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Qualitative Risk Analysis: Definition, Purpose, and Process

 


Qualitative Risk Analysis is a method used to assess risks based on their probability (likelihood) and impact (severity) using non-numerical, descriptive scales (e.g. Low/Medium/High). It helps prioritize risks for further action without complex calculations.


Key Features of Qualitative Risk Analysis

  1. Subjective Judgment – Relies on expert opinions, historical data, and experience.

  2. No Complex Math – Uses simple scales (e.g. 1–5 ratings) instead of statistical models.

  3. Fast & Cost-Effective – Ideal for initial risk screening or when data is limited.

  4. Visual Tools – Often presented via risk matrices or heat maps.


When to Use Qualitative Analysis?

✔ Early project stages (quick risk identification).
✔ When quantitative data is unavailable.
✔ For non-critical risks where detailed analysis isn’t needed.


Steps in Qualitative Risk Analysis

1. Identify Risks

  • Brainstorm risks (e.g. "Equipment failure " "Supply chain delay").

2. Assess Probability & Impact

  • Rate each risk using scales like:

    • Probability: Rare → Unlikely → Possible → Likely → Almost Certain

    • Impact: Negligible → Minor → Moderate → Major → Catastrophic

3. Plot on a Risk Matrix

Impact →
Probability ↓
LowMediumHigh
HighMedium RiskHigh RiskExtreme Risk
MediumLow RiskMedium RiskHigh Risk
LowVery Low RiskLow RiskMedium Risk

4. Prioritize Risks

  • Focus on High/Extreme risks (top-right of the matrix).

  • Ignore or monitor Low/Very Low risks.

5. Plan Responses

  • Mitigate (reduce probability/impact).

  • Accept (if cost to fix > risk impact).

  • Transfer (e.g. insurance).


Example: Construction Project Risk

RiskProbabilityImpactPriority
Worker injury due to fallsLikelyMajorHigh
Rain delaysPossibleModerateMedium
Tool theftUnlikelyMinorLow

Action: Implement fall protection training (High risk).


Qualitative vs. Quantitative Analysis

AspectQualitativeQuantitative
DataDescriptive (High/Medium/Low)Numerical (probabilities, $ impacts)
MethodExpert judgment, risk matrixMonte Carlo simulations, FMEA
Use CaseInitial screening, small projectsComplex projects (e.g., nuclear plants)

Advantages & Limitations

✅ Pros: Fast, easy to understand, no need for hard data.
❌ Cons: Subjective, less precise than quantitative methods.

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