Class 11 - AGENDA HOMEWORK 4 ON T DRIVE DUE OCT 1 QUIZ 3 ON...

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AGENDA HOMEWORK 4 ON T: DRIVE, DUE OCT. 1 QUIZ 3 ON TUES. MORE FORECASTING
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þ Form of weighted moving average þ Weights decline exponentially þ Most recent data weighted most þ Requires smoothing constant ( α ) þ Ranges from 0 to 1 þ Subjectively chosen þ Involves little record keeping of past data Exponential Smoothing
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Exponential Smoothing Last period’s forecast + α (Last period’s actual demand – Last period’s forecast) Ft = Ft – 1 + α (At – 1 - Ft – 1) where Ft = new forecast Ft – 1 = previous forecast α = smoothing (or weighting) constant (0 ≤ α ≤ 1)
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Exponential Smoothing Example Predicted demand = 142 Ford Mustangs Actual demand = 153 Smoothing constant α = .20
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Exponential Smoothing Example Predicted demand = 142 Ford Mustangs Actual demand = 153 Smoothing constant α = .20 New forecast = 142 + .2(153 – 142)
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Exponential Smoothing Example Predicted demand = 142 Ford Mustangs Actual demand = 153 Smoothing constant α = .20 New forecast = 142 + .2(153 – 142) = 142 + 2.2 = 144.2 ≈ 144 cars
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Effect of Smoothing Constants Weight Assigned to Most 2nd Most 3rd Most 4th Most 5th Most Recent Recent Recent Recent Recent Smoothing Period Period Period Period Period Constant ( α 29 α(1 -α 29 α(1 -α 292 α(1 -α 293 α(1 -α 294 α = .1 .1 .09 .081 .073 .066 α = .5 .5 .25 .125 .063 .031
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Impact of Different  225 200 175 150 | | | | | | | | | 1 2 3 4 5 6 7 8 9 Quarter Demand α = .1 Actual demand α = .5
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Impact of Different  225 200 175 150 | | | | | | | | | 1 2 3 4 5 6 7 8 9 Quarter Demand α = .1 Actual demand α = .5 þ Chose high values of  when underlying average is likely to change þ Choose low values of  when underlying average is stable
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Choosing  The objective is to obtain the most accurate forecast no matter the technique We generally do this by selecting the model that gives us the lowest forecast error Forecast error = Actual demand - Forecast value = At - Ft
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