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Case Study : Soup King Has Experienced Tremendous Growth Over The Past 5 Years

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Assignment Three Soup King has experienced tremendous growth over the past 5 years. Modeling our supply chain after the OGSM model, we have exceeded several corporate objectives listed within our 10 year plan. Although we have addressed and fixed issues relating to our product quality and production line, there are new concerns that must be addressed. As a company that prides itself on continuous improvement, Soup King needs to speedily address our weaknesses, while capitalizing on our strengths to continue to be competitive in the soup industry. Before Soup King can build upon our strengths, there are vulnerabilities within our supply chain that must be addressed. Amid shipment delays and unacceptable perfect order rates, we need …show more content…

Following the SCOR model principles, we need to see what effect demand has throughout our supply chain. Seeing how Bullwhip Effect can create strong demand variability for our suppliers further down the distribution channel, it is critical we can reduce this variability by creating an effective exchange of pertinent information. Similar to a POS system, I would like to have a real-time VMI network provided to our suppliers, with Soup King acting in the role of a customer. This should help reduce variability in demand orders and help better pinpoint the amount of product or suppliers should send to us. If our supply orders are constantly in queue and flexible, we can reduce waste and make the most efficient use of shipments to our plants. By reducing order-to-delivery times, we transfer a greater level of accountability to our supplier. In turn, this should decrease our own holding cost for unnecessary extra inventory, reducing COGS and following the principles of a lean-system of inventory management, as well as increasing our turnaround times for customers. In addition to this cost-cutting measure, a demand pattern analysis will be conducted to create better forecast over future time horizons. As detailed in my previous reports, the multiplicative season’s method should play a role in demand (since soup can be considered seasonal). Creating a time series, our demand forecast can help model seasonal pattern shifts, thereby relaying this information

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