Quality control begins at the recruitment and briefing stage, not the analysis stage. Interviewers and fieldworkers need to understand the objectives of a study before they’re deployed — not just the questionnaire, but why each question matters and what a “good” response looks like versus a rushed one.
Static back-checks after fieldwork closes catch some problems, but by then the sample is already compromised. Integrated project management means monitoring collection in real time — across face-to-face, telephonic (CATI), and online methods — so issues get caught and corrected while there’s still time to fix them, not written up as a limitations section.
Ensuring accuracy, completeness, and reliability means multiple checkpoints: verifying respondent eligibility, checking for straight-lining or inconsistent answers, confirming interviewer adherence to protocol, and reconciling data across collection modes when a study uses more than one method.
For government, NGO, and academic clients in particular, data quality isn’t just about client satisfaction — it often has downstream implications for policy decisions, funding reports, or published research. Corporate clients across FMCG, telecom, finance, and pharma face similar stakes when fieldwork data feeds directly into commercial decisions.
Quality assurance works best as a discipline built into the execution strategy from day one — understanding the client’s objectives, executing the right technique for the audience, and maintaining oversight throughout — rather than a review stage bolted on at the end.
Want to talk through the quality controls for your next project? Get in touch or request a quote.
Occasional notes on fieldwork practice and data collection in South Africa.
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