Purpose
Pinpoint exactly where the order-to-cash cycle is losing time and cash — down to the specific sub-step — and deliver a ranked, root-caused bottleneck list with an effort-vs-impact prioritization so the fix sequence is obvious. Solves the "our DSO is high but we don't know where the problem actually lives" diagnosis gap.
When to Use
Invoke this skill when the user asks to:
- Diagnose why DSO (Days Sales Outstanding) is high or rising
- Find where cash is getting trapped in the receivables process
- Decide which order-to-cash stage to fix first
- Reduce invoice-to-cash cycle time or cut collection delays
- Investigate high dispute rates, cash application backlogs, or invoicing errors
- Build a business case for O2C process or automation investment
Inputs Required
Before starting, collect:
- Current DSO and target DSO: Actual days and the goal
- Stage cycle times: Days spent (or estimated) at each O2C stage — order capture, credit, invoicing, collections, cash application, disputes
- Error/exception rates: Where available — invoice rejection rate, dispute rate, unapplied cash %, credit hold frequency
- AR aging profile: % current, 1–30, 31–60, 61–90, 90+ days past due
- Volume and mix: Monthly invoice count, average invoice value, customer concentration
- Known pain points: What the team already suspects is broken
- Tooling/staffing: ERP/billing system, team size, manual vs. automated steps
If precise cycle times or error rates are missing, use the aging profile and pain points to estimate stage contribution and flag each estimate as an assumption.
Instructions
Step 1: Map the Order-to-Cash Cycle and Allocate Cycle Time
Break total invoice-to-cash time into the six standard stages and assign days to each:
- Order capture: Order received → validated and entered
- Credit check/approval: Order entered → credit cleared or hold released
- Invoicing: Goods/service delivered → accurate invoice issued
- Collections: Invoice issued → follow-up activity → payment committed
- Cash application: Payment received → correctly applied to open items
- Dispute resolution: Dispute raised → resolved → re-billed or credited
Sum the stage days and reconcile against reported DSO. If the sum is materially below DSO, the gap itself indicates hidden delay (usually collections lag or unapplied cash) — flag it.
Step 2: Score Each Stage on Time Drag and Error Drag
For every stage, assign two ratings:
- Time drag (Low / Medium / High): How far the stage's cycle time exceeds a healthy benchmark
- Error drag (Low / Medium / High): How often the stage produces rework, exceptions, or downstream delay
Healthy-range benchmarks to anchor against:
- Order capture: under 1 day; error rate under 2%
- Credit check: under 1 day (auto-decision majority); manual holds under 10% of orders
- Invoicing: same-day to 2 days post-delivery; invoice error/rejection under 3%
- Collections: first touch by day 3–5 past due; 61+ aging under 15% of AR
- Cash application: same-day to 2 days; unapplied cash under 2% of receipts
- Dispute resolution: median under 10 days; dispute rate under 1% of invoices
A stage with High on either axis is a candidate bottleneck.
Step 3: Diagnose Root Causes Per Bottleneck Stage
For each candidate bottleneck, identify the underlying cause, not just the symptom. Use these common root-cause patterns:
- Order capture: Manual entry, incomplete order data, no order-form validation
- Credit check: Manual credit reviews, stale credit limits, no automated scoring, blanket holds
- Invoicing: Delivery-to-billing handoff gaps, PO/invoice mismatch, wrong tax/pricing, no e-invoicing where required
- Collections: No dunning cadence, reactive-only follow-up, no prioritization by balance/risk, contact data gaps
- Cash application: Missing remittance detail, manual matching, lockbox/bank feed gaps, short-pays not routed
- Dispute resolution: No ownership, no SLA, disputes not tracked to a system, root-cause disputes recurring (pricing, delivery, quality)
For each, state the symptom, the probable root cause, and the evidence in the data that supports it.
Step 4: Rank Bottlenecks and Build the Effort-vs-Impact Matrix
Rank all identified bottlenecks by cash impact — estimated DSO days recoverable or cash freed. Then place each into a 2x2 matrix:
- Quick Wins (High impact / Low effort): Do immediately
- Major Projects (High impact / High effort): Plan and resource
- Fill-Ins (Low impact / Low effort): Do opportunistically
- Reconsider (Low impact / High effort): Deprioritize
For each bottleneck, estimate DSO days recoverable and cash freed using: recoverable days × (annual revenue ÷ 365). State the assumption behind each estimate.
Step 5: Sequence the 90-Day Remediation Plan
Order the fixes into a phased plan:
- Days 1–30: All Quick Wins + kickoff of the top Major Project
- Days 31–60: Continue top Major Project; execute Fill-Ins
- Days 61–90: Complete Major Project; measure DSO movement; re-baseline
For each action, name the owning function, the leading indicator to watch, and the expected DSO impact.
Output Format
- Structure: O2C stage map with allocated days → per-stage time/error scoring table → root-cause diagnosis per bottleneck → ranked bottleneck list → effort-vs-impact 2x2 → 90-day sequenced plan
- Length: 1,000–1,400 words
- Format: Structured document with two tables (stage scoring; ranked bottlenecks with DSO/cash estimates) and a labeled 2x2 matrix
- Sections: Cycle Map & Time Allocation → Stage Scoring → Root-Cause Diagnosis → Ranked Bottlenecks → Effort-vs-Impact Matrix → 90-Day Remediation Plan
- Tone: Controller-to-CFO — analytical, quantified, prioritized; every recommendation tied to a cash or DSO number
Quality Checklist
Before delivering output, verify:
- [ ] All six O2C stages are mapped with days allocated, and the sum is reconciled against reported DSO
- [ ] Every stage has both a time-drag and error-drag rating benchmarked against the healthy ranges
- [ ] Each bottleneck names a root cause distinct from its symptom, with supporting evidence
- [ ] Bottlenecks are ranked by cash impact and each carries a DSO-days-recoverable and dollars-freed estimate
- [ ] Every item is placed in one of the four matrix quadrants (Quick Win / Major Project / Fill-In / Reconsider)
- [ ] The 90-day plan sequences actions with an owner and a leading indicator for each
Notes
- The most common hidden bottleneck is cash application, not collections — unapplied cash inflates DSO while masking that the money already arrived; check unapplied cash % first
- Recurring disputes are usually an upstream invoicing or pricing defect, not a dispute-team capacity problem — fix the source, not the queue
- When cycle-time data is thin, the AR aging profile is the best proxy: a 61+ bucket above 15% points to collections or dispute drag; a large unapplied balance points to cash application
- Blanket credit holds are a frequent Quick Win — moving 60–70% of orders to auto-approval often removes a full day from the front of the cycle with minimal effort
How to use this skill
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Installing in Claude Code:
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- Drag this file into a new chat, or copy and paste its contents
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