Four years ago, in a fit of naivete, I decided to write a book about Data Governance. I wasn’t naïve about Data Governance – I was naïve about what that book would bring about. But, first, some background. After I left my corporate gig, I did a state-of-the-state in the data industry to get a broader understanding of where I left things when I went too heads-down (someday I’ll write about that). I found that Data Literacy was a magic pill (spoiler: it’s not) and Data Governance had not changed since Brandy and Monica were lyrically fighting about a boy. When I googled “Data Governance” I was shocked. The definition spanned an entire page – and there in that dark moment “Disrupting Data Governance” was borne.
Recently a client asked me what Data Governance would (or perhaps should) look like in 2025 and beyond. I started to think about that moment in 2018 and all that has transpired since then with Data Governance. I have always believed that history informs the future. And, after over two decades in data, I can tell you that what goes around comes around. The pendulum is busy swinging back and forth between centralized and decentralized functions of Data Management (from organizational structure and Data Architecture to Data Governance). I have busted out my Data Industry Tarot Cards: Let’s take a look at what the future holds, shall we?
As we continue to make progress in Data Governance, we will start to see more organizations adopt a modern approach to the management of data. We have to say goodbye to old-school methods of command and control. The data is too big and too fast for that. When I speak with organizations struggling to make that leap, their number one concern is regulations and compliance. Large fines are starting to make their way to the bottom line because of poor Data Management. As we see this shift, some organizations will double down on the command and control and, I think, at least for Data Governance, this is a mistake. No question there are big implications to doing this wrong but holding on tightly will just force a break in the weakest link. The strongest structures can bend, and so should your Data Governance framework.
Data Governance Trends
These are the trends I see will likely play out in the next 18 months as Data Governance ratchets up the top of the hype rollercoaster.
Data Governance Growth
Last week I saw an advertisement on LinkedIn Learning for a Data Governance course. Certainly, their algorithm picked up that I post a lot about Data Governance, but it is also a good indicator that it is an increasing topic of interest to people.
The hype will increase and probably reach a fever pitch around mid-2024. Driving a lot of that hype will be the big legislative changes that are happening across the globe, the marketing budgets of consulting firms and software vendors alike will increase, and organization-focused Data Literacy efforts will create demand for Data Governance. I recently read that Data Governance is predicted to be a $5.1 billion industry by 2025 – it won’t get there without hype.
Agile Data Governance
While there are lots of us out there advocating for an agile approach to DG, if the past is our best predictor, we will see this play out as the “less is more” version of agile. Rather than adopting the true principles of agile, many enterprises will see it as an opportunity to have less with more. It just doesn’t work that way. Yes, delivering interactive value requires small efforts – but several of them. The overall volume of the work doesn’t change, nor should the resources that are dedicated to it. The other destructive way I see agile concepts take hold is through agile dogma. I wish it were that simple, but there is no one right way to do anything. As a result, agile Data Governance will struggle to gain traction and demonstrate results.
Data Catalogs
The hype will drive an increase in purchases (not necessarily usage) of data catalogs. Great for vendors, bad for most DG efforts. The reality of the growth of Data Governance from $2-plus billion to over $5 billion will be built on purchases of software and services. Those kinds of numbers become a siren call for vendors. Rarely does buying software address the problem you’re having. Too often we get caught up in the checkbox activity of buying software and deploying it before we even know the problem we’re trying to solve. Data catalogs can help but only when you know what processes you have, who does them, when, and how often.
Data Protection
An increase on the focus of data protection will distract most Data Governance efforts to a significant extent. This is because the risk is real, in dollars. Fines are starting to get to the point where you can’t ignore these efforts, yet Data Governance is not where the accountability for data protection should be. I attended an information governance conference this week and in one amazing keynote Odia Kagan outlined the trends happening in the privacy world. It is, without question, a full-time job. Data protection will overwhelm the scope of Data Governance for many organizations.
Data Governance Dreams
I don’t really dream about Data Governance, but if I could re-write the next four years so we can see a big shift in Data Governance, this is what it would look like:
Data Governance Scope
Many years ago, there was a cartoon taped up to a cabinet that held all the supplies for the academic department where I was working (as a part-time lecturer). It said, “Let’s organize this thing and take all the fun out of it.” It applies to so many things and one of them is the scope of Data Governance efforts. If I could wave a magic wand and do only one thing to the whole of Data Governance programs throughout the world, this is what I would do – I would tighten up their scope.
You cannot achieve greatness if you’re trying to be everything to everybody. Yes, Data Governance has a lot on its shoulders, but there is something to be said for drawing a line in the sand, saying what is out of scope, and focusing with laser-like intensity on what is in scope. In my perfect future world, organizations will start to realize that Data Governance can deliver value if they are thoughtful about its mechanisms, so they start to modify scope for Data Governance efforts. Sounds like fun, doesn’t it?
Data Governance by Design
As organizations limit the scope of their DG efforts, they also start to realize that data is a by-product of process, and they begin to think differently about processes, iterative value, and agility. More impactfully, they start to think differently about how Data Governance is deployed. For too long, organizations placed an undue burden on functions like data stewardship. I’m not saying stewardship isn’t important, but as long as we place the emphasis on the few and not the many, the data, its use, and insights will not be broad enough to create a strong data culture.
Data democratization is often talked about, and I wrote about it in the book “Disrupting Data Governance.” It is for all my confessions of being a pessimistic an idealistic notion. But if I could set the tone for a new world order for Data Governance sharing not only the burdens of governance but the benefits of using the data and that comes as Data Governance by design. Embedding every aspect of Data Governance into your day to day so you don’t even know you’re “doing Data Governance.”
Data Governance Team and Organizational Structure
No matter how good your scope and processes, the work cannot be done without people that are well-aligned in the enterprise. Yet so often I see very small teams, usually one person, buried in IT. Not every organization needs a “Chief Data Governance Officer,” but every organization does need to think critically about the team structure and organize it in such a way that reduces barriers to the teams that set the guidelines and the teams that do the work.
In this new world I see Data Governance teams, small but mighty, aligned evenly with other data teams. They sit outside of your IT function and are peers with business teams. That positions them well to coordinate activities from both sides of the enterprise. Obviously, every organization is different but the key takeaway here is to elevate your data governance team (emphasis on team).
Data Quality
If there is a “shout it from the rooftops” moment in this re-framing of what Data Governance should be in the next four years, it is this: There is no Data Governance without Data Quality and there is no Data Quality without Data Governance. If you buy into this as a data practitioner but seem to struggle to sell it to your leaders, you have one thing in your corner: artificial intelligence. Everyone wants to do it but precious few can, or at least are able to correctly. Without excellent Data Quality you will not achieve artificial intelligence, no matter what any vendor will tell you. The AI algorithms that will launch your company to the stratosphere (or what your marketing team says anyway) require data, lots of data, to create those algorithms. Bad data = bad algorithms. Just ask Watson.
It is this simple. If you want to do anything in artificial intelligence you must dedicate efforts towards Data Quality.
Strong Data Management Operations
Perhaps the best thing we can do for Data Governance is to break it apart. Many of the functions of Data Governance have been ascribed there because there was nowhere else to put them. Stronger Data Management operational functions could solve some of these problems allowing Data Governance to focus exclusively on aspects that are governance functions.
Regardless of what happens in the future, Data Governance isn’t going anywhere. The question now is, how will organizations navigate the next several years as these distractions and hype get to a fever-pitch? Successful organizations will avoid the pitfalls of hype and focus on the value. Many others will not, but that’s OK. There is always next year.