This might seem to be a strange question. However, sometimes organizational patterns are so predominant that they exist in peoples’ heads or outspoken as a common desirable state even if you never made own experiences.
It makes it easier to re-form on the one hand, since no legacy needs to be removed or changed. On the other hand, how do you change an idea that no-one ever could prove good or bad?
I am currently working in a data governance bootstrap setup at a global manufacturing and services customer, and I am facing exactly that situation. Thoughts evolve around strong central control, better and more standardization, finally educating everyone so that data is eventually becoming “good”.
I have no age-long background in data management, but attended enough big-scale warehouse, data platform and analytics projects to know that “central control of everything” is not working. The data dynamic is simply to high in todays enterprise. You can’t know it all, not to speak of the systemic challenge of convincing employees worldwide to wait with what they urgently need to do until the central governance team has approved the next standard definition. Only to see that the new standard doesn’t match the own context. And why would I, working in an remote corner of corporate empire, should trust that guy from headquarters who wants to constrain my way of doing business?
Coming from big-data-in-motion scenarios and agile devops setups, I know how hard it is to implement the thought of letting go, of delegating real decision power to the agile teams — and then to deliver valuable outcomes, of course. Although everyone uses the “agile” label these days, not every enterprise framework with that tag in the title has really hit that mark.
Nonetheless, I did some research how agile and data governance could go together, and was very happy to find the book “Disrupting Data Governance — A Call to Action” of Laura Madsen who brings these two domains together in a very personal yet professional way. I have to admit it might be easier to digest for a DevOps person than a Data Professional, just because there is less rethinking involved, but that’s a perfect fit for me. Suddenly it all comes together, fits in my thought model of how governance should work, and I am happy I discovered that book just in time.
The core message is “radically democratize your data, and focus on promoting its use”. Proctection and control can be passed over to the IT Security and Compliance organization, and then we can start building an enabling governance instead of a prohibiting one.
It’s a long way from these first thoughts to enough data literacy to try an organizational approach like data mesh, but it is a good first step.
Title image shows Data Governance from a Midjourney bot point of view ;)