"Tires for You" Case Study Refer to your reading for this Unit in the Coyle text for this assignment. Read the ?Tires for You, Inc.? Case Study, on p. 265. In a 1?2 page paper (excluding Title and Reference pages), answer Questions 1, 2 & 6 and attach your Tires4U Case worksheet with detailed calculations. Note that the Tables starting on pg 237 (Chapter 7) will come in very handy in completing the assignment. Tires for You, Inc. Tires for You, Inc. (TFY), founded in 1987, is an automotive repair shop specializing in replacement tires. Located in Altoona, Pennsylvania, TFY has grown successfully over the past few years because of the addition of a new general manager, Katie McMullen. Since tire replacement is a major portion of TFY?s business (it also performs oil changes, small mechanical repairs, etc.), Katie was surprised at the lack of forecasts for tire consumption for the company. Her senior mechanic, Skip Grenoble, told her that they usually stocked for this year what they sold last year. He readily admitted that several times throughout the season stock outs occurred and customers had to go elsewhere for tires. Although many tire replacements were for defective or destroyed tires, most tires were installed on cars whose original tires had worn out. Most often, four tires were installed at the same time. Katie was determined to get a better idea of how many tires to hold in stock during the various months of the year. Listed below is a summary of last year?s individual tire sales by month: Month Tires Used January 510 February 383 March 1,403 April 1,913 May 1,148 June 893 July 829 August 638 September 2,168 October 1,530 November 701 December 636 Total 12,752 Case Questions: Katie has hired you to determine the best technique for forecasting TFY demand based on the given data. 1. Calculate a forecast using a simple three-month moving average. 2. Calculate a forecast using a three-period weighted moving average. Use weights of 0.60, 0.25, and 0.15 for the most recent period, the second most recent period, and the third most recent period, respectively. 6. Based on the various methods used to calculate a forecast for TFY, which method produced the best forecast? Why? How could you improve upon this forecast?
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