You Can't Think Your Way to Data Governance

Loraine Lawson
Slide Show

Five Tips for Easier Data Governance

Five steps you can take to ease the trauma of starting data governance.

Thanks in no small part to Oprah Winfrey and pop psychology, we're a nation waiting for an "Ah-ha" - that moment in time when we have a paradigm-shifting epiphany. In its wake, we're assured, change is inevitable.


But it's a lie. Williams College professor and short story author Jim Shepard nicely summarized the flaw in this belief in "I Know Myself Real Well. That's the Problem."


"One effect of the tyranny of the epiphany in the short story is the assumption that an enhanced level of self-awareness is inherently liberating; in other words, once we realize we're doing something self-destructive or foolish, we won't do it again. Alas, we know from the rubble of our own lives that this isn't always the case."


Not only do we make this a false assumption in our own lives, but it's also infecting government, schools and businesses, even - and here we come to the point - data management.


In data management, you'll find the "tyranny of the epiphany" masking as equating a data governance framework with the actual work of data governance. Jim Harris, piggy-backing off comments made by data consultant Jill Dyche, addressed this problem recently:

And in her excellent article Data Governance Next Practices: The 5 + 2 Model,' Jill explained that data governance requires a deliberate design so that the entire organization can buy into a realistic execution plan, not just a sound bite. As usual, I agree with Jill, since, in my experience, many people expect a data governance framework to provide eureka-like moments of insight.

Ironically enough, all of this triggered an "ah-ha" moment for me. This is why AA uses the saying, "Fake it until you make it." While insight is important, what really creates change is action.


A data governance framework is important, but once you have one, you need to focus more on the "work" and less on the "frame" part.


"People need a mental model, that is why everybody loves frameworks and trust me we are great at creating frameworks but they are not enough and I think the mistake that people make is that once they see a framework, rather than understanding it's relevance to their organisation, they will just adapt it and plaster it up on the whiteboard and show executives without any kind of context," Dyche said in a recent interview. "So they are already defeating the purpose of data governance which is to make it work within the context of your business problems, not just have some kind of mental model that everybody can agree on but it's not really the basis for execution."


The full discussion includes a number of suggestions about how to move beyond talk and make data governance relevant and real.

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