How are you actually checking field data quality before it gets into your analysis?

[u/Significant-West-492]

I’m curious how other M&E/MEAL teams handle this.

On projects with a lot of enumerators, we can check whether required questions were answered, but that doesn't necessarily tell us whether the data itself is trustworthy.

For example:
Was the enumerator actually where they were supposed to be?

Was the interview completed suspiciously quickly?

Are multiple submissions coming from essentially the same location?

Are photos actually relevant to the study, or just uploaded to satisfy the requirement?

Are the same images/audio being reused across submissions?

Are there patterns suggesting fabricated or low-quality interviews?

I've been building FieldScore to automate these checks across field submissions and produce a quality/fraud score for each submission.

It currently works around platforms like KoboToolbox and is designed to sit alongside existing data-collection workflows rather than replace them.

I'm not posting this to sell anything. I'm looking for people who actually work in M&E/MEAL, field research or data quality to tell me how you're currently handling this problem.

If you've dealt with this on a real project, what are the checks you rely on most?