As seen throughout this course, by incorporating probabilities into decision analysis we are
able to gain a much more comprehensive perspective on the risks associated with our
decision making processes. The Expected Monetary Value (EVM) approach helps us
differentiate between our alternatives in terms of which ones will be most
profitable/valuable. We can apply this approach to Sensitivity Analysis, Risk Profiles, and
especially Decision Trees.
The decision tree provides us with a graphical representation of our decision-making
process, complete with each alternative and the path towards an outcome (Albright, 2015).
This is especially helpful when we are dealing with complex problems whereby
calculating probabilities for each branch would be difficult by hand.
In the Casualty Insurance industry this has become a very effective tool for Personal Injury
Attorney’s (Victor, N.D.). They can sit down with their clients and show them a very
digestible pictorial representation of how their case (the value of their settlement) will turn
out via various alternative resolution strategies such as 1. Settlement with the claims rep. 2.
Arbitration 3. Trial.
The problem with injury settlements is they are very subjective and may settle differently
depending on the type of resolution procedure you choose and even then let’s say you
choose to be heard in front of a Jury, they are so unpredictable that the same case same
facts can lead to a completely different award or no award depending on the jury. So
probability/risk is completely inherent in an Attorney’s efforts to advise their clients on the
appropriate route to take. Thus, a decision tree works perfectly to show a client the array of
possibilities of their case in a way that incorporates risk/probabilities/uncertainties
intelligently.