According to Open FAIR, why should qualifiers be applied to the results of a risk analysis?

Applying qualifiers to the results of a risk analysis is essential because quantitative results alone may not provide the full context necessary for making well-informed decisions. While numerical data can illustrate potential risks and their impacts, they often lack the qualitative considerations that can influence how those risks are perceived and acted upon.

For instance, the figures generated through a quantitative risk analysis may not account for specific circumstances or the broader business implications associated with potential losses. Qualifiers help contextualize these numbers, adding depth by factoring in aspects like the organization's strategic goals, stakeholder perspectives, and external environmental factors. This enriched understanding aids decision-makers in comprehensively evaluating risks rather than relying solely on bare statistics.

In contrast, while the aspects of loss tolerance being influenced by leadership, subjectivity in loss measures, and the dependencies involved in risk decision-making are all relevant, the focus on the limitations of quantitative data—specifically how it does not convey the complete picture—is a critical rationale for applying qualifiers in risk analysis. It emphasizes the need to integrate both quantitative and qualitative insights for sound decision-making.