Here's a fast way to evaluate the utility of your dashboard designHere's a super easy thing you can do today to evaluate your data product's dashboard. If you're displaying quantitative data of any sort, especially trends, then this will probably help you come up with opportunities to improve your design. Of course, testing the design with real users is always the best way to evaluate your product! With that, let's jump in.
It's quite easy, and I borrowed the technique (from Tufte):
For any and all your key UI widgets that sum up conclusion data, read the data aloud and then ask yourself "...as compared to what?"
If you cannot answer that question easily without leaving the dashboard or report, then you know you probably have room for improvement.
If you're going to tell the customer in a donut chart that the distribution of (3) values over some time period was "3,17, and 80" then the question is, "as compared to what?"
Keep digging further:
- Do I need to know what the previous values were? Over what period?
- How likely is the customer to know these values as given knowledge? (e.g. I bet you know what your typical home temperature is, but do you know what the barometric pressure at home typically is? Don't assume one design pattern always work for all the data points.)
- Is the absolute value of the data interesting, or is the change (delta) in these values what is interesting?
- Could the data be presented in a qualitative way (e.g. "3 = great, 17= so-so")
- Do I have to read or view a lot of ink to figure out "hey, there's really not much new here to look at from last month/week/etc."
- My average, min, or max
- Team/group/industry/competitor average/min/max/movement
- My change since last period
- My typical deviation / pattern
- My business's cycles
- A unique benchmark in your company, product, or the industry
- An index you created
- A SMALL, relatable unit people can grasp. In other words, showing $26,981,230.12 might be the real number, but printing $26.98M is easier to read.
- Even better, show that $27M as something like "2,000x the average value and 45x the #2 earner" puts that huge number into a relatable context.