Using Discrete Event Simulation to Model the Benefits of VMI and CPFR
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Collaborative Planning, Forecasting, and Replenishment or CPFR, is a cooperative business methodology where supply chain members exchange demand information and develop a single shared forecast. CPFR promises to improve demand forecast accuracy, reduce inventory levels, and improve fill rates. Many organizations, including Wal-Mart, Michelin, and Heineken have successfully utilized CPFR to reduce their costs, lower their levels of inventory, and improve their fill rates. With advance notice of promotions or new product introductions, members of the supply chain can plan their own replenishment and manufacturing activities accordingly, and reduce their reliance on higher levels of safety stock. Although there have been many successful CPFR pilot programs, few large scale implementations of CPFR can be found and some case studies have reported disappointing results. To determine when CPFR will deliver on its promises, a simulation study of a three-stage supply chain was devised. CPFR was compared to Vendor Managed Inventory (VMI), another popular information sharing supply chain methodology, and Independent Sourcing, where no information was shared and the supply chain members acted independently. A variety of demand patterns were tested, including steady demand and demand with promotions. The simulation was first tested using hypothetical data, then run with demand data provided by 3M, a large, conglomerate corporation. The simulation results showed that when the supply chain members of VMI and CPFR had access to the same information, the two methodologies performed comparably. When promotions were not present, the information shared in CPFR was similar to the information shared in VMI and thus, there was no statistically significant difference between the performances of VMI and CPFR. When the supply chain members of CPFR were privy to information not shared in VMI, as was the case when promotions were present, CPFR had lower costs and inventory levels than VMI. When promotions were planned by the retailer, their timing was only shared with the vendor in CPFR, and not with the vendor in VMI. To achieve the desired fill rates, the vendor in VMI held more inventory and therefore, incurred higher costs than CPFR. While VMI and CPFR are easily differentiated in literature, in practice, VMI implementations can have aspects of CPFR, and vice versa. Our research has revealed that complete information sharing is of the utmost importance. When crucial information is withheld from supply chain partners, the ability of CPFR or VMI to reduce costs and inventory levels greatly diminishes. When working with incomplete information, supply chain members carry higher inventory levels to compensate for uncertainty.
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Amanda Cha (2013). Using Discrete Event Simulation to Model the Benefits of VMI and CPFR. UWSpace. http://hdl.handle.net/10012/7232