forecast-scenarios
О программе
Этот навык позволяет разработчикам моделировать оптимистичные, пессимистичные и наиболее вероятные сценарии доходов с помощью анализа чувствительности для финансового планирования. Он идеально подходит для построения прогнозов, представления сценариев совету директоров и планирования в условиях неопределенности доходов. Инструмент включает такие методологии, как моделирование базового/оптимистичного/пессимистичного сценариев и метод Монте-Карло для стратегической оценки рисков.
Быстрая установка
Claude Code
Рекомендуетсяnpx skills add guia-matthieu/clawfu-skills -a claude-code/plugin add https://github.com/guia-matthieu/clawfu-skillsgit clone https://github.com/guia-matthieu/clawfu-skills.git ~/.claude/skills/forecast-scenariosСкопируйте и вставьте эту команду в Claude Code для установки этого навыка
Документация
Forecast Scenario Modeling
Create multiple revenue scenarios with variable assumptions to support strategic planning, board presentations, and risk management.
When to Use This Skill
- Annual and quarterly planning
- Board meeting preparations
- Fundraising projections
- Risk assessment and contingency planning
- Evaluating strategic initiatives
Methodology Foundation
Based on McKinsey Scenario Planning and FP&A best practices, combining:
- Base/Bull/Bear case modeling
- Sensitivity analysis (variable impact)
- Monte Carlo probability distributions
- Driver-based forecasting
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Structures scenario framework | Assumption values |
| Calculates scenario outcomes | Which scenario to plan for |
| Identifies key sensitivities | Risk tolerance levels |
| Models variable impacts | Strategic responses |
| Presents range of outcomes | Final forecast commitment |
What This Skill Does
- Scenario definition - Base, upside, downside cases
- Variable modeling - Test impact of changing assumptions
- Sensitivity analysis - Which variables matter most
- Probability weighting - Expected value calculations
- Action planning - What to do in each scenario
How to Use
Model revenue scenarios for [Period]:
Current Status:
- YTD Revenue: $X
- Current Pipeline: $X
- Run Rate: $X/month
Key Variables to Model:
- Win rate: [Current: X%, Range: X-X%]
- Average deal size: [Current: $X, Range: $X-$X]
- Sales cycle: [Current: X days, Range: X-X]
- New pipeline creation: [Current: $X/month]
- Churn rate: [Current: X%]
Create best, likely, and worst case scenarios.
Instructions
Step 1: Define Scenario Framework
| Scenario | Definition | Probability |
|---|---|---|
| Best Case (Bull) | Everything goes right | 15-20% |
| Likely Case (Base) | Realistic expectations | 50-60% |
| Worst Case (Bear) | Major headwinds | 20-25% |
Step 2: Identify Key Drivers
Rank variables by revenue impact:
| Driver | Impact | Controllability |
|---|---|---|
| Win rate | High | Medium |
| Pipeline volume | High | High |
| Deal size | Medium | Low |
| Sales cycle | Medium | Medium |
| Churn rate | Medium | Medium |
| Pricing | Low | High |
Step 3: Set Variable Ranges
For each driver, define realistic bounds:
Win Rate:
- Best: 35% (team is hitting stride)
- Likely: 25% (current performance)
- Worst: 18% (market headwinds)
Pipeline:
- Best: $5M (strong marketing)
- Likely: $4M (normal cadence)
- Worst: $2.5M (budget cuts)
Step 4: Calculate Scenarios
Revenue Formula (simplified):
Quarterly Revenue =
(Pipeline × Win Rate) +
(Expansion Revenue) -
(Churn)
Apply to each scenario:
Best Case:
$5M × 35% = $1.75M new + $200K expansion - $50K churn
= $1.9M
Likely Case:
$4M × 25% = $1M new + $150K expansion - $80K churn
= $1.07M
Worst Case:
$2.5M × 18% = $450K new + $100K expansion - $120K churn
= $430K
Step 5: Sensitivity Analysis
Test: "What if X changes by 10%?"
| Variable | +10% Impact | -10% Impact | Sensitivity |
|---|---|---|---|
| Win Rate | +$100K | -$100K | High |
| Pipeline | +$90K | -$90K | High |
| Deal Size | +$50K | -$50K | Medium |
| Churn | -$30K | +$30K | Medium |
Step 6: Calculate Expected Value
Expected Revenue =
(Best × Probability) +
(Likely × Probability) +
(Worst × Probability)
= ($1.9M × 20%) + ($1.07M × 55%) + ($430K × 25%)
= $380K + $589K + $108K
= $1.077M
Examples
Example 1: Quarterly Forecast Scenarios
Input:
Model Q2 scenarios:
Current Status:
- Q1 Revenue: $850K
- Q2 Pipeline: $4.2M
- Monthly run rate: $280K
Variables:
- Win rate: Current 24%, Range 18-32%
- Avg deal: Current $45K, Range $38K-$55K
- New monthly pipeline: Current $800K, Range $500K-$1.2M
- Monthly churn: Current $25K, Range $15K-$40K
- Expansion: Current $50K/month, Range $30K-$80K
Output:
## Q2 Revenue Scenario Model
### Scenario Definitions
| Scenario | Probability | Description |
|----------|-------------|-------------|
| 🐂 Bull | 20% | Strong execution, market tailwinds |
| 📊 Base | 55% | Continue current trajectory |
| 🐻 Bear | 25% | Market slowdown, execution challenges |
### Variable Assumptions
| Variable | Bear | Base | Bull |
|----------|------|------|------|
| Starting Pipeline | $4.2M | $4.2M | $4.2M |
| Win Rate | 18% | 24% | 32% |
| Avg Deal Size | $38K | $45K | $55K |
| New Pipeline/mo | $500K | $800K | $1.2M |
| Monthly Churn | $40K | $25K | $15K |
| Expansion/mo | $30K | $50K | $80K |
### Q2 Revenue Calculations
#### 🐂 Bull Case: $1.42M
Starting Pipeline Revenue: $4.2M × 32% = $1.34M
Adjustment for deal size: $1.34M × ($55K/$45K) = $1.64M effective
New Pipeline Added (Q2): $1.2M × 3 months × 32% × 50% (partial close) = $576K
Expansion: $80K × 3 = $240K
Churn: -$15K × 3 = -$45K
Total Bull: $1.64M (existing) + $576K (new) + $240K (exp) - $45K (churn) Weighted at Q2 stage: $1.42M
#### 📊 Base Case: $980K
Starting Pipeline Revenue: $4.2M × 24% = $1.01M
New Pipeline (partial close): $800K × 3 × 24% × 50% = $288K
Expansion: $150K Churn: -$75K
Total Base: $1.01M × 0.9 (timing) + $150K - $75K = $980K
#### 🐻 Bear Case: $580K
Starting Pipeline Revenue: $4.2M × 18% = $756K × 0.85 (pushed deals) = $643K
New Pipeline: $500K × 3 × 18% × 40% = $108K Expansion: $90K Churn: -$120K
Total Bear: $580K
### Scenario Summary
| Scenario | Revenue | vs Q1 | Growth |
|----------|---------|-------|--------|
| 🐂 Bull | $1.42M | +$570K | +67% |
| 📊 Base | $980K | +$130K | +15% |
| 🐻 Bear | $580K | -$270K | -32% |
### Expected Value
E(Revenue) = ($1.42M × 0.20) + ($980K × 0.55) + ($580K × 0.25) = $284K + $539K + $145K = $968K
**Recommended Forecast: $950K - $1.0M**
### Sensitivity Analysis
| If This Changes... | Revenue Impact |
|--------------------|----------------|
| Win rate +5% | +$210K |
| Win rate -5% | -$210K |
| Pipeline +$500K | +$120K |
| Deal size +$5K | +$80K |
| Churn +$10K/mo | -$30K |
**Highest Sensitivity**: Win rate (focus on deal execution)
### Scenario Action Plans
**If Trending Bull:**
- Accelerate hiring plan
- Increase marketing spend
- Prepare for capacity constraints
**If Trending Base:**
- Stay the course
- Focus on execution
- Build pipeline for Q3
**If Trending Bear:**
- Tighten expense controls
- Extend runway calculations
- Double down on existing customers
- Consider discounting to close deals
Example 2: Annual Planning Scenarios
Input:
Model 2026 annual scenarios for board:
2025 Results:
- Revenue: $4.2M
- Customers: 85
- ARR Growth: 45%
- NRR: 110%
2026 Planning Variables:
- New customer target: 40-80 new customers
- ACV range: $40K-$60K
- NRR range: 105%-120%
- Churn range: 5%-12%
Output:
## 2026 Annual Revenue Scenarios
### For Board Review
---
### Scenario Summary
| Metric | Bear | Base | Bull |
|--------|------|------|------|
| New Customers | 40 | 60 | 80 |
| New ACV | $40K | $50K | $60K |
| New ARR | $1.6M | $3.0M | $4.8M |
| NRR | 105% | 112% | 120% |
| Existing Base | $4.41M | $4.70M | $5.04M |
| **Total ARR** | **$6.0M** | **$7.7M** | **$9.8M** |
| **Growth** | **43%** | **83%** | **133%** |
### Detailed Calculations
#### 🐻 Bear Case: $6.0M ARR (+43%)
**Assumptions:**
- Conservative new sales (40 customers)
- Lower ACV ($40K avg)
- NRR dips (105%)
- Higher churn (10%)
Existing Customer Base: $4.2M × 105% NRR = $4.41M
New Customer Revenue: 40 customers × $40K = $1.6M
Total: $6.0M
**When This Happens:**
- Market downturn
- Sales execution issues
- Product-market fit challenges
- Key competitor gains ground
---
#### 📊 Base Case: $7.7M ARR (+83%)
**Assumptions:**
- Target new sales (60 customers)
- Target ACV ($50K)
- Maintain NRR (112%)
- Normal churn (7%)
Existing Customer Base: $4.2M × 112% NRR = $4.70M
New Customer Revenue: 60 customers × $50K = $3.0M
Total: $7.7M
**This Is Likely If:**
- Execute at current pace
- Market conditions stable
- Product roadmap delivers
- Team retention healthy
---
#### 🐂 Bull Case: $9.8M ARR (+133%)
**Assumptions:**
- Exceed targets (80 customers)
- Premium ACV ($60K)
- Strong NRR (120%)
- Low churn (5%)
Existing Customer Base: $4.2M × 120% NRR = $5.04M
New Customer Revenue: 80 customers × $60K = $4.8M
Total: $9.8M
**Required For This:**
- Strong product releases
- Successful enterprise push
- Favorable market timing
- Key hires perform
---
### Expected Value & Recommendation
E(ARR) = ($6.0M × 0.20) + ($7.7M × 0.55) + ($9.8M × 0.25) = $1.2M + $4.24M + $2.45M = $7.89M
### Board Recommendation
**Target: $7.5M ARR** (+79% growth)
| Metric | Target | Confidence |
|--------|--------|------------|
| New Customers | 55-60 | Medium-High |
| New ARR | $2.75M | Medium |
| NRR | 110%+ | High |
| Total ARR | $7.5M | Medium |
### Key Risks & Mitigations
| Risk | Impact | Mitigation |
|------|--------|------------|
| Sales hiring delays | -$1M | Recruit pipeline now |
| Enterprise deals push | -$800K | Parallel SMB motion |
| Key customer churn | -$500K | CSM investment |
| Competitor pricing | -$600K | Value selling training |
### Monthly Checkpoints
| Month | Bear | Base | Bull |
|-------|------|------|------|
| Q1 End | $4.8M | $5.2M | $5.8M |
| Q2 End | $5.3M | $6.2M | $7.4M |
| Q3 End | $5.6M | $7.0M | $8.6M |
| Q4 End | $6.0M | $7.7M | $9.8M |
Track monthly and adjust Q3 if trending to Bear.
Skill Boundaries
What This Skill Does Well
- Structuring scenario frameworks
- Calculating outcomes from assumptions
- Identifying key sensitivities
- Presenting range of possibilities
What This Skill Cannot Do
- Predict which scenario will occur
- Know your specific business dynamics
- Account for black swan events
- Replace expert judgment on probabilities
When to Escalate to Human
- Setting official targets
- Board/investor commitments
- Major strategic pivots
- Assumptions requiring domain expertise
Iteration Guide
Follow-up Prompts
- "What win rate do we need to hit Base case?"
- "Show me monthly revenue trajectory for each scenario."
- "Add a 'catastrophic' case if we lose our biggest customer."
- "What's the probability-weighted forecast?"
Scenario Planning Cycle
- Set variables and ranges
- Calculate scenarios
- Identify early warning signals
- Define trigger points for action
- Review monthly against actuals
Checklists & Templates
Annual Planning Template
## [Year] Revenue Scenarios
### Scenarios
| Case | Revenue | Growth | Probability |
|------|---------|--------|-------------|
| Bull | | | 20% |
| Base | | | 55% |
| Bear | | | 25% |
### Key Assumptions
| Variable | Bear | Base | Bull |
|----------|------|------|------|
### Sensitivity Analysis
| Variable | Impact per 10% |
|----------|----------------|
### Risk Register
| Risk | Scenario Impact | Mitigation |
|------|-----------------|------------|
References
- McKinsey Scenario Planning Guide
- FP&A Forecasting Best Practices
- SaaS Metrics and Financial Modeling
- CFO.com Revenue Forecasting
Related Skills
pipeline-forecasting- Feed into scenario modelslead-scoring- Input for pipeline assumptionsaccount-health- NRR/churn inputs
Skill Metadata
- Domain: RevOps
- Complexity: Advanced
- Mode: centaur
- Time to Value: 60-90 min for full model
- Prerequisites: Historical data, variable assumptions
GitHub репозиторий
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