How Do Dashboards Drive Behavior
*DigitalSherpa comment: Would love to see some examples of what you consider to be “good dashboards.” So many that I’ve come across are poorly designed or don’t fully capture the information needed. It would be interesting as well to hear your thoughts on how dashboards drive behavior. At the executive level? The Developers? The Customer?
Example of dashboards…good idea! I’ll see what I can find to post. In the meantime I think the question about how dashboards drive behavior is a good one and is tightly linked to design. I think it’s most useful to back into the answer, however. In other words, rather than designing a dashboard that will drive the right behavior, the right behavior needs to be defined in order to design the dashboard. The easiest way is to ask:
“What decisions will be made from this data?”
Decisions made from data are usually some version of ‘course correction’ or ‘go/no go’ decisions. So a dashboard that drives behavior is one that provides exactly the right data to inform those decisions.
The other necessary moving part is knowing what warning thresholds to set so the data is properly displayed. If the possible scale of responses on a fictitious measure is 1 – 10 (where ten is perfect, and one is complete failure) the dashboard design needs to accommodate the warning threshold. If the target for that fictitious measure is 7 (of a possible perfect 10), then there may need to be a warning when it reaches 8. Thresholds are highly subjective and need to be tailored to the dashboard user. In that example, a warning at 8 may be sufficient, or it may be appropriate to set the threshold at 9. In all cases, it comes back to the ‘what decisions will be made?’ question and more specifically asking what action will be taken on the threshold warning. So if 7 is the target, what action will be taken when the score is 9? If none, I would recommend trimming the warning threshold closer to the target (8).
The obvious comparison/metaphor is that of an actual stop light. The timing of a yellow light has some relationship to the speed limit on that road (I assume). On a road with a 25 mph speed limit, a four second yellow light is probably sufficient. On a road with a 60 mph speed limit, a four second yellow light probably doesn’t allow sufficient time for a course correction (slow down and stop).
*Side note* In an incredibly festive example of using your data power for evil instead of good, here are some stories of cities that deliberately shortened yellow light times and then installed traffic cameras to ticket red-light-runners as a way to increase revenue! Brilliant! (although unethical)
So those are my convoluted thoughts on dashboards that drive behavior. In short:
- Define what action will be taken (or is expected) from data and model the data display to that action.
- Clearly define the warning thresholds
- Avoid (at all costs) data for its own sake.
~Geek~
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