It’s no secret that Data Governance is difficult to get right. Many organizations are on their third or fourth go-round by now. The pattern usually goes something like this:
1) Executive sponsor gets excited about data, decides to do Data Governance (again) but get it right this time. Go-getters (aspiring Data Leaders) do a bunch of hard work to get things moving.
2) The Data Governance program is launched with great fanfare.
3) Data Governance council meets, often monthly, starting with near-universal participation with the exception of an executive or two who don’t really understand why they are there.
4) At each meeting data is talked about, next steps are defined, and people are assigned tasks.
5) Between meetings, sometimes people finish what they were assigned, but often they “didn’t have time”—but this month they will absolutely get to it.
6) Over time, meeting attendance diminishes and/or the meeting frequency slows down because there is not enough for the council to do.
7) After 12 to 24 months, the whole thing sort of fades away, and nobody seems to notice.
Many Data Governance programs end up as pointless, half-complete, miserable uses of people’s time and energy, while they last. If we identify the purpose of most Data Governance endeavors, it comes down to some mashup like,
“Making data a more transparent, usable asset that helps facilitate business operations and ensure compliance with regulatory mandates.”
Is that a helpful undertaking? Of course.
Will it ever work? Nope. Why in the world would we focus Data Governance this way?
Sadly, this general pattern happens more than it doesn’t. What’s the problem here? Why doesn’t this top-down Data Governance model seem to work?
Getting a bunch of folks together in a room to talk about data creates no Data Value by itself. Putting together policies, establishing data owners, documenting data definitions—none of these directly create Data Value. And frankly, these are so many steps removed from actual Data Value creation that most Data Governance organizations have no idea how much net positive impact their efforts have on the business. C’mon! We need to be better than that.
Will it be important to have some meetings to talk about data? Probably. But we need more direction and more concrete outcomes. We need accountability to balance the empowerment, and we’d better find a way to impact the business, quickly.
We don’t need Data Governance; we need to create Data Value. Data Governance is part of how we do that. Data Governance should remove friction from everything we do with data. If we can quickly and clearly reference the definition of a data element, that can save us a lot of time and energy, helping us continue on our path unabated. But what if we aren’t even moving yet? A frictionless environment doesn’t do us a lot of good.
Doing Data Governance to address some future pain or to help solve some ambiguous future efficiency goal is simply a subtle way to avoid accountability—instead, find a way to add Data Value now.
To do this, chances are that Data Governance will be involved in some way, so let’s build it over time in alignment with the actual value it contributes. But what if we don’t have the option to take a ninja-like approach to building Data Governance? What if we have been told that Data Governance is what we need to do as our job? What if we are doing lots of things with data, have plenty of momentum, and Data Governance is really what we need to remove friction so that we can work better with data?
That’s great! We certainly want to do Data Governance if it is well-justified, but it is important for people to realize that we should be deliberate in our objectives with Data Governance. It is not an end unto itself but must be used judiciously as a means-to-an-end.
Bob Seiner (publisher of TDAN.com) starts many of his talks by asking the audience who in the room has Data Governance that exists in their organization. Around half the room will raise their hands. Then Bob tells them he is going to ask them again and he wants everyone to raise their hands. The point he makes is that every organization is governing data to a degree. It might just not be well-organized, coordinated, or effective. His point is that some set of norms and expectations, even if not proactively managed, still influences folks’ data-related behaviors—and we will accomplish far more with our data if we put some structures in place, so those norms and expectations are more consistent and reliable.
I agree with Bob, as well as the other Data Governance experts out there, and I believe that Data Leadership is actually a complement to their works—the other side of the same coin, if you will. While Data Governance provides guidance, it does not inherently build momentum, which is exactly what Data Leadership is designed to do.
Data Governance always exists, but it does not accomplish very much without Data Leadership – but Data Leadership doesn’t accomplish anything without Data Governance (which fortunately for us, always exists in some form).
Data Governance is crucial to Data Leadership’s success – and Data Leadership might just be what saves your Data Governance efforts. Put this knowledge to work for you today.
And until next time, go make an impact!
This article draws heavily from my new Data Leadership book, coming out in early October, 2019. Go to https://dataleadershipbook.com for more information.
