Seasonal Profiles and Deseasonalized History Calculations
The seasonal index is evaluated to determine the Deseasonalized history calculation.
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The # of History Slices is the number of slices that are used for forecast calculations.
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• If the Seasonal Index is > 0.3 then the Deseasonalized History is calculated as follows:
Deseasonalized History = Total Demand / Seasonal Index
Where Total Demand = Demand + Adjustments (Outlier or User) + Copy Demand
• If the Seasonal Index <= 0.3 and the # of History Slices is less than the slices in a year (12 monthly or 52 weekly slices) then the Deseasonalized History is calculated as follows:
Deseasonalized History = Total Demand / (# of History Slices) (the average total demand for the number of history slices defined)
• If the Seasonal Index <= 0.3 and the # of History Slices is using all of the slices in the year of the slice then the Deseasonalized History is calculated as follows:
Deseasonalized History = Average of the Total Demand from of the year in which the slice is present
◦ The # of History Slices is set to 24
◦ In 2017–2018, the slice in September uses its own year’s average to calculate the Deseasonalized History.
◦ In 2018–2019, the slice in September also uses its own year’s average to calculate the Deseasonalized History.
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2017–2018
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Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
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Dec
|
Jan
|
Feb
|
Avg
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Demand
|
10
|
12
|
14
|
12
|
11
|
14
|
12
|
14
|
13
|
15
|
12
|
12
|
12.5
|
|
Seasonal Index
|
0.69
|
0.98
|
1.46
|
0.98
|
0.98
|
0.98
|
0.29
|
0.49
|
1.46
|
1.93
|
1.27
|
0.49
|
|
|
Deseasonalized History
|
14.49275
|
12.2449
|
9.589041
|
12.2449
|
11.225
|
14.29
|
12.5
|
28.571
|
8.904
|
7.77202
|
9.44882
|
22.449
|
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2018–2019
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
Jan
|
Feb
|
Avg
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Demand
|
12
|
12
|
16
|
12
|
11
|
18
|
14
|
14
|
19
|
15
|
12
|
12
|
13.9167
|
|
Seasonal Index
|
0.69
|
0.98
|
1.46
|
0.98
|
0.98
|
0.98
|
0.29
|
0.49
|
1.46
|
1.93
|
1.27
|
0.49
|
|
|
Deseasonalized History
|
17.3913
|
12.2449
|
10.9589
|
12.2449
|
11.225
|
18.37
|
13.917
|
28.571
|
13.01
|
7.77202
|
9.44882
|
24.4898
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• If the Seasonal Index <= 0.3 and the # of History Slices greater than the number of slices in a year but for any year, all of the slices are not being used then the Deseasonalized History is calculated as follows:
Deseasonalized History = Average of the Total Demand of the following year
◦ The # of History Slices is set to 22
◦ In 2017–2018, the slice in September uses average of Year 2018-2019 as Deseasonalized History because the # of History Slices is not using all slices of the Year 2017-2018.
◦ In 2018–2019, the slice in September uses its own year’s average as Deseasonalized History.
|
2017–2018
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
Jan
|
Feb
|
Avg
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Demand
|
10
|
12
|
14
|
12
|
11
|
14
|
12
|
14
|
13
|
15
|
12
|
12
|
12.5
|
|
Seasonal Index
|
0.69
|
0.98
|
1.46
|
0.98
|
0.98
|
0.98
|
0.29
|
0.49
|
1.46
|
1.93
|
1.27
|
0.49
|
|
|
Deseasonalized History
|
14.49275
|
12.2449
|
9.589041
|
12.2449
|
11.225
|
14.29
|
13.917
|
28.571
|
8.904
|
7.77202
|
9.44882
|
22.449
|
|
2018–2019
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
Jan
|
Feb
|
Avg
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Demand
|
12
|
12
|
16
|
12
|
11
|
18
|
14
|
14
|
19
|
15
|
12
|
12
|
13.9167
|
|
Seasonal Index
|
0.69
|
0.98
|
1.46
|
0.98
|
0.98
|
0.98
|
0.29
|
0.49
|
1.46
|
1.93
|
1.27
|
0.49
|
|
|
Deseasonalized History
|
17.3913
|
12.2449
|
10.9589
|
12.2449
|
11.225
|
18.37
|
13.917
|
28.571
|
13.01
|
7.77202
|
9.44882
|
24.4898
|
See also