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67 → 30days
Time-to-Hire
With AI funnel analysis
3–4 weeksearly
Attrition Predicted
Before resignation letter
₹1.8L → ₹90K
Cost Per Hire
Optimised sourcing
+12%avg
Revenue/Employee
After headcount audit
Real Pain → AI Solves It
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The Pain
We lost 3 senior engineers last quarter. HR says it's 'market conditions.' CEO wants to know the real reason before we lose 3 more.
Raw data signal
Engineer A: Resigned after 18mo | Performance: Top 10% | Last appraisal: 6mo ago | Salary: ₹18L (market: ₹22L). Engineer B: Resigned after 24mo | No promotion in 2 years | Team: Backend. Engineer C: Resigned after 14mo | Manager change: 3 months ago | 1:1 frequency: 0/month
OpsOracle AI Output
All 3 engineers share 2 of 3 attrition signals: compensation gap (₹4L below market), stagnation (no promotion/appraisal >6 months), or manager disconnect (Engineer C: zero 1:1s for 3 months after manager change). This is not market conditions — it is a preventable retention failure.
[THIS WEEK] Action
Immediate: compensation review for remaining Top-10% engineers vs current market bands. Assign skip-level 30-min check-ins for anyone under a recently-changed manager. HR to run quarterly promotion pipeline review — not annual.
Expected impact: Prevent ₹36–54L replacement cost per engineer (2–3× annual salary). Reduce voluntary attrition from estimated 24% to under 12%.
The Pain
We're hiring 40 people this quarter but HR says time-to-hire is 67 days. Leadership wants it under 30 days.
Raw data signal
Role 1: JD posted day 0 | Applications: 234 | Screened: 48 | Technical: 22 | Offered: 8 | Joined: 5 | Days: 71. Role 2: JD posted day 0 | Applications: 89 | Screened: 12 | Technical: 6 | Offered: 4 | Joined: 3 | Days: 63
OpsOracle AI Output
67-day average hides where time is lost. Role 1 funnel: 48 screened but only 22 reached technical (45% drop-off) — screening criteria too strict or recruiter bandwidth. Technical to offer: 8/22 = 36% — good. Offer to join: 5/8 = 62.5% — below the 80% target. Acceptance failures = offer timing or compensation.
[THIS WEEK] Action
Reduce screening filters from 8 to 5 criteria. Schedule technical rounds within 5 days of screening (vs current 14-day lag). Add compensation benchmark to JD to prevent late-stage offer rejection. Target: 45 days by month 2.
Expected impact: Close 40 roles 37 days faster. Save ₹2.4L/day in contractor cover costs per unfilled role.
The Pain
Headcount costs jumped 31% YoY but revenue only grew 18%. Board wants a headcount efficiency analysis.
Raw data signal
FY23: 142 employees | Revenue: ₹24Cr | HC cost: ₹8.4Cr | Revenue/employee: ₹16.9L. FY24: 186 employees | Revenue: ₹28.3Cr | HC cost: ₹11L | Revenue/employee: ₹15.2L
OpsOracle AI Output
Revenue per employee fell from ₹16.9L to ₹15.2L (-10%) while headcount grew 31%. 44 new hires contributed only ₹4.3Cr in incremental revenue — ₹9.8L revenue per new hire vs ₹16.9L legacy benchmark. The FY24 cohort is underperforming by 42%. Two likely causes: hires in non-revenue functions, or ramp time not yet realised.
[THIS WEEK] Action
Map each of the 44 new hires to a revenue or cost-saving driver. Freeze non-revenue headcount. Focus next 2 quarters on ramp acceleration — structured 90-day onboarding for revenue roles. Report revenue-per-employee monthly to leadership.
Expected impact: Close efficiency gap from ₹15.2L to ₹17L revenue/employee = ₹3.35Cr annual revenue improvement at current headcount.
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