Data Strategy & Architecture Review

Every function has its own platform, and every platform has its own version of the truth. Reports that should agree don't. The AI plans assume data the organisation cannot actually produce. Spending on platforms continues; confidence in them does not.

This is not a technical conversation. It is a business one that requires technical depth to have correctly.

A fixed-scope review over four to eight weeks, depending on the size of the estate. Conversations with the people who produce the data and the people who depend on it — not just the people who manage the platforms. A review of the estate as it is: architecture, governance, ownership, and the organisational structures that determine whether data is genuinely useful at executive level.

A written assessment of what the organisation actually holds and what condition it is in. A target architecture direction without unnecessary complexity. A governance and ownership model that names who decides. And a sequenced set of decisions — what to fix first, what to stop buying, what becomes possible once the foundations hold.

Data stops being a permanent programme and starts becoming a capability. The executive team can answer three questions it currently cannot: what do we hold, who owns it, and what can we responsibly build on it.

Currently architecting an AI Data Mesh programme for UK policing custody data — one of the most demanding accountability environments in public sector technology. Enterprise architecture across public sector, health, finance, telecoms, and retail. Thirty-seven years in technology across seventeen sectors, from computer operator to Group CTO.