Your Quotas Are Probably Impossible. Here's How to Check.

Quota grids look reasonable on paper. Client wants census-rep by age and gender, a 40/60 split on income brackets, and an even split by region. Sounds fine. Then you actually map those quotas against population data and discover that your "Northeast high-income males 18-24" cell requires sampling 80% of the roughly 12,000 people who match that description nationwide.

I've seen this kill projects. Operations commits to the quota grid, fieldwork launches, and three weeks later you're staring at a cell that's 60% filled with no realistic path to completion. The project manager is sending panicked Slack messages. The PM lead is extending field for the third time. The client is annoyed.

What the tool does

You enter your quota targets, cell by cell, and the planner checks each one against Census population proportions. It flags cells that will fill naturally, cells that will require moderate oversampling, and cells that are essentially impossible without supplemental sourcing. Color-coded: green, yellow, red.

The red cells are the ones that matter. If your quota grid has three or four red cells, you need to renegotiate the design before launching. Maybe you combine two age groups. Maybe you relax the income requirement. Maybe you boost the total sample to give yourself more natural fallout into the hard cells.

The point is to have this conversation before fieldwork starts, not during week two when you're already half-spent on sample budget.

Tech stack

React 18.2 + Babel CDN. Census ACS proportions drive the population estimates. The feasibility scoring uses a simple ratio: target cell count divided by estimated available population at typical panel penetration rates. Anything above 40% required capture is flagged yellow. Above 70% is red.