Use the data set below (Data Set E3) to answer the questions that follow. Data Set E3 Period Sales Volume 1 1000 2 1200 3 1450 4 1750 5 2200 6 2750
a. Find the four-period simple moving average forecasts for Periods 5 and 6.
b. Find the four-period weighted moving average forecasts for Periods 5 and 6 using weights of 0.05, 0.15, 0.30, and 0.50 from the earliest period to the latest period, respectively.
c. Which set of forecasts is more accurate, the simple moving average forecasts or the weighted moving average forecasts? Why is that set of forecasts more accurate in this particular case (using Data Set E3)?
d. Will that type of forecast always be more accurate? Why or why not?
a . Find the four period simple moving average forecasts for Periods 5 and 6.
Forecast for Period 5 = 1350
Forecast for Period 6 = 1650
b. Find the four period weighted moving average forecasts for Periods 5 and 6 using weights of 0.05, 0.15, 0.30, and 0.50 from the earliest period to the latest period, respectively.
Forecast for Period 5 = 1540
Forecast for Period 6 = 1902.5
c. Which set of forecasts is more accurate, the simple moving average forecasts or the weighted moving average forecasts?
In this case the weighted moving average forecasts are more accurate.
One can use the mean absolute deviation (MAD) to compare forecast accuracy. For the SMA, the MAD for the 2 periods is 975 . For the WMA forecast, the MAD is 753.8.
Why is that set of forecasts more accurate in this particular case (using Data set E2)?
Because demand is increasing in every period in Data Set E3 the weighted moving average forecast, which weighs more heavily recent periods of demand in calculating the forecast versus early periods of demand, is more capable of reflecting recent changes in demand patterns.
d. Will that type of forecast always be more accurate? Why or why not?
While the weighted moving average forecast works very well with this particular Data set, it might not be as effective if demand were more stable from period to period. When there's a greater degree of stability in demand from period to period, a simple moving average forecast would likely be more effective. Nonetheless, if demand patterns were very random it is uncertain which forecasting model would be more accurate. It is for this reason the textbook describes a number of different forecasting methods that when used together can help an organization see a more complete picture of what the future may hold. Use of the MAD is necessary to compare forecast accuracy.
The student may also note that while the weighted moving average forecast was more accurate, neither forecasting model would have aptly prepared the organization for the increasing demands that were experienced during periods five and six. The student might even mention some of the other models from the textbook. The exponential smoothing forecasting model and trend adjusted exponential smoothing forecasting model may be more effective for this particular Data set.
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