Anders Hardware Forecasting Exam Practice - Solutions

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Babson College *

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Economics

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Apr 3, 2024

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Forecasting Exam Practice: Anders Hardware Anders Hardware wants to improve their demand forecasting for two key products: hammers and snow shovels. The demand information is shown in the tables and graphs below. Answer each question using the available information and the forecasting techniques taught in class. 0 2 4 6 8 10 12 0 2 4 6 8 10 12 Hammer Demand What components of demand are visible in the graph for hammer demand? Trend, Level, Randomness What forecasting methods would be appropriate given the components of demand? Holt’s Model Use the table below to forecast demand for the next period using a 2-period moving average approach and report on the error. Use the measure of error that is most appropriate when the cost of forecast error is proportional to the size of the error. Period Demand Forecast Et At 0 99.20756 1 106.3515 2 113.343 102.7795 -10.5634 10.56344 3 113.2953 109.8472 -3.44813 3.448135 4 116.3856 113.3191 -3.06642 3.06642 5 127.2075 114.8405 -12.367 12.36704 6 131.4063 121.7965 -9.60974 9.60974 7 131.2359 129.3069 -1.92901 1.92901 8 142.6361 131.3211 -11.315 11.31501 9 141.0566 136.936 -4.12057 4.120567 10 153.6678 141.8463 -11.8215 11.82149 11 147.3622 MAD 7.582316
0 2 4 6 8 10 12 0 2 4 6 8 10 12 Snow Shovel Demand What components of demand are visible in the graph for snow shovel demand? Trend, Level, Randomness, Seasonality What forecasting methods would be appropriate given the components of demand? Winter’s Method Use the table below to forecast demand for the next period using a 4-period moving average approach and report on the error. Use the measure of error that is most appropriate when there is significant seasonality and demand variation. Period Seasonal Demand Forecast Et At % 0 131.1069029 1 191.5931851 2 102.7475697 3 84.37333392 4 157.164559 127.4552479 -29.7093 29.70931 18.90% 5 225.5766034 133.9696619 -91.6069 91.60694 40.61% 6 113.3893969 142.4655165 29.07612 29.07612 25.64% 7 98.4675411 145.1259733 46.65843 46.65843 47.38% 8 178.3187349 148.6495251 -29.6692 29.66921 16.64% 9 258.5521805 153.9380691 -104.614 104.6141 40.46% 10 135.2311426 162.1819634 26.95082 26.95082 19.93% 11 167.6423998 MAPE 29.94%
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