Method behind Measuring Change
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. Impact 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, and reports what the evidence actually says, including when that is inconvenient.
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. Three dimensions, each answering a different question.
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, critically, the gap between the population an intervention was designed for and the one it is landing with. Distribution is central, not a footnote.
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.
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. See the in-depth interview guide for how the Lab reaches depth in the qualitative work, and the European impact-tracking template for the shape of a full baseline-to-endline design.
Not all evidence carries the same weight. The Lab classifies every finding it reports against a five-tier pyramid, from what was delivered at the base to a causal contribution established at the top. The pyramid is the honest answer to the question every funder eventually asks, which is whether the number in the report is a claim, an observation, or a conclusion.
Two working rules follow from the pyramid. Most claims made about programmes sit on the bottom two tiers, and most reports present them as if they sat on the top two, which is where the reporting-loop pressure we describe in Why funders learn from grantees shows up in practice. And moving a study up the pyramid is a design choice made before the fieldwork, not a rhetorical move made in the write-up: a baseline captured, a second source lined up, a control identified. What you can honestly claim at the end is set by what you built in at the start.
Impact is not one thing. On any given study, we typically measure a mix of the following, calibrated to the specific decision the research is meant to inform.
We start from the decision, not the data. A short design conversation establishes what decision the research must inform, the population that holds the answer, and the specific evidence that would genuinely change the decision. Most research is wasted here, by gathering data that was never going to settle anything. See How It Works for the five-stage method the Lab runs on every engagement.
We build the instrument around the respondent. Short, clear, locally grounded, and structured for repetition and comparison. We use validated instruments where they exist and design bespoke ones where they do not. Every instrument is built for repeat use, so a single study becomes a time series with almost no marginal cost.
We capture a baseline before the intervention. Impact is a change, and a change needs a before. Baselines are captured with the same instrument that will be used again later, so the comparison is valid. Without this, an impact claim can only be asserted, not evidenced.
We reach respondents directly, in-language. Trained local researchers who know the place gather data by phone or in person, with informed, recorded, revocable consent. We reach the people the intervention is meant to serve, not proxies for them. See Field Research for the field methods behind this.
We report the inconvenient finding. Independence is the whole point. We publish what the evidence says, including the parts that contradict a client's hopes. That posture is what makes the finding worth the effort of gathering it.
Every engagement ends in something you can use, in the following forms:
Turnaround is typically measured in weeks. Instruments are designed for repetition, so what starts as a one-off becomes an ongoing measurement capability.
The Lab is most useful at a few specific moments:
There are excellent impact-measurement firms. The Lab's difference is a specific combination three organisations rarely hold together.
3ie IDinsight IPA J-PAL
Each is excellent at what it does. See 3ie on rigorous impact evidence, IDinsight on decision-focused evaluation, Innovations for Poverty Action and J-PAL on the RCT standard. The Lab does not try to be any of them.
To discuss a study or a collaboration, see Contact. For the field research behind the measurement, see Field Research. For the wider reading behind it, see Articles.