スキル一覧に戻る

forecast-scenarios

guia-matthieu
更新日 2 days ago
8 閲覧
111
20
111
GitHubで表示
メタaidesign

について

このスキルは、財務計画のための感度分析を用いて、開発者が最良シナリオ、最悪シナリオ、および想定収益シナリオをモデル化することを可能にします。予測の構築、取締役会向けシナリオの提示、収益の不確実性を考慮した計画策定に最適です。本ツールは、ベースケース/強気シナリオ/弱気シナリオのモデリングや、戦略的リスク評価のためのモンテカルロシミュレーションなどの手法を組み込んでいます。

クイックインストール

Claude Code

推奨
メイン
npx skills add guia-matthieu/clawfu-skills -a claude-code
プラグインコマンド代替
/plugin add https://github.com/guia-matthieu/clawfu-skills
Git クローン代替
git clone https://github.com/guia-matthieu/clawfu-skills.git ~/.claude/skills/forecast-scenarios

このコマンドをClaude Codeにコピー&ペーストしてスキルをインストールします

ドキュメント

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 DoesYou Decide
Structures scenario frameworkAssumption values
Calculates scenario outcomesWhich scenario to plan for
Identifies key sensitivitiesRisk tolerance levels
Models variable impactsStrategic responses
Presents range of outcomesFinal 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

ScenarioDefinitionProbability
Best Case (Bull)Everything goes right15-20%
Likely Case (Base)Realistic expectations50-60%
Worst Case (Bear)Major headwinds20-25%

Step 2: Identify Key Drivers

Rank variables by revenue impact:

DriverImpactControllability
Win rateHighMedium
Pipeline volumeHighHigh
Deal sizeMediumLow
Sales cycleMediumMedium
Churn rateMediumMedium
PricingLowHigh

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% ImpactSensitivity
Win Rate+$100K-$100KHigh
Pipeline+$90K-$90KHigh
Deal Size+$50K-$50KMedium
Churn-$30K+$30KMedium

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

  1. Set variables and ranges
  2. Calculate scenarios
  3. Identify early warning signals
  4. Define trigger points for action
  5. 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 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

GitHub リポジトリ

guia-matthieu/clawfu-skills
パス: skills/revops/forecast-scenarios
0
ai-skillsanthropicclaude-codeclaude-skillsmarketingmcp-server

関連スキル

content-collections

メタ

このスキルは、Content Collections(Markdown/MDXファイルを型安全なデータコレクションに変換するTypeScriptファーストのツール)の本番環境でテストされた設定を提供します。Zodバリデーションによる型安全性を実現し、ブログ、ドキュメントサイト、コンテンツ重視のVite + Reactアプリケーション構築時にご利用ください。Viteプラグインの設定、MDXコンパイルから、デプロイ最適化、スキーマバリデーションまで、すべてを網羅しています。

スキルを見る

polymarket

メタ

このスキルは、開発者がPolymarket予測市場プラットフォームを活用したアプリケーション構築を可能にします。API統合による取引や市場データの取得に加え、WebSocketを介したリアルタイムデータストリーミングにより、ライブ取引や市場活動を監視できます。取引戦略の実装や、ライブ市場更新を処理するツールの作成にご利用ください。

スキルを見る

creating-opencode-plugins

メタ

このスキルは、開発者がコマンド、ファイル、LSP操作など25種類以上のイベントタイプにフックするOpenCodeプラグインを作成することを支援します。JavaScript/TypeScriptモジュール向けに、プラグイン構造、イベントAPI仕様、および実装パターンを提供します。カスタムイベント駆動ロジックでOpenCode AIアシスタントのライフサイクルをインターセプト、監視、または拡張する必要がある場合にご利用ください。

スキルを見る

sglang

メタ

SGLangは、高性能なLLMサービングフレームワークであり、RadixAttentionプレフィックスキャッシュを活用したJSON、正規表現、エージェントワークフロー向けの高速で構造化された生成を特長とします。特にプレフィックスが繰り返されるタスクにおいて、大幅に高速な推論を実現し、複雑な構造化出力やマルチターン対話に最適です。制約付きデコードが必要な場合や、広範なプレフィックス共有を伴うアプリケーションを構築する場合は、vLLMなどの代替案ではなくSGLangを選択してください。

スキルを見る