visualizations.
Look, designing effective data visuals is a complicated and difficult task. As we’ve discussed in these pages before, a long and arduous journey is required to reach the point where we’re ready to convey your findings through images. But once you reach this last step in your journey, the work – in many ways – has just begun.
It can be frustrating for even the most accomplished among us. British data journalist, information designer, and author David McCandless captured this idea perfectly:
“Visualisation is hard. I’ve written books, created software, directed films in my career, but visualisation is by far the most challenging discipline I’ve ever engaged with. It’s something about the precision needed at every level, I think. Concept, data, story, design, style – all are precision arts. In visualisation, they’re stacked one on top of the other. If one sags or slips, the entire edifice can collapse.”
So where does a data analyst begin when facing a challenge that bedevils even world-renowned dataviz professionals? It starts by understanding some guiding principles that help us navigate the challenges of data visualization.
Today, we’ll kickoff this journey by discussing what makes for “good” data visualizations. In subsequent newsletters over the next few weeks, we will deep-dive into each specific principle so that you earn a clear understanding.
What Makes For “Good” Dataviz
Based on my experience, I have discovered that successful visual design excels in three key areas:
- First and foremost, it employs a sophisticated use of contrast to direct the audience’s attention;
- Second, it effectively communicates a clear meaning by highlighting important (although common) chart elements; and
- Third, it eliminates distractions through purposeful refined execution.
When a data visualization does these three things well, it becomes an invaluable part of your data story. It enhances understanding, improves communication, engages the audience, aids in decision-making, promotes memory retention, supports accessibility, encourages exploration, and ensures consistency. Put simply, mastering the art of data visualization makes you a better storyteller.
Let’s now take a look at each critical principle.
Sophisticated Use of Contrast
Probably the most important strategy to master is the use of contrast in visuals. By strategically utilizing contrast, you can draw the viewer’s attention to key data points and guide them through the visual’s story. Whether it’s a bold or subtle application of contrast, when done effectively, it ensures that the most crucial insights stand out with just a brief glance from your audience.
Contrast takes many forms including: size, color, shape, and what I call “contrived” contrast. As a designer, these elements can be used individually or in combination. Getting the use of contrast right is critical because, frankly, it is the first thing your audience will see and can make or break your data visualization in the first few seconds.
Next week, we will explore the principle of sophisticated contrast more deeply.
Clear Meaning
A good data visualization effectively conveys its intended message. The success of your entire story, not just your dataviz, depends on how well the audience grasps the meaning in your charts. With careful design, key chart elements can effectively present a clear insight to your viewers — without you even saying a word.
Carefully crafted titles and headlines, concise labels, informative annotations, and strategic visual cues all combine to successfully convey the intended information. Despite their familiarity — doubtless nearly every chart you’ve ever made had most if not all of these elements — they can be deceptively complex in their execution.
Two weeks from now, look for a newsletter that explains this principle more deeply.
Refined Execution
The third key element is ‘Refined Execution.’ This is where your carefulness and precision can create a significant impact. Choices pertaining to font, color scheme, and layout may seem minor, but they can greatly influence the reception of your message. Meticulous implementation strives for a visual balance that elevates, rather than distracts from, the data. By minimizing distractions, the audience’s attention is directed precisely where it needs to be.
Just as contrast draws attention to specific items and basic chart elements help convey a clear meaning, visual polish ensures that supporting data remains unobtrusive in the background. Refined execution can be thought of as a set of guidelines that eliminate distractions from charts. The focus areas of refined execution include: lines (which include fonts as fonts are essentially collections of straight and curved lines); shapes; space; and color.
Look forward to pro tips on the correct ways to apply visual polish to these elements three weeks from now.
Integrating These Elements
As we continue to explore these elements and examples, keep in mind that mastering them takes both perseverance and practice. But, most importantly, it requires you to know the difference between good design practices and bad ones. I am excited to offer you that understanding in the upcoming weeks.
