Data is important. Organizations worldwide spend trillions collecting, compiling, analyzing, visualizing, and distributing data. Data is collected for a multitude of reasons: to enhance decision-making, reduce risk through trend spotting, provide accountability, and to measure against performance indicators. Companies who manage the data process best often enjoy a significant competitive advantage over their less well-informed competitors.
Of course, different companies are at different levels of sophistication with this process. Countless resources are poured into POS data collection, massive ERP implementations are commonplace for data compilation, top talent is dedicated to data evaluation, and organizations often dedicate entire teams to reporting for distribution.
The two most overlooked steps in the data process are visualization and consumption. Strong data visualization is invaluable to an organization, so much so that most all organizations would do better to hire data designers.
How data is consumed and understood within an organization is hardly the focus that it should be. Understanding what data is being consumed, how it is consumed, and when it is consumed is essential to improving the entire data process in every organization.
Why is data visualization so difficult to achieve? More and more, companies are collecting every possible available piece of data that flows through them. This is the much touted and hardly understood phenomenon of big data. While large organizations don’t always do things right, they do understand the simple maxim of “knowledge is power.” This is precisely why organizations need to cut through the massive volumes of data they have collected and render it in a way that makes effortless understanding possible. It is in this way data starts to truly become powerful. The simple starting point of data visualization is creating something that people intrinsically choose to consume. Just as people make choices about what food to consume, people also make choices on what data to consume. Much like a great chef, a great data designer can make data much more appetizing.
Oftentimes data collection has an eight or nine figure price tag – setting up potential for buyer’s remorse of an enormous scale, akin to a billion-dollar meal no one enjoyed.
There are certain design principles that we can employ in order to increase how appetizing our data is. We must remember that one of the premises as to why visualization is so important is that executives don’t have the time, and often don’t have the know-how, to transform data to information, and information to knowledge.
At First Glance
As simple as this seems, title appropriateness and salience is of great importance when it comes to designing data reporting. Internet journalists reign in this regard, as their survival depends on traffic – they need to get people to view their content and they must structure their content in such a way that people desire to consume. Consider clickbait-fueled websites such as BuzzFeed: an instantly recognizable example of just how powerful title salience can be.
We can find more clues from our personal lives as to why setting expectations about time is so important. Think about how appealing this title is: “7 Things You Already Miss About the 90s.” Promising a finite experience is essential to gaining readership. Instead of a document entitled “A Summary of Competitive Threats,” “Top 5 Competitive Threats for 2014” is much more likely to be read. A short length quantified up front has digestible appeal, which explains why you love Vine, and why you skipped that 47-minute YouTube video.
Providing context and personalization is relatively simple and is an important step for creating readership and understanding when designing data. Arranging data into pre-existing category and classification systems provides context. A change as small as strategically moving what matters to the intended audience to the far left will make it such that a) readership rises significantly because the reader believes the report was created specifically for them, and b) understanding will increase because people understand their own context in a linear fashion.
Spatial organization is a hallmark of pretty much any product, writing, or fashion that is well designed, and in a business context it is important for a number of reasons:
/ Leaders know what they are looking for, and once they are used to seeing a specific layout, their eyes will instantly travel to where they need to be. This significantly speeds up review time and makes review more interesting and rewarding when you know what you want and where to find it.
/ We process information spatially; it’s easier to remember something when we can remember where it appears on the page.
/ Beautiful layouts aren’t just easier to process, but they are more appetizing, they actually will create a greater desire to consume that same information again.
When combined, these design principles make for an appetizing consumption experience. They make for effortless know- ledge. Borrowing from Maria Konnikova – who is describing why we love lists, though the sentiment is the same:
“An easy reading experience, in which the mental heavy lifting of conceptualization, categorization, and analysis is completed well in advance of actual consumption–a bit like sipping green juice instead of munching on a bundle of kale. And there’s little that our brains crave more than effortlessly acquired data.”
When leaders are presented with effortless knowledge, an organization starts making better decisions, and incremental continuous better decision-making is the difference between a dominant industry player and a struggling organization.