--- name: recruitment-analytics description: Analyze hiring funnel metrics, source effectiveness, time-to-hire, cost-per-hire, quality-of-hire, and diversity hiring data. Use when generating recruitment dashboards, identifying bottlenecks, optimizing sourcing channels, tracking recruiter performance, or presenting hiring metrics to leadership. Supports weekly, monthly, and quarterly reporting with trend analysis and AI-powered recommendations. Triggers on phrases like "hiring metrics", "recruitment dashboard", "time to hire", "cost per hire", "source of hire", "funnel analysis", "hiring report", "recruiting KPIs". --- # Recruitment Analytics Measure and optimize the hiring process with data-driven insights. ## Workflow 1. Pull data from ATS, HRIS, and sourcing tools for the reporting period. 2. Calculate core metrics: time-to-fill, time-to-hire, cost-per-hire, offer acceptance rate, quality-of-hire. 3. Analyze funnel conversion rates at each stage: applied → screened → interviewed → offered → hired. 4. Identify bottlenecks: stages with lowest conversion or longest average duration. 5. Evaluate source effectiveness: which channels produce the best candidates at the lowest cost. 6. Assess diversity metrics: applicant pool diversity vs. hired diversity at each stage. 7. Generate dashboard and executive summary. 8. Surface actionable recommendations based on trends and benchmarks. ## Core Metrics Definitions | Metric | Formula | Target | Benchmark (Tech) | |--------|---------|--------|-----------------| | **Time-to-Fill** | Days from requisition approval to offer acceptance | < 45 days | 36–52 days | | **Time-to-Hire** | Days from application to offer acceptance | < 30 days | 25–35 days | | **Cost-per-Hire** | (Internal costs + External costs) ÷ Total hires | Varies by role | $4,000–$9,000 | | **Offer Acceptance Rate** | Offers accepted ÷ Offers extended × 100 | > 85% | 80–90% | | **Application-to-Offer Rate** | Offers extended ÷ Applications received × 100 | 2–5% | 1–8% | | **Quality-of-Hire** | (Performance rating × 0.4) + (Retention × 0.3) + (Manager satisfaction × 0.3) | > 4.0/5.0 | 3.5–4.5 | | **First-90-Day Attrition** | New hires leaving within 90 days ÷ Total new hires × 100 | < 5% | 3–8% | | **Source-of-Hire Effectiveness** | Hires from source ÷ Cost from source | Maximize ratio | Varies | ## Funnel Analysis ### Stage Conversion Tracking ``` FUNNEL VIEW — Q1 2025 ====================== Stage Count Conversion Drop-off Avg Duration ──────────────────────────────────────────────────────────────────── Applications 2,450 — — — Resume Screen 890 36.3% 63.7% 2.1 days Phone Screen 312 35.1% 64.9% 3.4 days Technical Interview 145 46.5% 53.5% 5.2 days Final Round 68 46.9% 53.1% 4.8 days Offer Extended 42 61.8% 38.2% 2.1 days Offer Accepted 35 83.3% 16.7% 5.2 days Hired 35 100% — — Overall conversion: 1.43% (35 hired ÷ 2,450 applied) Total time-to-hire: 22.8 days (median) BOTTLENECK IDENTIFIED: → Resume screen: 63.7% drop-off is normal for volume roles → Phone screen: 64.9% drop-off — consider if screening criteria are too strict → Offer stage: 16.7% decline rate — investigate top decline reasons ``` ### Funnel Health Indicators | Signal | Meaning | Action | |--------|---------|--------| | High application count, low screen rate | JD attracts wrong candidates | Rewrite JD, refine targeting | | Low application count | Role not visible or uncompetitive | Increase sourcing, review comp | | High interview-to-offer drop-off | Interview process too harsh or poorly calibrated | Review interviewer training, calibrate scoring | | Low offer acceptance rate | Comp uncompetitive or process too long | Benchmark comp, accelerate process | | High first-90-day attrition | Poor hiring quality or bad onboarding | Review screening rigor, audit onboarding | ## Source Effectiveness Analysis ``` SOURCE EFFECTIVENESS — Q1 2025 ============================== Source Applicants Hires Cost/Hire Quality* ROI Score ──────────────────────────────────────────────────────────────────── Employee Referral 312 8 $2,100 4.3/5 ★★★★★ LinkedIn 685 9 $4,800 3.8/5 ★★★★☆ Indeed 420 5 $3,200 3.5/5 ★★★☆☆ Company Career Site 390 6 $1,800 3.9/5 ★★★★☆ Direct Sourcing 180 4 $5,600 4.1/5 ★★★☆☆ Agency 45 2 $12,000 3.6/5 ★★☆☆☆ University 18 1 $3,500 4.0/5 ★★★☆☆ Diversity Boards 100 2 $2,800 3.7/5 ★★★☆☆ *Quality = avg performance rating of hires from source at 6-month review RECOMMENDATION: → Increase employee referral incentive (highest ROI) → Reduce agency spend (lowest ROI, highest cost) → Maintain LinkedIn investment (volume + quality balance) → Test diversity board expansion (decent quality, room for scale) ``` ## Diversity Hiring Metrics Track representation at each funnel stage: ``` DIVERSITY FUNNEL — Q1 2025 ========================== Stage All Women Underrep. LGBTQ+ Disability ──────────────────────────────────────────────────────────────────── Applications 2,450 42% 38% 8% 5% Screened 890 40% 35% 7% 4% Interviewed 312 38% 33% 6% 4% Offered 42 36% 31% 5% 3% Hired 35 37% 32% 5% 4% WORKFORCE BASELINE (for comparison): Current workforce: Women 34%, Underrep. 28%, LGBTQ+ 6%, Disability 4% ASSESSMENT: ✓ Hiring slightly above workforce baseline for women (+3%) ⚠ Underrepresented groups declining through funnel (-6% from apply to hire) ✓ LGBTQ+ and disability representation maintained → ACTION: Review screening rubric for implicit bias at phone screen stage ``` ## Recruiter Performance Metrics ``` RECRUITER LEADERBOARD — Q1 2025 ================================ Recruiter Hires Time-to-Fill Offer Accept Quality Revenue Impact ───────────────────────────────────────────────────────────────────────────── Sarah M. 12 28 days 92% 4.2/5 $1.8M (sales hires) James L. 9 35 days 85% 4.0/5 $920K (eng hires) Priya K. 11 31 days 89% 4.1/5 $1.2M (mixed) David R. 7 42 days 78% 3.7/5 $650K (eng hires) NOTES: → Sarah: Top performer — consider expanding scope → David: Below target on time-to-fill and quality — recommend coaching session → All recruiters within acceptable range except David on quality metric ``` ## Reporting Cadence | Report | Frequency | Audience | Format | |--------|-----------|----------|--------| | Weekly pipeline snapshot | Every Monday | Hiring managers, recruiters | Slack/Email summary | | Monthly hiring dashboard | 1st of month | HR leadership, department heads | Interactive dashboard | | Quarterly business review | End of quarter | Executive team, board | Presentation deck | | Annual hiring summary | End of year | Board, all-hands | Written report | ## AI-Powered Recommendations Surface these insights automatically: ``` Based on Q1 data, the system recommends: 1. ⚡ REDUCE TIME-TO-FILL FOR ENGINEERING ROLES Current: 38 days | Target: 30 days Action: Pre-screen candidates with automated skills assessments Impact estimate: -5 to -7 days per hire 2. 💰 OPTIMIZE SOURCING BUDGET Current agency spend: $24,000 (2 hires, $12K each) Action: Reallocate $15K to employee referral bonus program Impact estimate: 3-4 additional hires at $2.5K avg cost 3. 🎯 IMPROVE PHONE SCREEN CONVERSION Current drop-off: 64.9% at phone screen Action: Review screening rubric; calibrate recruiters on "pass" threshold Impact estimate: +10-15% conversion = 30-45 more candidates advancing 4. 📊 DIVERSITY INTERVENTION NEEDED Underrep. group drop-off: 38% → 32% through funnel Action: Implement blind resume screening for phone screen stage Impact estimate: +5-8% representation at offer stage ``` ## Integration Points - ATS (Greenhouse, Lever, Ashby): Pipeline data, stage timestamps - HRIS: Hire dates, performance data for quality-of-hire calculation - Sourcing platforms: Channel attribution, spend tracking - Payroll: Cost-per-hire internal cost calculation - BI tools (Tableau, Looker, Power BI): Dashboard visualization - Slack/Email: Automated report distribution ## Edge Cases - **Mass hiring periods**: Adjust targets temporarily; track surge metrics separately - **Hard-to-fill roles**: Segment analytics by role difficulty; don't let outliers skew overall metrics - **New company / no baseline**: Use industry benchmarks as starting targets; build internal baseline over 6 months - **Remote/global hiring**: Segment metrics by region to account for market differences - **Hiring freeze impact**: Note freeze periods in trend analysis; exclude frozen weeks from time-to-fill calculations