Supply chain analytics is critical to identify the opportunities for automation and leverage any possible applications. Before embarking on automation initiatives, firms apply relevant analytical techniques to evaluate the potential value, risks and returns. One of the often-overlooked advantages of automated facilities is the precision, timeliness, and availability of process information. The analytics can leverage this opportunity to maximise the value of supply chain automation.

Optimising automation uptake requires advanced scenario analytics. In this course, students will become familiar with a range of analytical approaches to align initiates with demand volumes and variability. The range of data sources to analyse automation performance will be explored. Simulation, a common approach to analyse supply chain automation, will be covered in-depth. During this course, you will become familiar with contemporary data analytics in supply chain automation using a range of analytics methods.