Session18

Session18 - Operations Management Session 18: Trend and...

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Session 18 Operations Management 1 Operations Management Session 18:  Trend and Seasonality
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Session 18 Operations Management 2 Previous Lecture Forecast Forecast is not a single number Error measure MAD Moving average Exponential smoothing Tradeoff: stability and responsiveness Forecasting aggregate demand is easier than forecasting the  demand for a single product
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Session 18 Operations Management 3 Trend Date Trend data 0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 Trend data
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Session 18 Operations Management 4 Trend Data 0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 Trend data alpha = 0.2 alpha = 0.5
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Session 18 Operations Management 5 Trend Data Linear Regression Double exponential smoothing
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Session 18 Operations Management 6 Double Exponential Smoothing Separate level component and trend component Forecasting Equation  F t  =  L t  +  T t Level Equation L t  =  α  (Prior Value) + (1 –  ) (Past Forecast) t –1 L t  =  A t 1  + (1 –  ) ( L t 1  +  T t 1 ) Trend Equation T t  =   δ (Prior Trend) + (1 –  ) (Past Trend Estimator) t –1 T t  =   ( L t  –  L t 1 ) + (1 –  T t 1
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Session 18 Operations Management 7 Double Exponential Smoothing:   α  = 0.2 and  δ   = 0.3 Week Demand Forecast Level Trend 1 100 10 2 3 131.6
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Session 18 Operations Management 8 Double Exponential Smoothing:   α  = 0.2 and  δ   = 0.3 Week Demand Forecast Level Trend 1 115 110 100 10 2 121.3 111 10.3 3 131.6
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Session 18 Operations Management 9 Double Exponential Smoothing:   α  = 0.2 and  δ   = 0.3 Week Demand Forecast Level Trend 1 115 110 100 10 2 121.3 121.3 111 10.3 3 131.6 121.3 10.3
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Session 18 Operations Management 10 Varying Trend Example -1 0 1 2 3 4 5 6 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 Trend Series
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Session 18
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This note was uploaded on 05/08/2008 for the course BUAD 311 taught by Professor Vaitsos during the Spring '07 term at USC.

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Session18 - Operations Management Session 18: Trend and...

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