Leak 01 · Pricing & Margin - Uncontrolled quote discounting

Warning signs. None of these proves the leak exists. They tell you where to look.

• Large differences in realized margin between salespeople on similar customers and products.
• Similar customers receiving materially different prices for the same items.
• Frequent manual price overrides, often applied just before the quote is sent.
• Discounts clustered around certain reps or branches.
• Little relationship between discount depth and win rate.
• High-margin quotes winning at about the same rate as discounted ones.

The minimum viable set. Most of it is already in your ERP.

Start with a small sample. Gathering the exports, agreements, or observations is separate from running the check; agree that work with the person who owns the records.

1. 1Export the last 30 to 90 days of quote lines with suggested price, quoted price, cost, salesperson, and outcome.
2. 2Calculate discount percent on each line.
3. 3Compare median discount and gross margin by salesperson, then by branch, customer, and product family.
4. 4Look for outliers: the reps or branches whose median discount is well above the rest.

Discount % = (Suggested price − Quoted price) ÷ Suggested price

Then ask one question: Do the reps who discount substantially more actually win substantially more? If not, you have found somewhere worth investigating.

A conservative range, not a headline. The goal is a number management can trust enough to investigate.

Annual quoted revenue affected × unnecessary discount % × realistic recovery rate

Deliberately conservative. The goal is not the biggest possible number. It is a number management can trust enough to investigate.

Fixes fall into three layers. Not every problem needs software, and almost none needs AI first.

Process

Salespeople lack clear discount authority, escalation rules, or any review of the overrides they make.

Data

Pricing recommendations do not adequately reflect customer, product, volume, cost, or market conditions, so reps override them on instinct.

Technology

Pricing guidance is not surfaced at the moment the quote is created, or overrides are not captured in a form anyone can analyze.

Start with the simplest intervention that could solve it. Move down the list only if the one above is not enough.

1. Level 1

   Visibility

   A monthly discount report by salesperson and branch, with win rate beside it. Most of the behavior change comes from people knowing it is measured.

2. Level 2

   Guardrails

   Discount thresholds that require a manager’s approval, with the reason recorded.

3. Level 3

   Better pricing guidance

   Improve customer and product segmentation so the suggested price is one reps trust.

4. Level 4

   Workflow intervention

   Surface a warning, comparable transactions, and the margin impact inside the quoting screen at the moment the price is changed.

5. Level 5

   Intelligent pricing support

   Use historical transactions, customer characteristics, product relationships, and quote outcomes to recommend a price range and flag anomalous discounts for review.

• Deep discounts are sometimes correct. A competitive bid on a large project may be won only at a thin margin, and the analysis should not punish that.
• Win rate by discount band is confounded by customer type, order size, and competition. Control for those before drawing conclusions.
• Quotes without a recorded outcome are common. Decide how to treat them before calculating win rates.

ERP note. Most ERPs store the quoted price but not the price that was suggested before the override. If yours does not, the five-minute test can compare quoted price to list or matrix price instead, which is a weaker but still useful proxy.