Meat & Livestock News

Utilising Machine Learning to Enhance Employee Retention in the Red Meat Processing Sector

Employee retention remains a pivotal aspect of AMPC’s strategic vision. The Australian red meat processing industry often grapples with the challenge of retaining seasoned employees. Recent research conducted by AMPC suggests that machine learning could offer a solution. By predicting potential absenteeism or departures, processors can proactively manage their workforce, ensuring longer tenures.

The study used a machine learning model to analyse HR data from a specific red meat processor. This model utilised historical employee behaviour to detect similar patterns among current staff. Key data points encompassed sick leave, type of leave, days when leave was taken, pay grade, and service duration. Understanding that the model’s accuracy improves with more comprehensive data is crucial.

Amanda Carter, AMPC Program Manager, highlighted the broader implications of this research. She mentioned, “If this model proves effective, it could benefit the processing sector and the entire red meat supply chain. This could further enhance the global competitiveness of the Australian red meat industry.”

The research concluded that the machine learning model is indeed a promising tool for curbing turnover rates in red meat processing facilities. With slight modifications, it can be adapted to various plants. Carter added, “A couple of plants have shown interest in the model, and discussions are underway regarding potential implementation trials and data set expansion.”

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