Case Study

How to optimize price architecture to better capture market value

Discover how we helped our client unlock better growth.

Opportunity/Issue

A large agriculture cooperative sought support from our experts.

They needed help streamline pricing and capture more market value when purchasing animals from farmers.

An ineffective pricing process, including charging minimal threshold prices to the farmers, meant the company failed to maximize margins.

Approach/Solution

As a starting point, our team assessed all the price drivers and their impact on the purchase price, using this to develop an optimum price architecture for our client.

We brought together experts from our agricultural and digital teams.

We then we built a base model using linear regression analysis to understand the factors and pricing dynamics at play.

By adapting this to our client’s commercial objectives, we were able to create a bespoke solution fit for their needs.

The final system meant our client paid the right price to farmers based on product, supplier, market, and competitor dynamics. It also allowed for optimized year-end rebates and easy overall price comparison.

Outcome/Result

Once implemented, the dynamic pricing model helped our clients save between 1–2% from their spend per animal, allowing them to maximize margin growth.

Equally important, the model gave stakeholders across the organization confidence in effectively implementing the pricing strategy.

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