| name | finance-ops |
| description | Run AI-powered CFO analysis for cost detection, financial modeling, scenario planning, and operational efficiency optimization. Use when working with finance ops. |
| domain | operations |
| author | oyi77 |
| license | Apache-2.0 |
| subdomain | business-operations |
| tags | ["business-ops","finance","management","operations","ops"] |
| version | 1.0.0 |
Finance Ops
When to Use
Trigger phrases:
- "finance ops"
- "Help me with finance ops"
Use cases:
- When the task matches this skill's domain expertise
When NOT to use:
- For tasks outside this skill's scope
briefing = generate_cfo_briefing(
company_data=load_company_financials(),
period="2025-04"
)
Key sections:
1. Executive Summary
2. Cash Position & Runway
3. Unit Economics Update
4. Cost Analysis & Optimization
5. Risk Assessment
6. Board Metrics
print(f"Cash Runway: {briefing.cash_runway.months} months")
print(f"LTV/CAC: {briefing.unit_economics.ltv_cac_ratio}")
print(f"Optimization Opportunities: ${briefing.cost_opportunities.total_annual_value}")
### Example 2: Scenario Planning
```python
# Build 3-year financial model
model = FinancialModel(
assumptions={
"revenue": {
"starting_arr": 5000000,
"growth_rate": 0.75,
"net_retention": 1.15
},
"costs": {
"gross_margin": 0.75,
"sales_marketing": 0.40, # % of revenue
"r_and_d": 0.25,
"g_and_a": 0.15
}
}
)
# Run scenarios
scenarios = model.scenario_analysis({
"base_case": base_assumptions,
"upside_case": {**base_assumptions, "growth_rate": 1.00},
"downside_case": {**base_assumptions, "growth_rate": 0.50, "churn": 0.05},
"stress_test": {**base_assumptions, "growth_rate": 0.25, "churn": 0.08}
})
# Compare scenarios
for name, result in scenarios.items():
print(f"{name}: {result.year_3.arr} ARR, {result.cash_position} cash")
Example 3: Cost Audit
def run_cost_audit(spending_data):
findings = []
software_findings = analyze_software_spend(spending_data.software)
findings.extend(software_findings)
cloud_findings = analyze_cloud_spend(spending_data.cloud)
findings.extend(cloud_findings)
vendor_findings = analyze_vendor_contracts(spending_data.vendors)
findings.extend(vendor_findings)
total_opportunity = sum(f["annual_savings"] for f in findings)
return {
"findings": findings,
"total_annual_opportunity": total_opportunity,
"quick_wins": [f for f in findings if f["implementation"] == "immediate"]
}
audit_results = run_cost_audit(load_spending_data())
print(f"Total Savings Opportunity: ${audit_results.total_annual_opportunity:,}")
print(f"Quick Wins: {len(audit_results.quick_wins)}")
When NOT to Use
- For processes that change daily (too much overhead)
- When the team is too small to benefit from SOPs
- For one-time events that will not repeat
Overview
Finance Ops streamlines operational efficiency for operational excellence.
Workflow
- Assess — Evaluate current state and identify gaps
- Design — Plan improved processes and workflows
- Implement — Roll out changes with team alignment
- Measure — Track operational KPIs
- Iterate — Continuous improvement based on data
SOP Template
- Purpose — Why this process exists
- Scope — Who and what it covers
- Procedure — Step-by-step instructions
- Escalation — When and how to escalate
- Review — Schedule for periodic updates
Key Metrics
- Process completion time
- Error/rework rate
- Team satisfaction scores
- Cost per operation
- SLA compliance rate
Anti-Rationalization Table
| Rationalization | Reality |
|---|
| "We do not need SOPs" | Without SOPs, quality depends on memory. Document everything. |
| "Manual processes work fine" | Manual processes do not scale and are error-prone. Automate. |
| "Compliance is optional" | Compliance protects you legally. Build it in from the start. |
Process
- Prepare — Gather requirements, verify prerequisites, set up environment
- Execute — Run finance ops workflow with configured parameters
- Verify — Validate output meets requirements, document results
Verification
