ABC Cracker Company manufactures cheddar cheese fish crackers. They are shipped
ID: 3202915 • Letter: A
Question
ABC Cracker Company manufactures cheddar cheese fish crackers. They are shipped in full truckloads to the retailer customers’ DCs. Below is the number of truckloads ABC shipped per month during 2015:
1. generate all three types of forecasts using the data on the left marked 2015 and 2016. Then on a separate page for each type of forecast, generate the error terms using the demand marked 2017 on the right and the forecast determined from the 2015 and 2016 data.
2. Using a simple 3-period moving average, generate a monthly forecast for 2017
3. Using a simple weighted average, generate a monthly forecast for 2017. Use a three period average, with the weight being: alpha =0.6; alpha–1 =0.25; alpha-2= 0.15.
4. Use exponential smoothing to generate a monthly forecast for 2017. Assume F1 = 187. Use alpha =0.6
5. Create a table for the three forecasting methods you used here. Make sure you include statistics on: bias, MAD, MSE, MAPE, and tracking signal (this is just CFE/MAD). Indicate which forecasting method gives you the best result.
2015 TL shipped (demand) October 168 November 191 December 184 2016 2017 TL shipped (demand) January 179 197 February 162 179 March 170 187 April 196 216 May 180 198 June 136 150 July 185 204 August 190 209 September 179 197 October 187 206 November 213 234 December 204 224Explanation / Answer
1.
2. Forecast for 2017:
3. 3-period weighted moving average:
Formula:
4. Forecast using exponential smoothing:
Formula:
5. Reults:
Computation:
TL shipped (demand) 2-month simple moving average Error 3-month simple moving average Error 2015-October 168 2015-November 191 2015-December 184 179.5 2016-January 179 187.5 181 2016-February 162 181.5 184.6667 2016-March 170 170.5 175 2016-April 196 166 170.3333 2016-May 180 183 176 2016-June 136 188 182 2016-July 185 158 170.6667 2016-August 190 160.5 167 2016-September 179 187.5 170.3333 2016-October 187 184.5 184.6667 2016-November 213 183 185.3333 2016-December 204 200 193 2017-January 197 208.5 11.5 201.3333 4.333333 2017-February 179 200.5 21.5 204.6667 25.66667 2017-March 187 188 1 193.3333 6.333333 2017-April 216 183 -33 187.6667 -28.3333 2017-May 198 201.5 3.5 194 -4 2017-June 150 207 57 200.3333 50.33333 2017-July 204 174 -30 188 -16 2017-August 209 177 -32 184 -25 2017-September 197 206.5 9.5 187.6667 -9.33333 2017-October 206 203 -3 203.3333 -2.66667 2017-November 234 201.5 -32.5 204 -30 2017-December 224 220 -4 212.3333 -11.6667