Related Ideas
eyko Ideas
Revenue leakage between quote and cash often hides in handoffs between systems. A Quote-to-Cash Leakage Detection Playbook reads paired quote, contract, invoice, and payment data to identify where revenue is leaking and rank the leakage drivers by dollar impact.
The Challenge
A deal quoted at $480K signs at $440K after legal negotiations soften pricing terms. The $40K leakage rarely gets surfaced as quote-to-contract slippage; it gets absorbed as "contract terms" with no learning loop. Across the quarter the slippage compounds.
Invoiced amounts sometimes differ from contracted amounts due to billing-system limitations, misread terms, or manual entry errors. The errors stay in AR until customers catch them; uncaught errors become permanent leakage.
Some customers pay late; some don't pay specific line items. Bad debt and write-offs surface in the AR aging report, but the patterns by deal type, payment terms, or customer segment rarely flow back into quote-side decisions.
How eyko Solves It
A Quote-to-Cash Leakage Detection Playbook reads paired quote, contract, invoice, and payment data and computes leakage at each stage transition (quote-to-contract, contract-to-invoice, invoice-to-cash). It surfaces the leakage drivers ranked by dollar impact, attributes each driver to a specific process or system handoff, and recommends fixes at the most leverage-positive stage of the cycle.
The Playbook analyzed 12 months of quote-to-cash data across 1,840 deals. Total leakage: $4.2M (3.4% of contracted revenue). Decomposition: $2.4M quote-to-contract slippage (legal-negotiation softening), $0.9M contract-to-invoice errors (billing-system entry mistakes), $0.5M invoice disputes that did not collect, $0.4M payment-term extensions absorbed without renegotiation. The largest single leakage source: discount cap softening during legal review on enterprise deals.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Quote-to-Cash Leakage Detection identifies revenue leakage at each QTC stage transition using paired quote, contract, invoice, and payment data. The Playbook surfaces the leakage drivers ranked by dollar impact, attributes each driver to a specific process or system handoff, and recommends fixes at the most leverage-positive stage of the cycle so finance and revenue ops capture the leakage rather than absorb it.
Related Ideas
FAQ
Everything you need to know about QTC Leakage Map.
Quote-to-Cash Leakage Detection is an AI-driven analysis that identifies revenue leakage at each QTC stage transition using paired quote, contract, invoice, and payment data. The Playbook surfaces the leakage drivers ranked by dollar impact, attributes each driver to a specific process or system handoff, and recommends fixes at the most leverage-positive stage of the cycle.
The Playbook reads from your CRM (quote and contract data), CPQ system where in use (configuration history), billing system (invoice records), AR system (payment data, aging, disputes, write-offs), and contract management tool (legal-review activity). At least 12 months of paired stage-by-stage data anchors the leakage detection.
A general revenue-leakage report describes total leakage. QTC Leakage Detection attributes leakage to specific stage transitions and process drivers within the cycle. The two are complementary, but stage-level attribution is what produces actionable process fixes rather than a vague "we are leaking" assessment.
Yes. For each leakage driver the Playbook recommends a specific process change: discount-cap policy tightening, invoice automation, structured dispute reviews, or payment-term renegotiation. Each recommendation projects annualized leakage recovery so finance and revenue ops can prioritize the highest-impact fixes.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
