Data Governance is seeing an inflection point as AI presents unique opportunities to automate mundane tasks like data documentation, manual tagging, etc. Despite the opportunities, many leaders still report that data governance is hard. So curious, how is Data Governance changing for most strategic data management leaders? I'd love to hear from peers if anyone has been able to get measurable ROI from doing data governance, not just productivity gains like finding data more easily.
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Well said, <mention id="6847cd4558184f0001239f76" displayname="Dhiraj Saxena"></mention>! You’re spot on about AI’s role and the importance of building trust in the data used for projects, initiatives, or any business outcomes. Another major challenge for today’s strategic data leaders is connecting data challenges to business outcomes, a labor-intensive exercise, and not all leaders make it to see the ROI results.
I recommend checking out Hung le Hong's research as it really helped me deliver the ROI. By building a product where we monitor all our dashboards we can get ahead and identify folks who have been downloading data for example (so being more proactive instead of reactive). I believe educating the business and then demonstrating both your tangible and intangible benefits. It can be done! Good luck!
Thanks, <mention id="56efd103ee986da96f161ee9" displayname="Nichola Hopkins"></mention>. I’ll definitely check out Hung le Hong’s research. I like your approach of monitoring dashboards to proactively identify usage patterns instead of being reactive, and your emphasis on educating the business, communication is key. I also find that strategic data leaders need to work closely with training and enablement teams to build a full plan for improving data literacy. Just to clarify, are you taking a data product approach, designing with a target audience, problem statement, and value proposition in mind?
Hey Kash! While I was an analyst I spoke with literally thousands of data leaders - and my #1 recommendation, without question, was 'find a way to quantify the business value of your efforts'. We know this is the best way to ensure a continued focus on governance, to secure data stewardship support, to continue to receive funding, and on, and on. Yet, even though I recommended this hundreds and hundreds of times, I can count on one hand the number of data leaders who actually followed my advice. Amazingly, many still believe that quantifying the value governance is impossible - which is a complete myth.
Well said, Malcolm!! My upvote for you, couldn’t agree more. Being able to demonstrate ROI requires some thought and a framework to capture those quick wins. Often, these are communicated via slides but quickly forgotten. It’s almost like building your “quick win catalog” to list everything data governance brings to the organization, whether related to revenue, cost, or risk.<br><br>I’m hopeful that AI can change this. There’s an opportunity to automate data enrichment (probably through machine learning), making it easier to classify and tag data, suggest meaningful definitions, or provide business context based on semantics.<br><br>I’m curious if any peers here have made progress in capturing this type of value.
I am experiencing data governance should complement AI adaption. AI could be use the understand the multiple context around the data, however the demand is to build the trust for the data in use. This is where the challenge is and I see an opportunity for measurable ROI.