When making estimates and generating analysis results, what should be the main goal?

The main goal when making estimates and generating analysis results is to achieve accuracy with a useful level of precision. This approach emphasizes the importance of not only being correct in your measurements and analyses (accuracy) but also providing responses that are precise enough to be practical and actionable.

Accuracy refers to how close an estimate is to the true value, which is crucial because it ensures that the results are reliable and can be used for decision-making. However, simply being accurate without considering precision could lead to results that lack the necessary detail required for effective risk analysis.

A useful level of precision means that the estimates are not just rounded figures but provide enough detail to inform stakeholders and facilitate informed decisions. For example, stating that there is a risk of loss of $5,000, rather than saying "around $5,000," gives a clearer picture and assists in evaluating the situation more effectively.

Thus, the combination of accuracy and practical precision ensures that the analysis is both credible and provides meaningful insight, which is essential for risk management in the context of Factor Analysis of Information Risk (FAIR).