Auto Parts Forecasting Case Study

Prepared by: Mariela Tuero

Date: December 13th, 2013
Nova Southeastern University
H. Wayne Huizenga School of Business & Entrepreneurship Assignment for Course: QNT5040
Submitted to: Dr. Ronald Mesia
Submitted by: Mariela Tuero N00046141 3821 SW 129 Ave Miami, FL 33175 305-282-6727
Date of Submission: December 13th, 2013
Title of Assignment: Auto Parts Forecasting Case Study

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The director of marketing research needs to determine which forecast method is the most accurate in forecasting sales for the year 2008 based on the collected data on quarterly sales for the previous four years. After running four different methods of forecasting: regression with time series, regression with economic factors, Holtz-Winters additive model, and Holtz-Winter multiplicative model. Based on the error the most appropriate method of forecasting is regression with economic factors. Based on this model, sales for the year 2008 decrease significantly, which may be indicative of possible recession. Therefore, it is highly recommended that auto parts plans efficiently with the available resources to prevent large loss of money.

Background
Forecast is “a planning tool that helps management in its attempts to cope with the uncertainty of the future, relying mainly on data from the past and present and analysis of trends” (BusinessDictionary.com). A good forecast helps companies prepare to prevent large amount of money loses by planning more efficiently. In the Auto Parts forecasting case study, the director of marketing of a large manufacturer of spare parts for automobiles understands the consequences of forecasting errors and wishes to forecast the sales as