Using machine learning for staff retention in red meat industry

A challenge for the Australian red meat processing sector is retaining experienced employees. An AMPC research program has found that machine learning might make it possible to predict which employees are at risk of absenteeism or departure, so processors can actively manage staff to retain them for longer.

The project analysed HR data from a selected red meat processor and applied a machine learning model that used the data to learn from behaviours of past employees to help identify like patterns in current employees. It used data such as sick leave, leave type, days of the week leave was taken, pay scale and length of service.

AMPC Program Manager Amanda Carter said the model, if successful, might not only assist the processing sector but also have carryover benefit throughout the rest of the red meat supply chain, contributing to a more globally competitive Australian red meat industry.

The research program concluded that the machine learning model is a viable tool for reducing turnover in red meat processing plants and it could be suitable for different plants with minor adjustments.

“Two plants have already expressed interest in potentially adopting the model in practice, and consideration is now being given to how an implementation trial might work and what would be involved in expanding the dataset,” Carter said.

Image credit: iStock.com/FG Trade