In Steve Wexler, Jeff Shaffer, and Andy Cotgreave’s great book, The Big Book of Dashboards, they define a data dashboard as:

A visual display of data used to monitor conditions and/or facilitate understanding.

I was reminded of their definition because recently, I was invited to talk to different groups about how to start creating or improve their process for creating dashboards with their data. These groups were brought together in an ongoing Community of Practice by some of my Urban Institute colleagues.

I developed a new talk for the meeting, presenting some of the core issues I see with good dashboard design and considerations. I relied heavily on this great talk on dashboard design from Chantilly Jaggernauth as well as other  great (Tableau) dashboard examples from Kevin Flerlage, Lindsay Betzendahl, and many others. But to inform my thoughts, I first wanted to modify the definition of a dashboard a bit (my changes in bold):

A dashboard is an interactive visual display of data and information used to monitor conditions and/or facilitate understanding and exploration.

By adding “interactive” and “exploration,” I believe we can highlight within the definition of dashboards how they are commonly thought of—interactive data displays that enable people to sort, filter, and zoom. Without those words, I think a static infographic falls into this definition, and I want to keep the two communication concepts separate. (The “and information” part isn’t as important but does incorporate the images, sound, and video that some add to their dashboards.)

My (new) Urban Institute colleague Aleszu Bajak then added another phrase (in bold):

A dashboard is an interactive visual display of data and information used to monitor conditions, communicate analytical insights, and/or facilitate understanding and exploration.

At Urban, we’re often concerned with communicating conclusions from statistical analyses in clear and transparent ways. One of the groups at this talk had identified their target audience as not only policymakers in their state, but also citizens. They wanted their tools to be transparent with the public and make the data visible and available.

That made me think: Many people like dashboards and interactive data visualizations because they enable them to do something like click, hover, or scroll, but does the interactivity also make the data seem more trustworthy than a static set of graphs? Does the fact that a dashboard “feels” more alive—and often enables the user to immediately download the data—make it appear more open and transparent, and therefore more trustworthy?

I don’t know the answer to this question, I’ll admit. There are certainly ways to lie with dashboards and interactive data visualizations as much as you can with static graphs, but I have a feeling that the ability to hover, filter, and see the data change in real time provides users with confidence when exploring the data that they may have with static graphs or PDF reports. This increased autonomy is perhaps even more apparent when the user is provided with the ability to download the data, something that is instantly available inside standard dashboarding tools like Tableau and PowerBI.

Should everything be an interactive dashboard? No, I don’t think so. Not every use case nor every data communication effort requires this level of interaction. But as the tools get better and easier to use, it may be the case that simple dashboards will help us project more transparency, honesty, and objectivity with our data visualizations.

Photo by Stephen Phillips – on Unsplash