Maximizing Profit in a Feedlot Enterprise Using Systems Analysis Thinking and Linear Programming

Tuesday, July 22, 2014
Exhibit Hall AB (Kansas City Convention Center)
Kelli J Retallick , Kansas State University, Manhattan, KS
Tamar E Adcock , Kansas State University, Manhattan, KS
Tyler R Schultz , Kansas State University, Manhattan, KS
Jennifer M. Bormann , Kansas State University, Manhattan, KS
Robert L Weaber , Kansas State University, Manhattan, KS
Daniel W. Moser , Kansas State University, Manhattan, KS
Michael D. MacNeil , Delta G, Montana, MT
Abstract Text:

Systems’ thinking is a management discipline that concerns understanding a complex entity studying the components and interactions between them that form the entirety of that entity. In this case, a system analysis approach was applied to a stereotypical situation of a farmer/feeder. Feedlot enterprises were evaluated using linear programming to maximize profitability from excess feedlot capacity. The hypothetical feedlot analyzed was based on data recorded by Iowa State University Extension. Four alternative beef cattle enterprises: weanlings, yearlings, performance-tested bulls, and beef replacement heifers, were investigated as alternative uses for the excess capacity. An earthen feedlot facility with shelter was modeled. Capacity was constrained by 60,000 linear inches of bunk and a weekly feed holding capacity of 5000 bushels of whole corn. The objective function summed the products of per head profit and numbers of each class of cattle. Results from three alternative scenarios have been presented here. Linear programming models were solved using Microsoft Excel. Simulation 1 involved only the two initial constraints on capacity and maximum profit resulted when 4,630 yearlings and 159 performance-tested bulls filled the feedlot. This system assumed both yearlings and performance-tested bulls were turned over twice a year with consistent availability of cattle. In simulation 2 it was assumed the owner-operator owned 1500 weaned calves and these were forced into the solution. In this scenario, profit margins were maximized when 3,439 yearlings, 26 performance-tested bulls and the 1,500 weaned calves filled the feedlot. Simulation 3 included 200 owned replacement females. This constraint pushed the system to fill the feedlot with 3,200 yearlings, 1,500 owned weanlings, and 200 owned replacement females. This simulation exercise represents the value of applying both systems thinking and linear programming in real management situations to determine maximum profits with resources available.

Keywords: cattle, feedlot, profit