Why I built the lab

A lot of early service change thinking still happens through static decks, rough spreadsheets, and loosely structured conversations. Those formats are often good enough to begin a discussion, but they are not always good at showing which assumptions are really doing the work, where value is expected to come from, or how fragile a case might be under different conditions.

I built the lab to explore whether that earlier stage could be made more decision-useful: more explicit, more inspectable, and more testable before formal modelling or business case writing begins.

The platform brings together a set of lightweight interactive sandboxes for exploring how interventions and service changes might affect activity, cost, outcomes, and value under uncertainty.

Each sandbox focuses on a different intervention logic, but they share the same broad structure: define a population, estimate baseline risk or pressure, apply an intervention, model changes in events or activity, and test whether value appears under the chosen assumptions.

The aim is not to simulate the whole system in full detail. It is to create a more disciplined way to ask: what would need to be true for this idea to look worthwhile?

Before formal modelling, business cases, or evaluation plans are written, there is usually a messier stage where people are trying to work out whether an idea is plausible at all.

That is often where the most important questions should become clearer: what would need to be true for this to work, what is driving the value case, what looks fragile, and what should be validated next.

In practice, a lot of weak cases survive too long because the assumptions stay vague, while some strong ideas are never framed clearly enough to show where their value really sits. This project is an attempt to make that stage more rigorous.

These tools are illustrative only. They are not substitutes for formal economic evaluation, detailed service modelling, or local validation.

They are designed to support better framing, clearer thinking, and more transparent decision discussion — not to produce a final answer on their own.

The outputs should be treated as structured exploratory signals, not as decision-ready evidence.

I wanted the work to be visible, inspectable, and usable. That is why the project is open source, lightweight, and built around explicit assumptions rather than black-box outputs.

The point is partly methodological and partly practical. I am interested not just in individual models, but in how strategy, analytics, and economic reasoning might be turned into tools that people can actually interrogate.

In that sense, the lab is also a public working example of how I think: structured, assumption-led, product-oriented, and focused on making complex reasoning easier to inspect and use.

This is both a practical tool and a public portfolio project. It reflects my interest in health economics, decision support, product thinking, and applied analytics.

More broadly, it is an exploration of the space between strategy work, economic reasoning, and interactive products: not just analysing decisions after the fact, but helping structure them earlier and more clearly.

That is the direction I am increasingly interested in: work that combines analytical depth, real-world decision context, and usable tools.