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Unformatted text preview: ion tree is shown in Figure 11-6. .4 Simulation. A project simulation uses a model that translates the uncertainties specified at a detailed level into their potential impact on objectives that are expressed at the level of the total project. Project simulations are typically performed using the Monte Carlo technique. For a cost risk analysis, a simulation may use the traditional project WBS as its model. For a schedule risk analysis, the Precedence Diagramming Method (PDM) schedule is used (see Section 18.104.22.168). A cost risk simulation result is shown in Figure 11-7. Project Project Management Management Body of Body of KnowledgeE L KnowledgeE PL MP AM SA S 11.4.3 Outputs from Quantitative Risk Analysis .1 Prioritized list of quantified risks. This list of risks includes those that pose the greatest threat or present the greatest opportunity to the project together with a measure of their impact. .2 Probabilistic analysis of the project. Forecasts of potential project schedule and cost results listing the possible completion dates or project duration and costs with their associated confidence levels. .3 Probability of achieving the cost and time objectives. The probability of achieving the project objectives under the current plan and with the current knowledge of the risks facing the project can be estimated using quantitative risk. .4 Trends in quantitative risk analysis results. As the analysis is repeated, a trend of results may become apparent. A Guide to the Project Management Body of Knowledge (PMBOK Guide) 2000 Edition 2000 Project Management Institute, Four Campus Boulevard, Newtown Square, PA 19073-3299 USA NAVIGATION LINKS ACROYMNS LIST ACRONYMS LIST 139 ACROYMNS LIST Chapter 11--Project Risk Management Figure 115 | 11.5.2 Beta Distribution
0.1 Triangular Distribution
0.1 0.0 0.0 Beta and triangular distributions are frequently used in quantitative risk analysis. The Beta shown here is one example of a family of such distributions. Other distributions that are common include the uniform, normal, and log-normal. Figure 115. Examples of Commonly Used Probability Distributions ment ment 11.5 RISK RESPONSE PLANNING
Risk response planning is the process of developing options and determining actions to enhance opportunities and reduce threats to the project's objectives. It includes the identification and assignment of individuals or parties to take responsibility for each agreed risk response. This process ensures that identified risks are properly addressed. The effectiveness of response planning will directly determine whether risk increases or decreases for the project. Risk response planning must be appropriate to the severity of the risk, cost effective in meeting the challenge, timely to be successful, realistic within the project context, agreed upon by all parties involved, and owned by a responsible person. Selecting the best risk response from several options is often required.
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