Design and coordinate data collection

I have the draft data-collection plan for the field campaign next month; tidy the spreadsheet so it lists each sensor, its sampling frequency, responsible technician, and the exact column where their data should land, then email the final sheet to Nora in field ops and copy Oliver in analytics with a note that the plan must be confirmed by Monday.

Before I publish the data collection worksheet to the field team, make it easy for Nora to check: put the top-level sampling schedule at the top, mark any sensors needing calibration before deployment, add a clear column for the technician’s initials on completion, and highlight any missing GPS or timestamp requirements that would make the dataset unusable for analytics.

I set the plan at 15-minute intervals overnight but Nora’s techs say it’s not sustainable on the night shift and they’ll miss records. I’m worried lower frequency will break trend detection, but insisting could mean poor compliance. Do I push night frequency, revise the analysis to tolerate sparser data, or hire a temporary night tech? Recommend the best immediate compromise and how to record the decision so analytics can adjust models later.

On campaign after campaign I lose time reconciling columns, fixing timestamps, and mapping sensor IDs because each field team has its own conventions. It eats our analysis time and damages credibility with stakeholders. What habit should I change, and what three practical steps let me enforce consistent collection standards so delivered datasets are analysis-ready without rework?