This is an old post written way back in July, 2010.
I was in the Dulles airport waiting in the security line playing this texas hold'em game on my crackberry. A gentleman by the name of Scott noticed I was playing and quipped about how awful the interface was for this game. We did the usual chit chat about what we did and then we got into discussing business intelligence. Turned out he was a consultant and it was only recently that he was exposed to the world of BI. We talked about how much fun it was trying to figure out what to do with all this data and how to turn this into actionable information. This brought on an interesting topic on the sensitivity of the data not from a privacy standpoint but from a political standpoint. In particular, my new found friend talked about how it would be useful to analyze school enrollment information and the performance of students (anonymously, of course). However, that would never happen. Consider a metric that measures the enrollment by ethnicity. If a particular ethnic group is significantly lower than other groups the public may view the school as racially profiling their students. This is an extreme example but I wanted to drive home the point.
This begs the question, how do we mitigate the negative connotations associated with certain key performance indicators? Well, I don't think it's about that. When KPIs are not performing, they are by nature negative. Our energies shouldn't be spent on trying to explain that it's not bad. It should be about admitting to the deficiencies and letting people know what actions will be taken to address the issues. Is this likely going to be a standard practice? Probably not, but one can hope. :)
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