The situation
Twenty markets, four thousand potential users, and no agreement on what counted as a customer. Every market could answer its own questions and none of the answers reconciled.
The issue was not a shortage of dashboards
The organisation already had capable analysts, valuable data and strong local use cases. The constraint was the distance between them. Each market had built its own definitions, so the same question produced different numbers depending on who ran it, and reconciling those differences consumed more analyst time than producing them had.
That made this an ownership problem before it was a technical one. The early work was unglamorous: agreeing what a customer, an account and a territory meant, and deciding who had the authority to change those definitions later.
A catalogue people chose to use
The platform paired governed data products with a self-serve catalogue, so an analyst could find a certified dataset, see who owned it and understand what it excluded before building on top of it. Certification was visible rather than implied.
Adoption grew roughly 80% year on year without being mandated. That mattered more than the raw user count: the pull came from the catalogue being faster than rebuilding a dataset locally, which is the only durable reason anyone adopts a standard.
What made scale possible
A partner network and a structured training programme moved markets from consuming outputs to owning data products of their own. Governance worked as an accelerant here — approved patterns meant a market team could ship without a bespoke negotiation each time.
The programme ran multi-year in a regulated, data-sensitive environment. The lasting result was not the platform but the operating model around it: named owners, shared definitions and a route for local teams to extend the system without breaking it.