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Auto Parts Forecasting Case

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Executive Summary

The Auto Parts manufacturer for automobile spare parts, Director of Marketing Research Ted Ralley is currently working on the sales forecast for next year. Ted has previously noticed forecast errors are not inexpensive and must determine the sales forecast for 2008 based on the sales from the previous four years (2003-2007) as precisely as possible. After running the following methods: Holtz-Winters Additive Model, Regression with Times Series, Regression with Economic Factors, and Holtz-Winters Multiplicative Model. Built on the data and error the most appropriate method of forecasting is Regression with Economic Factors. According to this model, sales for the year 2008 will decrease significantly, which may be result in recession. Consequently, it is best that Auto Parts plan efficiently with the available resources to prevent any possible loss of revenue.
Background
Forecasting is a preparation disposition that aids organizations in its endeavors to survive the uncertainty of the future, relying primarily on data from the past and present and study of trends. Most companies essentially strategize their budget by analyzing the information provided to their organization’s forecast. Companies that prepare for the future by using the forecasting method are less likely to encounter losses even though forecasts are not always 100% accurate. But they still provide management with a greater indication of what can be avoided or used more/less based on previous trends and losses. In the Auto Parts forecasting case, Ted the director of marketing a large manufacturer of spare parts for automobiles understands the consequences of forecasting errors and has decided to forecast the sales as precisely as possible to better direct the company. Once Ted collected sales data for each quarter from 2003 to 2007 initially ran through the regression with

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