Checking survey data before main fieldwork - Simulation and manual data checking before fieldwork are the only reliable way to confirm a complex survey is collecting data correctly.

Storing intermediate variables for auditability - Dynamic calculations displayed directly to respondents without being stored make auditing impossible. Store intermediate values as survey variables before displaying them.

Designing screening questions for surveys - Screening questions that reveal their purpose to respondents inflate eligibility rates and contaminate the sample. Two design principles prevent this.

Including tracking and metadata in surveys - Tracking data collected during a pilot is cheap insurance against problems that only become apparent in main fieldwork. Collect it by default, evaluate it later.

Variable direction consistency in survey design - Mixing the direction of response scales across variables confuses respondents and analysts. Agreeing direction before coding prevents a systematic error that is invisible in the data.

Variable and survey naming conventions - Poor variable naming causes avoidable errors in analysis. Decisions made before coding starts determine how much pain comes later.

Survey versioning and content review management - Survey versioning is not a technical nicety - it is the only mechanism that allows changes during live fieldwork without corrupting existing response data.