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    Quantitative analysis:Forecasting with moving averages.

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    Tires for You, Inc. (TFY), founded in 1987, is an automotive repair shop specializing in replacement tires. Located in Altoona, Peensylvania, 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 bsuiness (it also performs ooil 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 ususally stocked for this year what they sold last year. He readily admitted that several times throughout the season stockouts occurred and customers had to go elsewhere for tires.

    Although many tire replacements were for deective or destroyed tires, most tires were installed on cars whose original tires had worn out. Most ofter, 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.

    Mth Tires Used
    Jan 510
    Feb 383
    Mar 1,403
    April 1,913
    May 1,148
    June 893
    July 829
    Aug 638
    Sept 2,168
    Oct 1,530
    Nov 701
    Dec 636
    TOTAL 12,752


    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.

    Mth Year 3 Demand Year 2 Demand
    Jan 501 526
    Feb 376 394
    Mar 1,377 1,446
    April 1,878 1,972
    May 1,127 1,183
    June 876 920
    July 814 854
    Aug 626 657
    Sept 2,128 2,235
    Oct 1,502 1,578
    Nov 689 723
    Dec 626 658
    TOTAL 12,520 13,146

    6. Based on the various methods used to calculate a forecast for TFY, which method produces the best forecast? Why? How could you improve upon this forecast.

    (I've done 3, 4, 5 - 10).

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    Solution Summary

    The problem deals with forecasting output using a 3-month moving average.