We make uncertainty visible, quantified, and actionable.

I have spent my career building decision systems for industries that resist simple models: oil and gas well planning, demersal fish market forecasting, energy portfolio optimisation. These are domains where uncertainty is structural, data is often sparse or unreliable, and the cost of a bad decision is real.

My background spans quantitative modelling, system architecture, and product development. I have worked in data science, engineering leadership, and as a technical founder — which means I can operate at the level of statistical methods, software systems, and organisational decision processes, and understand how they connect (or fail to connect).

42Analytics exists because I kept encountering the same problem: organisations with significant data assets and intelligent people, making worse decisions than the data should allow — because the tools they had were designed for insight production rather than decision support. I built the practice to close that gap.

We work with a small number of clients at a time, deliberately. The work we do is not scalable in the traditional sense — it requires deep understanding of the decision structure, the data environment, and the organisational context before any useful system can be designed.

Engagements typically start with a decision audit: mapping the decisions that actually matter in the organisation, what information would genuinely change those decisions, and what the current analytics stack does and does not provide. This frequently reveals that the problem is different from what was initially described.

We then design and build systems that address the actual problem, not the stated one. Outputs range from standalone tools to integrations with existing infrastructure, depending on what will actually be used.