How to write a good Data Governance Policy
It won’t surprise you to learn that I sometimes find myself writing a data governance policy for my clients. Sometimes my clients assume that I will just take a previous policy I’ve written and tweak it for them. However, this really wouldn’t be very helpful for the new client, as it wouldn’t be designed to meet their needs!
As with all things data governance, I don’t think that there is such a thing as a standard approach, and there certainly is not one for a data governance policy. If there is no such thing as a standard data governance framework, why would you think that a policy written for another organization would work for you?
Unfortunately, a lot of people don’t realise this and I’m often asked if I would share a template or an example for data governance policy that they can copy.
For a policy to be really useful (i.e. help you implement Data Governance successfully) it needs to be written with your organisation in mind, and consider the following:
· What is the scope of your data governance programme?
· What is it that your organization is going to do to manage its data better?
· What roles and responsibilities are you going to have to manage your data better?
· What kind of processes are you going to implement as a result of having data governance?
Now, the answers to these questions will not be the same for all companies and I can honestly say that every organization I have ever worked with has been unique in its approach to data governance.
I admit sometimes the differences are subtle, but for a policy to be valuable, these subtleties really do need to be addressed.
SO HOW DO YOU WRITE A GOOD DATA GOVERNANCE POLICY FROM SCRATCH?
If you are just starting to draft a data governance policy, then I recommend that you take the following approach:
Assemble key senior stakeholders in a room together and get them to tell you what principles they want to be included in the policy. What are the high-level things that you want to achieve by having a data governance framework and policy in place? This could be things like “all data has a data owner”, or it could be describing which data will have data quality standards and monitoring in place, or which data will have definitions in your data glossary.
For some clients, this list of principles has been as long as twelve and others as short as six.
I find that getting principles agreed is a lot easier than asking a group of people what they want to be included in a data governance policy. Plus the conversation around the principles will give you a really good idea about what they want to be covered in their policy. (And this additional information will also be important input when designing a more detailed data governance framework for your organization.)
Once you’ve drafted and circulated those principles for feedback, you should be able to make amendments and agree on a list of principles. With the principles agreed drafting your policy in accordance is fairly straightforward.
However, don’t make the mistake of believing that once it is drafted that everyone will immediately approve it because they already agreed the principles. Seeing the detail in black and white often gives rise to more questions, suggestions or changes from your key stakeholders.
At this point, I really have to emphasize that for data governance to be successful, you need the senior stakeholders engaged. So the answer is not to tell them they’re wrong, or to railroad them into accepting what you want to have in the data governance policy. If this framework is to be successful, it needs to have buy-in from everyone. So you need to take all input at this stage very seriously.
You can download a free version of the checklist here. (Don’t forget this is a high-level summary view, but everyone who attends either my face to face or online training gets a copy of the complete detailed checklist which I use when working with my clients.)