Suncrest Agribusiness Company: Optimizing Seed Production

  • Reference: IVEY-9B17D009-E

  • Year: 2001, 2014

  • Number of pages: 9

  • Geographic Setting: United States

  • Publication Date: Jun 28, 2017

  • Fecha de edición: Jun 28, 2017

  • Source: Ivey Business School (Canada)

  • Type of Document: Case

  • Industry Setting: Agriculture, Forestry, Fishing and Hunting;

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Description

Suncrest Agribusiness Company (Suncrest), an agribusiness firm based in the Midwestern United States, was one of the largest seed manufacturers in the world. Seed corn (i.e., the seed that farmers purchased to grow corn in their fields) was the company’s largest business segment in the North American market; yet the seed corn market was subject to both demand and supply uncertainty. Farmers chose whether to grow corn or a different crop based on the predicted prices for corn post-harvest, making the demand uncertain. The supply was similarly uncertain because the amount of seed that firms obtained from their fields was subject to random variations. In this challenging environment, Suncrest needed to develop a forecasting model that exploited available data to determine the optimal capacity to grow seed corn.

Learning Objective

This data-driven case can be used to introduce new domain and methodological concepts. The intended audience comprises MBA, M.Sc., and/or undergraduate students enrolled in modelling-focused courses. The agribusiness context also makes this case useful for courses focused on agribusiness and the food domain. After finishing the case, students should understand how to do the following: ·Evaluate the trade-offs between average profit, risk, and service quality in the context of production planning under supply and demand uncertainty. ·Process the point forecasts provided by a sales force, and use historical data for actual forecasts to deduce probability distributions for demand. ·Recognize the value of incorporating business uncertainties into decision making.

Keywords

agribusiness farming yield uncertainty