Improving Feedlot Profitability Using Operational Data in Mortality Prediction Modeling

Scalability and robustness of feed yard mortality prediction modeling to improve profitability

“…There are a smaller number of studies that could be described as prospective, as their objectives are to use operational data to make predictions and adjust management decisions concerning current animals within the feed yard. The most applicable prospective study for the purposes of the objective of this paper is Feuz, Feuz, and Johnson (2021). This study used operational feed yard data from a 2-year Noble Research Institute sustainability project.…”

“…Theurer et al (2014) used operational feed yard data to evaluate associations of rectal temperature at first treatment for BRD and the probability of not finishing the production cycle. Feuz, Feuz, and Johnson (2021) and Rojas et al (2022) are separated from the other noted prospective studies in their objectives to not only create predictive models, but also evaluate the economic consequences of using the model predictions as a management decision aid. However, Feuz, Feuz, and Johnson (2021) are the most relevant to the current study as their models focused on mortality prediction to be used as a decision aid to cull railers.…”

“…Feuz, Feuz, and Johnson (2021) and Rojas et al (2022) are separated from the other noted prospective studies in their objectives to not only create predictive models, but also evaluate the economic consequences of using the model predictions as a management decision aid. However, Feuz, Feuz, and Johnson (2021) are the most relevant to the current study as their models focused on mortality prediction to be used as a decision aid to cull railers. Cattle culled and marketed prematurely are commonly referred to as realizers or railers.…”

“…Managers readily accept the steep discounts for railers, as the alternative would be a complete loss of revenue in the event of premature death. Feuz, Feuz, and Johnson (2021) rightly note that "if a feedlot manager were able to predict which calves were going to die before the end of the feeding period, then naturally the manager would look to alter their management practices or market these animals prematurely in order to recoup a portion of the investment" (242). They ultimately concluded through simulation that the net return would increase on average by $14.01 per head for calves having been treated at least once for any health incident if the best-performing classifier (logistic) were used as a culling decision aid.…”

“…Through monitoring operational data, management can often identify trends and anomalies that are cause for concern and may warrant corrective action. Operational data has also proven useful in many scholarly research projects intended to improve feed yard efficiency and profitability (Rojas et al 2022;Feuz, Feuz, and Johnson 2021;Moya et al 2015;Amrine, White, and Larson 2014;and Theurer et al 2014). There are many components affecting profitability in the cattle feeding industry, not the least of which is a feed yard's mortality rate (Irsik et al 2006).…”