Operations and Supply Chain Management The Core

FORECASTING chapter 3 79
The seasonal indexes are found by averaging the corresponding quarter indexes. For example, for
quarter 1
​0.64 = __________
(0.69 + 0.58)
​ ​
2
The forecast including trend are calculated by multiplying the regression forecast by the corresponding
seasonal index. Quarter 10 corresponds to the second quarter of the year, so the
forecast is
​1,090.7 = 1,067.7 × 1.02​
Demand
1,800
1,600
1,400
1,200
Actual
Regression
Forecast Including
Seasonal
1,000
800
600
400
200
–
0 5 10
Period
15
INTERCEPT = 361.00
SLOPE = 70.67
Regression equation is
Y = 70.67 + 361.0 × t
SOLVED PROBLEM 4
A specific forecasting model was used to forecast demand for a product. The forecasts and the corresponding
demand that subsequently occurred are shown below. Use the MAD, tracking signal
technique, and MAPE to evaluate the accuracy of the forecasting model.
ACTUAL
FORECAST
Excel:
Forecasting
October
November
December
January
February
March
700
760
780
790
850
950
660
840
750
835
910
890
Solution
Evaluate the forecasting model using the MAD, the tracking signal, and MAPE.
ACTUAL
DEMAND
FORECAST
DEMAND
ACTUAL
DEVIATION
CUMULATIVE
DEVIATION (RSFE)
TRACKING
SIGNAL
ABSOLUTE
DEVIATION
October
November
December
January
February
March
700
760
780
790
850
950
Average demand = 805
660
840
750
835
910
890
40
−80
30
−45
−60
60
40
−40
−10
−55
−115
−55
1.00
0.67
0.20
1.13
2.25
1.05
40
80
30
45
60
60
Total dev. = 315