Getting data owners engaged can be really hard.
It doesn't really matter what role you are in.
Maybe you are in a data leadership position, such as Head of Data or Chief Data Officer.
Maybe you have a wider role such as COO or CFO - with data as one of the many areas you are responsible for.
Or maybe you are an associate or manager in a data team, responsible for day-to-day data activity.
How many of the following do you experience?
- Emails which are ignored;
- Meetings which get cancelled, or where you have "no shows";
- Promises from colleagues to do things, which they never do; or
- Flat out refusal to engage.
These outcomes are not necessarily your fault, but they are going to reflect badly on you when it comes to your feedback reviews and annual appraisals.
In my first data governance role, I experienced a lot of this. Over time, I've learned to adapt my ways of working in order to get more effective outcomes.
That's what I'll be sharing in this article.
First some theory
The Data Community
Data ownership is a powerful concept with a lousy naming convention, so I’m going to use the term “Data Community” to cover Data Owners, Data Stewards and any other terms which might be in use in your organisation.
- Data Leaders are senior colleagues who sponsor the data governance activity but have less involvement day to day,
- Data Owners are responsible for data governance activity taking place.
- Data Stewards are typically subject matter experts and are operationally responsible for the data.
All the members of your data community must know
- What their role means, why they have it and what responsibilities they have.
- What activities they need to carry out under business as usual.
- When and how to escalate data issues.
These colleagues will all be carrying out their roles alongside their day jobs, so they will need support from a central data team to co-ordinate their data activities. This will be a small team relative to the size of the organisation - one or two data governance and data quality professionals can manage a data community of several dozen.
Some data governance tools include functionality to manage the data community. I would view this as a value-adding benefit beyond the standard data dictionary and data lineage features.
A Data Committee will comprise select members of your data community. I will deliberately leave that for another article because it must not be one of the first things you set up. The committee needs to have engaged members and an agenda with real decisions to make. You won’t have that until you’ve delivered the initial elements of the framework.
So Charles, how do I get them engaged?
We're going to need a different approach for the different citizens of our data community, so let's work through them.
Data Leaders
These are senior people in the organisation and they will have limited time and attention unless you are fortunate enough to have a Data Leader with a passion, or at least an interest, in getting the most out of data in the organisation.
You need to establish credibility and expertise. If you are relatively junior in the business, then you may need a more senior person to engage (e.g. a CDO to talk to a CFO) even if they are using your materials to drive the conversation.
If you are an experienced hire or a consultant, then you can establish credibilty through whom you have worked with in the past.
This conversation is all about securing the "tone at the top", demonstrating that your data activity will contribute to the goals of your Data Leader.
Although data can help with any and all of increased revenue, reduced costs or mitigated risks; it is highly likely that your Data Leader has a particular focus.
You will need to find this out:
- Do they sponsor a particular initiative?;
- Do they speak about a particular theme at "all hands" or "town hall" meetings; or
- Maybe you can find this out through conversations with individuals in their team.
Ultimately, you will want their buy in to what you are aiming to achieve, so that they cascade this to their direct reports.
That way, when you engage with your target Data Owners, they are already aware of what you need, and that their leader or senior stakeholder wants this to happen.
Data Owners
If the Data Leader engagement has worked, then our Data Owners are already warmed up, but that does not mean that they will immediately do everything you ask.
Data Owners are generally mid-management to senior management and will have a great deal of business activity as well as increasing amounts of responsibility. Let's consider some potential blockers to their carrying out the activities required for effective Data Governance:
- They are too busy
- They don't see the point
- It's not in their remit
Being too busy applies to most of us, but it's a reasonable challenge when asked to do more work, especially if it isn't part of their day job or role description.
What the "busy-ness" means is that your data activities are not priority. Some busy people will work ever-harder to get things done, or delegate where possible. Others will do the most pressing activities and de-prioritise the rest.
You need to ensure that data activites are seen as a priority. If they genuinely aren't, then it's on you as a data professional to look at your operating model and make changes to it.
It's also possible that this person has been asked to do something similar in the past, and something negative about that experience is dissuading them from engaging with you.
As with the Data Leader, the Data Owner needs to be convinced of the benefits of carrying out your data activities.
Think about how you can align your needs with their goals.
Communication and engagement are also key. You will not engage by sharing a standard "how to do data" task list with them. You do need to engage with the individual and the specific role that they have in the organisation. This often means that you get them up to speed through one-to-one meetings and conversations, rather than a training session.
When you've engaged your Data Owners, they will propose to you who the Data Stewards should be.
Data Stewards
If the data set is small or niche, then the owner may also be the steward; but in most cases the Data Steward is a subject matter expert (SME) who reports in to the Data Owner.
For organisations which outsource some of their activites, the steward may not be an employee of the organisation. This is fine in terms of having an SME to talk to, but at least one of your data owner and stewards should be in-house headcount.
Data Stewards live and breathe their data sets. They know where all the issues are and may have tried to solve them. Too often, they are unable to get buy in or support to deal with data issues and so give up.
With your Data Governance role, you have the ability to let the stewards vent, and share with you all their data concerns. These can be recorded and tracked in your Data Issue Log, which you can learn about in this post.
Data Stewards need to know what you want from them, and how to do it. Your job is to make it clear and obvious, with them being aware that you are open and available to them for help and support.
But they still ignore me!
This is perfectly normal. There will always be colleagues who are not (yet) willing to be engaged in data. This is not a failing on you!
(Actually, if no one is willing to engage, it might be a failing on you. Sorry about that. Try going back to the top of the article, or give me a call.)
Don't be too concerned about winning everyone over to your data paradise. Start with the ones who are willing and able to engage.
Work with them.
Support them.
Give them value.
If what you are doing is beneficial for the business (spoiler:and it is) then the rest will come over in their own time.
Takeaways
- Your data stakeholders include Data Leaders, Data Owners and Data Stewards.
- Each of them considers data from a different direction, so you need to tailor your asks and your messages.
About Datazed Associates
Datazed Associates helps organisations implement pragmatic and effective data governance.
- MVPs designed and delivered bespoke to your needs and pain points.
- Training and upskilling so your colleagues can continue delivering data governance and data quality activities.
- Training for data owners and data stewards.
- Data governance and data quality resource on an interim or part-time basis.
- Data governance and data quality tool / product selection.
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