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

Variable Assumptions

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

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

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

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)

Key Risks & Mitigations

Monthly Checkpoints

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

Key Assumptions

Sensitivity Analysis

Risk Register

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 models

• lead-scoring

• Input for pipeline assumptions

• account-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