Core module

Every rebate, accrued and settled on one ledger

Buy-side and sell-side programmes on one configurable engine: terms as executable rules, accrual from transaction detail, claims raised in-window, settlement reconciled to the general ledger.

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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

Rebates decide your real margin and settle after every decision that depended on them.

Vendor entitlement earned across hundreds of agreements, claimed by whoever remembers — so the tail goes unclaimed.
Customer rebate liability accrued on an estimate, producing a settlement true-up nobody forecast.
Rebate-adjusted cost missing from pricing, so rebate-rich lines are priced too high and lost.
Retroactive tiers that reprice a whole year, discovered after the year is over.

The technical problem

The agreement is a PDF, so nothing can evaluate it.

Rates, thresholds and windows are prose in a document rather than queryable fields, so no engine can watch them.
Accruals are computed in spreadsheets from aggregate volume, disconnected from the lines that created them.
Qualifying transactions fail to attribute to an agreement because customer, product and entity identity do not resolve.
There is no locked period, so the base data keeps moving under a number that has supposedly closed.

What RevUpra does

Inside rebate management

Every structure

Flat, tiered, volume, growth, retroactive, lump-sum and mix-and-grow — combinable on one agreement.

Transaction-level accrual

Computed in-database against locked periods, posted to mapped GL accounts, drillable back to source rows.

Accrual review gate

Staged for human review with variances and outliers surfaced, before anything posts.

Claims & recovery

Raised in-window automatically; rejections return as a worklist with the original transaction attached.

Payouts, kept separate

What you owe out is a distinct object from what you are owed, with its own approvals and segregation of duties.

Live run rate & landing tier

A projected landing position per agreement, weekly — so a threshold is actionable, not archaeological.

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.

Rebate management benchmarks
Metric	Typical today	Target
Agreements held as executable rules	10 – 30% (largest only)	>95% of agreements
Entitlement claimed in-window	88 – 95%	>99%
Accrual variance at settlement	10 – 30%	<2%
Transactions attributed to an agreement	82 – 92%	>99.5%
Reconciliation effort per close	Days	60 – 90% reduction

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 measure of a rebate programme is not whether it calculates — it is whether the number can be defended line by line, and whether the tail of small agreements gets managed as well as the top twenty.

Leak points

What this closes

The leak points from our taxonomy that this module addresses directly.

Unclaimed entitlement

“The threshold was crossed. Nobody raised the claim.”

Financially

Volume crossed a tier, a growth kicker or a lump-sum threshold and nobody raised the claim before the agreement window closed. It runs in both directions. Buy-side it is pure margin — earned from a supplier, never invoiced, quietly written off at year end. Sell-side it is the mirror image: an entitlement a customer earned that was never accrued, which returns months later as a retrospective claim settled in full because nobody can still prove what was actually due.

Technically

The agreement terms live in a PDF in a shared drive, not in a system that can evaluate them against the transactions that earn them — purchases on the buy side, sell-through on the sell side. There is no engine watching the threshold, so no event fires when it is crossed. Discovery depends on a person remembering.

Typical cost: 0.3% – 1.1% of purchase spend
Benchmark: Best-in-class recover >98% of earned entitlement within one claim cycle.

How it closes: Agreement terms become executable rules on both sides of the trade. The accrual engine evaluates them nightly against real transactions and raises the claim — or the liability — itself.

See the module →

Accrual drift

“The liability on the balance sheet is not the liability you owe.”

Financially

Rebate accruals are estimated from last year’s rate on this year’s volume. When the true settlement lands, the difference is a true-up nobody forecast — an earnings surprise in either direction, and an audit finding waiting to happen.

Technically

The accrual is a spreadsheet calculation run monthly, disconnected from the transaction detail. There is no way to drill from the balance-sheet number back to the lines that created it, and no locked period to stop the base data from moving underneath it.

Typical cost: 10% – 30% true-up variance at settlement
Benchmark: A transaction-level accrual holds settlement variance under 2%.

How it closes: Accruals are computed in-database from the transaction lines themselves, against locked accounting periods, and every posted number drills back to its source rows.

See the module →

Identifier mismatch

“The match failed, so the money did not move.”

Financially

The same customer is three entities, the same part is four part numbers, and the GPO code matches none of them. Transactions that should have earned a rebate simply do not match the agreement, so they never accrue — and the loss is invisible because nothing errors.

Technically

Your master data, your partner’s master data and the ERP’s ship-to hierarchy were never reconciled. Matching is done by exact string join, which fails silently. The unmatched rows land in a suspense file nobody owns.

Typical cost: 0.4% – 1.5% of rebate-eligible revenue
Benchmark: Mature programmes hold unmatched transaction volume under 0.5% after cross-reference.

How it closes: A cross-reference engine reconciles partner, product and entity identifiers automatically, and every unmatched row is surfaced as work — not silently dropped.

See the module →

Contract drift

“You are operating a version of the deal nobody signed.”

Financially

The signed agreement says one rate; the system was configured with another, or an amendment was agreed by email and never applied. Every transaction from that point is priced or accrued wrongly, and the exposure compounds silently until renewal.

Technically

The contract is a document and the configuration is data, and nothing binds them. Amendments arrive as redlined attachments; applying them to the running configuration is a manual re-keying step with no verification.

Typical cost: 0.5% – 2.0% of contracted revenue
Benchmark: Best practice is zero drift — every executed term traceable to the clause that created it.

How it closes: The contract is the front door. Terms are mashed live from the deal, redlined with attribution, executed, and the executed version is what the engine runs.

See the module →

Terminology

Terms on this page, defined

Plain-language definitions with the reason each one tends to leak.

Rebate ↗: A payment made after a qualifying transaction, returning part of the price based on volume, growth, mix or behaviour agreed in advance.
Vendor rebate ↗: A rebate you earn from a supplier based on what you purchase from them.
Customer rebate ↗: A rebate you fund and pay to your own customers based on what they buy from you.
Accrual ↗: The liability or receivable recognised as a rebate is being earned, before it is actually settled.
Tiered rebate ↗: A rebate whose rate increases as cumulative volume crosses defined thresholds.
Growth rebate ↗: A rebate paid on the increase in volume over a prior-period baseline, rather than on total volume.

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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.

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