FP&A Scenario Modeling

SkillCommerce & finance

Build structured 3-scenario financial models (Base / Bull / Bear) for business planning or investment decisions. Sensitize revenue and cost drivers across scenarios, produce P&L summaries, cash flow bridges, and executive narratives. Aligns with FP&A 2.0 and CIMA Management Accounting standards. Use when leadership needs to understand the financial impact range of a decision. Do not use for statutory financial reporting or audit-ready financials.

Use FP&A Scenario Modeling in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add FP&A Scenario Modeling and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the FP&A Scenario Modeling skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

FP&A Scenario ModelingStart free

What this skill tells your AI

The instructions your AI receives, as published by hoavdc/codexkit in skills/codexkit-fpa-scenario-modeling/SKILL.md and read by Ahel’s review.

Purpose

Transform business assumptions into a structured 3-scenario financial model that gives leadership a clear view of upside, baseline, and downside outcomes.

When to use

  • annual or quarterly business planning cycle
  • before a major investment decision (new product, M&A, expansion)
  • when the CFO asks "what if revenue drops 20%?"
  • presenting financial impact range to the board

When not to use

  • statutory financial reporting (IFRS/GAAP compliance)
  • audit-ready financial statements
  • daily operational cost tracking

Inputs

  • business model type (SaaS, retail, manufacturing, services)
  • historical financials (last 2–3 years if available)
  • key revenue drivers (pricing, volume, churn, expansion)
  • key cost drivers (headcount, COGS, marketing spend, capex)
  • specific decision context (what are we modeling?)
  • time horizon (12 months, 3 years, 5 years)

Procedure

  1. Define 3 scenarios:
    • Base Case: most likely outcome based on current trajectory
    • Bull Case: upside scenario (best 30% of outcomes)
    • Bear Case: downside/stress scenario (worst 20% of outcomes)
  2. Identify key variables to sensitize:
    • Revenue-side: growth rate, gross margin, CAC, churn rate, ASP
    • Cost-side: fixed cost base, variable cost as % revenue, capex, working capital (DSO, DPO, DIO)
  3. Build scenario assumption table — side-by-side comparison of all variables across 3 scenarios.
  4. Calculate P&L summary per scenario: Revenue → Gross Profit → EBITDA → Net Profit.
  5. Build cash flow bridge per scenario: Operating CF → Investing CF → Financing CF → Free CF.
  6. Calculate key metrics per scenario: EBITDA margin, ROI, Payback Period, Break-even point.
  7. Create sensitivity table — identify which single variable has the largest impact on outcome.
  8. Write executive narrative — "Under the base case, the business generates…" with clear decision implications.

Output

  • scenario assumption table (side-by-side, 3 columns)
  • P&L summary per scenario (Revenue → EBITDA → Net Profit)
  • cash flow bridge per scenario
  • key metrics comparison table
  • sensitivity analysis (which variable moves the needle most)
  • executive narrative (1–2 paragraphs per scenario)

Definition of done

  • all 3 scenarios have distinct, justified assumptions
  • P&L, cash flow, and key metrics are calculated for each scenario
  • sensitivity analysis identifies the top 3 swing variables
  • executive narrative is decision-ready (not just numbers)

Examples

  • "Model 3 scenarios for our SaaS expansion into Southeast Asia over 3 years."
  • "What happens to EBITDA if raw material costs increase 15% (bear case)?"
  • "Build a scenario model for the board comparing organic growth vs. acquisition."

Quality Criteria

  • Data sources and assumptions are explicitly stated
  • Calculations are reproducible from provided inputs
  • Visualizations or tables have clear labels, units, and time ranges
  • Caveats and confidence levels are documented for estimates

Verification (4C)

CheckQuestion
CorrectnessAre formulas, aggregations, and statistical methods applied correctly?
CompletenessDoes the analysis cover all requested metrics and time ranges?
Context-fitAre the chosen metrics relevant to the business question being answered?
ConsequenceIf this data were used for a decision today, what blind spots remain?

Edge Cases

  • Missing or incomplete data — Document gaps and their potential impact on conclusions. Provide ranges instead of point estimates.
  • Outliers skewing results — Report with and without outliers. Document the decision to include or exclude.
  • Changing data definitions mid-period — Split analysis at the change boundary and note the schema difference.

Changelog

  • v1.0.0 — Initial release

Signals

GitHub stars
25
Forks
13
Last commit
Oct 2026
Advanced
Item type
skill
Key
codexkit-fpa-scenario-modeling
Source
github.com/hoavdc/codexkit