SKILL.md
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LTV = ARPU x Gross Margin x Customer Lifetime
LTV:CAC Ratio = LTV / CAC Target: > 3:1
Logo Retention = (Customers End - New) / Customers Start
Net Revenue Retention = (MRR End - Churn + Expansion) / MRR Start
## Burn MultipleBurn Multiple = Net Burn / Net New ARR
< 1.0x Excellent efficiency
1.0-1.5x Good efficiency
1.5-2.0x Average
2.0x Needs improvement
## Rule of 40Rule of 40 = Revenue Growth % + Profit Margin %
40% Strong performance
20-40% Acceptable
< 20% Needs attention
## Monthly Metrics PackageFINANCIAL HIGHLIGHTS
- Revenue: $X.XM (vs Plan: +/-Y%)
- Gross Margin: XX% (vs Plan: +/-Y%)
- Operating Loss: $X.XM (vs Plan: +/-Y%)
- Cash Balance: $X.XM
- Runway: XX months
REVENUE METRICS
- ARR: $X.XM (+Y% QoQ)
- Net New ARR: $XXK
- NRR: XXX%
- Logo Churn: X.X%
EFFICIENCY METRICS
- CAC: $X,XXX
- CAC Payback: XX months
- Burn Multiple: X.Xx
## Board Financial Presentation
1. Financial summary (1 slide)
2. Revenue performance (1-2 slides)
3. Expense breakdown (1 slide)
4. Cash flow and runway (1 slide)
5. Key metrics trends (1 slide)
6. Forecast outlook (1 slide)
## Revenue Build (Financial Model)
1. Starting ARR / customers
2. New logo assumptions (by segment)
3. Expansion rate
4. Churn rate
5. Pricing changes
6. Segment mix
## Expense Build (Financial Model)
1. Headcount plan (by department)
2. Comp and benefits
3. Contractors
4. Software / tools
5. Facilities
6. Marketing programs
7. Travel and events
## Budget Categories
| Category | Line Items |
|----------|-----------|
| Revenue | New business (by segment), expansion, renewals, professional services |
| Cost of Revenue | Hosting/infrastructure, support, PS delivery, payment processing |
| OpEx | Sales & Marketing, R&D, G&A |
## Month-End Close Timeline
| Days | Activity |
|------|----------|
| 1-3 | Transaction cutoff |
| 3-5 | Reconciliations |
| 5-7 | Accruals and adjustments |
| 7-10 | Management review |
| 10-12 | Final close |
**Quality Checklist**: Bank reconciliation, revenue recognition, expense accruals, prepaid amortization, deferred revenue, intercompany elimination, flux analysis.
## Revenue Recognition (ASC 606)
1. Identify the contract
2. Identify performance obligations
3. Determine transaction price
4. Allocate price to obligations
5. Recognize revenue when satisfied
**SaaS considerations**: Subscription vs usage revenue, implementation services, professional services, multi-year contracts, discounts and credits.
## Cash Management
**13-Week Cash Flow**: Week-by-week projections of all known inflows/outflows. Review weekly. Maintain minimum cash buffer.
**Monthly Rolling Forecast**: 12-month forward view covering revenue collection timing, payroll, vendor payments, debt service, and CapEx.
**Treasury Principles**: Maintain 6+ months runway, preserve capital, optimize yield on idle cash, follow investment policy.
**Cash Preservation Levers** (when extending runway):
1. Hiring freeze
2. Vendor renegotiation
3. Discretionary spend cuts
4. Payment term extension
5. Revenue acceleration
6. Bridge financing
## Due Diligence Data Room Checklist
**Financial data**:
- [ ] 3 years historical financials
- [ ] Monthly P&L by segment
- [ ] Balance sheet and cash flow
- [ ] ARR/MRR cohort analysis
- [ ] Customer unit economics
- [ ] Revenue recognition policy
- [ ] AR aging
- [ ] AP summary
**Projections**:
- [ ] 3-5 year financial model
- [ ] Key assumptions documented
- [ ] Sensitivity analysis
- [ ] Use of funds breakdown
- [ ] Path to profitability
## Financial Risk Categories
| Risk Type | Key Concerns |
|-----------|-------------|
| Market | Interest rate exposure, FX exposure, customer concentration |
| Credit | Customer creditworthiness, AR aging, bad debt reserves |
| Operational | Internal controls, fraud prevention, systems reliability |
## Example: Series-A SaaS Financial Snapshot
A Series-A company ($3M ARR, 35 employees, $12M raised) preparing for Series B:Unit Economics:
CAC: $22K | LTV: $88K | LTV:CAC: 4.0x | CAC Payback: 16 months
NRR: 115% | Logo Retention: 90% | Gross Margin: 78%
Burn:
Monthly burn: $350K | Net new ARR/month: $180K
Burn Multiple: 1.9x (average -- needs improvement for Series B)
Cash: $5.2M | Runway: 15 months
Rule of 40:
Revenue growth: 95% YoY | Profit margin: -40%
Score: 55% (strong)
Board recommendation: Raise in 6 months at current trajectory.
Target metrics for raise: Burn Multiple < 1.5x, NRR > 120%.
## Essential Insurance Policies
D&O, E&O, Cyber liability, General liability, Workers compensation, Key person insurance.
## Scripts
Unit economics calculator
python scripts/unit_economics.py --metrics data.csv
Cash flow projector
python scripts/cash_forecast.py --actuals Q1.csv --assumptions model.yaml
Financial model builder
python scripts/fin_model.py --template saas --output model.xlsx
Investor metrics dashboard
python scripts/investor_metrics.py --period monthly
## References
- `references/financial_modeling.md` -- Model building guide
- `references/saas_metrics.md` -- SaaS metrics deep dive
- `references/accounting_policies.md` -- Policy documentation
- `references/audit_prep.md` -- Audit readiness guide
## Tool Reference
### financial_health_scorer.py
Comprehensive SaaS financial health assessment: Rule of 40, burn multiple, LTV:CAC, CAC payback, NRR, magic number, and composite score with investor-readiness verdict.
Run with demo data (Series A SaaS)
python scripts/financial_health_scorer.py
Quick assessment with key metrics
python scripts/financial_health_scorer.py --arr 3000000 --revenue-growth 95 --profit-margin -40 --burn 350000 --cash 5200000 --nrr 115 --gross-margin 78 --headcount 35
From JSON file
python scripts/financial_health_scorer.py --input financials.json
JSON output
python scripts/financial_health_scorer.py --input financials.json --json
### burn_rate_calculator.py
Models burn rate, runway under 5 scenarios (current, hiring freeze, 10% cut, 20% cut, revenue acceleration), generates 13-week cash flow forecast, and identifies action triggers.
Run with demo data
python scripts/burn_rate_calculator.py
Quick calculation
python scripts/burn_rate_calculator.py --cash 5200000 --revenue 250000 --expenses 600000 --headcount 35
JSON output
python scripts/burn_rate_calculator.py --json
### scenario_modeler.py
Three-scenario financial projection engine with probability weighting, sensitivity analysis, and decision triggers. Projects base, upside, and downside cases over 8 quarters.
Run with demo data
python scripts/scenario_modeler.py
Quick model from key inputs
python scripts/scenario_modeler.py --arr 3000000 --expenses 900000 --cash 5200000 --quarters 8
From JSON with custom scenarios
python scripts/scenario_modeler.py --input scenarios.json
JSON output
python scripts/scenario_modeler.py --json