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Forecast Example2

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Given the following data, compute the
tracking signal and decide whether or not the
forecast should be reviewed.
Month
1
2
3
Actual
Sales
8
11
12
Forecast
Sales
10
10
10
1
Tracking signal is computed as the running sum of forecast
error (RSFE) divided by MAD. We compute RSFE by
summing up the forecast errors over time. Forecast errors
for January is the difference between its actual and
forecast sales. RSFE for January is equal to the
cumulative forecast errors.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast Forecast
Sales
Error
10
-2
10
10
10
Forecast Error =
RSFE
-2
RSFE = -2
Actual – Forecast =
8 -10 = -2
2
Forecast errors for February is the difference between its
actual and forecast sales. RSFE for February is equal to
the cumulative forecast errors of January and February.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast Forecast
Sales
Error
10
-2
10
1
10
10
Forecast Error =
Actual – Forecast =
RSFE
-2
-1
RSFE = -2 + 1
= -1
11 -10 = 1
3
Forecast errors for March is the difference between its
actual and forecast sales. RSFE for March is equal to the
cumulative forecast errors of January, February and
March.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast Forecast
Sales
Error
10
-2
10
1
10
2
10
Forecast Error =
Actual – Forecast =
RSFE
-2
-1
1
RSFE = -1 + 2
= 1
12 -10 = 2
4
Forecast errors for April is the difference between its actual
and forecast sales. RSFE for April is equal to the
cumulative forecast errors of January, February, March
and April.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast Forecast
Sales
Error
10
-2
10
1
10
2
10
4
RSFE
-2
-1
1
5
Forecast Error =
Actual – Forecast =
14 -10 = 4
RSFE = 1 + 4
= 5
5
MAD for January is computed by averaging the absolute
errors over time. Tracking signal for January is computed
by dividing its RSFE by MAD.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast
Sales
10
10
10
10
Absolute Error =
Absolute (Actual – Forecast) =
RSFE
-2
-1
1
5
MAD = 2
Absolute
Error
2
MAD
2
Tracking
Signal
-1
TS = RSFE/MAD
= -2/2 = -1
Absolute(8 -10) = 2
6
MAD for February is computed by averaging the absolute
errors of January and February. Tracking signal for
February is computed by dividing its RSFE by MAD.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast
Sales
10
10
10
10
Absolute Error =
Absolute (Actual – Forecast) =
RSFE
-2
-1
1
5
Absolute
Error
2
1
MAD = (2+1)/2
= 1.5
MAD
2
1.5
Tracking
Signal
-1
-0.67
TS = RSFE/MAD
= -1/1.5 = -0.67
Absolute(11 -10) = 1
7
MAD for March is computed by averaging the absolute
errors of January, February and March. Tracking signal for
March is computed by dividing its RSFE by MAD.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast
Sales
10
10
10
10
Absolute Error =
Absolute (Actual – Forecast) =
RSFE
-2
-1
1
5
Absolute
Error
2
1
2
MAD = (2+1+2)/3
= 1.67
MAD
2
1.5
1.67
Tracking
Signal
-1
-0.67
0.6
TS = RSFE/MAD
= 1/1.67 = 0.6
Absolute(12 -10) = 2
8
MAD for April is computed by averaging the absolute
errors of January, February, March and April. Tracking
signal for April is computed by dividing its RSFE by MAD.
Month
1
2
3
4
Actual
Sales
8
11
12
14
Forecast
Sales
10
10
10
10
RSFE
-2
-1
1
5
Absolute
Error
2
1
2
4
MAD
2
1.5
1.67
2.25
Tracking
Signal
-1
-0.67
0.6
2.22
Absolute Error =
TS = RSFE/MAD
Absolute (Actual – Forecast) =
Absolute(14 -10) = 4
MAD = (2+1+2+4)/4
= 5/2.25 = 2.22
= 2.25
9
Since the tracking signals for months January to April are
within +/- 4, the forecast needs not be reviewed.
Month
1
2
3
4
Tracking
Signal
-1
-0.67
0.6
2.22
10
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