8 Reasons Why Data Governance Fails


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Projects and Programs fail for a variety of reasons.  Data Governance is a particularly tough program, and I’d like to see as many programs succeed as possible.  Below are the top reasons I’ve seen that have caused Data Governance programs to fail.

1. No Success Shown
A good way to kill your program is to show no success out of the gate. Very quickly people will become disinterested, restless, and you’ll notice participate will wane. To prevent this, get a quick win that really excites upper management as well as the stewards. Fix a pain point for them or clean up something that everyone knows is a problem. Whatever you do, get a quick win.

2. Loss of Executive Buy-in
This can happen for a lot of reasons, including the other 7 listed here, so the key to this is to keep your executive sponsors up-to-date and engaged. You can do this through traditional status reporting as well as drop-in meetings and updates when you have success. Have a communication plan that keeps your executive sponsor and interested upper management engaged and updated.

3. Not Having a Proper Foundation
A recent article that I blogged on stated that 80% of Data Governance projects fail. Now, I’m not knocking the authors or anything, but the conclusions that were drawn were pretty obvious. If you start Data Governance before you have the proper foundation you are going to fail. A proper foundation includes proper data management for your organization, data models, metadata, etc. Basically, you need to at least have the basic foundation for what Data Governance will indeed govern. If you don’t have metadata, for instance, wouldn’t you first start a Metadata project to build up your data dictionary before starting your Data Governance Program? I would.


4. No Metrics
“If you don’t know where you are going, you’ll never know when you get there”. You need to know where you are, where you have been, and where you are going. Keep metrics on your scope, your progress, your maturity model, your dollars saved, your dollars earned, your risk mitigated, and anything else you can. The more tangible, the better. You will use the metrics to keep people interested, both your stewards and management.

5. Poor Planning
You need to plan before you start Data Governance. Put together a communication plan, get an idea of your scope, talk with your effected business units… in other words, be prepared. Each organization is different, but get all the red tape out of the way so that you don’t bog your council down with that stuff. Make sure everything for the first few months of your program is planned out so you can focus on executing and adjusting (being reactive) since you’ve already put the pro-active work in up-front.

6. Loss of Momentum
You need to keep things going. Being successful once justifies a project, not a program. Projects end, a true Data Governance program doesn’t. You’ll need to continually track your successes (and failures) and keep searching out new ones, keep your council invested in Data Governance, stay active in Enterprise projects, etc. You can’t slow down after you succeed, you need to keep on plugging!


7. Loss of Funding
This can happen for the same reasons as the loss of executive support, but it can also happen if you aren’t financially justifying your existence. If you cost more than you are worth, you aren’t going to be worth keeping around. Make sure you are doing work that pays for you to exist.

8. Being Viewed as ‘Overhead’
You don’t want to be seen as “just another department”, you want to be seen as a necessity – an integral part of the organizations growth and stability. Frame your talking points around things such as Data Governance enables scalability of the organization, sustainable increased revenue, and tangible risk mitigation. Don’t be just another group… be visible, and try to be the rockstar group.

  1. Carolyn S
    November 14th, 2007 at 16:46 | #1

    Does anyone have experience in developing a data governance strategy?

  2. November 20th, 2007 at 12:43 | #2

    I have developed data management strategies, policies and programs for many clients. I would agree that executive sponsorship is critical to success. Unless there is acknowledgment from senior stakeholders that data quality impacts their effectiveness in decision making, and that data governance is a critical element, then you’re doomed to fail.

  3. Mas Nishimura
    November 30th, 2007 at 17:35 | #3

    I’ve developed and implemented data strategies and have seem some policies continue and others falter over the last ten years. Although I agree the initially the Executive sponsorship is critical, what keeps the programs going to ultimate success is the existance of accurate quality metrics which shows both the initial success and continuing pertinence to the business.

  4. Raj Amesur
    December 26th, 2007 at 18:51 | #4

    I have designed and deployed critical business data performance models that use the foundation of data governance strategies.

    I would certainly agree to Executive Sponsorship and the tool simplicity that keeps the end-user and management aware at all times of their historical and current trends. Having ways to measure performance and trust data integrity is the starting point to success in any operational environment

  5. Dan O’Dea
    January 23rd, 2008 at 11:25 | #5

    I have been on two data governance groups. Although my experience is somewhat limited, one of the groups was for the Federal Government, so we were pretty serious about it. I am trying to get a data governance policy started at one of the companies I support, and the hardest part is convincing them they need one. Their stance of “Nothing bad has happened yet” is difficult to break into; they assume if nothing has gone wrong nothing ever will. It’s even harder being an outsider; the company is quite conservative and doesn’t like ideas coming in from outside.

  6. May 18th, 2009 at 11:00 | #6

    I have been working on DG and DQ since the 90′s in various kinds of commercial environments, and have made and seen my share of failed approaches. From that, and from my MDM experience, I’ve created an “Agile Data Governance” process that mitigates the reasons why DG fails (was excited to read this article). It incorporates creating the strategy, (your question), but also delivering policies and making changes in technologies that improve DQ.
    Best of luck on your DG pursuits!
    BTW, I think the article is very good. The only disagreement is on point 3, which I think is one area where we tend to lose the interest of our business leaders. My experience is that we tend to get very deep in very abstract discussions, and leaders lose the line-of-sight to the business problems and priorities they need to address.
    Other than that, this is a great list!
    Cheers!

  1. December 6th, 2007 at 08:55 | #1
  2. June 22nd, 2009 at 11:00 | #2