Employee retention is a key pillar in AMPCs strategic plan.
Retaining experienced employees is one of the biggest challenges in the Australian red meat processing sector. 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 in the job for longer.
The project looked at HR data from a selected red meat processor and applied a machine learning model which uses the data to learn from behaviours of past employees, to help identify like patterns in current employees. Data used included, but was not limited to, was sick leave, leave type, days of the week leave was taken, pay scale and length of service. It’s important to note, the more data added, the more accurate the prediction will be.
AMPC Program Manager Amanda Carter said, “If successful, the model might not only assist the processing sector but also have carry over benefit throughout the rest of the red meat supply chain, potentially resulting in a more globally competitive Australian red meat industry.”
The program concluded that the machine learning model is a viable tool for reducing turnover in red meat processing plants, and minor adjustments to the way it works would make it suitable for different plants.
Amanda said, “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 data set.”
Read the full report on AMPC’s website.