Eureka Case 30 min

La Cosecha Óptima

You are Felipe Izaguirre-Ponce, 43, Planning Director at Conservas del Norte, a Monterrey cannery. The year's tomato harvest has arrived, fixed. The model has an answer. You have to decide what to do with it.

The situation

Conservas del Norte cans and bottles prepared foods in Monterrey. Its two main products this season are salsa premium, bottled, and tomate triturado — crushed tomato in cans. The year's tomato harvest has just been delivered: 800 tons, and no more is coming until next season.

Felipe has to turn that fixed harvest into a production plan. Salsa premium earns far more per ton, but uses more tomato and more line time, and the salsa market can only absorb about 300 tons. Crushed tomato earns less — but the company's largest customer, a national supermarket chain worth nearly a third of revenue, buys it on a standing contract. The planning team has built a linear-programming model. Felipe has to decide how much to trust its answer.

Your job in this case: read the model's feasible region, find the optimum, and decide how far to follow it — because the supermarket has just asked for far more crushed tomato than the optimum says to make. The production schedule locks in five days.

The decision

What goes on the production schedule?

  • A · Run the model's optimum
  • B · Serve the supermarket — with the cost priced
  • C · Tilt toward the storable product

The rest of the case is locked

The data, the calculations, the decision itself and what happens next open with your institution's access code.

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