forecast-scenarios
Model best-case, worst-case, and likely revenue scenarios with sensitivity analysis for strategic planning. Use when: building financial forecasts; presenting board scenarios; planning headcount around revenue uncertainty; modeling pricing changes impact; preparing investor updates with upside/downside ranges
What this skill does
# 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
1. **Scenario definition** - Base, upside, downside cases
2. **Variable modeling** - Test impact of changing assumptions
3. **Sensitivity analysis** - Which variables matter most
4. **Probability weighting** - Expected value calculations
5. **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%)
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