PMI-RMP Cheat Sheet

Use this as your last-mile PMI-RMP® review. Pair it with the Syllabus for coverage and Practice for speed.

For exam format and official policy details, see Overview.

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Risk management in one picture (decisions, not paperwork)

    flowchart TD
	  A["Clarify appetite + thresholds"] --> B["Identify threats + opportunities"]
	  B --> C["Analyze (qualitative → quantitative when needed)"]
	  C --> D["Choose responses + assign owners"]
	  D --> E["Monitor triggers + metrics"]
	  E --> F["Update artifacts + close/transition"]
	  F --> B

If you can state these three items from any question stem, you’re usually close to the best answer:

• Threshold: what level triggers escalation or action?
• Exposure: how big is it (probability/impact), and what evidence supports that?
• Next decision: what action reduces exposure or increases value fastest?

What the exam is really asking

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Core definitions (fast)

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Appetite → tolerance → thresholds (keep them distinct)

Best-answer pattern: when thresholds are unclear, define them first—otherwise analysis won’t change decisions.

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Identification (what to pick when)

Good risk statement format: cause → event → impact.

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Qualitative analysis (probability × impact, done right)

Exposure scoring (concept)

\[ \text{Risk Exposure} = P \times I \]

Where (P\) is probability and (I\) is impact (cost, schedule, quality, value, compliance).

Rules

• Calibrate definitions of (P\) and (I\) up front (avoid “high means scary”).
• Include urgency/proximity when deciding what to act on first.
• If data is too weak for numbers, use ordinal ranking but keep rationale explicit.

Qualitative vs quantitative selection

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Quantitative analysis (what you must be able to interpret)

Expected Monetary Value (EMV)

\[ \text{EMV} = \sum_{i=1}^{n} p_i \times I_i \]

• Use EMV to compare options and estimate contingency reserve needs.
• EMV is not certainty; it’s an expected value given assumptions.

Decision trees (concept)

• Multiply outcomes by probabilities along branches.
• Compare expected values of decisions, then sanity-check against constraints (compliance, deadlines).

Monte Carlo simulation (concept)

• Output is a distribution (not a single answer).
• Typical exam interpretation:
  • “P80 date” = a date you have ~80% confidence of meeting.
  • Wider spread = higher uncertainty; reduce uncertainty with better inputs or risk responses.

Sensitivity analysis (concept)

• Identifies the variables that drive results the most (often shown as a tornado chart).
• Use it to pick where mitigation buys the most risk reduction.

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Response strategies (threats vs opportunities)

Response quality checklist

• time-bound actions
• clear owner (not “the team”)
• measurable success criteria
• secondary/residual risks identified

Response selection cues

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Reserves (concept table)

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Monitoring (make it actionable)

What to track

• triggers and thresholds (tripwires)
• exposure trend (up/down)
• response effectiveness (did it change (P\) or (I\)?)
• residual and secondary risks

Reporting sanity checks

• Every metric should connect to a decision (escalate, re-plan, fund response, stop).
• Prefer trends over one-point status.
• Keep stakeholder views consistent (no “two truths” dashboards).

Fast elimination rules

• A response with no owner or trigger is usually weak.
• Quantitative outputs without decision use are usually weak.
• If the threshold is undefined, claiming the risk is “acceptable” is usually weak.
• Monitoring that does not change a decision path is usually weak.

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Glossary (quick)

• RBS (Risk Breakdown Structure): hierarchical categories used to improve coverage and consistency.
• Heat map: visual map of probability vs impact used for prioritization.
• Risk burndown: trend view of risk exposure over time (should reflect real exposure changes).
• Dot plot: simple visualization of risk distribution/priority across items.