The third case study is Case 7.1 Tires For You, Inc. from your textbook. This case study explains the previous sales history of Tires For You, Inc. At the end, you will calculate the various forecasting methods. You are to read this case study and answer all four questions. It is expected that you use the calculations and strategies located within your textbook when answering these questions. It is also expected that you properly conduct research to add an additional dimension on top of your textbook readings to properly answer each of these questions.

Case 7.1. 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, Ian Overbaugh. Since tire replacement is a major portion of TFY's business (it also performs oil changes, small mechanical repairs, etc.), Ian was surprised at the lack of forecasts for tire consumption for the company. His senior mechanic, Skip Grenoble, told him that they usually 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 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. Ian 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 individual tire sales by month:

PERIOD	TIRES USED
2018
October	9,797
November	11,134
December	10,687
2019
January	9,724
February	8,786
March	9,254
April	10,691
May	9,256
June	8,700
July	10,192
August	10,751
September	9,724
October	10,193
November	11,599
December	11,130

Ian has hired you to determine the best technique for forecasting TFY demand based on the given data.

Case Questions

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, 0.30, and 0.10 for the most recent period, the second most recent period, and the third most recent period, respectively.

3.Calculate a forecast using the exponential smoothing method. Assume the forecast for period 1 is 9,500.

Use alpha = 0.40.

4.Once you have calculated the forecasts based on the above data, determine the error terms by comparing them to the actual sales for 2020 given below:

PERIOD	TIRES USED
2020
January	10,696
February	9,665
March	10,179
April	11,760
May	9,150
June	9,571
July	8,375
August	11,826
September	10,696
October	11,212
November	9,750
December	9,380

5.Based on the three methods used to calculate a forecast for TFY, which method produced the best forecast? Why? What measures of forecast error did you use? How could you improve upon this forecast?