Client question 02
What a technology, service, or programme actually changes, for whom, and through what pathway. Measured directly with the people it is meant to serve, and reported honestly.
Most writing about a new technology or programme arrives ahead of the evidence. Measurement closes that gap: it puts honest questions to the people the work is meant to serve, from the human side first, independently of the intervention. The Lab reports what the evidence actually says, including when it is inconvenient.
Measuring Change is two connected disciplines. The first is field research, the primary contact with the people a transition affects. The second is impact measurement, the frame that turns those conversations and numbers into a defensible reading of what changed. This page carries both.
The Lab works in settings that defeat conventional research: low-connectivity, multilingual, informal, dispersed. These are also the settings where bad evidence does the most damage. Running research well here demands researchers who speak the language, know the place, and understand the working lives of the people they talk to.
Grounded in real engagements: electric transport in Nairobi (Kenyan e-mobility case), decentralised clean energy in Lombok (Pyropower), water transparency in Nairobi (MiMaji), and five years of sustained fieldwork in Kenya. We do not parachute in. We work through people already part of the context.
Most research fails in one of two directions: too elaborate to repeat affordably, or too thin to tell you anything new. Our standard is the middle: structured enough to compare, rich enough to matter. For the distinction between qualitative and quantitative, and why the Lab leads from the qualitative and quantifies around it, see Qualitative vs Quantitative.
Every study sits inside the same measurement frame, so a result in one context can be read against another and a one-off study becomes a trajectory over time.
Who is actually being reached, and who is being missed. The most flattering-looking programme can be reaching the wrong people, or the same people repeatedly, or leaving the hardest-to-reach unmoved. We measure coverage, inclusion, and the gap between the population an intervention was designed for and the one it is landing with. Distribution is central, not a footnote.
How much things actually change for those reached. Beyond headline satisfaction: the magnitude of change in income, time, health, opportunity, or whatever the intervention is aiming at. And how meaningful the change is in the respondent's own terms, not in the language of the funder's logframe.
What it is like to be on the receiving end. Satisfaction, friction, unintended effects, and the qualitative texture that numbers alone cannot carry. What would the user change first? What would they never give up? The answers to those questions are usually where the useful insight lives.
Reach, depth, and experience read together give a project a picture of impact that a self-report or an output count cannot: whether the intervention landed with the right people, whether it made a material difference, and whether the people on the receiving end would recommend or repeat it.
Informed, recorded, revocable consent. Anonymisation by default. Sampling, translation, and quality control managed end to end. We interview to understand, not to confirm.
Every study passes an internal ethics check against these references:
Commissioned work belongs to the client and stays private unless the client chooses to publish. The case studies on this site are those exceptions.
See Who We Serve for how the fit works in each case.
Underlying methods in full: Field Research (the primary-contact method, ethics, sampling) and Impact Measurement (the reach / depth / experience frame, attribution, additionality). For how a study runs end to end, see How It Works. For reporting to a funder specifically, see Reporting to Funders. To discuss a study, see Contact.