Advanced Analytics

WesCEF understands the importance of developing and embracing new technologies, after all its businesses have been doing it for over 100 years.

Growing our business through Advanced Analytics

As WesCEF turns to the future, data analytics is essential to our success by helping identify new opportunities and in making better, informed decisions.

WesCEF collects a lot of data, but it’s rarely in a form that can be immediately modelled. That’s where WesCEF’s Advanced Analytics team comes in, helping to solves complex, data driven problems to improve business.  The team works closely with the Wesfarmers Data Analytics Centre in Melbourne, providing access to the latest in research and training.


Throughout our long history, our people have always been central to our success.

We need people who are curious, adaptable and enjoy collaborating with others to implement new technologies to secure our future for the next 100 years. Check out our current data analytics opportunities at WesCEF.


Ammonia Shipping Optimisation

Our Advanced Analytics team, with support from Wesfarmers’ Advanced Analytics Centre, developed an optimisation tool to consider multiple factors (shipping schedules, tank levels, demand forecasts) and suggested the optimal shipping arrival dates to reduce the amount of demurrage paid by WesCEF. Demurrage is an expense paid when a ship has a delay in unloading it’s cargo at the destination port.


Sodium Cyanide Optimisation

Several years of Sodium Cyanide plant data was analysed by WesCEF’s Advanced Analytics team to determine the optimal operating conditions to maximise production without increasing cost. The project resulted in an operator dashboard that gave the operators the ideal levels of multiple plant parameters to maximise production.


Nitric Acid Plant Dashboard

Plant operators worked with our Advanced Analytics team to analyse three years of plant data and performed complex regressions to develop a powerful algorithm that resulted in an operator dashboard displaying ideal levels of multiple plant parameters to maximise production.