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Licensing requirements exist across regulated industries. Standard selection tools, LIMRA's Career Profile among them, have not incorporated license status as a predictive measure since 1982. A Fortune 500 insurance carrier analyzed 10,362 agents from 2022-2025 to measure which screening fields actually predict first production milestone achievement. This page is the long form of what they found.
| Cohort | 2022 | 2023 | 2024 | 2025 |
|---|---|---|---|---|
| With insurance experience | 37.6% | 32.3% | 32.4% | 18.1% |
| Without insurance experience | 42.5% | 40.8% | 35.6% | 21.7% |
The equation holds regardless of whether the screen predicts production, the right signal must be identified. If a signal predicts both P and t, then ΔP = k × Δt. Total yield scales linearly: ΔProduction = k × Δt × n.
Requiring industry experience alone would have rejected 2,863 producing agents, eliminating $17.7M in annual production. The screen selects against producers.
Carrier internal analysis · 2022-2025Speed measured as days from contract to first production milestone; production as annual output per person.
| Speed bucket | With scoring (2025) | Without scoring (2022-2024) |
|---|---|---|
| 0-30 days | $13,137 | n = 0 |
| 31-60 days | $11,219 | $10,033 |
| 61-90 days | $10,395 | $11,665 |
| 91-120 days | $8,030 | $14,246 |
| 121+ days | $7,284 | $14,410 |
Each day faster to first production milestone correlates with $54 more annual production per person. Scales linearly with observed acceleration and annual hire volume.
Uses the same k = $54.35/day/person derived above, applied to your hire volume and production rate. Conservative, bounded at 95% ceiling and 80% floor so it can't over-promise. Webhook logs each run so we can sanity-check against your own data later.
You hire people. Some produce. Some don't.
What would it mean if your production rate doubled?
Get the full breakdown with net value, payback period, and what this means per hire.
skip, show me the breakdownBased on 1,690 producing agents at a Fortune 500 insurance carrier.
Avature ATS + HRIS production data. 2022-2025.
Four "rejects" combined produced $91,409. One "clean resume" produced $5,280. Across 677 candidates with zero traditional ATS keywords but a Nodes score of 75+: 33.7% production rate vs. 20-27% for the screened-in cohort.
Zero-keyword cohort · n = 677 · carrier 2025The equation holds regardless of whether S predicts P, the right signal must be identified. Companies can only test relationships on hired candidates; rejected candidates have no production data, which limits signal discovery to applicant survivors of initial screening. Fields change. The equation doesn't.
At 14% production rate, 59% of a year's hires never produce a single sale. The carrier improved to 28%: 160 additional producing agents, $3.19M premium credit generated, $8M avoided failed-hire costs, $630K net savings per 100 hires.