#92 Good Data Mesh Governance Through Empathy and Partnership – Interview w/ Jay Como and Elizabeth Calloway

Sign up for Data Mesh Understanding’s free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here

Episode list and links to all available episode transcripts here.

Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here.

Liz’s LinkedIn: https://www.linkedin.com/in/elizabeth-negrotti-calloway/

Jay’s LinkedIn: https://www.linkedin.com/in/jaycomoiii/

In this episode, Scott interviewed Jay Como, Head of Finance Data, and Elizabeth (Liz) Calloway, Director of Finance Data Products at Silicon Valley Bank. To be clear, they were only representing their own views and experiences.

Some key takeaways/thoughts from the conversation:

  1. The governance team should “wear them down with empathy.” Take the time to share your context, learn their context, make them feel seen and heard. That will get them to see you as a partner and good governance is truly about partnering, not mandating or being a gate/hurdle to get past.
  2. Great governance is the pathway to great data. Great data leads to great decisions which lead to great outcomes. Share that path to great outcomes so people can see a clear answer to “why are we doing this?” Governance isn’t just risk mitigation, it can be a significant – if almost always hidden/secret – value driver.
  3. To drive governance buy-in from data producers, again, lead with empathy. Let them in on the “why” – why does this matter? What is the business value? How can this benefit them?
  4. “Help me help you” is a good approach to talking to internal teams about data governance. You are there to drive value for them, take work off their plates when appropriate.
  5. You can further drive buy-in through helping teams get to quick wins. While the long-term is obviously important, incremental value-add is better than a big bang approach.
  6. Provide a constant stream of value, including executing on where you are helping, will drive teams to want to work with the central governance function. Drive value and the buy-in naturally comes with it.
  7. Good data governance is necessary to avoid fees, fines, and the huge revenue/business impact bad data can have. But don’t use those as a boogeyman, don’t use fear to sell good data governance.
  8. It’s easy for a centralized governance team to become a bottleneck. Focus on not solving all the problems for teams but being there to help when they need it. You are the backstop, not the stop sign. Be the support, not the roadblock.
  9. To prevent governance in general from being a bottleneck, you must have flexibility and pragmatism. If exceptions to requirements are necessary, then those exceptions are often a valid response to other constraints/pressures. But be very explicit about the reason and type of exceptions and also very explicit about the expectations for if/when those exceptions will be remediated.
  10. Good governance is about incremental improvements, not trying to do everything as a big bang. Set expectations, move forward. Fix for today and prevent the same issue in the future.

Jay started the discussion talking about the concept of governance-as-a-service – in other words, providing a service to internal stakeholders instead of a mandate of comply or else. And while governance may not be the most “sexy” aspect of data, it certainly is one of the most crucial.

For Jay, without good governance, data is often not nearly as correct and clean as it could be so internal stakeholders aren’t making as good of decisions as they could. He laid out a simple framework of great data leads to great decisions which lead to great outcomes. There obviously is a law of diminishing returns but find the line where the juice isn’t worth the squeeze.

As for driving buy-in internally, Jay recommends to “wear people down with empathy”. And be ready to repeat yourself, maybe with small variations until you find what resonates, to be able to make change. You don’t often win them over with a single conversation or presentation.

Liz started off by pointing to the fact that it’s quite easy to drive buy-in that good data governance provides value for data consumers. It’s driving that buy-in upstream that becomes a lot more difficult…

To get moving on that buy-in, Liz recommends flipping the script and changing the narrative and dialogue. It isn’t driving a mandate, it’s talking about what benefit this has to them and the organization. It’s not governance for the sake of it! That way, they are more open to guiding or shepherding them towards providing good data. So in all your communications, lead with empathy.

Jay discussed how they are taking on the really hard parts of governance from their business partners. That way, those business counterparts will see the governance team as a legitimate partner, not a dreaded gatekeeper. Provide them with a constant stream of valuable insight and work – decks, plans/roadmaps, etc. – and then execute on what you say you will. That will drive buy-in.

Jay also mentioned that acting like you are a highly regulated entity even if you aren’t will set you down a good path to understanding and protecting your data. It’s an investment but a big risk mitigation and potential value driver.

Liz talked about while governance is not a direct revenue stream – even if they add value to data, driving better outcomes – it is often also a major cost avoidance. Obviously for a highly regulated industry like banking, that can mean fees and fines. But many people are also pointing things like Unity Software’s $110 million negative revenue impact from ingesting bad data, announced in mid May 2022.

It’s not about driving fear for Liz. And talking about how bad data has a negative impact on the business feels basic or a bit obvious for her. But having the conversations, showing how better governance drives better outcomes, executing on the tough parts the governance team takes on, all that will drive buy-in.

Scott asked about how, if the governance team is taking work on from other teams, do they avoid becoming a bottleneck. Jay first off acknowledged it’s a real possibility and one to specifically try to avoid. One thing that has worked for him historically is to play a neutral party and extract the context so both sides understand the other instead of battle each other. Make everyone feel seen and heard rather than solving all the problems for them. But fixing issues where possible, not so teams are reliant on you but see you as the partner, has worked well for him to date.

Jay discussed a few ways to prevent general bottlenecks in the governance process. In data, we often take on tech debt unintentionally or sweep it under the rug. But Jay recommends being flexible with requirements BUT calling out very specifically when, why, and how you are waiving requirements in that specific situation. It’s not being lax, it’s being pragmatic that not everything has to be perfect as long as all parties are aware and there is a mitigation plan in place. Being explicit about exceptions and expectations means you can move much quicker. Be flexible but realistic.

Speaking of being realistic, Liz talked about how there is no magic wand to suddenly fix governance challenges. And things are never going to be in a perfect state. Good governance is about incremental improvements, providing roadmaps and executing on the roadmaps as a partner – and make your business partners feel heard along the way. Things change and being flexible is crucial. How can you fix the problem of today and then put processes in place to prevent that problem in the future? Nothing is black and white.

Jay quoted Jerry McGuire, “Help me help you!” The governance team is all about enabling other teams to drive value and prevent issues. So drive a perception of being the helpful team. It’s also quite difficult to get “your” plan implemented – it’s much easier to get “our” plan implemented.

In the new school data governance, as opposed to the old school, Jay believes we need to drive people towards caring about data governance at all. It can be a value-add, not just a hassle. Both Liz and Jay emphasized you can prove data governance as a value-add by helping teams get to quick wins – show the value. You want to balance that out with some long-term wins, not only the short, but it’s still another endorsement for driving to quick wins as Joe Reis emphasized in his episode.

Jay and Liz wrapped up by talking about the need for a great team and to drive forward with empathy. You need to work as partners with your internal constituents. Take some work off their plate to make things easier for them so you can drive more value together.

Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him on LinkedIn: https://www.linkedin.com/in/scotthirleman/

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

Leave a Reply

Your email address will not be published. Required fields are marked *