To successfully implement managed self-service business intelligence at any non-trivial scale, you need data governance. To build and nurture a successful data culture, data governance is an essential part of the success.
Despite this fact, and despite the obvious value that data governance can provide, data governance has a bad reputation. Many people – likely including the leaders you need to be your ally if you’re working to build a data culture in your organization – have had negative experiences with data governance in the past, and now react negatively when the topic of data governance is raised.
They now treat data governance as a four-letter word.
Stakeholders’ past experiences can make your job much more difficult as you attempt to work with them to enable managed self-service within an organization. Governance is what they need. Governance is what you want to help them achieve. When you say “governance” you’re thinking about erecting guardrails rather than roadblocks, about making it easier for people to do the right things when working with the right data… but that’s not what they hear.
The label shouldn’t really matter – but it does.
Data governance, and building a data culture in general, is as much about people as it is about processes and technology, and that means effective communication is key. Effective communication requires a shared vocabulary, and a shared understanding of the meaning of key words.
It may be time to think about rebranding. Not unlike how a corporation with a reputation for all the wrong things might change its name in an effort to leave all those negative connotations behind without really changing its ways, maybe we need to rebrand data governance… at least some of the time.
My idea when starting to write this post was to propose “Data Culture Enablement” as the more friendly label, but as I was searching around for related content, I found that Dan Sutherland of EY proposed something simpler: Data Enablement.
Dan’s post is coming at things from a different angle, but it’s clear he has a similar goal in mind: “emphasiz[ing] empowerment, innovation and instant business value consumption.”
While I was searching, I found a few more interesting articles out there – they’re all well worth your time to read if you’ve made it this far:
- R. Danes at SiliconANGLE highlights the value of data governance beyond the classic “thou shalt not” use cases. In this article she quotes the group chief data officer at ING Bank N.V. who says “Governance is just a horrible word,” and highlights how “People have really negative connotations associated with it.” ING may be the most mature organization I’ve ever engaged with in the context of data governance and metadata, so this is a fascinating quote from a very well-informed source.
- Ashish Haruray, a Data Protection and Controls SME at AXA XL highlights how the term data governance “can have negative connotations [and] may be met with resistance by executives and leaders who cannot relate to its true meaning.”
- Randy Bean and Thomas Davenport from Harvard Business Review have researched how companies are failing in their efforts to become data-driven, and cite business leaders who recommend “trying to implement agile methods in key programs, while avoiding terms like ‘data governance’ that have a negative connotation for many executives.”
People think governance is about somebody with a big stick but it’s not. It’s about getting people to communicate and talk about their data and being in a position to ask for what they need with their data. The people on the other end need to understand they have a responsibility to meet that requirement if possible.
But when asked explicitly about coming up with a new term, she replied “For a while, I toyed with the idea of starting a campaign to re-name it but I didn’t think it was worth adding to the confusion surrounding the term by coming up with another title.”
She’s probably right.
But because of the negative connotations that the term “data governance” carries today, we should all exercise care when we use it. We should be careful to ensure that the meaning we’re trying to convey is clearly received – regardless of the terms we’re using.
That feels like an ending, but I’m not done. I want to close with story.
Five years ago I was working on a data governance product, and as part of that work I talked with lots of customers and with Microsoft customer-facing employees. In those conversations I frequently heard people say things to the effect of “don’t use the ‘G word’ when you’re meeting with this leader – if you say ‘governance’ he’s going to stop listening and the meeting will end.” This didn’t happen in every conversation, but it happened in many.
Last month I hosted a multi-day NDA event with senior technical and business stakeholders responsible for adopting and implementing Power BI and Azure Synapse at some of the biggest companies in the world. The event was focused on Power BI and Synapse, but the customer representatives kept bringing up the importance of data governance in session after session, and conversation after conversation. It was like night and day compared to the conversations I had when I was trying to get people to care about governance.
Has the world changed that much, or am I just talking to different people now?
I think it’s probably a bit of both. The world has definitely changed – more and more organizations are recognizing the value and importance of data and are increasingly treating data as an asset that needs to be managed and curated. But these days I also engage mostly with organizations that are atypically mature, and are further along on their data culture journey than most. With this selection bias, it’s probably not surprising that I’m having a different experience.
I’ll close with a question and a thought: Who are you talking to about data governance?
Before you begin any data governance conversation, do your best to have a clear understanding of your audience and your goals in communicating with them. No matter what terms you use, it will make all the difference.
 I’m always terrified that I will post something that someone else has already posted. On more than one occasion I’ve completed and published a new post, only to find out that I had written the same thing months or years earlier on this blog. Sigh.
 I’m pretty sure I’ve referenced this post before. It’s good enough to reference again. You should read it again.
 Thankfully we had also included some key folks from the Azure Purview team as well.