Sales & Wholesale

Trade pricing and discount approval support

Assess discount requests against margin thresholds, the account's history, and comparable deals, and give the approver a recommendation with the margin consequence stated in cash terms.

Decision supportRepetitive judgmentRevenueCost reduction

1–3%

improvement in realised trade margin

Opportunity assessment

Business Impact
3

Moderate impact. Meaningful cost or revenue improvement, likely noticeable at function level but modest relative to total business scale.

Feasibility
3

Moderate effort. Requires configuration, prompt engineering, and testing. A capable team can get there but expect several months.

Data Readiness
2

Demanding data requirements. Relies on clean, integrated data across multiple systems. Significant data preparation work typically needed.

Risk Exposure
3

Moderate risk. Some customer or external exposure. Errors create rework or reputational impact but are recoverable.

Change Complexity
3

Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.

Tooling required

Specialist AI tool

Things to consider

  • Discount leakage is usually invisible because each individual approval looks reasonable. The value is in showing the approver where this deal sits against every comparable deal, which no spreadsheet does at the moment of decision.

  • You need true net margin including rebates, settlement discounts, and freight terms. Gross margin recommendations will approve deals that lose money once the back-end costs land.

  • Expect resistance from sales if it reads as a policing tool. Frame it as giving the account manager the evidence to defend a price, which is what a good one wants.

  • Experiment starter: Run last year's discount approvals through the model and quantify the margin difference between what was approved and what it would have recommended. If the gap is material, pilot it as an advisory step on deals above a value threshold.

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