Working Capital Optimizer

Diagnose and improve the cash conversion cycle for SMBs and growth-stage companies. This skill guides Sam Ledger (or any financial AI agent) through working capital analysis, identifies where cash is trapped, and produces a prioritized action plan with quantified cash release projections.

When to Use This Skill

Trigger phrases:

• "Our cash is tight but we're profitable — why?"
• "What's our DSO / DPO / cash conversion cycle?"
• "Help us optimize working capital"
• "How do we free up cash without borrowing?"
• "AR is aging — what should we do?"
• "Can we extend our AP terms?"
• "Inventory is piling up and tying up cash"
• "Working capital analysis for [company]"

NOT for:

• Tax filing or compliance — use a compliance workflow
• Equity or debt capital raises — use startup-financial-model or cap-table-manager
• Real-time accounting system sync — use qbo-automation skill
• Payroll or GL reconciliation — use payroll-gl-reconciliation skill
• Retail inventory management software — use vendor-specific tooling

Core Metrics

Cash Conversion Cycle (CCC)

CCC = DSO + DIO - DPO

Where:
  DSO = Days Sales Outstanding     (how long to collect from customers)
  DIO = Days Inventory Outstanding (how long inventory sits before sale)
  DPO = Days Payable Outstanding   (how long before you pay suppliers)

Lower CCC = Better (cash returns faster)
Negative CCC = Excellent (paid by customers before paying suppliers — e.g., Amazon)

DSO — Days Sales Outstanding

DSO = (Accounts Receivable / Revenue) × Days in Period

Example:
  AR Balance: $150,000
  Revenue (last 90 days): $450,000
  DSO = ($150,000 / $450,000) × 90 = 30 days

Industry benchmarks:
  < 30 days: Excellent
  30-45 days: Acceptable
  45-60 days: Needs attention
  > 60 days: Cash flow risk

DPO — Days Payable Outstanding

DPO = (Accounts Payable / COGS) × Days in Period

Example:
  AP Balance: $80,000
  COGS (last 90 days): $270,000
  DPO = ($80,000 / $270,000) × 90 = 26.7 days

Strategy: Maximize DPO (pay as late as allowed) without damaging supplier relationships.
Target: Match or slightly exceed supplier terms (Net 30 → pay day 28-30, not day 5)

DIO — Days Inventory Outstanding

DIO = (Inventory / COGS) × Days in Period

Example:
  Inventory: $120,000
  COGS (last 90 days): $270,000
  DIO = ($120,000 / $270,000) × 90 = 40 days

For service businesses: DIO = 0 (no physical inventory)

Analysis Workflow

Step 1: Gather Inputs

Collect from financial statements or QBO export:

Balance Sheet (current period):
  □ Accounts Receivable balance
  □ Inventory balance (if applicable)
  □ Accounts Payable balance
  □ Accrued Expenses
  □ Deferred Revenue (if any)

Income Statement (trailing 90 days preferred):
  □ Revenue
  □ Cost of Goods Sold (COGS)

AR Aging Report:
  □ Current (0-30 days)
  □ 31-60 days
  □ 61-90 days
  □ 90+ days (specify amounts)

AP Aging Report:
  □ Current
  □ Overdue amounts
  □ Key supplier names and terms

Step 2: Calculate Current State

def calculate_working_capital_metrics(
    ar: float,
    inventory: float,
    ap: float,
    revenue_90d: float,
    cogs_90d: float,
    period_days: int = 90
) -> dict:
    """
    Calculate core working capital metrics.
    
    Args:
        ar: Accounts Receivable balance
        inventory: Inventory balance (0 for service businesses)
        ap: Accounts Payable balance
        revenue_90d: Revenue for the measurement period
        cogs_90d: COGS for the measurement period
        period_days: Length of measurement period (default 90)
    
    Returns:
        Dict with DSO, DIO, DPO, CCC, and working capital amount
    """
    dso = (ar / revenue_90d) * period_days if revenue_90d else 0
    dio = (inventory / cogs_90d) * period_days if cogs_90d and inventory else 0
    dpo = (ap / cogs_90d) * period_days if cogs_90d else 0
    ccc = dso + dio - dpo
    
    working_capital = ar + inventory - ap
    
    return {
        "dso_days": round(dso, 1),
        "dio_days": round(dio, 1),
        "dpo_days": round(dpo, 1),
        "ccc_days": round(ccc, 1),
        "working_capital_usd": working_capital,
        "ar_usd": ar,
        "inventory_usd": inventory,
        "ap_usd": ap,
        "assessment": _assess_ccc(ccc, dso, dpo)
    }

def _assess_ccc(ccc: float, dso: float, dpo: float) -> str:
    if ccc < 0:
        return "excellent"
    elif ccc <= 30:
        return "good"
    elif ccc <= 60:
        return "acceptable"
    elif ccc <= 90:
        return "needs_improvement"
    else:
        return "critical"

Step 3: AR Aging Analysis

def analyze_ar_aging(aging_buckets: dict, total_ar: float) -> dict:
    """
    Analyze AR aging and identify collection risk.
    
    Args:
        aging_buckets: {"0_30": x, "31_60": x, "61_90": x, "90_plus": x}
        total_ar: Total AR balance (validation check)
    
    Returns:
        Risk assessment and recommended actions
    """
    at_risk = aging_buckets.get("61_90", 0) + aging_buckets.get("90_plus", 0)
    at_risk_pct = at_risk / total_ar if total_ar else 0
    
    recommendations = []
    
    if aging_buckets.get("31_60", 0) / total_ar > 0.3:
        recommendations.append({
            "action": "Send reminder notices to 31-60 day balances",
            "priority": "medium",
            "cash_impact": aging_buckets["31_60"],
            "timeline": "within 1 week"
        })
    
    if aging_buckets.get("61_90", 0) > 0:
        recommendations.append({
            "action": "Direct phone outreach to 61-90 day accounts",
            "priority": "high",
            "cash_impact": aging_buckets["61_90"],
            "timeline": "this week"
        })
    
    if aging_buckets.get("90_plus", 0) > 0:
        recommendations.append({
            "action": "Place 90+ day accounts on collections / payment plan",
            "priority": "critical",
            "cash_impact": aging_buckets["90_plus"],
            "timeline": "immediately"
        })
    
    return {
        "at_risk_usd": at_risk,
        "at_risk_pct": round(at_risk_pct * 100, 1),
        "collectible_estimate_usd": at_risk * 0.75,  # 75% recovery assumption
        "risk_level": "critical" if at_risk_pct > 0.20 else "moderate" if at_risk_pct > 0.10 else "low",
        "recommendations": recommendations
    }

Step 4: AP Optimization Analysis

def analyze_ap_optimization(
    ap_balance: float,
    avg_payment_day: float,
    standard_terms_days: int,
    monthly_cogs: float
) -> dict:
    """
    Identify AP extension opportunities.
    
    Strategy: Pay on due date, not early (unless early-pay discount justifies it)
    """
    # Days of additional cash float if paying on terms vs. current practice
    days_to_extend = max(0, standard_terms_days - avg_payment_day)
    daily_cogs = monthly_cogs / 30
    cash_freed = days_to_extend * daily_cogs
    
    # Early pay discount analysis
    # Example: "2/10 Net 30" = 2% discount if paid within 10 days
    # Annualized cost of NOT taking discount = 2% / (30-10) * 365 = 36.5% annualized
    # If cost of capital < 36.5%, TAKE the discount
    
    return {
        "current_avg_payment_day": avg_payment_day,
        "standard_terms_days": standard_terms_days,
        "days_of_extension_available": days_to_extend,
        "estimated_cash_freed_usd": round(cash_freed, 0),
        "recommendation": (
            f"Extend payment timing by {days_to_extend} days to terms. "
            f"Frees ~${cash_freed:,.0f} in working capital."
        ) if days_to_extend > 0 else "Already paying close to terms. Focus on negotiating extended terms with key suppliers."
    }

Step 5: Generate Action Plan

Structure recommendations by cash impact and implementation speed:

def generate_action_plan(metrics: dict, ar_analysis: dict, ap_analysis: dict) -> dict:
    """
    Produce prioritized working capital improvement plan.
    """
    quick_wins = []      # < 30 days, low friction
    medium_term = []     # 30-90 days
    strategic = []       # 90+ days, structural changes
    
    total_cash_release_estimate = 0
    
    # AR Quick Wins
    if ar_analysis["at_risk_usd"] > 0:
        quick_wins.append({
            "lever": "AR Collections",
            "action": f"Collect 61-90 day and 90+ day balances (${ar_analysis['at_risk_usd']:,.0f} at risk)",
            "cash_impact_usd": ar_analysis["collectible_estimate_usd"],
            "timeline_days": 30,
            "effort": "medium"
        })
        total_cash_release_estimate += ar_analysis["collectible_estimate_usd"]
    
    # AP Extension
    if ap_analysis["estimated_cash_freed_usd"] > 0:
        quick_wins.append({
            "lever": "AP Extension",
            "action": ap_analysis["recommendation"],
            "cash_impact_usd": ap_analysis["estimated_cash_freed_usd"],
            "timeline_days": 14,
            "effort": "low"
        })
        total_cash_release_estimate += ap_analysis["estimated_cash_freed_usd"]
    
    # DSO Reduction
    if metrics["dso_days"] > 45:
        dso_target = 35
        daily_revenue = metrics["ar_usd"] / metrics["dso_days"] if metrics["dso_days"] else 0
        cash_from_dso = (metrics["dso_days"] - dso_target) * daily_revenue
        medium_term.append({
            "lever": "Invoice Terms",
            "action": f"Shorten payment terms from Net {int(metrics['dso_days'])} to Net {dso_target}. Offer early-pay incentive (1% Net 10).",
            "cash_impact_usd": round(cash_from_dso, 0),
            "timeline_days": 60,
            "effort": "medium"
        })
    
    # Structural AP Terms Negotiation
    strategic.append({
        "lever": "AP Terms Renegotiation",
        "action": "Renegotiate key supplier terms from Net 30 to Net 45/60",
        "cash_impact_usd": None,  # Depends on negotiation outcome
        "timeline_days": 90,
        "effort": "high"
    })
    
    return {
        "total_estimated_cash_release_usd": total_cash_release_estimate,
        "quick_wins": quick_wins,
        "medium_term": medium_term,
        "strategic": strategic,
        "summary": f"Estimated ${total_cash_release_estimate:,.0f} in working capital can be freed within 30-60 days through focused collection and AP timing improvements."
    }

Industry Benchmarks

Output Format

Executive Summary (for client delivery)

WORKING CAPITAL ANALYSIS — [Company] — [Date]

CURRENT STATE:
  DSO: [X] days | Target: [Y] days | Gap: [Z] days
  DIO: [X] days (N/A for services)
  DPO: [X] days | Target: [Y] days
  CCC: [X] days | Status: [Good/Acceptable/Needs Improvement/Critical]

  Working Capital: $[X]
  AR at Risk (60+ days): $[X] ([Y]% of AR)

KEY FINDINGS:
  1. [Most important issue — quantified]
  2. [Second issue — quantified]
  3. [Third issue — quantified]

PRIORITIZED ACTION PLAN:
  QUICK WINS (0-30 days, ~$[X] cash release):
    □ [Action 1] → $[impact]
    □ [Action 2] → $[impact]

  MEDIUM-TERM (30-90 days, ~$[X] additional):
    □ [Action 3]
    □ [Action 4]

  STRATEGIC (90+ days):
    □ [Action 5]

NEXT STEP: [Single most important immediate action]

Structured JSON Output

{
  "company": "Acme Corp",
  "analysis_date": "2026-03-15",
  "period": "Q1 2026 (Jan-Mar)",
  "metrics": {
    "dso_days": 52,
    "dio_days": 0,
    "dpo_days": 24,
    "ccc_days": 28,
    "working_capital_usd": 185000,
    "assessment": "needs_improvement"
  },
  "ar_aging": {
    "current_0_30": 90000,
    "days_31_60": 45000,
    "days_61_90": 22000,
    "days_90_plus": 18000,
    "total": 175000,
    "at_risk_pct": 22.9,
    "risk_level": "critical"
  },
  "action_plan": {
    "total_estimated_cash_release_usd": 62500,
    "quick_wins": [
      {
        "lever": "AR Collections",
        "action": "Collect 61-90 and 90+ day balances ($40,000 at risk)",
        "cash_impact_usd": 30000,
        "timeline_days": 30
      },
      {
        "lever": "AP Extension",
        "action": "Extend payment timing by 6 days to terms. Frees ~$12,500.",
        "cash_impact_usd": 12500,
        "timeline_days": 14
      }
    ]
  }
}

Example Usage

User: "Our QBO shows $175k AR, $70k AP, $2M in revenue last year. We're profitable but always feel cash-strapped. What's going on?"

Sam's response:

Working Capital Snapshot:

  Revenue run rate: $2M/yr → ~$500k/quarter
  AR: $175,000
  AP: $70,000

  DSO = ($175,000 / $500,000) × 90 = 31.5 days ← borderline, worth watching
  DPO = ($70,000 / estimated COGS) × 90 = need COGS to confirm
  CCC = approx 25-35 days

Potential issues despite good DSO:
  1. Revenue recognition vs cash: if billing is end-of-month heavy, AR spikes temporarily
  2. AP payment behavior: if you're paying invoices early (day 5 of Net 30 terms), you're 
     giving suppliers a 25-day float for free — roughly $58k in "gifted" working capital
  3. High AR concentration: if 20% of customers account for 80% of AR, one slow payer 
     tanks your cash position

Next step: Pull AR aging report from QBO. If 30+ day buckets are > 15% of AR, 
that's your primary fix. Also check when you're actually paying AP.

Integration Points

• qbo-automation — Pull AR aging, AP aging, and balance sheet data directly from QuickBooks Online
• ar-collections-agent — Execute collection workflows on identified aging accounts
• thirteen-week-cash-flow — Feed working capital metrics into 13-week rolling cash forecast
• kpi-alert-system — Set DSO/DPO threshold alerts for ongoing monitoring
• vendor-payment-optimizer — Detailed AP vendor-by-vendor payment term analysis
• financial-analysis-agent — Full financial health assessment including working capital context
• budget-vs-actual — Compare working capital targets vs actuals over time

Quick Reference Formulas

DSO = (AR / Revenue) × Period Days
DPO = (AP / COGS) × Period Days
DIO = (Inventory / COGS) × Period Days
CCC = DSO + DIO - DPO

Working Capital = Current Assets - Current Liabilities
Net Working Capital = AR + Inventory - AP (operating focus)

Current Ratio = Current Assets / Current Liabilities  (target ≥ 1.5)
Quick Ratio   = (Cash + AR) / Current Liabilities     (target ≥ 1.0)

Annual Cash Impact of 1-Day DSO Reduction = Annual Revenue / 365
Annual Cash Impact of 1-Day DPO Extension = Annual COGS / 365