Margin intelligence

Every deal has a path. Every gap has a cost.

Follow revenue from commercial decision to realised margin — and see exactly where value escapes. Leakage is not a bad deal; it is money that left without anyone making a decision.

The leak map

  1. Commit
  2. Transact
  3. Earn
  4. Settle
  5. Realise
  1. Commit

    Deal

    Deal modelling

    Price erosion & discount stacking

  2. Commit

    Contract

    Terms become rules

    Contract drift

  3. Transact

    Transact

    Orders, shipments, sell-through

    Identifier mismatch

  4. Earn

    Incentive

    Rebates earned

    Unclaimed entitlement

  5. Earn

    Promotion

    MDF & co-op

    Promotion & MDF spend leakage

  6. Settle

    Accrual

    The liability posts

    Accrual drift

  7. Settle

    Claim

    Money is asked for

    Unvalidated channel claims

  8. Settle

    Settlement

    Cash actually moves

    Deduction & dispute write-off

  9. Realise

    Margin

    What you kept

    Reporting latency

Every arrow is a handoff between systems — and every handoff is where value escapes

Governed AI agents · one ledger · one audit trail

RevUpra Platform

Select any stage to open its leak

Indicative value at risk

$60M$160M a year

Across 7 of the nine leak points, at the published benchmark ranges. The other 2 — accrual drift and reporting latency — are a variance and a delay, not a share of revenue. Multiplying either by a revenue figure would produce a confident number that means nothing, so they are excluded rather than guessed.

Read this as an order of magnitude, not a total. The ranges are quoted against slightly different bases — net revenue, channel revenue, purchase spend, MDF spend — so applying them to a single figure estimates the size of the problem rather than adding it up. Ranges are indicative benchmarks drawn from published channel-incentive and pricing research together with our own implementation experience. They vary widely by programme complexity, channel depth and data quality — treat them as the opening question in a diagnostic, not a guarantee.

The same problem, stated twice

Once for the person who owns the P&L, once for the person who owns the systems. Neither column is a summary of the other.

The financial problem

The variance you keep explaining as mix is mostly leakage.

  • Entitlement earned and never claimed, because no system was watching the threshold.
  • Claims paid without validation, because checking each line cost more than the line.
  • Concession stacks nobody ever saw summed, approved one defensible step at a time.
  • Accruals estimated rather than calculated, producing true-ups that distort periods months later.

The technical problem

Nothing fails, so nothing alerts.

  • Unmatched transactions land in a suspense file with no owner — they do not error, they just stop existing.
  • Agreement terms live in documents rather than as executable rules, so no event can fire when a threshold is crossed.
  • The three prices for a transaction live in three systems and are never compared.
  • Reporting aggregates live over transaction tables, so the answer takes hours and nobody explores.

How RevUpra closes them

Control at every join

Leak diagnostic

A structured assessment against the nine leak points using a quarter of your own data — not a benchmark deck.

Exception queues, not suspense files

Everything that fails to match becomes named, owned work rather than a silent drop.

Executable agreement terms

Rates, thresholds and windows as queryable fields the engine evaluates, so entitlement raises itself.

Line-level claim validation

Every submitted line checked against its authorisation; only exceptions reach a person.

Stack visibility at approval

The combined effective rate of every concession, shown before the last approval rather than after settlement.

Materialised financial reads

Channel and margin positions available in days, not weeks, so decisions land inside the period.

Benchmarks

What good looks like

Use this as a self-assessment. If you cannot produce one of these numbers for your own programme, that is itself the finding.

Revenue leak detection benchmarks
Metric Typical today Target
Transactions matched to an agreement 82 – 92% >99.5%
Claim lines validated before payment 20 – 50% >99%
Vendor entitlement claimed in-window 88 – 95% >99%
Accrual variance at settlement 10 – 30% <2%
Days to gross-to-net close 25 – 45 <5 business days
Ranges are indicative benchmarks drawn from published channel-incentive and pricing research together with our own implementation experience. They vary widely by programme complexity, channel depth and data quality — treat them as the opening question in a diagnostic, not a guarantee.

Two to four percent of the revenue flowing through incentive programmes is a common recovery once leakage is closed. The honest number for your business comes from a diagnostic against your own data.

The platform underneath

One platform. One commercial truth.

The leaks are not nine separate problems to buy nine tools for. They are one problem — the commercial decision and the financial record living in different systems — which is why closing them takes a single layer that spans the whole journey.

Commercial control

The decision, and the terms it becomes.

  • Deal Modeler
  • Contract lifecycle + e-sign
  • Pricing engine
  • Price protection
  • Special agreements

Incentive control

Everything earned around the transaction.

  • Vendor rebates
  • Customer rebates
  • Trade promotions (MDF / co-op)
  • Ship & debit
  • Channel incentives

Financial control

What reaches the ledger, and what settles.

  • Accrual engine
  • Claims & validation
  • Settlement
  • Usage-based billing
  • e-Invoicing

Shared across all of it

  • Governed AI agents
  • Data layer
  • Integration hub
  • Audit trail
  • UR-DEF reporting
  • Tasks & approvals
  • Custom apps
  • Signet e-signature

See what RevUpra can recover for you.

Thirty minutes, tailored to your programmes. We walk an agreement through modelling, contracting, accrual, claim and settlement using examples close to your own — and model an indicative ROI against your volumes.