WK5.1 Forecasting

Shemekia Trimiar Bellevue University, Class SCLM456-861N Bus Logistics Systems Analysis Assignment # 5.1 Forecasting Professor Gary Lawson November 3, 2023 Forecasting in manufacturing: find a case study and share its summary with the class. Reference your material properly. The forecast for Reynolds Metals Co. (Reynolds) is to analyze inventory levels and sales demand with upgraded software. The focus of the company, Reynolds, is to improve shrinking levels of inventory, retain current customers, and gain new customers. In the article Forecasting for Dollars (Fryer, 1997), "in the manufacturing business, the company that can most closely predict not only what to make but also how much to make, and when-wins" and "that even a 1% improvement in forecasting can translate to millions of dollars in savings" and "inventory that we don't have to hold on to." As a company that produces products such as aluminum foil and plastic wrap, customer demand varies, but the company must also push products outside customer orders. The previous Reynolds software, IBM 9672, has been replaced with Logility Planning Solutions. The software change resulted in Reynolds being able to enter and update data daily, bringing about immediate changes in the forecast. The upgraded software was the changing force in decreasing high levels of inventory and streamlining the manufacturing of products not only for make-to-order transactions but also from the demand forecast of make-to-stock. Ideally, Reynolds would like the system to work as follows: "First, the system loads information, such as sales history, to predict the month's demand. That forecast is sent to a distribution planning module and merged with inventory and customer-order projections." Reynolds uses software based on Demand Planning and Inventory Planning, as the latter focuses on the balance of inventory levels and customer service, and the former focuses on customer and product purchase histories. For a business analyst, there would be no more combing through hundreds of reports and extracting data that is relevant would be relevant to that specific time. Instead, the data input from the upgraded system could be visualized through graphical presentations to see and show sales trends from the past three years. These graphs are then interpreted to determine how much a customer orders and how consistently to improve both Reynolds and the customer inventory levels. Since Reynolds is a process manufacturer, the demand forecast should correlate with a forecasting software system. The reality of the upgraded system from a 20-year-old IBM software presented some issues within the company. The reason for implementing the new system for Reynolds was to have precise input data for forecasting customer needs while eliminating forecasting errors. The forecasting error rates dropped from 15% to 5%, reducing inventory significantly. So, the implementation by Reynolds has a positive impact on lowering high inventory levels and customer service. Furthermore, it controls the inventory levels and distribution of products as just-in-time deliveries are improving. Therefore, the newly implemented software presents flexibility and cross-functional communications, which includes market and distribution management.
Also, correlating with the distribution center is a substantial competitive advantage. Another competitive advantage is that the forecasting information with the new system would allow customers to have access to review Reynolds' forecast demands. Customers would be able to see the changes in the items that they would purchase. Overall, the result? "A win-win situation for customers and Reynolds alike. Says Seibert: "It's another way to set us apart." References Fryer, B. (1997). Forecasting for dollars. InformationWeek , (635), 140-142. Retrieved from, http://ezproxy.bellevue.edu/login?url=https://www.proquest.com/trade-journals/forecasting- dollars/docview/229042113/se-2 Weston, R. (1998, February 23). Reynolds foils forecasting errors. Computerworld , 32(8), 53+. Retrieved from, https://link-gale-com.ezproxy.bellevue.edu/apps/doc/A20347301/GBIB? u=nebraska_bell&sid=bookmark-GBIB&xid=9ff4605e
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