Case study

A nimble pricing model for seasonal fruit

Client

A leading tree fruits cooperative based in British Columbia with a membership of over 270 growers producing over $100M of fruit annually 

Impact

Increase of 10% in top line revenue and a decrease of 15% of downgraded fruit.

Issue

The client was struggling with pricing its fruit appropriately, losing revenue by improperly grading top tier fruit and thereby achieving lower prices. They needed help to build a pricing model that was nimble enough to adjust to different seasonal yields and resulting grades, as well as reduce the amount of improperly graded fruit.

Approach

Through intensive data analysis, we built a probability model that estimated the volume of fruit in each grade and forecasted revenue against historical market prices. By understanding the probability of improperly graded fruit by facility, the model was able to detect anomalies and flag to management to do spot checks of certain batches. We then developed a pricing model that accurately reflected market pricing based on yield, grade, and varietal.

Outcome

By improving their ability to detect grading errors, the client was able to immediately reduce the amount of downgraded fruit that would otherwise command a higher price. A model that allowed them to be more nimble and better reflect market value of their fruit also increased their overall top line revenue by 10%.