Data Visualization: Blending Art and Science to Tell Data Stories

In this special guest feature, Caitlin Willich, Associate Partner, Technology, Media and Entertainment at Clarity Insights, discusses how data visualization will continue to increase in importance as the amount of data the enterprise deals with grows. We need to develop teams capable of translating that data into stories our executives can understand and execute on. Clarity Insights is a strategic partner for the nation’s leading organizations, providing data and analytics consulting services and enabling data-driven culture changes.

Data scientists and advanced analysts are among the most sought-after U.S. workers. On careers website Indeed.com, job postings for data scientists rose 75 percent from January 2015 to January 2018, and IBM predicts that by 2020 the number of data science and analytics job listings will increase by another 28 percent.

But what businesses are finding is that it takes more than a left-brained analyst to cull real business insights out of data. Today we are dealing with quantities of data that only a few years ago were science fiction. The demands of big data have widened the gap between business and information technology, and dashboards alone don’t provide context for all the numbers. Bringing those insights to life takes more than statistical analysis skills—it takes tribal knowledge and deep industry understanding to have the ability to tell a story from big data. Building a compelling narrative, complete with actionable insights, is necessary to facilitate deeper understanding of your business through data.

The art of data storytelling

Smart companies and consultancies using data analytics aren’t overlooking the importance of these “softer” skills. Enter the data storytellers. Data storytellers are good communicators and writers; often, they are visually-oriented and artistic. Companies are creating hybrid data visualization teams, combining people with analytical and creative skills to create one unit that can both analyze the data and present the underlying story. They transform petabytes of often obscure data into meaningful information for the business, creating visualizations that the average business decision maker can quickly understand.

Technically, the “data artist” is not a new thing. One of the first was Charles Minard. He created a statistical visualization of Napoleon’s march on Moscow. He combined several sets of data—number of troops, direction, volume of troops, temperature, etc.—to create what is largely considered to be the first visualization of hard data. Today he might have used the same information, but with help of modern technology could have added additional layers of information to further enrich the story.

Gathering the right components

A good story needs chapters, or checkpoints along the way, and should close with an understanding of the big picture, how each of those work together for a net result. And perhaps most importantly, it needs a main character: in this case, the data. While analytics are at the root of discovering insights, it’s not just about turning that data into charts anymore; we now aim to tell a story that provides insight or allows you to take action.

The “artist” turning the data into a story needs to have enough business experience to understand the business need, which in turns provides the ability to offer cognitive perception and actionable insights. Today’s data analytics is a three-legged stool: science, art and cognitive perception. Without all three of these, the data gets stuck in the “information bucket,” delivering information on a page instead of an actionable new insight.

Building the right team

Those three key elements may be found in a team of two or three people, but rarely in just one brain. For example, you want someone who is an organizational guru—maybe someone who organizes their closet by color—paired with an artistic employee who may enjoy making flower arrangements or painting. Additionally, we at Clarity Insights are finding that these teams are well formed when a more senior person from a traditional business intelligence (BI) background is paired with a less-seasoned, but still experienced, player adept at the more nuanced parts of storytelling. The hybrid model works.

Data visualization will continue to increase in importance as the amount of data the enterprise deals with grows. We need to develop teams capable of translating that data into stories our executives can understand and execute on. These are not simply charts and graphs, but instead stories that reveal the underlying conflicts, heroes, and conclusions hidden within the data. Only then can real, actionable insights be uncovered.

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