As I read through the large amount of information on change management, I’m struck by the parallels between change management and data governance. The focus is on processes. It ensures that no matter what changes happen in a corporation, whether it’s downsizing or rapid growth, significant changes are implemented in an orderly fashion and make everyone more effective.
On the other hand, humans are resistant to change. Change management aims to gain buy-in from management to achieve the organization's goal of an orderly and effective transformation. Sound familiar? Data governance speaks to this ability to manage data properly, no matter what growth spurts, mergers or downsizing occurs. It is about changing the hearts and minds of individuals to better manage data and achieve more success while doing so.
Change Management Models
As you examine data governance models, look toward change management models that have been developed by vendors and analysts in the change management space. One that struck my attention was the ADKAR model developed by a company called Prosci. In this model, there are five specific stages that must be realized in order for an organization to successfully change. They include:
- Awareness - An organization must know why a specific change is necessary.
- Desire - The organizational must have the motivation and desire to participate in the call for change.
- Knowledge – The organization must know how to change. Knowing why you must change is not enough.
- Ability - Every individual in the company must implement new skills and processes to make the necessary changes happen.
- Reinforcement - Individuals must sustain the changes, making them the new behavior, averting the tendency to revert back to their old processes.
I often talk about business users and IT working together to solve the data governance problem. By looking at the extensive information available on change management, you can learn a lot about making changes for data governance.
2 comments:
Great post Steve, I think change management is probably the single biggest area most organisations overlook on their DQ/DG initiatives.
One of the recurring themes of all the data governance practitioners I interview (and you're no exception!) is the absolute need for a data governance change agent who understands the process of change and can communicate this into actions the business and tech communities can relate to.
(We've published a whole rack of useful change management resources that your readers may find useful: http://www.dataqualitypro.com/data-quality-home/category/change-management)
Good post! The parallels are spot on. Can't overemphasize the last two aspects in the change management process when looking at data governance - and this is where the big challenges lie: 1-there must be buy-in up and down the enterprise (saw a post by Navin Sharma at PBBI a while back that talked about how it's "Everybody's Business" and 2-it can't work unless folks are working it on an ongoing basis. There's one key difference I think though between change management and data governance projects - and maybe it presents the biggest issue of all in getting data governance to stick - change management is "sexier" - it is generally applied to take a company to a new and exciting better place. Data governance is a little more like brushing your teeth properly: it's smart, it's necessary, and it's just not exciting. So, what do you think - how does a company put the pizzazz in to data governance?
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