Forecast Error = Actual – Forecast = 8 -10 = -2
10
1 Given the following data, compute the tracking signal and decide whether or not the forecast should be reviewed. A ctual Forecast Month S ales S ales 1 8 10 2 11 10 3 12 10
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Given the following data, compute the tracking signal and decide whether or not the forecast should be reviewed. - PowerPoint PPT Presentation
Transcript of Forecast Error = Actual – Forecast = 8 -10 = -2
1
Given the following data, compute the tracking signal and decide whether or not the forecast should be reviewed.
Actual ForecastMonth Sales Sales
1 8 102 11 103 12 10
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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.
Actual Forecast ForecastMonth Sales Sales Error RSFE
1 8 10 -2 -22 11 103 12 104 14 10
Forecast Error =
Actual – Forecast =
8 -10 = -2
RSFE = -2
3
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.
Actual Forecast ForecastMonth Sales Sales Error RSFE
1 8 10 -2 -22 11 10 1 -13 12 104 14 10
Forecast Error =
Actual – Forecast =
11 -10 = 1
RSFE = -2 + 1
= -1
4
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.
Actual Forecast ForecastMonth Sales Sales Error RSFE
1 8 10 -2 -22 11 10 1 -13 12 10 2 14 14 10
Forecast Error =
Actual – Forecast =
12 -10 = 2
RSFE = -1 + 2
= 1
5
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.
Actual Forecast ForecastMonth Sales Sales Error RSFE
1 8 10 -2 -22 11 10 1 -13 12 10 2 14 14 10 4 5
Forecast Error =
Actual – Forecast =
14 -10 = 4
RSFE = 1 + 4
= 5
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MAD for January is computed by averaging the absolute errors over time. Tracking signal for January is computed by dividing its RSFE by MAD.
Actual Forecast Absolute TrackingMonth Sales Sales RSFE Error MAD Signal
1 8 10 -2 2 2 -12 11 10 -13 12 10 14 14 10 5
Absolute Error =
Absolute (Actual – Forecast) =
Absolute(8 -10) = 2
MAD = 2 TS = RSFE/MAD
= -2/2 = -1
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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.
Actual Forecast Absolute TrackingMonth Sales Sales RSFE Error MAD Signal
1 8 10 -2 2 2 -12 11 10 -1 1 1.5 -0.673 12 10 14 14 10 5
Absolute Error =
Absolute (Actual – Forecast) =
Absolute(11 -10) = 1
MAD = (2+1)/2
= 1.5
TS = RSFE/MAD
= -1/1.5 = -0.67
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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.
Actual Forecast Absolute TrackingMonth Sales Sales RSFE Error MAD Signal
1 8 10 -2 2 2 -12 11 10 -1 1 1.5 -0.673 12 10 1 2 1.67 0.64 14 10 5
Absolute Error =
Absolute (Actual – Forecast) =
Absolute(12 -10) = 2
MAD = (2+1+2)/3
= 1.67
TS = RSFE/MAD
= 1/1.67 = 0.6
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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.
Actual Forecast Absolute TrackingMonth Sales Sales RSFE Error MAD Signal
1 8 10 -2 2 2 -12 11 10 -1 1 1.5 -0.673 12 10 1 2 1.67 0.64 14 10 5 4 2.25 2.22
Absolute Error =
Absolute (Actual – Forecast) =
Absolute(14 -10) = 4MAD = (2+1+2+4)/4
= 2.25
TS = RSFE/MAD
= 5/2.25 = 2.22
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Since the tracking signals for months January to April are within +/- 4, the forecast needs not be reviewed.
TrackingMonth Signal
1 -12 -0.673 0.64 2.22
