The Mulago Foundation is a private foundation focused on the prospect of creating a better life for the world’s poor. Concentrated in rural settings in developing countries, the Foundation’s work is in four areas that contribute to this overarching goal — livelihoods, health, education, and conservation. The Mulago team looks for investment opportunities in promising products and services that address these high-priority problems. When it comes to health, the organization is particularly committed to improvements affecting the lives of mothers and children.
When it comes to making investments, one of the most important aspects of the Mulago approach is the ability of the organization to have a measurable impact. Leaders of the Foundation admit that they are “unabashedly obsessed with impact.” However, many of the organizations applying to Mulago for funding struggle with how to effectively measure their results. Too often, innovators and entrepreneurs either under- or overinvest in data collection. Those who underinvest in understanding their impact can find themselves spending far too much money to achieve too few results. Those who overinvest in gathering information can waste valuable time and resources tracking metrics that produce a flood of data but do little more than “clog the works.”
To help organizations meet this challenge, Mulago needed to develop an approach to the measurement of impact that was simple enough for an early-stage, resource-constrained organization to carry out, but rigorous and focused enough to mean something. This mini-case study describes the five-step framework that the Foundation developed.
This story is part of the Global Health Innovation Insight Series developed at Stanford University to shed light on the challenges that global health innovators face as they seek to develop and implement new products and services that address needs in resource-constrained settings.
Acknowledgements: We would like to thank Laura Hattendorf of the Mulago Foundation for her participation. This research was supported by the National Institutes of Health grant 1 RC4 TW008781-01.