Event Risk vs Decision Risk
Event risk is what most people mean they talk about "risk". It is the expected value of an event, its undesirable consequences and probability of its occurrence. Determining risk amounts to answering:
- What can go wrong? –An event occurs that may have bad consequences
- How likely is it? – Probability dependent on past statistics and model results
- What are the consequences? –Money, time and possibly lives are wasted
NASA and others have entire handbooks on assessing event risk.
During decision-making, risks are inherent in uncertain knowledge, information and models. Uncertainty creates the risk that a poor decision will be made. This doesn't say that the alternative chosen will fail, that is even risk. Drawing analogy to event risk, decision risk focuses on:
- What can go wrong? – A poor choice is made
- How likely is it? – Probability dependent on uncertain knowledge, and the fusion of the team’s interpretation of information and models
- What are the consequences? –Money, time and possibly lives are wasted
One problem the IG wants to address is selecting new employees. Clearly the risk here is a decision risk - they want to ensure that they don't make a poor hiring choice. They also want to manage their portfolio of projects. Here the risk that the project can go wrong affects the risk that they make a poor decision. The higher the event risk associated with an option, the higher the decision risk may be.
Both types of risk are based on probabilities. However, traditional probability methods (often called frequentist methods) are good fro event risk, but are not capable of managing knowledge uncertainty. Rather, Bayesian probability methods are specifically designed to integrate accumulating, uncertain, incomplete and conflicting knowledge.
Can I convince the IG folks of this? We will see.
Labels: decision making, decision risk, event risk

