Qualitative risk estimation

The classification of a hazard is made based on expert judgment.

In practice, this can be undertaken via the collective opinion of the attendees at a hazard identification workshop.

For a straightforward hazard:

  • Identify the causes of the hazard and document them as a table or short explanation;

  • Identify the possible consequences of the hazard and the factors that affect those consequences, and document as a table or short explanation;

  • Identify the existing safety measures that control the hazard;

  • Identify the practical additional safety measures that might be implemented to control the hazard further.

Semi-quantitative estimation

  • Used when some data is available, or a good degree of judgment can be applied to estimates of the frequency and consequences of each accident;

  • Typically uses a 5 x 5 matrix with the frequency and consequence rankings broadly separated by a fixed factor, but this does not have to be the case;

  • The size of the matrix and the factor difference in frequency and consequence rankings should suit a particular stakeholder’s operation.

The main advantages of using a risk matrix:

  • It is an easily understandable representation of relative risk levels;

  • A tie can be applied relatively quickly;

  • It is readily understandable by those whose inputs and opinions are needed to apply it;

  • It enables the combination of frequency and consequences to be represented in an intuitive visual way.

The explicit risk estimation involves:

  • Identifying the possible causes of the hazard and estimating the likelihood of each cause resulting in an accident;

  • Identifying the possible consequences of the hazard and assessing their severity.

Tables

Likelihood

Consequence

Frequency/Consequence

Calibrating the risk matrix

Risk classification matrices are used for ranking and comparing the risk of different hazards.

The matrix must be calibrated so that relative risk of different hazard is preserved across the various risk classifications.

  • Achieved by having the same factor difference (a factor of 5) between each frequency and consequence category.

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