DGX Monthly: Can you explain what your DG team does in plain English?

DGX Monthly – September

Hi everyone,

Chad Barendse here, co-founder of DGX, and welcome to the September newsletter.

Quieter month after the summit, which has given me more time to think about where this discipline is heading.

The old shape of data governance was compliance. Policy libraries, steering committees, maturity assessments, a register nobody opened twice. The new shape is engineered. Controls in the pipeline, definitions in the platform, access decided by a system rather than an email, AI in scope whether you planned for it or not. Most teams are stuck between the two, running the old operating model while being asked for the new outcomes.

Somewhere in that we lost the ability to say plainly what we do and why we’re here.

So three questions I have been asking myself lately is. Why are we here? What does the team actually do? And what happens to the organisation if we’re not here at all?

Try answering those in front of people who don’t work in data. We fall in the trap of explaining what we implement not the outcomes we are trying achieve.

Part of it is the language. “Unmitigated exposure in the control environment” instead of “we could lose customer data”. The first one isn’t more rigorous, it’s just harder to argue with. Plain English makes you accountable for what you’re actually claiming.

Here’s where I’ve landed. Four outcomes.
→ We protect data, so we don’t have a breach.
Find where the sensitive data lives, work out who can reach it, take away the access nobody needs. Most organisations can’t answer the middle one honestly.

→ We make data fit for purpose, so customers aren’t impacted.
When the data’s wrong the customer wears it. Wrong balance, wrong letter, wrong decision on their claim. Quality checks on the data behind those decisions, not on everything.

→ We make data discoverable and understood.
Two teams reporting different numbers to the same executive is a governance problem, not a reporting one. One agreed definition of a customer, an active account, a complaint, and the lineage to back it up. Shared meaning, not a bigger catalogue.

→ We make sure data and AI are used responsibly.
Know what a model was trained on, know what it influences, and make sure someone’s name sits against the outcome.

So now I’ll turn it back to you. Can you say what your team does in plain English, and what outcomes you’re delivering for your organisation, without reaching for a 20 slide deck?

Thanks for reading.

Meme of the Month

Credit: Chad Barendse

Award Winner Spotlight: Brad Hill, Rising Star in Data Governance

We caught up with Brad Hill, Data Enablement Analyst at Aware Super and winner of the Rising Star in Data Governance award at ADG Summit 2026, to hear more about his work and where he sees the industry heading.

A few highlights from the conversation:

On his role: “My focus is on understanding how Data Governance can help the broader business improve in three key areas: Auditability, Continuity and Trust.”

On making an impact in governance: “Be curious, keep an open mind, and invest time in understanding what the people around you do every day. You don’t need to know everything, but you do need to know the people who do.”

On where governance is heading: “We don’t need to reinvent the wheel. The foundational principles remain the same. What is changing is our ability to harness the growing volume of metadata and operational information around us.”

👉 Read the full spotlight

Congratulations again, Brad.