It is inevitable that there are ways that the software creator intends a feature to be used, and there are ways that it ends up being used. 🤓 Sometimes, these unintended uses can be even better than the initial idea, but other times, they can end up causing harm.
In a recent chat with Daniel Vacanti, we discussed this very thing about ActionableAgile™️ Analytics. I can say I was more than mildly surprised when one of my favorite features came up: the pace percentile feature on ActionableAgile's Work Item Aging chart. I love this feature because it helps you get early signals of slow work. However, after talking to and training many people, Dan saw that people very often misinterpret what this particular signal really tells us.
How did he come to that conclusion? He talked to them about the decisions they would make because of the signals and saw that they weren't necessarily picking up what was intended. Instead, the decisions people were likely to make could lead to worse outcomes than currently presented on the chart.
What do you think? Are you interpreting the signals correctly? Head over to our user community to discuss!
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