Results were good, but not good enough. Volume held steady, customers kept buying — and yet, leadership faced constant pressure from the Board: margins weren't moving.
Management's reaction was immediate: more sophisticated pricing algorithms must mean better margins. Especially in an indexed industry, where prices are largely determined by external forces — as is the case in food or commodities.
The model was classic cost-up pricing. Final decisions rested with the sales reps. There were controls, incentives, and oversight. On paper, everything was under control. In practice, something wasn't adding up.
The logic suggested that incorporating more variables into the algorithm was the answer: customer segment, geography, product mix, and order volume. With that, margins should improve almost immediately.
They didn't.
Back to basics. We turned our attention to the sales rep at the moment of truth. And like most good things, the changes came down to three:
01 — Ready
The system defaulted to showing only the price the customer had paid in their last transaction. On a call, speed is everything. That number became an automatic anchor to the past. The customer didn't remember it — the system did. Past prices were systematically being pushed forward. The sales rep didn't know what price they should be selling at.
02 — Willing
Sales reps trusted the suggested price from the new algorithm, but when it came time to negotiate, they gave in. The fear of losing the sale weighed more heavily. This wasn't surprising — their incentives rewarded volume, not margin. The sales rep didn't want to expand margin.
03 — Able
The model assumed negotiators. Reality revealed order-takers. Between excessive controls, the operational pressure of high call volumes, and a lack of role-specific training, pushing a pricing strategy simply wasn't an option. Given their profile, the sales rep wasn't able to conduct a more consultative sale.
From the sales rep's perspective, everything made sense. They were doing what they knew, wanted, and could do. That was the problem.
At that point, leadership stopped asking how to make the pricing strategy more sophisticated — a mission that was becoming increasingly impossible — and started asking a different question:
What do I need to change in order to execute that strategy?
The answer wasn't to build more — it was to simplify.
The solution addressed all three findings: the system stopped showing the last price and started showing the target price. The weight of the volume incentive was adjusted, and controls were reduced to just one: mandatory minimum prices.
The impact was immediate. The simplest solution was the one that moved the needle.
The lesson
Pricing is a governance problem before it is a formula problem. When economic decisions are delegated without clear criteria, margin becomes accidental.
Continuing to refine algorithms and leverage technology is necessary. But doing so without resolving how to execute — who knows, who wants to, and who is able — is unlikely to change the outcome.
Sometimes, simple moves more than sophisticated.
