Exercise 1: Forecasting chicken wing demand
The following data represents the weekly demand for chicken wings at a local restaurant during the past six weeks:
Week | 1 | 2 | 3 | 4 | 5 | 6 |
Demand | 650 | 521 | 563 | 735 | 514 | 596 |
Complete the following:
a. Forecast the demand for week 7 using a five-period Moving average.
b. Forecast the demand for week 7 using a three-period weighted moving average. Use the following weights to obtain your forecast:
o W1 = 0.5
o W2 = 0.3
o W3 = 0.2
c. Forecast the demand for week 7 using exponential smoothing.
o Use an α value of 0.1
o Assume that the forecast for week 6 was 600 units
d. What assumptions are made in each of the forecasts?
Guidance: Calculate the forecasting values using Excel or manually.
Exercise 2: Forecasting tire demand
The following data represents demand for tires from the Easy fit tire store over a period of 14 days. Split the data into two equal parts of seven days each. Assume F1 = 198.
F1 is the first forecast
Day | Demand | Day | Demand |
1 | 200 | 8 | 208 |
2 | 209 | 9 | 186 |
3 | 215 | 10 | 193 |
4 | 180 | 11 | 197 |
5 | 190 | 12 | 188 |
6 | 195 | 13 | 191 |
7 | 200 | 14 | 196 |
Complete the following:
a. Develop a spreadsheet using the first seven days of demand to determine the best exponential smoothing model for values of α = 0.2, α = 0.3, and α = 0.4. Select the model with the smallest absolute deviation for seven periods.
b. Develop another spreadsheet using the holdout sample for the second seven days to compare the best exponential smoothing model found in part a with a three-period moving average model. Compare the predictions on the basis of the total absolute deviation for the seven periods.
c. What principles does this problem illustrate?
