financial-forecasting

Financial Forecasting

You create financial forecasts projecting future financial performance. You research market benchmarks and comparable company data yourself — do not ask the user for data they would need to look up. Only ask the user for decisions and confirmations.

This skill complements cost-benefit-analysis (which evaluates specific decisions) and roi-modeling (which calculates returns) by projecting the overall financial trajectory of a business or project.

Forecasting Methods

Method	Approach	Best for
Straight-line	Constant growth rate projection	Mature, stable businesses
Growth rate	Linear, exponential, or S-curve	Growth-stage businesses
Driver-based	Key drivers → financial outcomes	Complex businesses with clear operational metrics
Bottom-up	Units × price, customers × ARPU	Businesses with known unit economics
Top-down	Market size × market share	Early-stage or market entry
Hybrid	Bottom-up + top-down triangulation	Most accurate for established businesses

Phase 1 — Setup

Input handling

Follow shared foundation §7 — interview mode. When input is missing or insufficient, interview to gather at minimum:

Dimension	Required	Default
Business/project context	Yes	—
Historical financial data	No	Will use research + benchmarks
Business model	No	Inferred from context
Time horizon	No	3 years
Granularity	No	Monthly Y1, quarterly Y2-3
Key drivers	No	Will be identified

Exit interview when: Business context is clear enough to identify revenue model, cost structure, and key drivers.

1. Collect input

Accept one of:

• A business or project description
• A file path to historical financial data or existing forecasts
• Pasted financial data or business case content
• No input or vague input → enter interview mode

2. Detect scope

From the input, identify:

• Business: What the business or project is
• Revenue model: How it makes money (subscription, transactional, marketplace, etc.)
• Stage: Pre-revenue / early / growth / mature
• Data availability: Historical data provided or research-based
• Time horizon: Forecast period (default: 3 years)
• Granularity: Monthly Y1, quarterly Y2-3 (adjustable)

3. Confirm scope

**Business**: [name]
**Revenue model**: [type]
**Stage**: [pre-revenue / early / growth / mature]
**Data source**: [historical data / research-based]
**Time horizon**: [N years]
**Granularity**: [monthly Y1, quarterly Y2-3]

Ask the user to confirm or adjust. Ask diagram render mode and output path per the diagram-rendering and autonomous-research mixins.

Phase 2 — Research

Use WebSearch and WebFetch per the autonomous-research mixin.

2a. Industry benchmarks

• Gross margins, operating margins, net margins for the industry
• Revenue growth rates for comparable companies
• Cost structure benchmarks (COGS %, OpEx % of revenue)
• Industry-specific ratios and KPIs

2b. Comparable company data

• Public company financials in the same space
• Startup benchmarks (if early-stage): typical burn rates, funding milestones
• Unit economics benchmarks: CAC, LTV, churn rates for the industry

2c. Market context

• Market growth rates and trends
• Pricing benchmarks
• Seasonal patterns (if applicable)

Phase 3 — Business Model Analysis

Revenue model identification

Model	Revenue formula	Key drivers
Subscription/SaaS	Customers × ARPU; MRR/ARR with churn	New sales, expansion, contraction, churn rate
Transactional	Transactions × average order value	Traffic, conversion rate, AOV
Marketplace	GMV × take rate	Buyers, sellers, GMV, take rate
Licensing	Licenses × price; maintenance/support	New licenses, renewals, support contracts
Services	Consultants × utilization × rate	Headcount, utilization rate, bill rate
Freemium	Free users × conversion rate × ARPU	User base, conversion, monetization

Cost structure mapping

Category	Type	Driver
COGS	Variable	Per unit or % of revenue
Salaries	Fixed (stepped)	Headcount × avg salary; hiring plan
Marketing	Semi-variable	Budget + % of revenue
Infrastructure	Semi-variable	Base + per-user/per-transaction scaling
Rent/office	Fixed	Lease terms, escalation
R&D	Fixed (stepped)	Engineering headcount

Key driver identification

Identify 3-7 operational metrics that drive financial outcomes. Examples:

• Website visitors → conversion rate → customers → ARPU → revenue
• Sales team size → demos/month → close rate → new ARR
• Market size → market share → addressable revenue

Present business model summary for user confirmation.

Phase 4 — Revenue Forecast

Method selection

Choose based on data availability and business stage:

• Pre-revenue: top-down or assumption-based bottom-up
• Early stage with some data: bottom-up + growth rate
• Established with history: driver-based or hybrid

SaaS/Subscription revenue model

Component	Calculation	Period
Beginning MRR	Previous period ending MRR	Monthly
+ New MRR	New customers × ARPU	Monthly
+ Expansion MRR	Upsells, upgrades	Monthly
- Contraction MRR	Downgrades	Monthly
- Churned MRR	Lost customers × their ARPU	Monthly
= Ending MRR	Sum	Monthly
ARR	Ending MRR × 12	Annual

Revenue table

Period	[Segment 1]	[Segment 2]	Total Revenue	Growth %
M1	[amount]	[amount]	[total]	—
M2	[amount]	[amount]	[total]	[%]

Monthly for Year 1, quarterly for Years 2-3 (or as specified).

Phase 5 — Expense Forecast

Fixed costs

Item	Monthly	Annual	Escalation	Notes
[item]	[amount]	[amount]	[% per year]	[justification]

Variable costs

Item	Unit cost	Driver	Formula	Notes
[item]	[amount]	[metric]	[unit cost × driver]	[justification]

Semi-variable costs

Item	Fixed base	Variable component	Formula	Notes
[item]	[amount]	[rate × driver]	[base + variable]	[justification]

Headcount plan (if applicable)

Role	Start	Hires Q1	Q2	Q3	Q4	Y2	Y3	Salary

Total expense table

Period	COGS	Salaries	Marketing	Infrastructure	Other OpEx	Total

Phase 6 — P&L Projection

Line item	Y1	Y2	Y3	Benchmark
Revenue	[amount]	[amount]	[amount]	—
COGS	[amount]	[amount]	[amount]	[% of rev]
Gross Profit	[amount]	[amount]	[amount]	—
Gross Margin %	[%]	[%]	[%]	[industry %]
Operating Expenses	[amount]	[amount]	[amount]	—
EBIT	[amount]	[amount]	[amount]	—
Operating Margin %	[%]	[%]	[%]	[industry %]
Interest & Tax	[amount]	[amount]	[amount]	—
Net Income	[amount]	[amount]	[amount]	—
Net Margin %	[%]	[%]	[%]	[industry %]

Flag margins that deviate significantly from industry benchmarks.

Phase 7 — Cash Flow Forecast

Operating cash flow

Item	Y1	Y2	Y3
Net Income	[amount]	[amount]	[amount]
+ Depreciation/Amortization	[amount]	[amount]	[amount]
+ Working capital changes	[amount]	[amount]	[amount]
Operating Cash Flow	[amount]	[amount]	[amount]

Investing cash flow

Item	Y1	Y2	Y3
Capital expenditure	[amount]	[amount]	[amount]
Investing Cash Flow	[amount]	[amount]	[amount]

Financing cash flow

Item	Y1	Y2	Y3
Funding / loans	[amount]	[amount]	[amount]
Repayments	[amount]	[amount]	[amount]
Financing Cash Flow	[amount]	[amount]	[amount]

Cash position

Period	Net Cash Flow	Cumulative Cash	Burn Rate (monthly)	Runway (months)

Burn rate = total monthly cash outflow (for pre-profit companies) Runway = cash balance / monthly net burn rate

Phase 8 — Unit Economics

Metric	Y1	Y2	Y3	Benchmark
CAC	[amount]	[amount]	[amount]	[industry]
LTV	[amount]	[amount]	[amount]	[industry]
LTV:CAC	[ratio]	[ratio]	[ratio]	≥ 3:1
CAC Payback	[months]	[months]	[months]	< 12 months
Gross Margin	[%]	[%]	[%]	[industry]
Contribution Margin	[amount]	[amount]	[amount]	—

Formulas

• CAC = Total Sales & Marketing / New Customers
• LTV = (ARPU × Gross Margin %) / Monthly Churn Rate
• LTV:CAC = LTV / CAC (target ≥ 3:1, flag if < 1.5:1)
• CAC Payback = CAC / (Monthly ARPU × Gross Margin %)

Show evolution over time — unit economics should improve as the business scales.

Phase 9 — Scenario Modeling

Scenario definitions

Parameter	Best case	Base case	Worst case
Revenue growth	[higher]	[expected]	[lower]
Churn rate	[lower]	[expected]	[higher]
Customer acquisition	[faster]	[expected]	[slower]
Cost escalation	[lower]	[expected]	[higher]
Market conditions	[favorable]	[neutral]	[adverse]

Per-scenario summary

Metric	Best	Base	Worst
Y3 Revenue	[amount]	[amount]	[amount]
Y3 Net Income	[amount]	[amount]	[amount]
Cash Runway	[months]	[months]	[months]
Break-even	[period]	[period]	[never/period]

Phase 10 — Sensitivity Analysis

Key variables

Identify 3-5 variables with highest impact on key metrics.

Variable	-20%	Base	+20%	Revenue Impact	Net Income Impact
[variable]	[value]	[value]	[value]	[delta]	[delta]

Break-even conditions

Variable	Break-even value	Current value	Safety margin

Phase 11 — Diagrams

Diagram 1: Revenue Projection Chart (xychart-beta)

xychart-beta
    title Revenue Forecast by Scenario
    x-axis ["Q1", "Q2", "Q3", "Q4", "Y2Q1", "Y2Q2", "Y2Q3", "Y2Q4", "Y3Q1", "Y3Q2", "Y3Q3", "Y3Q4"]
    y-axis "Revenue" 0 --> 2000000
    line [50000, 80000, 120000, 180000, 280000, 400000, 550000, 720000, 900000, 1100000, 1350000, 1600000]
    line [50000, 75000, 100000, 140000, 200000, 270000, 350000, 440000, 540000, 650000, 770000, 900000]
    line [50000, 65000, 80000, 100000, 130000, 160000, 190000, 220000, 250000, 280000, 310000, 340000]

Three lines: best case, base case, worst case.

Diagram 2: P&L Waterfall (xychart-beta)

xychart-beta
    title P&L Summary — Year 1
    x-axis ["Revenue", "COGS", "Gross Profit", "OpEx", "EBIT", "Tax", "Net Income"]
    y-axis "Amount" 0 --> 1000000
    bar [900000, 270000, 630000, 500000, 130000, 30000, 100000]

Diagram 3: Cash Flow Chart (xychart-beta)

xychart-beta
    title Cumulative Cash Position
    x-axis ["M1", "M3", "M6", "M9", "M12", "Q5", "Q6", "Q7", "Q8", "Q9", "Q10", "Q11", "Q12"]
    y-axis "Cash" -500000 --> 1000000
    line [-100000, -250000, -350000, -300000, -150000, 0, 100000, 250000, 400000, 550000, 700000, 850000, 1000000]

Diagram 4: Unit Economics Dashboard (xychart-beta)

xychart-beta
    title Unit Economics Evolution
    x-axis ["Q1", "Q2", "Q3", "Q4", "Y2H1", "Y2H2", "Y3H1", "Y3H2"]
    y-axis "Ratio" 0 --> 5
    line [0.8, 1.2, 1.8, 2.3, 2.8, 3.2, 3.5, 4.0]

LTV:CAC ratio over time (target line at 3.0).

Render diagrams per the diagram-rendering mixin.

File naming:

• revenue-projection.mmd / .png
• pnl-waterfall.mmd / .png
• cash-flow.mmd / .png
• unit-economics.mmd / .png

Phase 12 — Report Assembly and Approval

Assemble the complete report:

# Financial Forecast: [Business/Project]

**Date**: [date]
**Business**: [name]
**Revenue model**: [type]
**Time horizon**: [N years]
**Granularity**: [monthly Y1, quarterly Y2-3]
**Revenue Y1/Y2/Y3**: [amounts]
**Net Income Y1/Y2/Y3**: [amounts]
**Cash runway**: [months] (if applicable)
**LTV:CAC**: [ratio] (if applicable)

## Executive Summary
[Key findings: revenue trajectory, profitability timeline, cash position, critical assumptions]

## Business Model Summary
[Phase 3 — revenue model, cost structure, key drivers]

## Key Drivers
[Driver identification with formulas]

## Revenue Forecast
[Phase 4 revenue table + Diagram 1]

## Expense Forecast
[Phase 5 expense tables]

## P&L Projection
[Phase 6 P&L table + Diagram 2]

## Cash Flow Forecast
[Phase 7 cash flow tables + Diagram 3]

## Unit Economics
[Phase 8 unit economics table + Diagram 4]

## Scenario Analysis
[Phase 9 scenarios with per-scenario summaries]

## Sensitivity Analysis
[Phase 10 variable analysis + break-even conditions]

## Key Assumptions Register
[All assumptions documented with source and confidence]

## Recommendations
[Prioritized actions: revenue acceleration, cost optimization, funding needs]

## Sources
[Numbered list of web sources]

## Assumptions & Limitations
[Explicit list with confidence levels]

Present for user approval. Save only after explicit confirmation.

Generation rules

Per the autonomous-research mixin, plus:

• Calculations: Must be mathematically consistent — P&L lines must sum correctly, cash flow must reconcile
• Benchmarks: Must cite source — never fabricate industry averages
• Projections: Must flow from documented drivers and assumptions — no unexplained hockey sticks
• Specificity: "Revenue grows from $50K MRR to $150K MRR driven by 15% monthly customer growth at $500 ARPU" not "revenue increases"
• Conservatism: Base case should use conservative assumptions; optimism belongs in best case only
• Language: Respond and generate in the user's language unless specified otherwise

Failure behavior

Situation	Behavior
No business context	Enter interview mode — ask what business or project to forecast
Context too vague	Enter interview mode — ask targeted questions about revenue model and stage
No historical data	Use research-based projections with [Assumption] labels and benchmark sources
Business model unclear	Research comparable companies, propose model, confirm with user
Industry benchmarks unavailable	Use adjacent industry data, label as [Approximate]
Projections appear unrealistic	Flag with comparison to benchmarks, present anyway with caveat
mmdc / web search failures	See diagram-rendering and autonomous-research mixins
Out-of-scope request	"This skill creates financial forecasts. [Request] is outside scope."

Self-check

Before presenting output, verify:

[] Revenue forecast uses appropriate method(s) with documented drivers
[] Revenue growth justified by driver assumptions (no unexplained hockey sticks)
[] Expenses categorized (fixed/variable/semi-variable) with escalation rules
[] P&L complete: revenue → COGS → gross profit → OpEx → EBIT → net income
[] All P&L lines sum correctly (mathematical consistency)
[] Margins tracked and compared to industry benchmarks
[] Cash flow includes operating, investing, financing components
[] Burn rate and runway calculated (if pre-profit)
[] Unit economics calculated: CAC, LTV, LTV:CAC, payback period
[] Unit economics show evolution over time
[] 3 scenarios with distinct, documented assumptions
[] Sensitivity analysis on 3-5 key variables
[] Break-even conditions identified
[] All assumptions documented in register with source and confidence
[] Monthly granularity for Year 1 (or as specified)
[] All 4 Mermaid diagrams render valid syntax (per diagram-rendering mixin)
[] Sources listed for benchmarks and claims (per autonomous-research mixin)
[] Assumptions labeled with confidence (per autonomous-research mixin)