I highly recommend the use of a DG Framework to help your stakeholders understand the full scope of what it means to have Data Governance. Otherwise some people have a misunderstanding that this is just a group that meets 2x/month and solves some data problems. However, since you asked for top 3, here are some critical things to understand before even going down the path of conducting an assessment:
1. Do you have a C-level executive sponsor that is fully on board with the need for Data Governance (the business drivers/reasons) and understands their responsibilities as the executive sponsor?
2. Do you or can you have a funding mechanism in place to support data governance activities?
3. Will the organization culture be receptive to DG efforts? What are the primary barriers? What will need to be addressed or overcome to be successful?
I like Alissa's response. I would also add asking about what is being governed. For instance, some people want to govern all capabilities of data management. Some want to start with one capability (e.g., data quality, metadata) and grow from there. You need to start data governance with a specific purpose, not because it's something other people are doing.
DG is all about people process and tools related to the data.
Alissa mentions a sponsor. It's Critical to have one!
But, you may not be at that stage yet for a full blown DG initiative. You may be focused on one small area for whom you are doing an assessment. If you are doing a full blown DG initiative, the need for a sponsor would certainly come out of the assessment.
I like to start with the basics.
Who is doing what - with what data?
(this of course expands into a multitude of additional questions... which teams? How are they doing whatever they are doing? Which data elements do you need to be focused on?).
Who is making decisions on what is supposed to be done with the data?
(this also expands to a multitude of additional questions... are they the right people? are they the right decisions? when do they know they need to make a decision? are they tracking any of the decisions made).
What data is the important data?
(again - expands to more questions - Which are the Critical Data elements? Which need to be protected (PHI or PII)? Do we have a process in place TO protect them? Why is it important? To whom is it important? Do we know who should see the data and who should not?)
I know - you asked for 3 questions...and I gave you about 16.... It takes more than 3 licks to get to the center of a tootsie roll pop (though quite a lot more than 16).
What you're always trying to do is match skills to business goals. This includes data governance. I always ask about business goals. I want to tie data governance into business initiatives so that's another question.
I love your tootsie roll pop analogy! Very fun and very true. We always talk about the layers of an onion but tootsie roll pops are definitely more fun. Great guidance as well.
Robert S Seiner
The top three questions I use for a DG assessment against industry best practice are:
1. What are we presently doing that supports this and can be leveraged to support achieving this best practice?
2. Where is there opportunity to improve related to this best practice?
3. What is the gap between our present practices and what we define as best practice and what risks do we run into if we do not fully achieve this best practice?
These questions all assume that you have best practice defined for your organization. Visit TDAN.com and do a search on "best practice" and perhaps you will find additional questions there. Thanks.
Robert S Seiner[All DATAVERSITY Members] @ Apr 16, 2020 - 03:22 PM (America/Eastern)
I always ask what their overall Data Strategy is - what data is critical to govern, how do they need to govern it and who should be responsible.
Robert S Seiner
Two questions that I ask often are:
What can't you do, that you would like to do (or need to do), because you don't have the data to support doing it? This can include make decisions, perform analytics, protect data, trust and have confidence in the data ...
What could you do better, if you had better data to do it? This could include produce better reports in more a timely manner, spend time efficiently and effectively, get answers to burning (or just operational) questions ...
You get the idea ... let me know if this is helpful.
To the great list of responses, I would add a tip from a consultant friend - the fastest way to figure out which conversation to have is to ask if they see data as an asset or a cost.
If they see data as an asset, the conversation revolves around capabilities, priorities and budget (and things like change velocity, tools, etc).
OTOH, if they see data as an expense to be minimized, then the conversation changes drastically - you have to justify the expense <in concrete terms> for why you should create and fund a governance program. There are lots of ways to justify the expense, but some insight into existing pain points and strategic goals (assuming they're documented and communicated) at multiple levels of management will enable you to craft your argument in a targeted manner.
You won't get high level sponsorship if they can't justify the expense. Quantifiable, measurable goals and milestones that help reinforce your case are important. Depending on the relative maturity of the organization, you may have to take baby, baby steps in order to fulfill that promise.
This is very helpful and very much in the direction I was going. Thanks so much!
Where's the pain? Who feels it? Does the boss care? (It's a twist on the basic change management protocol.)
I agree with Alissa's comment to select a data governance framework (DAMA-DMBOK, ARMA-IGBOK, …). It will provide a structure for understanding strengths and weaknesses. It's like a keel keeping you on course. The parameters of your governance framework might serve to help frame the questions.
I also agree that it's important to identify the objectives by understanding current pain points you want to address. And it may help the people who don't think about data everyday understand the problem.
I also like the approach Jeanne Ross et al took in Enterprise Architecture as Strategy: understand what the organization MUST be able to do, the data that supports those activities, and the operating model needed.