Make Data Dashboards Useable with Levels of Detail

My team and I have recently been working on a data display project; some might call it a dashboard. I’ve never been particularly excited by dashboards because most are just too overwhelming. Inevitably people spend time squinting at confusing charts trying to read the tea leaves of data and devine answers when they should be looking for questions.

Further, most dashboards look complicated. If it’s difficult to understand, it must be right! Right? The trouble is that most people can’t discern anything meaningful from the morass of data displayed on disparate charts.

So, how can we make a valuable dashboard for everyone? After many iterations, we had to look outward for inspiration and found some in an unusual place – cartography. The experience of looking at a map is remarkably similar to looking at a dashboard.

Level 1 – General Comprehension

At the highest conceptual level, you can only understand a few things – the shape and size of the landmass, the ratio of land to water, and the borders of the most prominent countries. You certainly can’t pick out the street you live on or navigate the area you’re in right now. So, what if all the roads were on the map? They would be so tightly drawn together it would be impossible to see anything. You have to zoom in.

Level 2 – Directional Comprehension

The more you zoom in, the more detailed information you can see and understand. Here, at the state level, we can start to discern directional features like highways, arterial roads, bodies of water that were invisible previously, even cities and towns. Still, individual streets would be too dense to see, but you probably can get closer to where you’re aiming to be. Let’s zoom in again.

Level 3 – Navigable Comprehension

You can start making decisions at this level — finding places you might want to go, navigating from A to B, even avoiding traffic. Major street names are visible, and you’d be able to communicate specific directions to someone who isn’t looking at the map. With this tactical information, you can get somewhere.

How to Zoom out of Data

No one looks at charts for fun. Most people look at charts because they’re in search of answers. Unfortunately, it’s a consistently disappointing experience. There are no answers in a chart – only questions.

Suppose our goal is to take dozens of disparate data points and help the dashboard viewers find their way through it to find meaningful insight. In that case, the answer is pretty simple but not intuitive — show less information.

In the dashboard above, we’re charting information from a customer base. It’s impossible to understand what any individual customer is doing. You can expect this at the most zoomed-out level.

Instead of over-delivering data, we present helpful general trends. We can even show a bit of metadata for context without cluttering the charts. Only general trends or changes of magnitude can get the viewer to the next step. It’s enough to compare trends and notice aberrations in the data set visually – people are fantastic at that. From here, the viewer can find a thread to pull on. In this case, "why hasn’t anyone published a digital ad this month?" or "why is there an upward trend in open support tickets?"

As we zoom in, the viewer should be presented with more appropriate data to refine their question. That cycle should continue until they gather enough information that they can move forward. Then our job is done – our viewer can stop looking at charts and do something.

Like we do with maps, zooming in to data is a powerful way to make information understandable and the best way to help your viewers do more with their data.