Different panels graded differently across regions, so the same submission could pass in one office and fail in another.
A shared rubric plus an iteration timeline gave every reviewer the full story — prompts, edits, and trade-offs — for calibrated, defensible decisions.
Distributed hiring across US and India delivery centers created a fairness problem: the same candidate could pass in one region and fail in another, purely because panels graded differently.
The problem: inconsistent bars
Without a shared view of how a candidate worked, reviewers fell back on instinct — and instinct varied by office, by interviewer, and by day.
- The same submission got different verdicts by region
- No shared evidence behind decisions
- Slow, contested calibration meetings
The shift: shared evidence, shared rubric
A common rubric paired with an iteration timeline gave every reviewer the full story — prompts, edits, test runs, and trade-offs — so decisions were calibrated and defensible.
- One rubric across every region
- Replayable iteration timeline per candidate
- Decisions backed by evidence, not gut feel
The outcome
A single consistent bar across regions, 38% higher reviewer agreement, and 29% faster time-to-offer — fairer for candidates and faster for the business.