Build an Insight Engine

This week I’m attending a strategic tactic workshop — the kind where cross‑functional teams wrestle with evidence, pressure‑test assumptions, and try to turn inputs into something that actually informs action. And quite often we’ll be looking for the nuggets or “insights” among lots and lots of data points.

We don’t have an insight problem.

We have an insight engine problem.

Even in rare disease I find that teams are drowning in data but starved of clarity. We generate observations, dashboards, trackers, and “insight” slides… yet the strategic signal often gets lost in the operational noise.

Across organisations, the same capability gaps show up:

• Decisions aren’t explicitly defined, so insight work drifts toward activity rather than impact.

• Evidence standards vary wildly, making synthesis slow and inconsistent.

• Teams optimise for reporting, not for strategic escalation.

• Insights arrive too late, or in formats that don’t influence planning cycles.

• No one owns the engine, so everyone owns a piece of the chaos.

Pharma doesn’t need more data.

It needs systems that turn data into strategic advantage — to consistently, repeatably, and at the speed decisions are made.

It’s partly because of this that I wrote my own guide - a primer - on insight generation to outline what businesses and brand teams actually need to do to build an insight engine that works.