1. 1. COST RISK ASSESSMENT CHAPTER 23 Karthika Karuppan Chetti, Thuy Maria Le, Hanh Nguyen, Shangyin Gao
2. 2. RISK MODEL DEFINITION Cost Risk Assessment: applied the most for the longest period of time A single value occurs rarely
3. 3. RISK ANALYSIS SAMPLING TECHNIQUES Monte Carlo Technique Most commonly used technique A large number of random sampling.
4. 4. RISK ANALYSIS SAMPLING TECHNIQUES Generate random numbers from all areas Iterations will represent all areas of the distribution right away Latin Hypercube
5. 5. PROBABILITY DISTRIBUTIONS Most used distribution in project risk assessment Contain more information than uniform distribution Used when a range is known with some certainty but the relative likelihood is unclear for any particular value Used frequently in the situations where no greater likelihood of an overrun than an underrun
6. 6. RISK ASSESSMENT OUTPUTS Tool: Software program: @RISK Purpose: To estimate the probability of total cost. Outputs: Total cost, revenue and profit Sampling: Latin Hypercube and Monte Carlo Number of iterations: 100
7. 7. RISK ASSESSMENT OUTPUTS
8. 8. RISK ASSESSMENT OUTPUTS
9. 9. RISK ASSESSMENT OUTPUT STATISTICS Skew The degree of asymmetry of the distribution curve The higher value of skew, the more asymmetric the curve Left-skewed and right-skewed curve
10. 10. KURTOSIS How flat or peaked a distribution curve is The higher kurtosis, the more peaked the curve is, i.e. most of the values clustering near the expected value False optimism in developing distributions
11. 11. MONTE CARLO SIMULATION CHART Relating output values to probabilities Presented by value vs. by probability Cumulative Percentage Values ($ x millions) Probability 2.0 53% 2.5 86% 3.0 98% Cumulative Percentage Probability Value ($ x millions) 0% 1.0 10% 1.1 20% 1.3 Etc. Etc.
12. 12. PURPOSE OF COST RISK ASSESSMENT Determine the degree of variability in the estimate numbers and the risks in using that. Provide a strong numerical basis to make decision on cost risk allocations and bid price
13. 13. HOW TO APPLY RISK ASSESSMENT Small likelihood of an underrun means the large likelihood of an overrun If the probability of underrun is low, i.e. the probability of overrun is high, the final estimate should be increased to reduce risk Specific high cost risk items can be identified Acceptable level of risk depends on the project, the market conditions, and the corporate strategy.
14. 14. EXAMPLE Estimate = $210 millions Probability of underrun: 10% Probability of overrun: 90% Estimate = $220 millions Probability of underrun: 60% Probability of overrun: 40% Estimate = $230 millions Probability of underrun: 90% Probability of overrun: 10% Estimate = $250 millions Probability of underrun: 100% Probability of overrun: 0% 0% 20% 40% 60% 80% 100% 200 220 240 $ x millions Risk Assessment
15. 15. TRADEOFF IN COST RISK ALLOCATIONS High bid price lose the contract Low bid price cancellation of the contract Trying to keep the price as low as possible while still having a reasonable chance of performing the work for the estimated amount
16. 16. CONDUCTING A RISK ASSESSMENT Purpose Figures out risks Prevent problems from occurring Process Identify risks and benefits Best course of action Risk Assessment Planning process of a project Six steps - conducting a risk assessment
17. 17. SIX STEPS - CONDUCTING A RISK ASSESSMENT 1. Identify 2. Assess 3. Analyze 4. Make Decisions 5. Implement 6. Review
18. 18. IMPLEMENTATION EXAMPLE PERT Technique in the 1960s Cost risk analyses- project management tool Used in smaller projects Small cost, short duration, capital improvement projects Problem - Internal politics Risk analysis - outcome was dictated 95% confidence level Underrun 100% confidence level - Overrun
19. 19. CONCLUSION Existence of uncertainty Estimate as a single point value Better option offers a value analyze its likelihood of being exceeded Using Monte Carlo approach Sampling of possible outcomes with improved accuracy in larger samples Management Program of risk management
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