Most impact investors articulate a Theory of Change (ToC) when entering a sector or making an investment.
The logic usually looks something like this:
Investment → business growth → more services delivered → improved lives.
But in practice, many ToCs remain largely static once they are written. They help explain intent, but they are rarely revisited or stress-tested using outcome data.
Welfare metrics such as DALYs averted could help change that.
Here's how:
1️⃣ Welfare Metrics Force the Causal Chain to Be Explicit
A theory of change often contains several implicit assumptions:
• that services reach the intended population
• that services are delivered with adequate quality
• that utilisation leads to meaningful health improvements.
Estimating welfare outcomes requires each step of this chain to be examined.
2️⃣ It Helps Identify Weak Links in the Impact Pathway
Welfare modelling often reveals where the impact pathway breaks down. For example:
An investor may assume that expanding diagnostic capacity will significantly reduce mortality. But modelling might show that the welfare gains are limited because:
• treatment adherence is low
• referral systems are weak
• patients present late.
In this sense, welfare measurement becomes a diagnostic tool for the theory of change itself.
3️⃣ It Encourages Iteration, Not Just Reporting
Impact reporting often focuses on demonstrating success to limited partners.
But welfare analysis can also support learning.
Organisations such as GiveWell routinely revisit and revise their cost-effectiveness models as new evidence emerges. Assumptions are updated, interventions are re-evaluated, and priorities shift accordingly.
A similar mindset could strengthen impact investing.
