finance-ops

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

# 30-minute cost audit
def run_cost_audit(spending_data):
    findings = []
    
    # Software spend analysis
    software_findings = analyze_software_spend(spending_data.software)
    findings.extend(software_findings)
    
    # Cloud infrastructure analysis
    cloud_findings = analyze_cloud_spend(spending_data.cloud)
    findings.extend(cloud_findings)
    
    # Vendor agreement review
    vendor_findings = analyze_vendor_contracts(spending_data.vendors)
    findings.extend(vendor_findings)
    
    # Calculate total savings opportunity
    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"]
    }

# Run the audit
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

1. Assess — Evaluate current state and identify gaps
2. Design — Plan improved processes and workflows
3. Implement — Roll out changes with team alignment
4. Measure — Track operational KPIs
5. 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

1. Prepare — Gather requirements, verify prerequisites, set up environment
2. Execute — Run finance ops workflow with configured parameters
3. Verify — Validate output meets requirements, document results

Verification

• All steps executed successfully
• Results validated against acceptance criteria
• Error handling tested with edge cases
• Documentation updated with findings