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Sunday, June 20, 2010

Principle Before Practice

Before I begin, a caution. Do NOT think that I am taking a negative position re: data governance. On the contrary, I firmly believe that the concept is essential. But what is the concept?

As I watch data governance related position descriptions parade by on,, etc., I am struck by the focus on the practice of data governance. They are all about tools and skills and methods and all either assume that everyone knows what the goals are or (worse yet) that goals for this company are the same as those for every other company.

I have learned at least one thing in my 27 year adventure in all things data-related and that is that doing something, no matter how efficiently or effectively, is very often a wasted effort without some forethought about the principles that we are attempting to implement.

Principles provide the glue that links all of our efforts together and the medium that allows us to be productive even when our last effort was a failure.

As with so many initiatives around data, this wave (governance) has crested and achieved the status of "best practice" without ever achieving measurable ROI. We have seen smaller-scale successes--enough to keep hopes high--but not, to date, the enterprise wide success that was used to sell the initiative in the first place.

But maybe I'm getting ahead of myself. What is the principle that data governance represents? Some candidates are:

  • Make life easier for DBA's by reducing the rate of database schema changes
  • Make life easier for developers (programmers) by making requirements less ambiguous
  • Reduce cost due to rework by making the rules for data quality and completeness more accessible at the point of capture
  • Make the data warehouse more useful by applying the same rules to data everywhere it is captured.
  • Reduce the number of sales lost because we can't keep track of our customers
  • Establish process consistency so that we can begin improvement efforts
  • Stop those sobs from delivering junk and expecting me to fix it
  • Define and establish (standard) processes to reduce variability in output quality
  • your favorite here

Which one(s) do you like? I believe the answer is all of the above and then some. What is the principle that unifies all of these goals? I discussed this in a broader context in a prior post. My point though is that if we don't have a firm and commonly held idea of the principle(s) we are attempting to implement, then no matter what we do, which tools we use, or how skilled the workers are, we aren't going to accomplish anything meaningful. To put it another way, "If you don't know where you're going, any route will do."