Brent Dykes has written a smart and pragmatic book called Effective Data Storytelling. I’m only a few chapters in and he’s already given me a fresh way of reframing what we've set out to do with Juicebox.
Brent draws a critical distinction between informing and communicating:
"When you inform someone, you're simply disseminating data in a passive, clinical manner. You expect the audiences to interpret and comprehend the data for themselves.
On the other hand, communicating is about clarifying what the data means. When you communicate, you become an active, discernible participant in the delivery of the information...you must engage them by communicating in a way that guides them through the numbers and motivates them to act."
Visual analytics tools have historically settled for informing. It makes sense: Their focus has been about making the analyst super-powered in their ability to do analysis.
Meanwhile, the mechanisms and thought put into what it takes to reach audiences have been secondary. There has been little concern for “guiding them through the numbers and motivating them to act.”
And to be fair, if an analyst is working alone or with a small group of peers, creating data narratives that change perceptions just isn’t as important. These tools are strengthening the relationship between Analyst and Data.
Visual analysis tools focus on the relationship between the Data Analyst and the Data, to the exclusion of the outside audience.
Times are changing. More people are working with data. Analyst groups are seldom situated in a separate and isolated team. Quite the opposite: analytics leaders that I speak with are interested in getting their people closer to the business and decision-makers.
As a result, anyone who works with data has another role — analytics translator. They need to reach people, communicate the meaning of the data, motivate action. This responsibility is no less important than the analysis itself. In fact, we know that when you fail in translating for their audience, the best analysis can be wasted.
Communicating > Informing
Now the communication with people needs to come to the forefront. We need solutions that help us tell data stories, connect with audiences, share insights, and build the bridge between data translators and data audiences.
At Juice, we want to bring human communication back to the forefront. We have our a theory of what it takes to connect people using data. It comes in three parts:
The familiar flow of a storytelling helps engage people;
It is better to facilitate a dialogue about the data (vs. deliver a monologue);
Data communication should guide audiences to smarter actions.
For over a decade, we've been talking about bridging the "last mile" of analytics -- the gap between the analysis and the audience who could be made smarter. It is a communication gap, and we mean to fill it with a truckload of Juiceboxes.