30 June 2022

# Risk Management processes : Perform Quantitative Risk Analysis

Purpose

• Quantitative risk analysis is the process of numerically analyzing the effect of identified risks on overall project objectives.
• In this process, you will use mathematics and statistics to predict the potential effect of risks on your project.
• “No one can argue with numbers”- if they were developed correctly.
• In quantitative analysis, you use many statistical and mathematical techniques.
• There are different risk simulation software that can aid you in quantitative analysis.
• It’s a risk analysis approach you can use to create an approach to make decisions in the presence of uncertainty.

Inputs

• Project management plan
• Risk management plan
• Purpose
• The risk management plan is a place for miscellaneous (different) information that you need to consult in each process.
• Here, you may want to review the definitions of probability and impact you set for your current project.
• RMP specifies wether quantitative risk analysis is required for the project
• Resources available for the analysis
• Expected frequency of analyses
• Schedule management plan
• On these plans, you will base your modeling and simulation
• Cost management plan
• Scope baseline
• Project scope statement
• Project type and an understanding of the work needed to complete the project
• Schedule baseline
• Cost baseline
• Outputs from other parts of project planning
• Project documents
• Assumptions log
• Assumptions to test
• Basis of estimates
• Duration estimates
• Milestones list
• Quantitative analysis determines the confidence level associated with achieving this targets
• Schedule forecasts
• Cost estimates
• Cost forecasts (Earned Value Management)
• ETC
• EAC
• BAC
• TCPI
• Resource requirements
• Risk register
• In the risk register, you will find the list of prioritized risks (as the quantitative assessment is relatively expensive, you need to be selective of which risks need further analysis).
• Prioritized risks from the Perform Qualitative Risk Analysis process.
• List of risks carried forward for additional analysis ,…,.
• Risk report
• Source of overall project risk
• Current overall project risk status
• EEF
• Purpose
• You might find specific studies for your type of project.
• Industry studies of similar projects
• Published material, including data bases or checklists
• OPA
• Purpose
• For the lessons learnt from past projects.
• Information from similar completed projects
• Historical records
• how were similar risks quantified in the past
• Scales for probability and impact
• if they are standardized for your department or company
• Data about the risks to be used during this step to measure their precision

Tools and Technics

• Expert judgment
• You should seek the advice of experts on them as needed.
• Expert judgment analysis of the environmental project factors
• Data gathering
• Interviews
• You interview experts to get different estimates on risk impact.
• Diagramming techniques
• Other information gathering techniques
• Interpersonal and team skills
• Facilitation
• Risk workshops
• Representation of uncertainty
• Purpose
• These are used to represent the probability of risk events in ranges of continuous numbers.
• These representations are used, in turn, in simulation.
• Probability distribution
• Triangulal
• Normal
• Lognormal
• Beta
• Uniform
• In a uniform distributionyou have only two values: maximum and minimum.
• Uniform distribution method is used for a portion of the project : early concept stage of design
• Discrete distributions
• Models
• Probabilistic branches
• Time and cost impact of the risk
• Relationship between certain risks
• Alternative paths
• Data analysis
• Documentation reviews
• Checklist analysis
• Provide a quick and simple listing of the project risks
• Assumptions analysis
• SWOT analysis
• SWOT Analysis examines the degree to which organizational strengths offset (contrebalance, compense) threats and opportunities that may serve to overcome weaknesses.
• Simulation
• Simulation
• Used to virtually run the project many times on a computer, utilizing the Monte Carlo technique.
• Risk Exposure
• Monte Carlo Simulation
• Monte Carlo sampling refers to the traditional technique for using random or pseudo-random numbers to sample from a probability distribution.
• Monte Carlo sampling techniques are entirely random in principle — that is, any given sample value may fall anywhere within the range of the input distribution.
• With enough iterations, Monte Carlo sampling recreates the input distributions through sampling.
• Determine the Level of Risk the Project Currently Has
• Quantitative risk analysis model
• Project end dates
• Project cost at completion
• S-curve
• Criticality analysis
• Latin Hypercube sampling
• After analyzing the risks and developing the risk response plan, Monte Carlo and Latin Hypercube techniques let you know if the overall project risk has been reduced or not after developing the risk response strategies.
• Determine Project Cost and Length if No Further Risk Management Actions Are Taken
• Expected Monetary Value of the Project
• Cost and schedule estimating
• Determine the Probability of Achieving Total Cost or Completion Date Objectives for the Project
• Failure Modes and Effects Analysis (FMEA)
• fault tree analysis
• Trends in Risk as the Perform Quantitative Risk Analysis Process Is Repeated Throughout the Life of the Project
• Sensitivity analysis
• Sensitivity analysis is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned (réparti), qualitatively or quantitatively, to different sources of variation in the input of a model.
• To find risks that have the biggest effect on the project.
• Helps to determine which individual project risks have the most impacts potential impact on project outcomes
• Sensitivity analysis includes
• Increased understanding or quantification of the system
• Model development
• Decision making or the development of recommendations for decision makers
• Decision tree analysis
• Use it to find expected impact of different risk scenarios on the project.
• Expected Monetary Value of Risks of each branch
• Decision tree sketch
• 3 nodes
• Circle / chance nod
• The event
• A chance node, represented by a circle, shows the probabilities of certain results.
• In a decision tree diagram, a circle represents events, and a rectangle or square represents a decision.
• Square / decision node
• The decision
• A decision node, represented by a square, shows a decision to be made.
• In a decision tree diagram, a rectangle or square represents a decision and a circle represents events.
• Triangle
• The final outcome
• An end node shows the final outcome of a decision path.
• Alternatives branches
• Each branch indicates a possible outcome or action
• Rejected alternatives
• Shows a choice that was not selected
• They are easy to understand
• Tey are useful with or without hard data, and any data requires minimal preparation
• You can add new options to existing trees
• Their are valuable in picking out the best of several options
• They may easily combined with other decision making tools
• However, decision trees can become excessively complex.
• In such cases, a more compact influence diagram can be a good alternative.
• Influence diagrams narrow the focus to critical decisions, inputs, and objectives.
• Influence diagram
• Indicates which elements have the greatest influence on key outcomes
• Monte Carlo analysis
• S-curve
• Document the Non-Top Risks
• Other quantitative analysis
• Schedule risk analysis
• Probalistic analysis

Outputs

• Purpose
• Now, the risk register will include information on the expected completion date and cost.
• The risk register will include the overall probability of achieving the project objectives.
• The list of prioritized risks will be improved and fine tuned.
• Any new insights.
• Since you are using modeling and computers can generate different possible outputs you might find a trend or some abnormalities that catches your attention.
• You need to think on how to improve on that by looking at what risks might cause that abnormalities or failures and how to control it.
• Prioritized list of quantified individual project risks
• The quantified probability of meeting project objectives
• Trends in quantitative risk analysis
• Initial contingency time and cost reserves needed
• Assessment of overall project risk exposure
• Possible realistic and achievable completion dates and project costs, with confidence levels, versus the time and cost objectives for the project
• Recommended risk responses
• Risk report
• Results of assessment of overall risk exposure
• Detailed probabilistic analysis of the project
• Prioritized list of individual project risks
• Trends in quantitative risk analysis results
• Recommended risk responses
• Risk Register plan and representation Updates 