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Agent&Capital  ·  Accelr8 Research Briefing

Commercial and Pricing Integrity

Sub-model 04  ·  June 2026  ·  V1  ·  Confidential  ·  For PE due diligence and IC use

Pricing is the highest-leverage line in the business: a 1% price improvement lifts operating profit by ~8%, and off-invoice leakage averages 16.3% of list price. On an illustrative £120M revenue base, the composite value at risk is £2.6M to £6.6M annually, of which £1.5M to £4.3M is recoverable through discount governance and price realisation. This briefing sets out the seven hypotheses tested by the Accelr8 Commercial module, mapping the Commercial Engine lever onto the Revenue Quality and Margin Integrity pools.

Signal from the research

Profit from 1% price
~8%
Operating-profit uplift from a 1% price rise, volume held (McKinsey)
Off-invoice leakage
16.3%
Average gap between invoice and pocket price (McKinsey lighting case)
Pocket vs list price
~50%
Realised price after the full waterfall in the studied case (McKinsey)
Realised-price gain
1%+
Capturable by actively managing the pocket-price waterfall (McKinsey)

Seven testable hypotheses

# Hypothesis Evidence base Test during sprint Recovery Priority
C1 Pocket-Price Leakage McKinsey: off-invoice discounts, rebates, terms and freight average 16.3% of list; pocket price ~half of list in the studied case. Rebuild the pocket-price waterfall from ERP and CRM; quantify each leakage step £360K to £960K High
C2 Discount Governance Gap Exception and off-policy discounts granted at rep discretion without approval; discount creep over time. Detect discounts beyond policy bands by rep, customer and deal size £300K to £800K High
C3 Price Realisation Drift List increases not flowing to net price; contractual escalators under-indexed or never applied. Compare realised price trend against list and contractual escalators £250K to £700K Med-High
C4 Cross-entity Price Inconsistency Same product or service sold at materially different net prices across divisions and geographies (Synergy Hunter). Compare net price for like-for-like products across entities and segments £200K to £600K Med-High
C5 Customer Concentration Risk Revenue quality exposed to a small number of accounts; concentration depresses durability and exit value. Quantify revenue and margin concentration by customer and cohort Risk amplifier Medium
C6 SKU and Customer Margin Dispersion A tail of products or customers sold below contribution margin once fully costed. Build margin-per-SKU and margin-per-customer maps; surface loss-making tail £150K to £500K Medium
C7 Rebate and Promotion Over-spend Customer rebates and promotions paid beyond threshold, double-counted, or with no measurable lift. Reconcile rebate and promo accruals against qualifying volumes and uplift £120K to £350K Medium

Composite value at risk, £120M revenue base

Hypothesis Exposed base Leakage rate Value at risk Recovery potential
C1 Pocket-Price£120M revenue0.3 to 0.8 pts£360K to £960K£360K to £960K
C2 Discount Gov.£120M revenue0.25 to 0.7 pts£300K to £800K£300K to £800K
C3 Realisation Drift£120M revenue0.2 to 0.6 pts£250K to £700K£250K to £700K
C4 Cross-entity£40M multi-entity0.5 to 1.5%£200K to £600K£200K to £600K
C5 ConcentrationTop accountsQualitativeRisk amplifierProtects revenue quality
C6 Margin Dispersion£20M tail1 to 3%£150K to £500K£150K to £500K
C7 Rebate/Promo£8M to £12M2 to 4%£120K to £350K£120K to £350K
Total composite (excluding C5 amplifier)£1.5M to £4.3M£1.5M to £4.3M
Why pricing first when revenue is healthy: with an ~8x profit response to 1% of price, modest realised-price gains compound hard. At a 10x EBITDA multiple, the recoverable range implies £15M to £43M of enterprise value, with no volume assumed.

Sources

McKinsey The Power of Pricing (1% price to ~8% operating profit; 16.3% off-invoice leakage; pocket-price waterfall). Pocket-price-waterfall methodology corroborated across pricing literature (PriceBeam, BlackCurve, Conga).
Disclaimer: Figures are illustrative for a fictitious mid-market PortCo with ~£120M revenue and a 10x EBITDA exit multiple, for demonstration only. Pricing percentages are published benchmarks from the cited research; the realised effect depends on elasticity and competitive dynamics. The 40-day diagnostic sprint replaces these estimates with measured actuals.
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