Critical Success Factors fro Risk Management Processes- Important Topic for PMI-RMP Exam

Critical Success Factors (CSF's) is an Important Topic you will face in PMI-RMP Exam, at least 6-7 Questions will ask you directly/Indirectly about them.

The most useful way to get all of these questions on this topic is to understand deeply these factors and their effect on the risk management in general and their effect on the six processes of the risk management.

These factors are mentioned in PMI Standard Practice of Risk Management Book and they were discussed in deep details thru the book.

Below are these factors for each process and for risk management in General;

1. CSF for Project Risk Management• Recognizing Risk Management Value — Awareness of the value for the risk.
• Individual Commitment/Responsibility — All Stakeholders in the project should be responsible about the risk
• Open and Honest Communication — All stakeholders should be involved in the Project Risk Management
process. 
• Organizational Commitment — Organizational commitment can only be established if risk management is aligned with the organization’s goals and values. Project Risk Management may require a higher level of managerial support than other project management disciplines becausehandling some of the risks will require approval of or responses from others at levels above theproject manager.• Risk Effort Scaled to Project — Project Risk Management activities should be consistent with the value
of the project to the organization and with its level of project risk, its scale, and other organizationalconstraints. In particular, the cost of Project Risk Management should be appropriate to its potentialvalue to the project and the organization.• Integration with Project Management — Project Risk Management does not exist in a vacuum,
isolated from other project management processes. Successful Project Risk Management requiresthe correct execution of the other project management processes.

2. CSF for the Plan Risk Management Process•  Identify and Address Barriers to Successful Project Risk Management•  Involve Project Stakeholders in Project Risk Management•  Complying with the Objectives of the Organization, Rules, Policies, and Practices   

3. CSF for the Identify Risks Process•  Early, Iterative, Comprehensive and Emergent    Identification.•  Explicit Identification of Opportunities•  Multiple Perspectives•  Risks that Linked to Project Objectives•  Complete Risk Statement•  Ownership and Level of Detail•  Objectivity 

4.  CSF for the Perform Qualitative Risk Analysis Process

•  Use Agreed Upon Definitions and Approach for the risk terms and Methodology.
•  Collecting High-Quality Information about Risks•  Iterative Qualitative Risk Analysis 

 5. CSF for the Perform Quantitative Risk Analysis Process

•  Unbiased Data and collecting High-Quality data related to    Risk.

•  Prior Risk Identification and Qualitative Risk Analysis

• Appropriate Project Model

•  Overall Project Risk Derived from Individual Risks

•  Interrelationships Between Risks in Quantitative Risk Analysis

 6. CSF for the Plan Risk Responses Process

• People  

• Planning 

• analysis
  
7. CSF for the Monitor and Control Risks Process •  Integration between Risk Monitoring and Control with Project Monitoring and Control•  Continuously Monitor Risk Trigger Conditions•  Maintain Risk Awareness 

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TOP 10 Books to Prepare and Pass your PMP Exam

If you are planning to pass your PMP exam from the first time you have definitely study and read the below 10 books which are recommended by all experts to pass the PMI-PMP Exam from the first trial

1. PMP Exam Prep, Seventh Edition: Rita’s Course in a Book for Passing the PMP Exam by Rita Mulcahy

2.The PMP Exam: How to Pass on Your First Try, Fourth Edition by Andy Crowe PMP PgMP

3.Head First Pmp: A Brain-Friendly Guide to Passing the Project Management Professional Exam by Jennifer Greene and Andrew Stellman

4. PMP Project Management Professional Exam Study Guide by Kim Heldman

5. The PMP Exam: Quick Reference Guide (Test Prep series) by Andy Crowe PMP PgMP

6. PMP Exam Prep, Sixth Edition: Rita’s Course in a Book for Passing the PMP Exam by Rita Mulcahy

7. PMP Certification All-In-One Desk Reference For Dummies by Cynthia Snyder Stackpole

8. PMP Practice Makes Perfect: Over 1000 PMP Practice Questions and Answers by John Estrella, Charles Duncan, Sami Zahran and James Haner

9. CAPM/PMP Project Management Certification All-in-One Exam Guide with CD-ROM, Second Edition by Joseph Phillips

10. All-in-One PMP Exam Prep Kit (Test Prep series) by 
Andy Crowe

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Latin Hypercube Sampling

Most risk analysis simulation software products offer Latin Hypercube Sampling (LHS). It is a method for ensuring that each probability distribution in your model is evenly sampled which at first glance seems very appealing.

The technique dates back to 1980 when computers were very slow, the number of distributions in a model was extremely modest and simulations took hours or days to complete. It was, at the time, an appealing technique because it allowed one to obtain a stable output with a much smaller number of samples than simple Monte Carlo simulation, making simulation more practical with the .

Computing tools available at the time.

What is Latin Hypercube sampling

** The Main Principle is to divide the Area Into Strata 

Latin Hypercube Sampling (LHS) is a type of stratified sampling. It works by controlling the way that random samples are generated for a probability distribution. Probability distributions can be described by a cumulative curve, like the one below. The vertical axis represents the probability that the variable will fall at or below the horizontal axis value. Imagine we want to take 5 samples from this distribution. We can split the vertical scale into 5 equal probability ranges: 0-20%, 20-40%, …, 80-100%. If we take one random sample within each range and calculate the variable value that has this cumulative probability, we have created 5 Latin Hypercube samples for this variable:

This methodology is used to generate more more accurate simulation results in general when comparing it with other simulation sampling methods, with lower standard errors level, with lower or fewer sampling trials.

this method was established in 1979 by the governmental research of statistical mathematics in united kingdom and set the reference to many developed methodologies in this field around the world, the idea was derived from developing the normal distribution changing under certain conditions by setting a limit of fixed data and facultative results.

The optimal Latin hypercube option generates a large number of random Latin hypercube designs, then iteratively improves each of them and uses the best of the improved designs. This is very effective at finding a good design, but requires additional processing time. For example, a 20-variable 300-evaluation design takes about five minutes of CPU time. Optimal Latin hypercube uses centered L2 discrepancy (a measure of uniformity) as the optimality criteria. If a time limit is specified in the study definition, HEEDS will stop improving the sampling design when the specified wall-clock-time limit is reached. HEEDS will use the best design found to that point.