In: Operations Management
Goodyear Tire and Rubber Company is the ninth largest tire manufacturer in the world. Here are the sales revenues for the past five years:
Year |
Revenue (millions) |
1 |
$4,877.9 |
2 |
5,065.4 |
3 |
5,525.6 |
4 |
5,729.8 |
5 |
5,499.7 |
a.When might a manager prefer linear trend/double exponential smoothing techniques to moving average/simple exponential smoothing techniques and why? (5 points)
b. Based on MAD for the last three years (years 3, 4, and 5), which method (linear-trend or double-exponential smoothing method with a = 0.4 and b = 0.2 (start with initial estimates S1 = $4,867.90 and T1 = $201.5 for year 1)) provides the better forecasts? Explain. Then, use your selected forecasting method, forecast the revenue for year 6 and year 7.
A and B combined
Linear trend:
n= | 5 | |||||
X | Y | X^2 | XY | Forecast | AD | |
Week | Revenue | (a+bX) | ||||
1 | 4,877.90 | 1 | 4877.9 | 4958.08 | ||
2 | 5,065.40 | 4 | 10130.8 | 5148.88 | ||
3 | 5,525.60 | 9 | 16576.8 | 5339.68 | 185.92 | |
4 | 5,729.80 | 16 | 22919.2 | 5530.48 | 199.32 | |
5 | 5,499.70 | 25 | 27498.5 | 5721.28 | 221.58 | |
Sum | 15 | 26698.4 | 55 | 82003.2 | MAD | 202.2733 |
a = | 4767.28 | |||||
b = | 190.80 | |||||
Y = a+ bX | ||||||
6 | 5912.08 | |||||
7 | 6102.88 |
Doublt exponential
a = | 0.4 | b= | 0.2 | ||||
Period | Sales | St | S't | S (2*St-S't) | T | Forecast (S+T) | |
Base | Trend | AD | |||||
1 | 4,877.90 | 4,867.90 | 4,867.90 | 4,867.90 | 201.50 | 5069.40 | |
2 | 5,065.40 | 4871.90 | 4869.50 | 4874.30 | 202.78 | 5077.08 | |
3 | 5,525.60 | 4949.30 | 4901.42 | 4997.18 | 227.36 | 5224.54 | 301.06 |
4 | 5,729.80 | 5179.82 | 5012.78 | 5346.86 | 297.29 | 5644.15 | 85.65 |
5 | 5,499.70 | 5399.81 | 5167.59 | 5632.03 | 354.33 | 5986.36 | 486.66 |
MAD | 291.12 | ||||||
6 | 5,499.70 | 5439.77 | 5276.46 | 5603.07 | 348.53 | 5951.61 | |
7 | 5,499.70 | 5463.74 | 5351.37 | 5576.11 | 343.14 | 5919.25 |
So as per the MAD for 3-5 we see the MAD for linear trend is lower and hence it is better in forecasting year 6 and 7 (shown above)