ON-DEMAND VIDEO
Data governance is the part of the data conversation that most organizations know they need and few have actually built. In this session, Don Baker connects the master data foundations covered earlier in the Data Summit to the organizational structures and decision-making frameworks that make them sustainable over time. He provides a clear message: you don't need a large team or a perfect system to get started — but you do need to get started.
Key Insights:
- Governance doesn't require a dedicated data team — it requires nominated owners, clear rules about what can go in each field, and two intake forms you probably already have
- AI only creates value when decision-making is intentionally designed around it; deploying it without clean data and defined processes produces answers, not insights
- When organizations realize AI-driven productivity savings, reinvesting in critical thinking roles delivers more long-term value than headcount reduction
- A trade system is not a data warehouse or a data cleansing tool — expecting it to absorb and reconcile data it was never designed to handle is one of the most common and costly mistakes in CPG commercial operations
- Smaller organizations have a structural advantage in data governance: fewer approvals, fewer barriers, and the ability to try something and iterate without the organizational drag that slows larger companies down
- Progress over perfection is the only realistic path to a data foundation that actually supports better decisions
"Most organizations, even the biggest ones, don't have groups that are responsible for managing the connections of the data and the use of the business. And it's simple to do — it's harder to maintain than it is to set up."
Don Baker, The Partnering Group
