The quality of an impact report is set long before anyone writes a word of it — it’s set by how the underlying data was collected. A well-written report built on a poorly designed survey still produces a number a funder shouldn’t trust.
Design the sample before the questionnaire
Deciding who gets surveyed, and how that group represents the broader beneficiary population, matters more than the wording of any individual question. A convenience sample of the most engaged beneficiaries will consistently overstate a program’s impact relative to a representative one.
Mixed methods catch what surveys alone miss
Quantitative surveys tell an organization what changed; interviews and structured observation tell it why and for whom. Impact evidence built on surveys alone tends to miss the beneficiaries a program isn’t reaching — exactly the group most useful to know about.
Validate before you report, not after
Cross-checking a sample of collected data against an independent source — a partner organization’s records, a spot-check visit — before it goes into a report catches errors while they’re still cheap to fix. Catching them after publication costs the organization’s credibility instead.
Consent is part of the methodology, not a compliance step
In impact-sector data collection, informed consent from beneficiaries isn’t a form to file away — it shapes what can honestly be reported and how. Building it into the collection design from the start avoids having to walk back a finding later because the underlying consent didn’t cover it.
This kind of methodological rigor — sampling, mixed methods, validation, consent — is the foundation Insights Lab builds every measurement engagement on.