PMI-RMP Exam Dumps - PMI Risk Management Professional (PMI-RMP) Exam

 

When stakeholders are concerned about the potential impact of a project, such as staff reductions, the risk manager should perform a stakeholder analysis. This analysis will help identify the stakeholders’ interests, their levels of influence, and how their concerns should be addressed in the project plan. By understanding these factors, the project team can develop strategies to engage stakeholders effectively, address their concerns, and increase project support. PMI emphasizes the importance of stakeholder analysis in risk management as it helps in aligning stakeholder expectations with project goals​​.

 

Residual risks are the risks that remain after the risk response plan has been implemented. They are the risks that are accepted by the project team and stakeholders as part of the project. Residual risks may have low probability or impact, but they still need to be monitored and controlled throughout the project. The first thing that the risk manager should do when a risk owner identifies and reports some residual risks is to analyze, document, and communicate them to the relevant stakeholders. The risk manager should assess the probability and impact of the residual risks, and determine if they require any further response or contingency plan. The risk manager should also update the risk register and the risk report with the information about the residual risks, and share them with the stakeholders who need to be aware of them. This will help the project team and stakeholders to be prepared for any potential occurrence of the residual risks, and to take appropriate actions if needed. References: PMI, The Standard for Risk Management in Portfolios, Programs, and Projects, 2019, p. 94-95, 101.

 A decision tree analysis is a tool that helps to evaluate and select the best option among different alternatives based on costs and probabilities. A decision tree analysis uses a graphical representation of a decision problem, where each node represents a decision point, a chance event, or an outcome. The branches of the tree show the possible choices, events, or consequences that can occur at each node. The end nodes of the tree show the expected value or payoff of each option, which is calculated by multiplying the probability and the cost or benefit of each outcome. A decision tree analysis can help to compare the expected values of different options and choose the one that maximizes the benefit or minimizes the cost1. A decision tree analysis can also help to incorporate uncertainty and risk into the decision making process, as it shows the range of possible outcomes and their likelihoods2. Therefore, the project manager should perform a decision tree analysis to evaluate and select the best option based on costs and probabilities for a mega facility development project. Performing a FMECA fault tree analysis, conducting a sensitivity analysis, or conducting an analytic hierarchy process are not the best options to evaluate and select the best option based on costs and probabilities. A FMECA fault tree analysis is a tool that helps to identify and analyze the potential causes and effects of failures in a system or process. It uses a graphical representation of a failure event, where each node represents a basic or intermediate event that contributes to the failure. The branches of the tree show the logical relationships between the events, using AND or OR gates. A FMECA fault tree analysis can help to calculate the probability and severity of failures, as well as to prioritize and mitigate the risks3. However, a FMECA fault tree analysis does not help to compare different options or alternatives, as it focuses on a single failure scenario. Conducting a sensitivity analysis is a tool that helps to measure how the uncertainty in the input variables of a model affects the output or outcome of the model. It uses a graphical or numerical representation of the relationship between the input and output variables, showing how the output changes when the input changes. A sensitivity analysis can help to identify the most critical or influential variables, as well as to test the robustness or reliability of the model4. However, a sensitivity analysis does not help to compare different options or alternatives, as it focuses on a single model or option. Conducting an analytic hierarchy process is a tool that helps to evaluate and select the best option among different alternatives based on multiple criteria. It uses a mathematical method of pairwise comparison, where each alternative is compared to each other in terms of each criterion. The results of the comparisons are then aggregated into a matrix, which shows the relative importance or preference of each alternative. An analytic hierarchy process can help to rank the alternatives and choose the one that best satisfies the criteria5. However, an analytic hierarchy process does not help to incorporate costs and probabilities into the decision making process, as it relies on subjective judgments and preferences. References: 1, 2, 3, 4, 5.

A decision tree analysis is a quantitative risk analysis technique that helps evaluate and select the best option based on costs and probabilities. It visually represents different decision paths and their associated probabilities, allowing the project manager to compare and select the most appropriate option for the project.

The expected outcome of developing the risk management plan is to define how risk management activities will be executed throughout the project. This includes the processes, tools, and techniques that will be used to identify, assess, and manage risks.

 The risk management plan is a document that describes how risk management activities will be structured and performed throughout the project. It provides guidance on how to identify, analyze, respond, monitor, and control risks, as well as how to communicate, document, and report them. The risk management plan also defines the roles and responsibilities of the project team and stakeholders in risk management, the risk categories and breakdown structure, the risk thresholds and appetite, the risk management tools and techniques, and the risk management budget and schedule. The risk management plan is an output of the plan risk management process, which is the first process in the project risk management knowledge area. Developing the risk management plan is essential for ensuring that the project risks are closely managed and aligned with the project objectives and stakeholder expectations. References: PMI, Project Risk Management, 2nd edition, 2019, p. 67-681

Comprehensive and Detailed In-Depth Explanation:

Extreme Programming (XP) emphasizes continuous feedback, early testing, and adaptive planning. When discrepancies arise, XP encourages identifying root causes and taking corrective actions without delaying value delivery.

Option D: Run a spike, identify what went wrong during implementation, and request a change to enhance value delivery (Correct Answer).

A spike is a time-boxed research activity used to explore a problem, test assumptions, and mitigate uncertainty in XP methodology.

By running a spike, the team analyzes what went wrong in implementation and applies the findings to ensure future iterations align with customer needs.

The PMI-RMP Guide states that “proactive risk response planning helps teams course-correct and maintain delivery momentum” (PMI-RMP Exam Prep Study Guide, 2021, p. 142).

The Agile Practice Guide supports the use of spikes, highlighting that “spikes allow agile teams to validate uncertainties in requirements, leading to more informed decision-making” (PMI & Agile Alliance, 2017, p. 89).

Option A: Release this version and leave changes to be done at the end of the project phase (Incorrect).

XP emphasizes continuous improvement and early defect resolution rather than postponing fixes.

Leaving changes until later may increase technical debt and reduce user satisfaction.

Option B: Arrange a workshop where all ideas will be discussed and take corrective actions ensuring value delivery (Partially Correct but Not the Best Answer).

While workshops help gather feedback, they do not provide technical validation of what went wrong.

A spike (Option D) is a better approach because it directly investigates the issue and leads to actionable changes.

Option C: Ask the development team to brainstorm and come up with suggestions that will improve the delivery date (Incorrect).

Brainstorming may generate ideas but does not analyze the root cause of the discrepancies.

Without a structured approach like a spike, there is a risk of guessing rather than using data-driven solutions.

Final Verdict:

The best answer is D (Run a spike, identify what went wrong during implementation, and request a change to enhance value delivery) because a spike provides empirical insights, leading to more effective corrective actions.