Many governance programs start with strong intent. Better quality, clearer ownership, safer use of sensitive information, and fewer disputes over which number is correct. Yet in practice, many programs stall. The latest Experian Data Governance Masterclass discussion highlighted that the root causes are often not technical. They are behavioural and organisational. In other words, governance stalls when it feels separate from how the business delivers outcomes.
Where momentum is commonly lost
Tim Moon, founder at the DGX Group, and Belinda Toniolo, a data governance leader from RACV called out several patterns that show up across industries:
- Governance is introduced too late, so it looks like a blocker rather than a partner.
- Teams are asked to do extra work without a clear benefit to their own goals.
- Governance tries to do everything at once, which slows delivery and reduces confidence.
- Accountability is unclear, so decisions change depending on who is asked.
- Data issues are treated as someone else’s problem, so ownership never sticks.
“If you are more than two levels away from your C level, start getting a seat at a higher table.”
– Tim Moon, Founder, DGX Group
One approach is to start with what the business already cares about
A consistent message from Kylie Kirkby, a data trust and governance leader from Bendigo and Adelaide Bank, was to begin with the customer, the operational outcome, or the business target. If you cannot connect governance to what a team is trying to achieve, you may find it more difficult to get engagement. Kylie framed this as switching roles: put yourself in the shoes of the person using the data. What are they trying to solve? What is getting in their way? Governance outcomes should follow the problem, not lead it.
“Put yourself in the position of your customer and solve problems for them, and then generate the data governance outcomes.”
– Kylie Kirkby, Head of Data Trust & Governance, Bendigo and Adelaide Bank
Data quality can be a useful conversation starter
Belinda shared a practical tip that resonated: use data quality as the quiet achiever. It is often the easiest entry point because it makes the issue visible. For example, if analysis shows a 20 percent failure rate in a dataset, the business impact can be immediate. You might not be able to market to those customers. That type of evidence raises eyebrows and can help open doors.
“Did you know that you have a 20 percent failure rate in this area, which means you cannot market to at least 20 percent of those customers?”
– Belinda Toniolo, Head of Data Governance, RACV
You may not need to win every battle
Tim made a pragmatic point about focus. If you have five areas to work with and only a small team, prioritise. Work with the groups where you can make progress, deliver a visible improvement, and circle back to others. This can help build momentum and reduces the risk of wasting time trying to convince people who are not ready.
“If you cannot find a common point, move on and go to the ones where you can make progress, and then circle back.”
– Tim Moon, Founder, DGX Group
Make prioritisation an executive responsibility
Andrew Andrews, regional advocate from the EDM Association emphasised that governance teams should not carry prioritisation alone. When everything is important, nothing is. A practical way to break the deadlock is to make executives allies in triage, because they are best placed to balance risk, reward, and investment.
“Make your executive sponsors your best friends in this process, because it is on the executive to help decipher where the work gets done.”
– Andrew Andrews, Regional Advocate A/NZ & Middle East, EDM Association
Build trust through visibility, not perfection
A great audience question asked what happens when data quality changes and trust is diluted. Belinda’s response was direct: you cannot prevent every issue, because changes happen across the business every day. What builds trust is how quickly you detect issues, how transparently you communicate them, and how effectively you support the fix. Kylie added an important nuance: trust does not mean everything is 100 percent accurate. It means people have visibility into the level of quality, so they can use the data appropriately.
“We do not consider trust to mean everything has to be 100 percent accurate. Visibility is the most important thing.”
– Kylie Kirkby, Head of Data Trust & Governance, Bendigo and Adelaide Bank
Governance programs stall when they are disconnected from business outcomes. They can regain momentum when they solve visible problems, create clarity on ownership, and build trust through transparency.
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