Living with Imperfect Data by Jim Ericson.
From the post:
In a keynote at our MDM & Data Governance conference in Toronto a few days ago, an executive from a large analytical software company said something interesting that stuck with me. I am paraphrasing from memory, but it was very much to the effect of, “Sometimes it’s better to have everyone agreeing on numbers that aren’t entirely accurate than having everyone off doing their own numbers.”
Let that sink in for a moment.
After I did, the very idea of this comment struck me at a few levels. It might have the same effect on you.
In one sense, admitting there is an acceptable level of shared inaccuracy is anathema to the way we like to describe data governance. It was especially so at a MDM-centric conference where people are pretty single-minded about what constitutes “truth.”
As a decision support philosophy, it wouldn’t fly at a health care conference.
I rather like that: “Sometimes it’s better to have everyone agreeing on numbers that aren’t entirely accurate than having everyone off doing their own numbers.”
I suspect because it is the opposite of how I really like to see data. I don’t want rough results, say in a citation network but rather all the relevant citations. Even if it isn’t possible to review all the relevant citations. Still need to be complete.
But completeness is the enemy of results or at least published results. Sure, eventually, assuming a small enough data set, it is possible to map it in its entirety. But that means that whatever good would have come from it being available sooner, has been lost.
I don’t want to lose the sense of rough agreement posed here, because that is important as well. There are many cases where, despite Fed and economists protests to the contrary, the numbers are almost fictional anyway. Pick some, they will be different soon enough. What counts is that we have agreed on numbers for planning purposes. Can always pick new ones.
The same is true for topic maps and perhaps even more so for topic maps. They are a view into an infoverse, fixed at a moment in time by authoring decisions.
Don’t like the view? Create another one.