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CHAPTER 3 - Management Science II Dr.T.T.Narendran MODULE 3...

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Management Science II Dr.T.T.Narendran Indian Institute of Technology Madras MODULE 3 Forecasting Forecast: an educated guess for the future based on objective analysis (to the extent possible) Despite inaccuracy same Forecast is better than no Forecast But analytical Forecast is better than intuitive Forecast Type of Forecast Demand (Common) Environmental (Social, Political, economic) Sales characteristics: RCTS Users Long range – Facilities Medium range – Production Planning Short range – Product Forecast Forecast Types Based On Source Subjective Opinion Index Averages Statistical Combination
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Management Science II Dr.T.T.Narendran Indian Institute of Technology Madras Market Survey Subjective Opinion Collective opinion of sales department Advantage People directly concerned Disadvantage Too much influence of immediate past Big Boss opinion Can’t blame anyone for goods Index Of Business Activity Trend of gross national income, per capita income index of construction etc., Not very accurate Averages Average of past sales Moving average Weighted average (for nearer past) Methods of least squares let Y=f(x) be the function.
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Management Science II Dr.T.T.Narendran Indian Institute of Technology Madras Sum of deviation & M.A.D i.e. Could mislead by canceling out . So take and minimize it set the error f = Then minimum error function is obtained by minimizing this E function. Combination Use other information to stratify methods e.g.: Impact of advertisement, New competition, Obsolescence's, General economy etc., Market Survey Draw demand Vs time Determine which technique to try Evaluate expected error Look for better techniques if necessary
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Management Science II Dr.T.T.Narendran Indian Institute of Technology Madras Forecaster Could Be Constant (Random Fluctuation only) Linear (Trend) Cyclic (combination)
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Management Science II Dr.T.T.Narendran Indian Institute of Technology Madras Forecasting (constant) Least Squares Fit Year X Y XY X2 1967 -5 2 -10 25 1968 -4 3 -12 16 1969 -3 6 -18 9 1970 -2 10 -20 4 1971 -1 8 -8 1 1972 0 7 0 0 1973 1 12 12 1 1974 2 14 28 4 1975 3 14 42 9 1976 4 18 72 16 1977 5 19 95 25 X=0 Y=113 XY=181 X2=110 Forecasting equation is Y=10.3 + 1.6X
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