BUS605: Strategic Project Management

Quantitative Risk Analysis is completed on the prioritized risks from Qualitative Analysis studying the effect of risk event deriving a numerical value. Quantitative Risk Analysis is performed to access the probability of achieving specific project objectives, to quantify the affect of the risk on the overall project objective, and to prioritize the risk based on significance to overall project risk.

The inputs for Quantitative Risk Analysis are:

• Organizational process assets - Organizational process assets utilized are any information from the project archives on projects of a similar nature, any study by risk specialists on a similar project, and any available proprietary risk database.
• Project Scope Statement - The Project Scope Statement provides information on whether the project is a new and exciting endeavor with a significant change in process. These types of projects have high levels of risk.
• Risk Management Plan - The Risk Management Plan contains the budget, the definitions of probability and impact, the probability and impact matrix, risk categories, and risk timing and schedule. All of these components are needed to perform Quantitative risk analysis.
• Risk Register - The Risk Register lists the threats and opportunities the project team has identified and has the categories and priority from qualitative risk analysis.
• Project Management Plan – The project management plan has the schedule management plan and cost management plan. The schedule management plan details how to control the project schedule and the cost management plan describes how to budget and control project costs.

In order to accurately perform Quantitative Risk Analysis, one needs to keep in mind the purpose or outcome is to have a well thought through and realistic number is the probabilistic analysis. The first methodology is to endeavor on a data gathering mission, gathering SMART data, validating the data, and illustrating in a graphical format. The other methodology is to perform a statistical analysis of the data. Given the two methodologies, the tools and techniques used to perform Quantitative Risk Analysis are:

• Interviewing – Interviewing is employed to assess the probabilities of achieving specific project objectives based on input from relevant stakeholders and subject matter experts. In the interview it is a good mix to obtain the optimistic, pessimistic, and most likely scenario for a given objective. The end result is to have a bought into, agreed to, realistic and formal gage of probability. There are three methods commonly employed:
  • Direct – Direct interviewing is when a subject matter expert is accountable for providing the optimistic, pessimistic, and most likely values.
  • Diagrammatic – Diagrammatic method utilizes diagrams for subject matter experts to determine subjective possibilities.
  • Delphi – The Delphi technique lets a group of experts anonymously contribute their assessment.
• Probability Distribution – A probability distribution describes how probabilities are distributed upon events. It is used to graphically illustrate risk probability representing the probability density function. The vertical axis indicates the probability of the risk event, and the horizontal axis depicts the impact of the risk event.
• Sensitivity Analysis – Sensitivity analysis measures the impact of one risk with all other variables at a level plane. The risk currently being analyzed is given variable values based upon the possible outcomes. This is a great method to ascertain the impact of a single risk, however the method does not yield a combined effect for risk analysis.
• Expected Monetary Value – Expected monetary value analysis calculates the average outcome when the future is not set in stone. In order to calculate EMV multiply the monetary value of a possible outcome by the probability it will occur. EMV analysis is commonly used in conjunction with decision tree analysis.
• Decision Tree Analysis – Decision tree analysis is a detailed review of the information available to evaluate different outcomes. Decision trees enable the considertion of probability and impact for every branch of the decision under analysis. Solutions are based on alternatives which provide the greatest expected value when every implication, costs, rewards, and subsequent decisions are considered.
  
• Modeling and Simulation – A model is mock-up of a system or problem. A simulation imitates functionality. A common model and simulation is the Monte Carlo Analysis. It illustrates how processes can occur under different conditions, without risk to the production systems and data. The steps to perform a Monte Carlo Analysis are:
  1. Establish a Range of Values for Each Task
  2. Determine the Probability Distribution for Each Task
  3. Choose Random Values for the Simulation
  4. Perform the Simulation
  5. Analyze the Data

The sole output of the Quantitative Risk Analysis process is an updated Risk Register. Components of the output of Quantitative Risk Analysis (updates to the Risk Register) are:

• Probabilistic analysis of the project - The probabilistic analysis of the project is comprised of possible schedule and cost outcomes including estimated completion dates and costs, along with associated confidence levels. This information provides a foundation for prioritizing risks and managing trends in risks and risk results.
• Probability of achieving cost and time objectives - The probability of achieving the cost and time project objectives is pretty self explanatory. Mainly this is a way to quantify the contingency reserves to an acceptable level for the organization. Contingency reserves are the funds, budget, or time needed above the estimate to reduce the risk of overruns of project objectives to a level acceptable to the organization. A probabilistic analysis of your project can be used to calculate and set aside sufficient contingency reserves to cover potential shortfalls.
• Prioritized list of quantified risks – The prioritized list of quantified risks clearly identifies which risks pose the greatest threat or opportunity to the project by requiring a large risk contingency or by influencing the critical path.
• Trends in quantitative risk analysis - When project managers examine quantitative analysis results over time, they often spot trends. Observing and responding to trends can help you identify and eliminate root causes of risk, reduce risk probability, or control risk impact. Managing trends contributes to making you a successful risk manager.

The output of Quantitative Risk Management provides information for handling a project's most threatening risks and promising opportunities. A probabilistic analysis assists you with estimating contingency reserves to ensure stakeholder comfort.

Quantitative Risk Management helps to assess the probability of meeting time and cost objectives. Prioritizing high-threat risks allows one to respond proactively before the iceberg has hit. Monitoring trends enables you to adjust risk management activities over time. Taken together, all of these outputs help you to be a successful risk manager.

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Source: Elyse, http://www.anticlue.net/archives/000819.htm
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