What are tools & techniques of perform quantitative risk analysis process?

1. Collecting data.

2. Brain Storming

3. Distribution of Risk

4. Risk Evaluation

5.Study Monetary impact.

6. Remodelling

7.  Expert Advise.

8.Docmentation Control

9. Risk Analysis of the project

10. Prioirtising

11. Time impact. Etc

there are many tools for quantitative risk analysis like: failure and event tree, loyer of protection analysis (LOPA), analyse des modes de défaillance leurs effetset leurs criticité(AMDEC), les reseaux de petri......

Quantitative Risk Analysis and Modeling Techniques:

·    Sensitivity analysis. Sensitivity analysis helps to determine which risks have the most potential impact on the project. It examines the extent to which the uncertainty of each project element affects the objective being examined when all other uncertain elements are held at their baseline values. One typical display of sensitivity analysis is the tornado diagram, which is useful for comparing relative importance of variables that have a high degree of uncertainty to those that are more stable.

·    Expected monetary value analysis. Expected monetary value (EMV) analysis is a statistical concept that calculates the average outcome when the future includes scenarios that may or may not happen (i.e., analysis under uncertainty). The EMV of opportunities will generally be expressed as positive values, while those of risks will be negative. EMV is calculated by multiplying the value of each possible outcome by its probability of occurrence, and adding them together. A common use of this type of analysis is in decision tree analysis. Modeling and simulation are recommended for use in cost and schedule risk analysis, because they are more powerful and less subject to misuse than EMV analysis.

·    Decision tree analysis. Decision tree analysis is usually structured using a decision tree diagram that describes a situation under consideration, and the implications of each of the available choices and possible scenarios. It incorporates the cost of each available choice, the probabilities of each possible scenario, and the rewards of each alternative logical path. Solving the decision tree provides the EMV (or other measure of interest to the organization) for each alternative, when all the rewards and subsequent decisions are quantified.

Modeling and simulation:  

A project simulation uses a model that translates the uncertainties specified at a detailed level of the project into their potential impact on project objectives. Simulations are typically performed using the Monte Carlo technique. In a simulation, the project model is computed many times (iterated), with the input values randomized from a probability distribution function (e.g., cost of project elements or duration of schedule activities) chosen for each iteration from the probability distributions of each variable. A probability distribution (e.g., total cost or completion date) is calculated.

For a cost risk analysis, a simulation can use the traditional project WBS or a cost breakdown structure as its model. For a schedule risk analysis, the precedence diagramming method (PDM) schedule is used.