SUPPLY CHAIN MANAGEMENT I THUMBS UP FOR ANSWERS TO ALL QUESTIONS 1. What role do
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Question
SUPPLY CHAIN MANAGEMENT I THUMBS UP FOR ANSWERS TO ALL QUESTIONS
1. What role does forecasting play in the supply chain of a build-to-order server manufacturer such as Dell?
2. How could Apple use collaborative forecasting with its sup- pliers to improve its supply chain?
3. What role does forecasting play in the supply chain of a mail- order firm such as L.L. Bean?
4. What systematic and random components would you expect in demand for chocolates?
5. Why should a manager be suspicious if a forecaster claims to forecast historical demand without any forecast error?
6. Give examples of products that display seasonality of demand.
Explanation / Answer
Although Dell builds to order, they obtain PC components in anticipation of customer orders and therefore they rely on forecasting. This forecast is used to predict future demand, which determines the quantity of each component needed to assemble a PC and the plant capacity required to perform the assembly.
Collaborative forecasting requires all supply chain partners to share information regarding parameters that might affect demand, such as the timing and magnitude of promotions. Apple could share with their components suppliers all of the promotions, e.g., holiday, back-to-school, etc., they have planned. These suppliers could, in turn, notify their suppliers of discrete components that a spike in demand is anticipated. These demand forecasts for end items determine the demand for components and coupled with knowledge of fabrication times, allows all members of the supply chain to provide the right quantity at the right time to their customers.
LL Bean has historically operated almost exclusively in a make-to-stock mode and with very few exceptions, stocked products that did not go out of style as rapidly as many other clothing and accessory lines. A pre-worldwide web existence would have relied on communication with manufacturers about what products might be featured on the front of their catalog. The lead times involved in printing and distributing the catalog and producing the product line were such that elaborate planning and forecasting tools were not required. A quick visit to the web site demonstrates that this is changing; the featured products on the web site can be changed daily or programmed to rotate each time the web page is refreshed. LL Bean and their supply chain, including the logistics component, are well aware of the demand forecast and can all receive sales data as orders are placed. LL Bean probably has an extranet to communicate sales data with suppliers and allows customers to create accounts to manage purchases, wish lists, and track orders.
Systematic components are level, the current deseasonalized demand; trend, the rate of growth or decline in demand for the next period; and seasonality, the predictable seasonal fluctuations in demand. The demand for chocolates is probably highly seasonal, one would expect demand to spike for certain holidays such as Valentine’s Day, Halloween, and Christmas.
The primary difficulty with such a claim is that forecasts are always wrong, hence, an estimate of error should be provided with the forecast. Given a set of data, it is possible to create a forecasting model that is 100% accurate, but such a model would contain ridiculous cubic, quartic, and possibly higher-order terms. The model would work only on that data.
Products that display seasonality include, heating oil, electricity, natural gas, wrapping paper, school supplies, sporting goods (summer, winter, etc.), facial tissues, beverages (coffee, beer, iced tea, etc.), ice cream, pizza delivery, and tax preparation services. All products display some form of seasonality if you look at them in a global perspective.
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