/forecast-scenarios

name: forecast-scenarios
description: "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"
license: MIT
metadata:
  author: ClawFu
  version: 1.0.0
  mcp-server: "@clawfu/mcp-skills"

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

Tota