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Quick Recap

Quick Recap. Continuation of previous lecture….

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Quick Recap

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  1. Monitoring and Controlling Quick Recap

  2. Continuation of previous lecture…. • Lesson 7: Analyzing Risks and Planning Risk ResponsesTopic 7A: Examine a Risk Management Plan Topic 7B: Identify Project Risks and TriggersTopic 7C: Perform Qualitative Risk AnalysisTopic 7D: Perform Quantitative Risk AnalysisTopic 7E: Develop a Risk Response Plan

  3. Outputs • Sources of risk (i.e., categories) • Stakeholder actions • Estimates • Staffing plans • Common sources of risk: • Changes in requirements • Design errors, omissions, and misunderstandings • Poorly defined R & R • Insufficiently skilled staff

  4. Outputs • Potential Risk events • Specific discrete events that might effect the project • Generally include: • Probability • Alternative outcomes • Timing • Frequency (more than once?)

  5. Outputs • Risk Symptoms • Triggers, or trip wires, or indicators • Indirect manifestations of risk events • Poor morale • Lack of reported progress • Inputs to other processes • Improved estimating • More training

  6. Risk Quantification Risk quantification consists of evaluating the risks and risk interactions to assess the range of possible project outcomes.

  7. PHASE 2: RISK QUANTIFICATION GOALS OF QUANTIFICATION (OR ASSESSMENT) INCREASE THE UNDERSTANDING OF THE PROJECT IDENTIFY THE ALTERNATIVES AVAILABLE ENSURE THAT UNCERTAINTIES AND RISKS ARE ADEQUATELY CONSIDERED IN A STRUCTURED AND SYSTEMATIC WAY AND INCORPORATED INTO THE PLANNING AND DEVELOPMENT PROCESS ESTABLISH THE IMPLICATIONS OF THESE UNCERTAINTIES ON ALL OTHER ASPECTS OF THE PROJECT

  8. Risk Quantification - Inputs • Stakeholder risk tolerances • Sources of risk • Potential risk events • Cost estimates • Activity duration estimates

  9. Risk QuantificationTools and Techniques • Expected monetary value • Statistical sums • Simulation • Decision trees • Expert judgment

  10. RISK ANALYSIS TECHNIQUES • Brainstorming - spontaneous contribution of ideas from team • Delphi method - method to derive consensus using expert opinion • Monte carlo - iterative simulation using random numbers to • Incorporate probabilistic data and derive a • Probability distribution of the final result • Sensitivity analysis - evaluate effect of a change in a single • Variable on the entire project • Decision tree analysis - graphical "either / or" choices • Utility theory - takes attitude of decision maker into account • Decision theory - Technique to reach decision under uncertainty • And risk. Points to best possible course no matter • The forecast accuracy • Probability analysis - next page

  11. SIMPLE PROBABILITY SIMPLE PROBABILITY EQUATION: Pr (Event #1) x Pr (Event #2) = Pr (Both Events) P(t) = P(A) * P(B) OR 0.70 X 0.80 = 0.56 OR 56% NOTE: THIS APPLIES TO INDEPENDENT EVENTS ONLY

  12. PROBABILITY EXAMPLE DATA: Probability of Scope = 0.70 Probability of No Scope = 0.30 Probability of Approval = 0.80 Probability of No Approval = 0.20 EXAMPLE: Pr(Scope) x Pr(Approval) = 0.70 x 0.80 = 0.56 Pr(Scope) x Pr(No Approval) = 0.70 x 0.20 = 0.14 Pr(No Scope) x Pr(Approval) = 0.30 x 0.80 = 0.24 Pr(No Scope) x Pr(No Approval) = 0.30 x 0.20 = 0.06 Total= 1.00 PRACTICAL APPLICATION -- DECISION TREE ANALYSIS

  13. Expected Monetary Value (EMV) • Product of two values • Risk event probability • Risk event value • Valuation of the risk event is key • Must include tangible as well as intangible value • 1 week slippage with minor client impact • 6 week slippage with major client impact

  14. Expected Monitary Value Example Given the following: CostProbability Optimistic $100,000 0.20 Most likely $130,000 0.60 Pessimistic $180,000 0.20 Expected Value Calculation: Optimistic $100,000 x 0.20 = 20,000 Most likely $130,000 x 0.60 = 78,000 Pessimistic $180,000 x 0.20 = 36,000 Expected Monitary Value $134,000 (*EMV = Opt imistic + 4(most likely) + Pessimistic) 6 * formula if probability is not known

  15. EMV Example • If no probabilities are given, use EMV=(Opt + 4*ML + Pes)/6 • EMV= ($100 +4*$130+$180)*1000/6 = $133,333

  16. Descriptive Statistics • Mean • Mode • Median • Variance • Standard Deviation • Range

  17. Descriptive Statistics Example Test scores are 10, 20, 25, 40, 45, 45, 50, 55, 55, 60, 60, 60, 65, 65, 65, 70, 70, 70, 70, 70, 75, 80, 80, 85, 90, 90, 90, 95, 100 Mean: number obtained by dividing the sum of a set of quantities by the number of quantities in the set. (answer is 1855 / 29=64) Mode: value or item occurring most frequently in a series of observations. (answer is 70 -it occurs 5 times) Median: middle value in a distribution, above and below which lie an equal number of values (answer is 65) Variance: average of the squares of the variations from the mean of a frequency distribution. (answer is 486.4) Standard deviation: square root of the variance. (answer is 22) Range: measure of the dispersion equal to the difference or interval between the smallest and the largest of the set of quantities. (answer is 90 or 100-10)

  18. Approximations • Mean = (Opt + 4*ML + Pes)/6 • SD = (Max - Min)/6

  19. Exercise

  20. So What? • Normal Distribution • Mean is expected value • Mean = Mode = Median • Standard deviation is a measure of dispersion about the mean • 68.27% of cases occur between Mean + SD and Mean - SD • 95.45% of cases occur between Mean+2SD and Mean-2SD • 99.73% of cases occur between Mean+3sd and Mean-3SD

  21. Mean Blue = 68% Blue + Green = 95% Blue + Green + Red = 99.7% 34.1% 34.1% 1.1% 13.6% 13.6% 1.1% - SD - 3SD - 2SD + SD + 2SD + 3SD Normal Distribution

  22. Mode Median Mean Skewed Normal Distribution

  23. Mean = (a + 4m + b) / 6 Mean = (a + m + b) / 3 2 2 Variance = [(b - a) + (m - a) (m - b)] / 18 BETA vs. TRIANGULAR DISTRIBUTIONS BETA TRIANGULAR DISTRIBUTION DISTRIBUTION EXPECTED VALUE EXPECTED VALUE P P R R O O B B A A B B I I L L I I T T Y Y COST ESTIMATE COST ESTIMATE Variance = [(b - a) / 6]

  24. Simulation Simulation uses a representation or model of a system to analyze the behavior or performance of the system. • Monte Carlo analysis is best known • results used to quantify risk of various schedule choices

  25. Monte Carlo • Requires Optimistic, Most Likely, and Pessimistic estimates. • Uses random number generator to select which value to use • Calculates the database multiple times to develop a probability distribution of the data

  26. Decision Trees Aggressive schedule EMV = $110,000 Conservative schedule EMV = $7,000 Given the following decision tree: Outcome 250 k 100 k 45 k 20 k EMV 150 k 40 k 9 k 16 k 60% Choice event aggressive 40% Choice event 20% Choice event conservative 80%

  27. UTILITY THEORY • Definition • Endeavors to formalize management’s attitude toward risk of the decision maker. • Types • Risk Seeking • Risk Neutral • Risk Averse

  28. Expert Judgment Expert judgment can often be applied in lieu of or in addition to the mathematical techniques described above. Derived from: • team members • others in or outside of organization • published findings • industry averages / statistics

  29. QUALITY RISK • GOALS OF RISK MANAGEMENT • - Increase understanding of project • - Improve plans, delivery, and id greatest risks • - Where to focus attention • REMAINING MAJOR PROJECT RISK AREA ... • What if project fails to perform as expected during operational life / product life cycle? Conformance to quality requirement remembered long after cost and schedule performance. \ Quality management has most impact on long-term perceived & actual success of project

  30. SCHEDULE RISK CAN MANAGE “CRITICAL PATH” BUT NOT MANAGE DURATION REASON --> SCHEDULE RISK Highest risk path = path with most project completion risk Risk in all activity duration because future is uncertain LONGEST DURATION ACTIVITY ¹ RISKIEST Therefore, need to id & manage what could contribute to project delay -- could override management of critical path

  31. B FINISH E START A D SCHEDULE RISK (CONT'D) C MOST MEAN ACTIVITYLOWLIKELYHIGHEXPECTED A-B 8 9 10 9 B-C 4 5 6 5 C-E 0 0 0 0 B-E 1 6 7 4.7 A-D 4 9 14 9 D-E 1 2 7 3.3

  32. B FINISH E START A D SCHEDULE RISK (CONT'D) SUM OF SUM OF SUM OF PATHMOST LIKELYMEANSHIGHS A-B-C-E 14 14 16 A-B-E 15 13.7 17 A-D-E 11 12.3 21 MOST RISKY A-B-E A-B-C-E A-D-E

  33. Risk Quantification- Outputs Opportunities to pursue, threats to respond to Opportunities to ignore, threats to accept

  34. Risk Response Development Risk response development defines the enhancement steps for opportunities and responses to threats.

  35. Risk Response Development • Defines steps for • enhancing opportunities • responding to threats

  36. Types of Responses • Avoidance - eliminate • Mitigation • Reduce EMV by reducing probability • Reduce Impact - buy insurance • Acceptance • Active: develop plan to deal with risk if it occurs • Passive: Accept risk (e.g., lower profit)

  37. PLANNING ALTERNATIVES • Project Managers have Several Response Options • Avoidance • Absorption • Adjustment • Deflection • Contingent Planning • A Combination of the Above

  38. AVOIDANCE • Defined • Characterized by project manager statements such as: “This alternative is totally unacceptable to me • You would take the appropriate steps to avoid this situation.

  39. ABSORPTION • Risk is Recognized-But Not Acted Upon • Accept the Risk AS IS • It’s a Matter of Policy • Retained & Absorbed (by prudential allowances) • Unrecognized, Unmanaged, or Ignored (by default)

  40. ADJUSTMENT • Modification of the Project • Scope • Budget • Schedule • Quality Specification • Combination of the Above

  41. DEFLECTION • Involves transfer of risk by such means as: • Contracting Out to Another Party • Insurance or Bonding • By Recognizing it in the Contract

  42. CONTINGENT PLANNING Contingent planning is a means to address risks to the Project through a formal process and provide resources To meet the risk events. It is the establishment of management plans to be invoked In the event of specified risk events Examples: The provision and prudent management of a contingency allowance in the budget The preparation of schedule alternatives and Work-arounds Emergency responses to deal with major specific Areas of risk An assessment of liabilities in the event of a Complete project shut-down

  43. Types of Responses • Prevent risk from occurring • Reduce the probability that the event will occur • Eliminate means P=0 • Reduce the impact (think “containment”) • Buy insurance (monetary) • Alternative strategies (additional supplier to PDQ)

  44. CONTRACT STRATEGY • To Select the Right Form of Contract Requires: • Identification of Specific Risks • Determination of how they should be shared between the parties, and • The insertion of clear, legal language in the contract documents to put it into effect.

  45. CONTRACT TYPE vs. RISK SCOPE OF WORK INFORMATION VERY LITTLE PARTIAL COMPLETE UNCERTAINTY HIGH MODERATE LOW DEGREE OF RISK HIGH MEDIUM LOW 100% 0% AGENCY (BUYER) SUGGESTED RISK ALLOCATION SELLER (CONTRACTOR) 100% 0% CONTRACT TYPES CPIF CPFF FPPI FFP CPPF

  46. Project A Well defined scope and work content. High probability of achieving realistic cost estimate at 100% Project B Fairly well defined scope and work content. Fair probability of achieving 100% cost estimate Project c Poorly defined scope and content. Low probability of 100% cost estimate CONTRACT TYPE vs. RISK (CONT'D) P R O B A B I L I T Y 80% 90% 95% 100% 110% 120% 140% COST ESTIMATE VALUE Suggested types of +/- 15%: FFP contract for various spreads +/- 25%: CPFF +/- 50%: CPIF > 50%: CPPF

  47. FAST-TRACKING • Awarding contracts before all the information is complete to reduce the overall time for the project • Much higher risk category!! • Appropriate contingency allowances must be increased accordingly.

  48. Risk Response Development - Inputs Opportunities to pursue, threats to respond to Opportunities to ignore, threats to accept

  49. Risk Response DevelopmentTools and Techniques • Procurement • Buy outside skills • Contingency planning • what to do if the event occurs • containment • Alternative strategies • Prevention • Insurance

  50. Risk Response Development - Outputs • Risk management plan • Inputs to other processes • Contingency plans • Reserves • Contractual agreements

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