1. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 PERTEMUAN 14

2. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-2 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Forecasting

3. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-3 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Learning Objectives Students will be able to: 1.Understand and know when to use various families of forecasting models 2.Compare moving averages, exponential smoothing, and trend time-series models 3.Seasonally adjust data. 4.Understand Delphi and other qualitative decision-making approaches

4. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-4 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Learning Objectives - continued Students will be able to: 5.Identify independent and dependent variables and use them in a linear regression model. 6.Compute a variety of error measures.

5. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-5 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Chapter Outline 5.1 Introduction 5.2 Types of Forecasts 5.3 Scatter Diagrams 5.4 Measures of Forecast Accuracy 5.5 Time-Series Forecasting Models 5.6 Causal Forecasting Models 5.7 Monitoring and Controlling Forecasts 5.8 Using the Computer to Forecast

6. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-6 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Introduction Eight steps to forecasting: 1.Determine the use of the forecast 2.Select the items or quantities to be forecasted 3.Determine the time horizon of the forecast 4.Select the forecasting model or models 5.Gather the data needed to make the forecast 6.Validate the forecasting model 7.Make the forecast 8.Implement the results

7. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-7 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Forecasting Models - Fig. 5.1 Moving Average Exponential Smoothing Trend Projections Time Series Methods Forecasting Techniques Delphi Methods Jury of Executive Opinion Sales Force Composite Consumer Market Survey Qualitative Models Causal Methods Regression Analysis Multiple Regression Decomposition

8. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-8 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Scatter Diagram for Sales Fig. 5.2 Radios Televisions Compact Discs

9. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-9 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Decomposition of Time Series Time series can be decomposed into: Trend (T): gradual up or down movement over time Seasonality (S): pattern of fluctuations above or below trend line that occurs every year Cycles(C): patterns in data that occur every several years Random variations (R): “blips”in the data caused by chance and unusual situations

10. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-10 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Decomposition of Time Series Two Models Multiplicative model: demand = T * S * C * R Additive model: demand = T + S + C + R

11. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-11 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Product Demand Showing Components Trend Actual Data Cyclic Random

12. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-12 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Moving Averages n Moving average:  demand in previous n periods

13. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-13 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Calculation of Three- Month Moving Average MonthActual Shed Sales Three-Month Moving Average January10 February12 March13 April16 May19 June23 July26 (10+12+13)/3 = 11 2 / 3 (12+13+16)/3 = 13 2 / 3 (13+16+19)/3 = 16 (16+19+23)/3 = 19 1 / 3

14. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-14 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Table 5.2

15. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-15 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Weighted Moving Averages Weighted moving average =

16. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-16 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Calculating Weighted Moving Averages Weights Applied Period 3 Last month 2 Two months ago 1 Three months ago 3*Sales last month + 2*Sales two months ago + 1*Sales three months ago 6 Sum of weights

17. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-17 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Calculation of Three- Month Moving Average MonthActual Shed Sales Three-Month Moving Average 10 12 13 16 19 23 January February March April May June July26 [3*13+2*12+1*10]/6 = 12 1 / 6 [3*16+2*13+1*12]/6 =14 1 / 3 [3*19+2*16+1*13]/6 = 17 [3*23+2*19+1*16]/6 = 20 1 / 2

18. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-18 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Table 5.3

19. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-19 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Exponential Smoothing New forecast = previous forecast+  (previous actual - previous) or: where F t = F t-1 +  (A t-1 - F t-1 ) F t-1 = previous forecast  = smoothing constant F t = new forecast A t-1 = previous period actual

20. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-20 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Selecting the Smoothing Constant (  ) Select  to minimize: Mean Absolute Deviation = MAD Mean Square Error = MSE Mean Absolute Percent Error = MAPE Bias =  forecast errors

21. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-21 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Table 5.4

22. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-22 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Table 5.5

23. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-23 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Exponential Smoothing with Trend Adjustment Forecast including trend (FIT t+1 ) = new forecast (F t ) + trend correction(T t ) where T t = (1 -  )T t-1 +  (F t – F t-1 ) T i = smoothed trend for period 1 T i-1 = smoothed trend for the preceding period  = trend smoothing constant F t = simple exponential smoothed forecast for period t F t-1 = forecast for period t-1

24. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-24 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Exponential Smoothing with Trend Adjustment Simple exponential smoothing - first-order smoothing Trend adjusted smoothing - second-order smoothing Low  gives less weight to more recent trends, while high  gives higher weight to more recent trends

25. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-25 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Trend Projection General regression equation:

26. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-26 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Midwestern Manufacturing’s Demand Forecast points Trend Line Actual demand line

27. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-27 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Seasonal Variations MonthSales Demand Average Two-Year Demand Average Monthly Demand Seasonal Index Year 1 Year 2 80100 90940.957 758580940.851 809085940.904 90110100941.064 Jan Feb Mar Apr May115131123941.309 … …………… Total Average Demand 1,128 Seasonal Index: = Average 2 -year demand/Average monthly demand

28. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-28 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Using Regression Analysis to Forecast Y Triple A' Sales ($100,000's) X Local Payroll ($100,000,000) 2.01 3.03 2.54 2.02 1 3.57

29. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-29 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Using Regression Analysis to Forecast - continued Sales, YPayroll, XX2X2 XY 2.011 3.0399.0 2.541610.0 2.0244.0 2.011 3.5 74924.5  Y = 15  X 2 = 80  X = 18  XY = 51.5

30. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-30 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Using Regression Analysis to Forecast - continued Calculating the required parameters:

31. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-31 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Standard Error of the Estimate

32. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-32 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Standard Error of the Estimate - continued  points data of number equation regression the from computed variabledependent the of value point data each of value        n Y YY where n YY S c c X,Y          n XYbYaY S X,Y or:

33. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-33 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Triple A’s Calculations

34. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-34 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Triple A’s Calculations - continued        n XYbYaY S X,Y   .. ).)(.()..(. S X,Y    

35. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-35 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Correlation Coefficient

36. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-36 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Triple A’s Calculations - continued

37. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-37 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Correlation Coefficient - Four Values - Fig. 5.7

38. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-38 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Monitoring/Controlling Forecasts The Tracking Signal

39. To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-39 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 Monitoring/Controlling Forecasts The Tracking Signal