Fictional Case Study: Reducing Avoidable Turnover at XY Financial
Summary
Key Result
With 25,000 employees at 17% attrition, XY Financial turned a costly annual problem into a data-backed, quarterly savings plan worth $5–7M per quarter, using transparent risk scoring, horizon-scaled economics, and scenario testing.
Company Profile
| Attribute | Details |
|---|---|
| Company | XY Financial (fictional, based on real project scale) |
| Industry | Financial Services |
| Employees | 25,000 |
| Baseline Attrition | ~17% annually (≈4,250 exits/year) |
| Goal | Reduce costly turnover and evaluate ROI of proactive retention programs under financial constraints |
1. Business Problem
XY was losing ~4,250 employees per year, straining recruitment and productivity. Replacing each leaver cost well over a year's salary when accounting for:
- Hiring costs
- Onboarding expenses
- Lost productivity
HR wanted to pilot targeted interventions (e.g., manager coaching, workload adjustments, retention bonuses), but Finance insisted on a rigorous, data-backed business case before releasing budget.
2. Approach Using the Predictor App
We used the Attrition Savings Predictor to:
- Estimate risk of departure for every employee (25k rows scored)
- Compare intervention strategies: fixed risk thresholds vs Top-K targeting
- Apply horizon scaling (quarterly vs annual) so CFOs saw costs and savings on a realistic budget lens
- Run what-if scenarios (reducing workload, improving manager quality) to simulate program levers
- Locate the "economically optimal threshold" — where expected savings outweigh costs the most
3. Assumptions & Parameters
Financial Parameters
- Replacement cost: 1.2× annual salary (scaled to horizon)
- Average salary: $82,000
- Effective replacement cost (annual view): ~$98,400
- Intervention cost: $750 per participant (lump sum)
- Effectiveness: 30–35% (probability that a likely leaver stays if treated)
- Planning horizon: tested annual vs quarterly
Model Performance
| Metric | Value | Interpretation |
|---|---|---|
| AUC (ROC) | ~0.68 | Good ranking ability |
| Precision @ Top 10% | ~0.41 | 4 out of 10 flagged will actually leave |
| Lift (Top 10% vs baseline) | ~2.4× | Top 10% risk group 2.4× more likely to leave |
| Calibration | ±3 points | Predicted risk matches observed outcomes |
4. Strategy Experiments
A) Threshold-Based Plan
- Threshold: ~0.28
- Employees flagged: ~6,000
- Expected true leavers: ~1,400
Savings (Annual View)
| Component | Calculation | Amount |
|---|---|---|
| Gross prevented attrition | 1,400 × 0.35 × $98,400 | $48M |
| Intervention cost | 6,000 × $750 | $4.5M |
| Net savings | Gross - Cost | $43.5M |
B) Top-K Strategy (Top 15%, Coverage 60%)
- Cohort: 25,000 × 15% × 60% ≈ 2,250 treated employees
- Characteristics: Riskier group than threshold baseline; higher precision
- Net savings (annual view): ~$21M
- Quarterly horizon: drops to ~$5.2M, but still positive ROI
C) What-If Leverage
Applied improvements to treated cohort: - Workload reduction: -1.0 - Manager quality improvement: +0.5
Results
- Aggregate risk delta: ~24 points reduction
- Δ Net savings: +$6M annually vs baseline plan
- Key insight: Gain achieved without extra per-head program cost — from shifting predictors the model recognized as causal
5. Outcome & Decision
Executive Decision
- Chose: Top-K pilot (15% × 60% coverage) in two divisions
- Horizon: 3-month scaling for budget-relevant costs and benefits
- Finance approval: Based on app-demonstrated ROI
Financial Justification
| Scenario | Quarterly Savings |
|---|---|
| Baseline ROI | ~$5.2M |
| With What-If Applied | ~$7M |
Implementation
- HR built an A/B test into the pilot to validate the assumed 30–35% effectiveness
6. Key Learnings
Scale Impact
Scale is everything. At 25k headcount, even modest effect sizes create multi-million dollar swings.
Transparency Value
Transparency matters. CFOs trusted the threshold breakeven formula and auditors valued the calibrated logistic regression.
Financial Alignment
Horizon scaling bridged HR and Finance. Annual savings looked huge, but quarterly scaling made it realistic for cashflow planning.
Targeting Efficiency
Targeted interventions pay. Top-K + Coverage gave tighter ROI than a blunt threshold.
Note
This case study is entirely fictional and "XY Financial" does not exist to my knowledge.