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.