1. MIE 754 - Class #13 Manufacturing & Engineering Economics Term Project Term Project – Next week guest lecture Concerns and Questions Concerns and Questions Quick Review Quick Review Today’s Focus: Today’s Focus: Chap 5 Estimating for Economic Analyses (continued)

2. Concerns and Questions? b Mid-Term Exam - to be determined (approx 2-3 weeks), following Chap 17 b Supplemental reading for Chap 17 to be distributed shortly b Reminder - Chap 5 homework due next class

3. Quick Recap of Previous Class  What is a cost estimate?  What’s the purpose of a cost estimate?  Sources of errors in cost estimating  Sources of data  Quantitative estimating techniques

4. Quantitative Estimating Techniques 1. Time-series - when cost (revenue) elements are a function of time. Collect data; study underlying relationships. Regression - estimating causal relationships within time-series dataRegression - estimating causal relationships within time-series data Exponential Smoothing - estimating future extensions to historical data patternsExponential Smoothing - estimating future extensions to historical data patterns

5. Quantitative Estimating Techniques 2. Subjective - expert judgment is applied to the results of time-series techniques (how future might differ from the past) Delphi Technique - voice opinions anonymously and through an intermediaryDelphi Technique - voice opinions anonymously and through an intermediary Technology Forecasting - procedures for data collection and analysis to predict future technological developments and their impactsTechnology Forecasting - procedures for data collection and analysis to predict future technological developments and their impacts

6. Quantitative Estimating Techniques 3. Cost Engineering - identify and utilize various revenue/cost drivers to compute estimates

7. Exponential Smoothing  Assumes trends and patterns of the past will continue into the future  More weight on current data  No assumption of linearity with  ’= smoothing constant, S t =  ‘x t + (1 -  ‘)S t-1 (0  ’  1) Usually (0.01  ’  0.30)

8. (Forecast for period t+1, made in period t)=  ’(Actual data point in period t)  ’(Actual data point in period t) + (1-  ’)(Forecast for period t, + (1-  ’)(Forecast for period t, made in period t-1) made in period t-1)  ’ = 1 implies?  ’ = 0 implies?

9. Example Problem 5-8 b Actual sales of a firm were 500 units for year 1 and 600 for year 2. You forecsted it would be 550 units for year 2, and now you wish to forecast for year 3 and beyond. What would be your forecast for year 3 if your smoothing constant was 0.1, 0.5, and 0.97?What would be your forecast for year 3 if your smoothing constant was 0.1, 0.5, and 0.97? Suppose actual sales for years 3 - 7 are 700, 800, 700, 600, 600 respectively. What would have been the forecast for each year 4-7 using the 3 smoothing constants?Suppose actual sales for years 3 - 7 are 700, 800, 700, 600, 600 respectively. What would have been the forecast for each year 4-7 using the 3 smoothing constants? Desirability of low or high smoothing const?Desirability of low or high smoothing const?

10. Example Problem 5-8

11. Sources of Data  Accounting Records  Other Sources Within the Firm  Sources Outside the Firm  Research & Development

12. Quantitative Estimating Techniques 3. Cost Engineering - identify and utilize various revenue/cost drivers to compute estimates

21. Cost Indexes b A dimensionless number that indicates how costs and prices change with time b Used to estimate present or future costs based on past costs. b In-class notes and examples follow b Also refer to Virtual Classroom web site for examples

22. Refer to on web site for example calculations

23. In-class example

24. Sources and Limitations of Indexes b Sources Engineering News RecordEngineering News Record Producer Prices and Price IndexesProducer Prices and Price Indexes Consumer Price Index ReportConsumer Price Index Report b Limitations of Indexes They represent composite dataThey represent composite data They average dataThey average data Various base periods are used for different indexesVarious base periods are used for different indexes Accuracy is limited for periods greater than 10 yearsAccuracy is limited for periods greater than 10 years

29. Worked In-class