Modified Case 7.1: Tires for You, Inc. - Truck Division Background 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, lan Overbaugh. Since tire replacement is a major portion of TFY's business (it also performs oil change, small mechanical repairs, etc.), lan was surprised at the lack of forecasts for tire consumption for the company, particularly for the larger tractor trailer tires. 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 through the season stockouts occurred and their trucking company customers had to go elsewhere for tires. Although many tire replacements were for defective or retreaded tires whose replacement treads had peeled away during use, most of these tires were installed on trucks whose original tires had simply worn out. lan was determined to get a better idea of how many tires to hold in inventory during the various months of the year. Listed below is a summary of individual truck tire sales by month: 2019: 2020: Period October November December January February March April May June July August September October November December Tires Used 7083 7552 6146 5677 6704 6145 4653 5209 6644 5207 4739 5677 6640 7087 5750 The TFY, Inc. general manager, Mr. Overbaugh, has hired your consulting firm to build a forecast for the monthly demand expected in 2018. In particular, your firm has been contracted to do the following: Tasks 1. Calculate a month-by-month forecast for 2017 using both a three-month simple moving average and a three-month weighted moving average (with weights 0.62, 0.29, and 0.09 for the most recent period, the second most recent period, and the third most recent period, respectively.) Show all calculations in a table. 2. Determine and compare the accuracies of the 2017 forecasts for the two types of forecasts requested in Task 1, using the Mean Squared Error as the measure of forecast error. (Show all calculations in the Task 1 table). Which one resulted in the lower error? Based on the results of your calculations, which forecasting method would you recommend to TDY, Inc