1.Suggest a forecasting methodology (based on the models discussed in class) and
ID: 2935880 • Letter: 1
Question
1.Suggest a forecasting methodology (based on the models discussed in class) and provide forecasts for
the next five weeks. In order to validate your methodology, Ms. Enterprise requires that it must generate
a Mean Absolute Deviation (MAD) no greater than those given in Table 1 when applied to the last ten
most recent weeks. In other words, the first ten weeks are used to make a forecast model, and the recent
ten weeks are used to validate the forecast model.
2. Additionally, suggest 2 forecasting methods (based on your research) that might be appropriate for the
given data set. This implies that your group will have to review literature published in journal papers
and identify two that might be appropriate for this situation. You are expected to explain why these
methods are suitable. Select one of the methods, use the data and develop the forecast for the next
five weeks. Please cite the journal paper used for reference.
MAD is 10 for every product
Table 1
Week Product 1 Product 2 Product 3 Product 4 Product 5 1 140 145 100 18 55 2 155 164 82 22 46 3 145 178 70 25 58 4 152 200 55 27 37 5 155 215 110 32 32 6 145 205 85 35 48 7 147 170 74 39 67 8 135 142 62 41 68 9 137 119 115 43 52 10 140 147 88 47 42 11 120 162 78 53 32 12 150 180 67 55 43 13 161 199 121 58 37 14 143 220 93 60 61 15 149 208 84 64 45 16 140 175 71 66 48 17 142 140 128 69 53 18 157 121 99 72 38 19 148 146 89 75 57 20 144 160 77 79 40Explanation / Answer
To estimate the data of week 21st to 25th data, we will consider the data of first 10 weeks and the validity of the estimated data will be based upon the data of the last 10 weeks (as mentioned in the question).
The estimate for the next week is found using the formula
t+1 = Yt + (1-) t
In this equation, t+1 represents the forecast value for period t + 1; Yt is the actual value of the current period, t; t is the forecast value for the current period, t; and is the smoothing constant, or alpha, a number between 0 and 1.
In this question we will estimate the data using three different values of alpha i.e, 0.3, 0.5 and 0.7.
The appropriate value of alpha will be chosen according to the last 10 weeks value of MAD.
Here I will solve the for product 1 and similarly can be found out for all the products.
Since for first week we do not have any previous information therefore we will use the actual value as the estimated value.
week
Product 1 alpha=0.3 MAD
1
140
140
-
2
155
140
15
3
145
144.5
0.5
4
152
144.65
7.35
5
155
146.855
8.145
6
145
149.2985
4.2985
7
147
148.009
1.00895
8
135
147.7063
12.70627
9
137
143.8944
6.894385
10
140
141.8261
1.82607
21
141.8261
141.2782
6.414352(average)
22
141.2782
141.4426
23
141.4426
141.3933
24
141.3933
141.4081
25
141.4081
141.4036
Alpha =0.5 MAD
1
140
140
140
-
2
155
140
140
15
3
145
144.5
150.5
2.5
4
152
144.65
146.65
5.75
5
155
146.855
150.395
5.875
6
145
149.2985
153.6185
7.0625
7
147
148.009
147.5856
1.53125
8
135
147.7063
147.1757
12.76563
9
137
143.8944
138.6527
4.382813
10
140
141.8261
137.4958
0.808594
21
139.1914
141.2782
6.186198 (average)
22
139.5957
140.6522
23
139.3936
140.3352
24
139.4946
140.0527
25
139.4441
139.8853
Alpha=0.7 MAD
1
140
140
2
155
140
15
3
145
150.5
5.5
4
152
146.65
5.35
5
155
150.395
4.605
6
145
153.6185
8.6185
7
147
147.5856
0.58555
8
135
147.1757
12.17567
9
137
138.6527
1.652699
10
140
137.4958
2.50419
21
137.4958
139.2487
6.22(avg)
22
139.2487
138.0217
23
138.0217
138.8806
24
138.8806
138.2794
25
138.2794
138.7003
Since MAD for alpha =0.5 is minimum , therefore we will use the estimations found using alpha =0.5.
2. The other methods that can be used to estimate the data are the normal average approach in which you can calculate the mean of the previous data and find the estimates by assuming the mean equal to the previous mean.
It can also be estimated using weighted moving average approach. In this methods weights are assigned to different parameters anfd then the estimate is calculated.
1
140
140
-
2
155
140
15
3
145
144.5
0.5
4
152
144.65
7.35
5
155
146.855
8.145
6
145
149.2985
4.2985
7
147
148.009
1.00895
8
135
147.7063
12.70627
9
137
143.8944
6.894385
10
140
141.8261
1.82607
21
141.8261
141.2782
6.414352(average)
22
141.2782
141.4426
23
141.4426
141.3933
24
141.3933
141.4081
25
141.4081
141.4036
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