Work

I get stuck into messy transformation and leave it clearer.

Most days that means sitting between business, risk and engineering — making sure people are solving the same problem before anyone scales the wrong answer.

What I actually do

I turn unclear, high-risk programs into something you can run: shared definitions, explicit ownership, and delivery that doesn’t depend on heroics.

  • Make the real problem visible when everyone has a different version of it
  • Get business, risk and technology working from one model
  • Design data and reporting people will actually use
  • Cut rework by landing decisions early, not polishing slides late

Where I’m most useful

Call me when the work is messy, ownership is fuzzy, and buying another tool won’t fix it.

  • Systems need to talk to each other, but nobody agrees on the words
  • Data means different things in different teams
  • Stakeholders are optimising for different outcomes and don’t realise it
  • Delivery slows because decisions keep bouncing

How I work

I treat most “tech problems” as alignment problems wearing a technical costume. The job is to make assumptions speakable — then simplify before anyone scales the mess.

  • Ask the awkward question early
  • Write the decision down where everyone can see it
  • Name an owner, not a committee
  • Prefer a clear thin model over a clever thick one

Selected work

Click a case for more detail.

Enterprise transformation program

Big multi-org change: systems, suppliers, workforce transition, and reporting that had to hold.

Here’s what was actually hard: not the tech stack — the handoffs. Teams meant different things by the same field names, so onboarding and provisioning kept breaking in the seams.

  • Aligned definitions across systems and vendors
  • Designed the data flows for onboarding and provisioning
  • Supported large workforce and supplier transitions
  • Built reporting executives could follow without a translator

Result: fewer surprises in transition, clearer ownership, less operational risk.

Data governance and control uplift

Regulated environments where “we have platforms” still didn’t mean “we trust the numbers.”

The gap wasn’t missing software. It was missing visibility — who owned a definition, how data moved, and what you could safely decide from it.

  • Practical control frameworks teams could run, not shelfware
  • Clear ownership across business and technology
  • Better traceability and reporting
  • Closer alignment with risk and regulatory expectations

Data migration and reporting

Migrations that looked “done” on mappings — until business validation kept failing.

Mapping logic alone wasn’t enough. People were working from different assumptions about quality, so rework kept looping.

  • Business-driven validation and reconciliation
  • Clearer definitions and quality rules upfront
  • Structured reporting for control and visibility
  • Less rework by settling decisions before build scaled

Logging and monitoring platform

Cloud transformation needed observability people beyond engineering could understand.

The goal wasn’t dashboards for their own sake. It was making systems readable at scale — for ops, tech and business stakeholders.

  • Logging strategy tied to architecture principles
  • Views for technical and business audiences
  • Support for monitoring and incident response
  • Shared visibility across teams