What are we even trying to solve with Data Governance?
When you start out on a Data Governance journey, you often get The Dreaded Question.
It tends to come in variations such as “Why are we doing this thing?”, or “Should we really be spending our time and resources on this”, or even “This is another example that you guys just don’t understand what is important for the business” (which is technically more of a statement than a question).
These questions often come from powerful men and women, whose time feels much more valuable than yours, and they can be very intimidating. When this happens, you need a good answer.
Here are the five key reasons for Data Governance I always bring up:
Drive transparency: Getting data aligned and prepared for BI and analytics is a tale as old as time, and for many out there it is still the main headache that Data Governance needs to solve. Misaligned data just makes any kind of analysis difficult and time consuming, and it requires a ton of manual effort. And don’t even get me started on what this means for all the companies that are trying to find their feet in AI.
Enable digitalization: In the past, if someone emailed you an order (or maybe even faxed it), it did not matter that there was a customer service person, who had to spend anywhere between 15 minutes and a few hours putting together an offer. In an eCommerce setting that is simply not possible anymore. Instead, digital transformations require tight data and process integration - and the data needs to be aligned!
Reduce IT complexity & costs: I’m not saying that the ever-increasing technical complexity from misaligned data is the reason that so many CIOs are bald, but the indications are there. The fact is that constantly having to compensate for data is a sure-fire way to ensure that your IT costs go up, and that your projects constantly get delayed
Reduce FTE overhead: This one has many names; “optimization”, “improving the colleague experience”, “working smarter, not harder”. However, you want to put it, when everyone has their own little data silo - whether they be analytical or operational - the wheel is constantly being re-invented. And most decision makers tend to agree that tying up tons of people doing mostly similar but slightly different things, is neither effective nor efficient.
Prevent fragmentation: Every once in a while, I clean out my attic. And every time, I promise myself that I am going to be more thoughtful about not throwing stuff up there. But of course, I never am. It is the same with data. The main reason that Data Governance is not a project is that the roles, responsibilities and ways of working need to be anchored throughout the organization. Without Data Governance, data alignment and ownership will fracture over time - just like the cleanliness of my attic.
Those are my five key takeaways for Data Governance. Depending on the situation and context I switch it up a bit, but this usually does a pretty good job of answering “the question”.
Let me know if these correspond with the story you tell about Data Governance. And extra points if you can spot the one, I intentionally left out.