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
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.
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.
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