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Perform Quantitative Risk AnalysisIntroduction Quantitative Risk Analysis refers to the thorough and complete numeric analysis of the overalleffect of the total quantifiable amount of risks involved in the project objectives.Purpose and Objectives Numeric estimation of overall effect of risk on project objectives based on current plans andinformation. Results evaluate the likelihood of success and estimate contingency reserves for time and costthat are appropriate to both risks and project stakeholders. Monte Carlo, a quantitative technique, provides realistic estimation of project cost. It is inappropriate if the qualitative risk analysis provides enough information especially in thecase of smaller projects. The Plan Risk Management process should ensure the application of quantitative risk analysis inprojects. Calculating estimates of overall project risk is the focus of the Perform Quantitative Risk Analysisprocess. An overall risk analysis, such as one that uses quantitative technique, estimates the implicationof all quantified risks on project objectives. The implementation of overall risk analysis using quantitative methods requires:oooo Complete and accurate representation of the project objectives built up fromindividual project elements. e.g., Project schedule or cost estimate.Identifying risks on individual project elements such as schedule activities or lineitem costs at a level of detail that lends itself to a specific assessment of individualrisks.Including generic risks that have a broader effect than individual project elements.Applying a quantitative method (such as Monte Carlo simulation or decision treeanalysis) that incorporates multiple risks simultaneously in determining overallimpact on the overall project objectives.Results of the quantitative risk analysis compared to the project plan gives the overallestimate of the project risk and answers the following questions:ooooWhat is the probability of meeting the project’s objectives?How much contingency reserve is needed to provide the organization with the levelcertainty it requires based upon its risk tolerance?What are those parts of project which contribute most risk when all risks areconsidered simultaneously?Which individual risk contributes the most to overall project risk? 2012 RMstudy.comPage 1 of 12

Perform Quantitative Risk Analysis Estimation of overall project risk using quantitative methods helps to distinguish projectswhere quantified risks threaten objectives beyond the tolerance of the stakeholders.Critical Success Factors for the Perform Quantitative Risk Analysis ProcessThe critical success factors for the Perform Quantitative Risk Analysis process are:ooooooPrior Risk Identification and Quantitative Risk AnalysisAppropriate Project ModelCommitment to Collecting High-Quality Risk DataUnbiased DataOverall Project Risk Derived from Individual RisksInterrelationships between the Risks in Quantitative Risk Analysis1. Prior Risk Identification and Quantitative Risk Analysis Perform Quantitative Risk Analysis Process happens after the Identify Risks and PerformQualitative Risk Analysis Processes. Reference to a prioritized list of identified risks ensures that Perform Quantitative Risk AnalysisProcess will consider all the significant risks while analyzing.2. Appropriate Project Model Frequently used project models include the project schedule, line-item cost estimates, decisiontree and other total-project models. Sensitive to the completeness and correctness of the model of the project that is used.3. Unbiased DataSuccessful gathering of data about risks should be done by interviews, workshops, and expertjudgment.4. Overall Project Risk Derived from Individual RisksThe Perform Quantitative Risk Analysis process is based on a methodology that correctly derives theoverall project risk from the individual risks. E.g., Monte Carlo simulation for risk analysis of cost andschedule, decision tree for making decisions when the future is uncertain.5. Interrelationships between the Risks in Quantitative Risk Analysis Common root cause risks likely to occur together are addressed by correlating the risks that arerelated. Using a risk register to list risks or root cause risks and attaching it to several project elements. 2012 RMstudy.comPage 2 of 12

Perform Quantitative Risk AnalysisTools and Techniques for the Perform Quantitative Risk Analysis ProcessThe characteristics of tools and techniques used for quantitative risk analysis are as follows:1. Comprehensive Risk Representation Risk models permit representation of any, if not all, of the risks, opportunities, and threats thathave impact on an objective simultaneously.2. Risk Impact Calculation Facilitates the correct calculation of the effect of many risks and are described at the level oftotal project.3. Quantitative Method Appropriate to Analyzing Uncertainty The methods should be able to handle the way uncertainty is represented, be it the probabilityof occurrence or probability of distributions for a range of outcomes. E.g. Monte Carlosimulation permitting the combination of probability distributions of line-item costs or scheduleactivity durations.4. Data Gathering ToolsThey include:ooAssessment of historical data and workshopsInterviews or questionnaires5. Effective Presentation of Quantitative Analysis Results Results from quantitative tools are not available in standard project management methods suchas project scheduling or cost estimating. E.g. Probability distribution of project completion datesor cost estimation. The results include:o Probability of achieving a project objective such as finishing on time or within budget.o Amount of contingency reserve needed to provide a required level of confidence.o Identity or location within the project model of the important risks. 2012 RMstudy.comPage 3 of 12

Perform Quantitative Risk AnalysisThe elements of the quantitative risk analysis are illustrated in Figure 7.1.Figure 7.1 Structure of Quantitative Risk Analysis6. Iterative Quantitative Risk Analysis Periodical analysis of individual risks of project enhances the success of quantitative risk analysis. The frequency of analysis is planned in the Plan Risk Management process, and events within theproject also influence it.7. Information for Response PlanningOverall project contingency reserve in time and cost should be reflecting in the project schedule andbudget.Quantitative Risk Analysis provides information to modify the project.Documenting the Results of Quantitative Risk Analysis Process The contingency reserves calculated are incorporated into the cost estimates and the scheduleto establish a prudent target and a realistic project. If the contingency reserves required exceeds the time or resources, changes in the project scopeand plan may result. The results of the quantitative risk analysis are recorded and passed on to the personnel/ groupfor any further action required to make full use of the results. 2012 RMstudy.comPage 4 of 12

Perform Quantitative Risk AnalysisTECHNIQUESThe Perform Quantitative Risk Analysis seeks to determine the overall risks to project objectiveswhen all risks potentially operate simultaneously on the project. It provides answers to several questions regarding the project. They are as follows:oooooooHow likely is the project to complete on the scheduled date or earlier?How likely is the project actual cost to be the budgeted cost and less?How reliable will the product be that the project produces?What is the best decision to make in the face of uncertain results?How much contingency in time and cost is needed to provide the organization with itsdesired degree of confidence in the results?How should the design of the product or system be changed most economically to increaseits reliability?What are the individual risks that seem to be the most important in determining the overallproject risk?1. Decision Tree Analysis: Causes the organization to structure the costs and benefits of decisions when the results aredetermined in part by uncertainty and risk. Solution of the decision tree helps select the decision that provides the highest ExpectedMonetary Value or expected utility to the organization. Critical success factors:oooo Careful structuring of the decision tree; all alternative decisions that are materially differentshould be considered; decision trees should be specified completelyAccess to high-quality data about probability, cost, and reward for the decisions and eventsspecified using historical information or judgment of experts.Use of a utility function that has been validated with the organization’s decision makers.Availability and understanding of the specialized software needed to structure and solve thedecision tree.Weaknesses:ooooooSometimes difficult to create the decision structure.Probabilities of occurrences can be difficult to quantify in the absence of historical data.The best decision may change with relatively plausible changes on the input data, meaningthat the answer may not be stable.The organization may not make decisions based on a linear Expected Monetary Value basis,but rather on a non-linear utility function; these functions are difficult to specify.Analysis of complicated situations requires specialized (through available) software.There may be some resistance to using technical approaches to decision making. 2012 RMstudy.comPage 5 of 12

Perform Quantitative Risk Analysis Specialized and widely available software used specifies the structure of the decision withdecision nodes, chance nodes, costs, benefits, and probabilities User can evaluate the different decisions using functions based on Expected Monetary Value ornon-linear utility functions of various shapes.An example is shown below here:Figure 7.2: Example of Decision Tree for Choosing between an Experimental Technology vs. Commercial Off theSheet (COTS) Technology.Source: Precision Tree from Palisade Corporation The negative numbers represent outflows or investments (e.g. COTS)The percentage represents probabilities of the event occurring (e.g. MajorProblems)The positive numbers represent rewards or values (e.g., after “Fix the problem”)“True” indicates the decision option taken from the square decision node, whereas“false” indicates the decision option not taken.2. Expected Monetary Value (EMV): Allows the user to calculate the weighted average (expected) value of an event that includesuncertain outcomes. It is well-suited to Decision Tree Analysis. Incorporates both the probability and impact of the uncertain events. Simple calculation that does not require special software. Critical success factors include: 2012 RMstudy.comPage 6 of 12

Perform Quantitative Risk Analysisooo Identification of all possible events that need to be included in the EMV calculation.Access to historical data or expert opinions on the values of probability and impact that areneeded for the calculation of EMV.Understanding of the difference between EMV and the output of simulation tools such asMonte Carlo analysis.Weaknesses are:oooAssessment of probability of risky events’ occurring and of their impact can be difficult tomake.EMV provides only the expected value of uncertain events; risk decisions often require moreinformation than EMV can provide.Sometimes used in situations where Monte Carlo simulation would be more appropriate andprovide additional information about risk.The EMV calculation for an event by weighting the individual possible outcomes by theirprobabilities of occurring is shown in Figure 7.3 below.Example of an Expected Monetary Value (EMV) Calculation for a Business Strategy that Depends onUncertain Market DemandUncertain OutcomeReward ( 000)ProbabilityContribution to EMVHigh Market Demand80030%240.0Moderate Market Demand45045%202.5Low Market Demand25025%62.5Total EMV505.03. Fault Tree Analysis (FMEA): A Fault Tree Analysis is the analysis of a structured diagram which identifies elementsthat can cause system failure.This technique is based on deductive logic and can be adapted to risk identification toanalyze how risk impacts arise. The effective application of this technique requires adetailed description of the area being discussed.The undesired outcome is first identified and then all possible conditions/failures whichlead to that event are identified. This reveals potentially dangerous elements at eachphase of the project.Disadvantage:o Opportunities may be missed in this step as emphasis is laid on threats. Thetools required in this technique are generally available only to experts. 2012 RMstudy.comPage 7 of 12

Perform Quantitative Risk AnalysisFigure 7.4 Fault Tree Analysis of the Possible Causes of a Crash at the Main Road Junction4. Monte Carlo Simulation: Used primarily for project schedule and cost risk analysis in strategic decisions. Allows all specified risks to vary simultaneously. Calculates quantitative estimates of overall project risk; reflects the reality that several risks mayoccur together on the project. Provides answers to questions such as:oooHow likely the base plan to be successful?How much contingency in time and cost do we need to achieve our desired level ofconfidence?Which activities are important in determining the overall project risk? 2012 RMstudy.comPage 8 of 12

Perform Quantitative Risk Analysis Critical success factors include:oooo Creation of a good project model and typical models include the cost estimate and theschedule.Use summary-level models such as project schedules and cost estimates.Access to high-quality data on risks including the risks impact on project elements, uncertainactivity durations and uncertain cost elements; the credibility depends on the quality of thedata collectedUse of correct simulation tools.Weaknesses include:oooooSchedules are not simple and often cannot be used in simulation without significant debugging by an expert scheduler.The quality of the input data depends heavily on the expert judgment and the effort andexpertise of the risk analyst.Simulation is sometimes resisted by management as being unnecessary or too sophisticatedcompared to traditional project management tools.Requires specialized software which must be acquired and learned, causing a barrier to itsuse.Produces unrealistic results unless input data include both threats and opportunities.Examples of the output of schedule and cost risk results are shown in Figures 7.5 and 7.6.Figure 7.5: Example Histogram from Monte Carlo Simulation of a Project ScheduleSource: Pertmaster v 8.0 Primavera Pertmaster 2012 RMstudy.comPage 9 of 12

Perform Quantitative Risk AnalysisFigure 7.6: Example Histogram from Monte Carlo Simulation of a Project Estimate.Source: Crystal Ball v. 7.3.8 from Oracle Hyperion (Decisioneering)5. Post-project reviews/ Lessons Learned/Historical Information: The review of risk databases of previous projects, such as those that arise from postproject reviews or lesso

The Plan Risk Management process should ensure the application of quantitative risk analysis in projects. Calculating estimates of overall project risk is the focus of the Perform Quantitative Risk Analysis process. An overall risk analysis, such as one that uses quantitative technique, estimates the implication