UitbreidenOS When to activate
Quarterly or when attrition rate exceeds target. Analyzes employee data to uncover departure patterns and predict flight risk.
When NOT to use
Not for termination decisions or performance management. Not for compensation analysis — use compensation-analyzer for that. Not as substitute for stay interviews with at-risk individuals.
Retention Analysis Checklist
Execute in order:
- Gather headcount and attrition data — Current headcount by team/level; separations (voluntary, involuntary, planned) for past 12–24 months
- Calculate key metrics — Voluntary attrition rate %, regrettable vs. non-regrettable, tenure distribution
- Cohort analysis — Break down by hire class (when hired), team, level, tenure, demographics (optional)
- Identify patterns — Which cohorts have high exit rates? Any seasonal trends?
- Root cause analysis — Why are people leaving? Conduct stay interviews with at-risk employees
- Segment at-risk population — Who shows early warning signs? (low engagement, high external activity, recent conflicts)
- Model intervention impact — What's the ROI of a $10K retention bonus vs. cost of replacing?
- Recommend actions — Compensation, career path, role redesign, management change, etc.
Key Metrics & Definitions
Voluntary Attrition Rate
Formula: (# voluntary separations in period) / (average headcount) × 100
Example: 2 voluntary departures ÷ 50 avg headcount = 4% quarterly attrition = 16% annualized
Benchmark: 12–13% annual voluntary attrition (SaaS). Lower is better; >15% indicates problems.
Regrettable vs. Non-Regrettable
Regrettable: High performer who leaves (cost of replacement: $100K+). Preventable.
Non-regrettable: Underperformer or misfit who leaves (cost of replacement: $40K, saves management effort).
Example breakdown:
- Total voluntary departures: 5
- Regrettable (want them to stay): 3 (high performers, key roles)
- Non-regrettable (OK they left): 2 (underperformers, role misfit)
Target: <30% of departures non-regrettable (meaning most exits are unwanted losses).
Tenure Cohort Analysis
Cohort: Group hired in same period (e.g., "Q1 2024 hires").
Track: At 6 months, 12 months, 24 months: how many are still with company?
Example:
- Q1 2024: 10 hires → 6 months: 9 remaining (90% retention) → 12 months: 8 remaining (80% retention)
- Q3 2023: 8 hires → 12 months: 5 remaining (62% retention) ← cohort issue; onboarding problem?
Benchmark: Aim for >90% at 6 months, >80% at 12 months (SaaS).
Attrition Root Cause Categories
When analyzing departures, categorize by stated reason:
| Root Cause | Signal | Prevention |
|---|---|---|
| Compensation/equity | "I got an offer for 20% more" | Benchmark regularly; stay competitive; refresh equity grants |
| Growth ceiling | "No clear path to next level" | Transparent career ladder; manager coaching on growth; succession planning |
| Management | "My manager and I didn't align" | Manager training; 360 feedback; skip-level check-ins |
| Work-life balance | "Too much on-call / burnout" | Workload assessment; role adjustment; team sizing |
| Culture fit | "Values misalignment" or "remote became in-office" | Hiring clarity on culture; flexibility options; team dynamics |
| Career shift | "Going back to school" or "industry change" | Natural; non-regrettable |
| Personal/family | "Relocation" or "spouse's job" | Understand context; may offer return option |
| Opportunity elsewhere | "Better project/role fit at competitor" | Understand what we're missing; competitive positioning |
Track ratio: If >40% compensation-driven, you have a pay problem. If >30% management-driven, you have a people manager problem.
Flight Risk Assessment Framework
Early Warning Signs
Employees showing multiple of these indicators warrant stay interview:
| Signal | Severity | How to Monitor |
|---|---|---|
| Reduced engagement (less speaking in meetings, low energy) | Medium | Manager observation; skip-level 1:1 |
| Active job search (LinkedIn activity, interview scheduling) | High | Recruiter intel, LinkedIn alerts, colleague mentions |
| Recent conflict or performance issue | Medium–High | Manager feedback; performance review notes |
| Started external projects (consulting, side gig) | Medium | Casual observation; work agreement review |
| Declined stretch assignment or promotion | Medium | Manager discussion; understand "why not" |
| Frequent "quiet quitting" signals (minimal contribution, boundary-setting) | Low–Medium | Manager feedback; productivity trends |
| Anniversary of major milestone (1-year, 2-year, 5-year) | Low | Data; some departures cluster post-milestone |
| Expressed frustration with process, pay, growth | Low–Medium | 1:1 feedback; manager notes |
Retention Risk Score
Create a risk score (1–10) for each at-risk employee:
Risk Score = (Signal A × weight) + (Signal B × weight) + ...
Where:
- Active job search = 3 points
- Recent conflict = 2 points
- No promotion past due date = 2 points
- Engagement drop = 1 point
- Below-market compensation = 2 points
- Manager turnover (recent change) = 1 point
- <1 year tenure = 1 point
Score 6–7 = Monitor closely
Score 8–10 = Engage stay interview immediately
Retention Analysis Output Template
# Retention Analysis — [Period] [Year]
**Prepared:** [YYYY-MM-DD]
**Analysis Period:** [e.g., Jan–June 2026]
**Prepared for:** [CEO, Leadership Team, HR]
---
## Executive Summary
**Voluntary attrition rate:** [X]% for period (annualized: [Y]%)
**Benchmark:** 12–13% annual target
**Status:** [On target / Above target / Below target / URGENT]
**Key findings:**
- [Finding 1: e.g., "Cohort hired Q1 2025 has 35% attrition — onboarding issue"]
- [Finding 2: e.g., "Engineering team losing senior ICs to competitor offers"]
- [Finding 3: e.g., "Non-regrettable attrition is 60% — many underperformers left, which is good"]
---
## Headcount Summary
| Period | Headcount Start | Hires | Voluntary Departures | Involuntary | Headcount End | Voluntary Attrition % |
|--------|---|---|---|---|---|---|
| Q1 2026 | 120 | 8 | 2 | 1 | 125 | 1.6% |
| Q2 2026 | 125 | 6 | 3 | 0 | 128 | 2.3% |
| **YTD** | **120** | **14** | **5** | **1** | **128** | **2.0% (annualized: 8%)** |
---
## Attrition by Team
| Team | Headcount | Voluntary Departures | Attrition % | Benchmark | Status |
|------|-----------|---|---|---|---|
| Engineering | 60 | 2 | 3.3% | 10% | Good |
| Product | 12 | 1 | 8.3% | 12% | Good |
| Sales | 20 | 1 | 5% | 15% | Good |
| Marketing | 15 | 1 | 6.7% | 12% | Good |
| Operations | 8 | 0 | 0% | 12% | Excellent |
| Finance | 5 | 0 | 0% | 12% | Excellent |
| **TOTAL** | **120** | **5** | **4.2%** | **12%** | **On target** |
---
## Attrition by Level
| Level | Headcount | Departures | Attrition % | Concern Level |
|-------|-----------|---|---|---|
| L1 (Junior IC) | 25 | 2 | 8% | Monitor (typical for junior) |
| L2 (Senior IC) | 45 | 2 | 4.4% | Good |
| L3+ (Staff+) | 15 | 1 | 6.7% | Monitor (losing experience) |
| Manager | 20 | 0 | 0% | Excellent |
| Director+ | 5 | 0 | 0% | Excellent |
---
## Cohort Retention Analysis
| Hire Class | Hired | At 6 Mo | At 12 Mo | Current | Retention |
|---|---|---|---|---|---|
| **Q1 2025** | 12 | 11 (92%) | 9 (75%) | 8 (67%) | ⚠️ Low |
| **Q2 2025** | 14 | 13 (93%) | 12 (86%) | 11 (79%) | Medium |
| **Q3 2025** | 10 | 9 (90%) | 8 (80%) | 8 (80%) | Good |
| **Q4 2025** | 8 | 7 (88%) | 7 (88%) | 7 (88%) | Good |
| **Q1 2026** | 8 | 8 (100%) | N/A | 8 (100%) | Excellent |
**Insight:** Q1 2025 cohort has retention problem. Likely onboarding or role-fit issue. All left by month 15.
---
## Recent Departures & Exit Analysis
| Employee | Title | Tenure | Regrettable | Stated Reason | Actual Reason (inferred) |
|---|---|---|---|---|---|
| Jane Doe | Senior Engineer | 3.2 years | Yes | "Better opportunity" | Competitor offer + no clear path to Staff |
| John Smith | Product Analyst | 1.8 years | No | "Career change" | Underperformer; leaving for non-PM role |
| Sarah Chen | Marketing Manager | 2 years | Yes | "Relocation" | New job in LA; we didn't offer remote |
| Alex Rodriguez | Engineer | 0.9 years | No | "Personal" | Bad fit; silent quitting pattern |
**Regrettable departures:** 2/4 (50% regrettable rate — we're losing talent)
---
## Attrition Root Cause Summary
| Root Cause | Count | % | Action |
|---|---|---|---|
| Compensation/offer elsewhere | 1 | 20% | Benchmark salary; improve competitive positioning |
| Growth/career path | 1 | 20% | More clarity on promotion timeline |
| Relocation/personal | 1 | 20% | Offer flexibility; remote option |
| Culture/role fit | 1 | 20% | Improve hiring filtering; onboarding review |
| **Total** | **5** | **100%** | — |
---
## Flight Risk Assessment
**At-risk employees identified through signal analysis:**
### 🔴 High Risk (likely to leave in next 3 months)
**Employee:** [Name, Title]
**Signals:** Active job search (LinkedIn activity), recent conflict with manager, below-market compensation
**Risk Score:** 8/10
**Recommendation:** Stay interview this week. Understand concerns; offer: compensation review, role adjustment, or management change
### 🟡 Medium Risk (monitor closely)
**Employee:** [Name, Title]
**Signals:** Engagement drop (less speaking, boundary-setting), no promotion in 2+ years
**Risk Score:** 6/10
**Recommendation:** Manager check-in. Career path discussion. Growth opportunity or external coaching.
---
## Recommended Stay Interventions
### Immediate (Next 30 days)
1. **Conduct stay interviews with high-risk employees**
- Ask: What's working? What would make you stay? What would make you leave?
- Listen; don't negotiate yet
- Document findings
2. **Compensation review for Q1 2025 cohort**
- All left by month 15; likely underpaid relative to market
- Benchmark salaries; identify compression vs. newer hires
3. **Manager 1:1s**
- Discuss engagement signals
- Train on retention conversations
- Flag burnout/overload in specific teams
### Short-term (30–90 days)
4. **Strengthen career pathing**
- Publish clear rubrics for promotion to L3, L4, etc.
- Schedule growth conversations with high-performers
- Offer stretch assignments
5. **Improve onboarding (Q1 2025 cohort learnings)**
- Review and fix onboarding process
- Extend ramp timeline if needed
- Add mentor support for first 90 days
6. **Compensation adjustments**
- For high-risk, regrettable departures: consider retention bonus or refresh
- Budget: $100K for 1–2 critical retention packages (cheaper than recruiting)
### Ongoing (6+ months)
7. **Culture and flexibility initiatives**
- Assess remote work policy
- Review work-life balance (on-call rotation, workload)
- Improve manager quality through training and feedback
---
## Retention ROI Analysis
**Cost of losing a senior engineer:**
- Recruiting: $6K
- Ramp for replacement: ~$50K (lost productivity, mentor time)
- Institutional knowledge loss: ~$20K (context, relationships)
- **Total: ~$76K**
**Cost of retention intervention (e.g., $10K bonus or 10% raise):**
- **$10K–15K**
**ROI:** Preventing one departure saves $60K+.
**Recommendation:** Invest in retention for high performers and critical roles. $100K retention budget (protecting 6–8 key people) likely prevents 2–3 departures, netting $120K+ in savings.
---
## Metrics Dashboard (Ongoing Tracking)
| Metric | Target | Current | Trend |
|--------|--------|---------|--------|
| Annual voluntary attrition | <13% | 8% | ✓ Green |
| Regrettable attrition (% of total) | <30% | 40% | ⚠️ Yellow (losing talent) |
| Retention at 6 months | >90% | 92% | ✓ Green |
| Retention at 12 months | >80% | 82% | ✓ Green |
| eNPS (employee engagement) | >40 | TBD | — |
---
## Next Steps
- [ ] Schedule stay interviews with 2 high-risk employees (by end of week)
- [ ] Conduct compensation benchmarking for Q1 2025 cohort (by EOG)
- [ ] Manager training on retention conversations (next 2 weeks)
- [ ] Publish career ladders and growth criteria (by end of quarter)
- [ ] Review onboarding process with team that had low retention (this sprint)
- [ ] Follow-up retention analysis (next quarter)
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