Lessons from the 2016 CCSMG Conference
Today at the Chemical Customer Service Management Group annual conference in Orlando Florida, I presented on Predictive Analytics. The presentation revolved around challenges including process variation and data integration. Using Vendor Managed Inventory (VMI) as an example, I explained that integrating data from buyers, sellers, carriers and tank monitoring systems can help a supply chain organization keep their customer’s tanks full. One of the main concerns was related to inaccurate demand signals.
There are several approaches to addressing the concern of inaccurate demand signals. One way is ‘multi-echelon VMI’, which enables the direct capture of demand data from end-customers allowing a more accurate replenishment of intermediate storage facilities. The predictive power of this application is that it smooths out demand variation and supports economic order quantities while taking into account the individual demand profiles of each customer.
The end result of this system is to predict stock-out conditions and provide decision-support information to the end users – allowing them to react within the parameters of their supply chain capabilities.