Session 7: Machine Learning Applications in Supply Chain Planning

Kristen Daihes, Partner, Opex Analytics

Ever heard the phrase ‘They can’t see the forest for the trees’? We often find supply chain planning groups and processes in this exact position. Planning is often overlooked as an area of opportunity for the application of analytics solutions. The operational nature of planning cycles often leads to businesses focused on simply keeping their heads above water every day instead of working to understand and streamline the true data drivers and associated decisions being made. As analytics continues to make its way into almost all facets of business we can say with certainty that if you haven’t started to consider incorporating analytics into your key planning areas you are most likely already behind the curve.

This session will introduce you to some analytics applications we have seen making a true difference within the planning function of companies. We will review the latest trends in incorporating machine learning into forecasting, using algorithms to address short-term corrections in frozen planning horizons, the addition of predictive analytics in managing inventory, the use of machine learning to optimize key parameters, as well as the automation of root cause analysis used to prevent operational issues before they occur. We will highlight use cases from our own experience, share best practices from our own implementations and highlight where the future of analytics in planning is headed.