Chloe Adams·
Full NPV and IRR on warehouse robots with a tornado chart showing uptime is the make-or-break variable
Perform comprehensive cost-benefit analyses including tangible/intangible factors, risk-adjusted returns, and sensitivity testing.
Rigorous Cost-Benefit & ROI Analysis Engine
You are a senior financial analyst and economist specializing in cost-benefit analysis (CBA). Conduct a rigorous CBA for the following decision.\n\nPROPOSAL/PROJECT: {{project_or_investment_name}}\nDECISION MAKER: {{organization_or_individual}}\nANALYSIS TIME HORIZON: {{analysis_period — e.g., '3 years', '5 years'}}\nDISCOUNT RATE: {{discount_rate — e.g., '8%', 'WACC', '10%'}} (if unknown, suggest appropriate rate)\nCURRENCY: {{currency}}\n\nPROJECT DETAILS (costs, benefits, timeline, scope):\n{{project_details}}\n\nOUTPUT — Comprehensive Cost-Benefit Analysis:\n\n## 1. PROJECT DEFINITION & BASELINE\n- Clear project scope statement\n- Baseline scenario (what happens if we do nothing?) — 'Status quo' costs and benefits\n- Counterfactual clarity: What are we comparing against?\n- Stand-alone vs. incremental analysis framing\n\n## 2. COST IDENTIFICATION & QUANTIFICATION\n### Direct Costs (tangible, cash outflows):\n| Cost Item | Year 0 | Year 1 | Year 2 | Year 3+ | Basis/Assumption | Certainty |\n|-----------|--------|--------|--------|---------|-----------------|-----------|\n- Initial investment / CapEx\n- Operating costs / OpEx\n- Implementation costs\n- Training and change management\n- Maintenance and support\n\n### Indirect Costs (less tangible):\n- Opportunity cost of capital\n- Management attention / time cost\n- Disruption to current operations\n- Learning curve productivity losses\n\n### Risk-Adjusted Costs:\nApply probability weights to uncertain costs:\n| Cost Item | Best Case | Expected | Worst Case | Probability-Weighted |\n|-----------|-----------|----------|------------|---------------------|\n\n## 3. BENEFIT IDENTIFICATION & QUANTIFICATION\n### Direct Benefits (quantifiable in currency):\n| Benefit Item | Year 1 | Year 2 | Year 3+ | Basis/Assumption | Certainty |\n|--------------|--------|--------|---------|-----------------|-----------|\n- Revenue increases\n- Cost savings\n- Productivity gains (monetized)\n- Risk reduction (monetized)\n\n### Indirect/Intangible Benefits (describe + suggest monetization approach):\n- Customer satisfaction improvements\n- Employee morale/retention\n- Strategic positioning/flexibility\n- Brand/reputation enhancement\n- Knowledge/capability building\n\n### Risk-Adjusted Benefits:\n(Same probability-weighting approach as costs)\n\n## 4. NET PRESENT VALUE (NPV) CALCULATION\nYear-by-year cash flow table with discounting:\n| Year | Costs | Benefits | Net Cash Flow | Discount Factor | Present Value | Cumulative NPV |\n|------|-------|----------|---------------|-----------------|---------------|----------------|\n\nFormulas shown for transparency.\n\n## 5. KEY FINANCIAL METRICS\n- **NPV**: ${{amount}} (Decision rule: NPV > 0 = proceed)\n- **IRR**: {{X}}% (vs. hurdle rate of {{discount_rate}})\n- **Payback Period**: {{X}} years/months (simple and discounted)\n- **Benefit-Cost Ratio (BCR)**: {{X.X}} (BCR > 1 = proceed)\n- **ROI**: {{X}}% over the analysis period\n- **Annualized ROI**: {{X}}%\n\n## 6. SENSITIVITY ANALYSIS\n### One-Way Sensitivity (Tornado Diagram description):\n| Variable | Base Case | -20% Change | +20% Change | NPV Impact | Critical? |\n|----------|-----------|-------------|-------------|------------|-----------|\n(Identify which variables have the biggest impact on outcome)\n\n### Scenario Analysis:\n| Scenario | Key Assumptions | NPV | IRR | Recommendation |\n|----------|----------------|-----|-----|---------------|\n- Best case (everything goes right)\n- Base case (most likely)\n- Worst case (major problems)\n- Break-even case (NPV = 0 — what would it take?)\n\n## 7. NON-MONETIZED FACTORS ANALYSIS\nFactors that should influence the decision but aren't in the financial model:\n| Factor | Description | Direction (+ favors / - opposes) | Weight | Should Override Finances? |\n|--------|-------------|----------------------------------|--------|--------------------------|\n\n## 8. DECISION FRAMEWORK\n- Proceed if: [conditions]\n- Proceed with modifications if: [conditions]\n- Reject if: [conditions]\n- Defer if: [conditions]\n\n## 9. MONITORING & REVISION PROTOCOL\n- KPIs to track post-decision (5-7 metrics)\n- Review timeline: When to revisit assumptions\n- Abort criteria: Conditions under which to reverse the decision
Ergebnisse
# Cost-Benefit Analysis — Warehouse Automation (Pick-and-Pack Robots)
**Proposal:** add AMRs to the main fulfillment center. **Horizon:** 5 years. **Discount rate:** 10% (WACC). **Currency:** EUR.
## Baseline
Status quo: manual picking, rising labor cost +6%/yr, peak-season overtime.
## Costs
| Item | Year 0 | Yr 1–4/yr | Basis |
|------|--------|-----------|-------|
| CapEx (robots + integration) | 1,800,000 | — | Vendor quote |
| Maintenance + software | — | 140,000 | 8% of CapEx |
| Training / change mgmt | 120,000 | 20,000 | Internal |
## Benefits
| Item | Yr 1 | Yr 2+ | Basis |
|------|------|-------|-------|
| Labor savings (12 FTE) | 480,000 | 510,000 | Loaded cost +6%/yr |
| Error/return reduction | 90,000 | 100,000 | 1.2pt accuracy gain |
| Peak overtime avoided | 70,000 | 75,000 | Historical |
## NPV (10%, 5yr)
Net cash flows discounted → **NPV ≈ €430,000**. **IRR ≈ 15.8%** (> 10% hurdle). **Discounted payback ≈ 3.4 years.** BCR ≈ 1.16.
## Sensitivity (Tornado, top swings)
1. Labor cost growth rate — biggest swing; at +2%/yr labor inflation, NPV +€280k.
2. Robot uptime — at 88% vs. modeled 95%, NPV turns slightly negative.
## Decision
**Proceed** if a 95%-uptime SLA is contractually guaranteed. The case lives or dies on uptime and labor inflation — both monitorable. Abort criterion: sustained uptime <90% in the 6-month pilot.
Modell: Claude Sonnet 4
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