1. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 2 Chapter 13 Forecasting u Demand Management u Qualitative Forecasting Methods u Simple & Weighted Moving Average Forecasts u Exponential Smoothing u Simple Linear Regression

2. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 5 Types of Forecasts u Qualitative (Judgmental) u Quantitative – Time Series Analysis – Causal Relationships – Simulation

3. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 11 Delphi Method 4. Summarize again, refining forecasts and conditions, and again develop new questions. 5. Repeat Step 4 if necessary. Distribute the final results to all participants.

4. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 6 Components of Demand 1234 x x x x x x xx x x x xxx x x x x x xx x x x xxx x x x x x x x x x x x x x x x x x x x x Year Sales What’s going on here?

5. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 7 A Trend is Worth Noting u Start by identifying the trend u What is the trend in the sales of personal computers? u Are there any seasonal effects, cyclical factors or other predicted events that might affect the sales of personal computers?

6. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 10 Delphi Method l. Choose the experts to participate. There should be a variety of knowledgeable people in different areas. 2. Through a questionnaire (or E-mail), obtain forecasts (and any premises or qualifications for the forecasts) from all participants. 3. Summarize the results and redistribute them to the participants along with appropriate new questions.

7. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 12 Judgmental Forecasting Applications Small and Large Firms Technique Low Sales < $100M High Sales > $500M Manager’s opinion40.7%39.6% Jury of executive opinion40.7%41.6% Sales force composite29.6%35.4% Number of Firms2748 Source: Nada Sanders and Karl Mandrodt (1994) “Practitioners Continue to Rely on Judgmental Forecasting Methods Instead of Quantitative Methods,” Interfaces, vol. 24, no. 2, pp. 92-100.

8. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 13 Quantitative Forecasting Applications Small and Large Firms Technique Low Sales < $100M High Sales > $500M Moving average29.6%29.2% Straight line projection14.8%14.6% Naive18.5%14.6% Exponential smoothing14.8%20.8% Regression22.2%27.1% Simulation3.7%10.4% Classical decomposition3.7%8.3% Box-Jenkins3.7%6.3% Number of Firms2748 Source: Nada Sanders and Karl Mandrodt (1994) “Practitioners Continue to Rely on Judgmental Forecasting Methods Instead of Quantitative Methods,” Interfaces, vol. 24, no. 2, pp. 92-100.

9. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 14 Time Series Analysis Pick a model based on: 1. Time horizon to forecast 2. Data availability 3. Accuracy required 4. Size of forecasting budget 5. Availability of qualified personnel

10. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 30 Forecast Errors u Study the formula for a moment u Now, what does MAD tell you?

11. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 31 Example--MAD MonthSalesForecast 1220n/a 2250255 3210205 4300320 5325315 Determine the MAD for the four forecast periods

12. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 32 Solution MonthSalesForecastAbs Error 1220n/a 22502555 32102055 430032020 532531510 40

13. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 15 Simple Moving Average u Let’s develop 3-week and 6-week moving average forecasts for demand. u Assume you only have 3 weeks and 6 weeks of actual demand data for the respective forecasts

14. 16 © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill

15. 17 © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill

16. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 18 In-Class Exercise u Develop 3-week and 5-week moving average forecasts for demand. u Assume you only have 3 weeks and 5 weeks of actual demand data for the respective forecasts

17. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 19 In-Class Exercise (Solution)

18. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 20 Weighted Moving Average Determine the 3-period weighted moving average forecast for period 4. Weights: t-1.5 t-2.3 t-3.2

19. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 21 Solution

20. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 22 In-Class Exercise Determine the 3-period weighted moving average forecast for period 5. Weights: t-1.7 t-2.2 t-3.1

21. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 23 Solution

22. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 24 Exponential Smoothing u Premise--The most recent observations might have the highest predictive value. u Therefore, we should give more weight to the more recent time periods when forecasting F t = F t-1 +  (A t-1 - F t-1 )

23. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 25 Exponential Smoothing Example  Determine exponential smoothing forecasts for periods 2-10 using  =.10 and  =.60. u Let F 1 =D 1

24. 26 © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill

25. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 27 Effect of  on Forecast

26. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 28 In-Class Exercise Determine exponential smoothing forecasts for periods 2-5 using  =.50 Let F 1 =D 1

27. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 29 In-Class Exercise (Solution)

28. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 35 Simple Linear Regression Model u b is similar to the slope. However, since it is calculated with the variability of the data in mind, its formulation is not as straight- forward as our usual notion of slope Y t = a + bx 0 1 2 3 4 5 x (weeks) Y

29. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 36 Calculating a and b

30. © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 37 Regression Equation Example Develop a regression equation to predict sales based on these five points.

31. 38 © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill

32. y = 143.5 + 6.3t 135 140 145 150 155 160 165 170 175 180 12345 Period Sales Forecast 39 © The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill