How Analysis, Likelihood, and Impact Models Work Together

Risk analysis, whether inherent or residual, depends on the interaction of three models. Likelihood and impact models supply results to an analysis model.

A likelihood model expresses the chance that circumstances defining a risk will actually occur.
An impact model expresses the potential loss associated with a risk.
An analysis model accepts number values from a likelihood model and an impact model, and uses them to calculate an overall risk score.

There are, however, two types of analysis:

"Qualitative" means that a user selects labels to initiate analysis, and the process returns a label as a risk rating. Qualitative likelihood and impact models convert the input labels to numbers. A qualitative analysis model uses those numbers to calculate a numeric risk rating, but converts it to a label. The numbers are used only in the background. Before you create a qualitative analysis model, ensure that qualitative likelihood and impact models exist to support it.
"Quantitative" means that a user enters numbers to initiate analysis, and the process returns a number as a risk rating. "Semiquantitative" likelihood and impact models pass the numbers selected by the user to the quantitative analysis model (but also generate labels describing the likelihood and impact inputs). The quantitative analysis model calculates the overall risk rating. Before you create a quantitative analysis model, ensure that semiquantitative likelihood and impact models exist to support it.

To create or edit any of these model types, select the Models tab in the Risks work area. Then, in a Models page, locate the panel that displays records of the type of model you want to work with.

Or, to create a model, select a quick action from the Risk Management springboard. There's one Create quick action for each type of analysis, impact, and likelihood model. (Depending on the number of quick actions available to you, you may need to select a Show More option on the springboard.)