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Lecture operations management chapter 3: forecasting

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Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc All rights reserved  You should be able to: List the elements of a good forecast Outline the steps in the forecasting process Describe at least three qualitative forecasting techniques and the advantages and disadvantages of each Compare and contrast qualitative and quantitative approaches to forecasting Describe averaging techniques, trend and seasonal techniques, and regression analysis, and solve typical problems Explain three measures of forecast accuracy Compare two ways of evaluating and controlling forecasts Assess the major factors and trade-offs to consider when choosing a forecasting technique Student Slides 3-2 Forecast – a statement about the future value of a variable of interest  We make forecasts about such things as weather, demand, and resource availability  Forecasts are an important element in making informed decisions Student Slides 3-3 Actual ∑ MAD = ( Actual ∑ MSE = t − Forecast t MAD weights all errors evenly n t − Forecast t ) n −1 MAPE = Student Slides ∑ Actualt − Forecast t × 100 Actualt n MSE weights errors according to their squared values MAPE weights errors according to relative error 3-4 Forecasts that project patterns identified in recent time-series observations  Time-series - a time-ordered sequence of observations taken at regular time intervals Assume that future values of the time-series can be estimated from past values of the time-series Student Slides 3-5 These Techniques work best when a series tends to vary about an average  Averaging techniques smooth variations in the data  They can handle step changes or gradual changes in the level of a series  Techniques Student Slides Moving average Weighted moving average Exponential smoothing 3-6 Technique that averages a number of the most recent actual values in generating a forecast n At −i ∑ Ft = MA n = i =1 n where Ft = Forecast for time period t MA n = n period moving average At −1 = Actual value in period t − n = Number of periods in the moving average Student Slides 3-7 The most recent values in a time series are given more weight in computing a forecast  The choice of weights, w, is somewhat arbitrary and involves some trial and error Ft = wt ( At ) + wt −1 ( At −1 ) + + wt − n ( At − n ) where wt = weight for period t , wt −1 = weight for period t − 1, etc At = the actual value for period t , At −1 = the actual value for period t − 1, etc Student Slides 3-8 A weighted averaging method that is based on the previous forecast plus a percentage of the forecast error Ft = Ft −1 + α ( At −1 − Ft −1 ) where Ft = Forecast for period t Ft −1 = Forecast for the previous period α = Smoothing constant At −1 = Actual demand or sales from the previous period Student Slides 3-9 A simple data plot can reveal the existence and nature of a trend Linear trend equation Ft = a + bt where Ft = Forecast for period t a = Value of Ft at t = b = Slope of the line t = Specified number of time periods from t = Student Slides 3-10 Slope and intercept can be estimated from historical data b= n ∑ ty − ∑ t ∑ y n∑ t − (∑ t ) y − b∑ t ∑ a= n or y − bt where n = Number of periods y = Value of the time series Student Slides 3-11 The trend adjusted forecast consists of two components  Smoothed error  Trend factor TAFt +1 = St + Tt where St = Previous forecast plus smoothed error Tt = Current trend estimate Student Slides 3-12 Alpha and beta are smoothing constants Trend-adjusted exponential smoothing has the ability to respond to changes in trend TAFt +1 = St + Tt St = TAFt + α (At − TAFt ) Tt = Tt−1 + β (TAFt − TAFt−1 − Tt−1 ) Student Slides 3-13 Regression - a technique for fitting a line to a set of data points  Simple linear regression - the simplest form of regression that involves a linear relationship between two variables The object of simple linear regression is to obtain an equation of a straight line that minimizes the sum of squared vertical deviations from the line (i.e., the least squares criterion) Student Slides 3-14  The better forecasts are, the more able organizations will be to take advantage of future opportunities and reduce potential risks  A worthwhile strategy is to work to improve short-term forecasts  Accurate up-to-date information can have a significant effect on forecast accuracy:  Prices  Demand  Other important variables  Reduce the time horizon forecasts have to cover  Sharing forecasts or demand data through the supply chain can improve forecast quality Student Slides 3-15 ... the forecasting process Describe at least three qualitative forecasting techniques and the advantages and disadvantages of each Compare and contrast qualitative and quantitative approaches to forecasting. .. evaluating and controlling forecasts Assess the major factors and trade-offs to consider when choosing a forecasting technique Student Slides 3-2 Forecast – a statement about the future value of a variable

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