Demand Planning - Demand Planning & Fulfillment 1/26/12...

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Demand Planning & Fulfillment 1/26/12 Forecasting Basic Time Series Approaches: Naïve Forecast F t+1 = D t Reacts quickly to changes Generally too volatile Assumes only the last data point is useful for predicting the future Cumulative Mean Average everything from the previous periods Good only if the system shows extreme stability Is very slow to react to trends or large changes in the demand level Assumes all past data is equally important in predicting the future Moving Average Pick a number of periods that you’re going to take an average from If N is small, the forecast will quickly respond to “real” changes but might respond to noise If N is large, the forecast is unlikely to respond to noise, but will be slow to respond to “real” changes in the system The optimal value of N is usually chosen by analyzing past data and minimizing the errors One way of measuring accuracy is the MSE = Mean Squared Error
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Demand Planning - Demand Planning & Fulfillment 1/26/12...

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