I’m proud of this one.

Working with the British Heart Foundation has been one of the most impactful engagements I have been involved in at Simpson Associates. What started as a brand new data science environment in Databricks scaled into an enterprise-grade platform transforming data across everything from medical research to finance, retail, volunteers, and customers.

The Numbers

A few headline stats:

• Coding and compiling time reduced from 3 days to under 6 minutes. That is not a typo.
• Advanced analysis of over 124,000 people trained in CPR through data-driven targeting of the RevivR app.
• A 1.5 billion-row prescription dataset integrated and queryable in minutes with Genie.

What Made It Work

The BHF engagement was not just a technology deployment — it was a people-centric programme. Simpson Associates had staff on the ground supporting and enabling BHF’s own team alongside external partners. That meant managing the platform, supporting delivery of outcomes, and ensuring knowledge transfer happened throughout.

The breadth of the platform matters here too. Because Databricks covers the full spectrum — from raw ingestion through to AI-powered analytics — BHF could consolidate tooling rather than maintain a patchwork of systems. The 1.5 billion-row prescription dataset being queryable in minutes rather than days is a direct result of that architectural consistency.

Why This Matters Beyond BHF

The lesson from this engagement is one I take into every customer conversation: value engineering has to come before technology selection. The reason that compile time dropped so dramatically is because we understood the problem first — slow, manual, brittle pipelines — and designed a solution around fixing it. The technology was the vehicle, not the destination.

If you’re in a similar position — running legacy pipelines, struggling with scale, or trying to unlock the analytical potential of your data — I’d genuinely love to have a conversation. Drop me a message on LinkedIn.