The Attribution and ROI Framework defines how to connect a specific hiring action (a recovery playbook triggered, a recruiter reassigned, a brief re-run) to a specific mandate outcome (close date moved forward, offer accepted, mandate recovered) and to a specific financial value (cost of vacancy days saved, placement fee avoided, revenue contribution unlocked). The framework operates at three levels: action-level attribution (did this intervention change the trajectory?), mandate-level ROI (what was the total cost and outcome of this search?), and portfolio-level efficiency (what is the aggregate cost per placement and time-to-fill across all mandates?).
Why Hiring ROI Is Difficult to Calculate
The challenge of attribution in hiring operations is not data collection — it is causality. When a VP Sales search closes in 38 days, is that because the outreach sequence was excellent, because the candidate pool was unusually deep, because the hiring manager was unusually decisive, or because the Failure Prediction Engine caught a stall at week 3 and triggered a recovery? Without a defined attribution framework, the answer is always "a combination of factors" — which is analytically useless.
"A CFO doesn't fund a hiring system because it has good health scores. They fund it because it produces a measurable reduction in cost-per-placement, a measurable compression of time-to-fill, and a measurable reduction in the cost of vacancy. The Attribution Framework produces those numbers."
Attribution Level Matrix
| Level | Unit of Analysis | Key Metrics | Calculation Method | Reporting Audience |
|---|---|---|---|---|
| Action | Individual intervention | Response rate delta; stage velocity delta; Health Score delta post-intervention | Before/after comparison at 72hr, 7-day, 14-day intervals | Recruiter / TA Manager |
| Mandate | Individual search | Days-to-close vs. SLO; cost per placement; offers extended vs. accepted; candidate withdrawal rate | Actual vs. target for each metric; vs. industry benchmark | VP People / Head of TA |
| Portfolio | All active and closed mandates in period | Average days-to-close; cost per placement; offer acceptance rate; YTD vs. budget; recovery playbook ROI | Aggregate of mandate-level data; trend over rolling 90 days | CEO / CFO / Board |
Frequently Asked Questions
What is the cost-of-vacancy calculation used in the ROI framework?
Cost of vacancy is calculated as: (Annual OTE of the open role / 252 working days) x an impact multiplier based on role type. The impact multiplier for a VP Sales role is typically 2–3x (revenue-generating role with team dependency). For a VP Engineering, 1.5–2x. For a Chief of Staff, 1x. A $250K OTE VP Sales role has a cost-of-vacancy of approximately $2,000–$3,000 per working day. A 30-day velocity improvement over industry median produces $60,000–$90,000 in recovered value — which typically exceeds the retained search fee.
How does the framework handle attribution for mandates that fail despite intervention?
Failed mandates are as valuable to the attribution framework as successful ones — because they provide negative signal data. The framework records which interventions were applied, the outcome, and the pre-intervention failure probability. Failed mandates that received appropriate interventions update the prediction model to reflect cases where the recovery window had already closed. Failed mandates that received no intervention confirm the failure prediction accuracy.
What is the attribution evidence for Majhi Group's 41-day benchmark close?
The 41-day VP search close on a $275K mandate had full attribution data: intake on day 1, sourcing on day 3, first outreach on day 4 (DNS/MX verified sequence), 29% response rate achieved by day 9, shortlist of three Evidence Dossiers delivered day 14, first interview round day 17, second round day 22, reference verification day 28, offer extended day 39, signed day 41. Each stage outcome was logged against its SLO, producing a complete causal record of the close velocity.