In the paper, Probabilistic Approaches: Scenario Analysis, Decision Trees and Simulations, the author looks at decision trees as an assessment of risk in a sequence. Therefore, the subject in question must pass a series of tests, failure at any point leads to a complete loss of value. The example given is pharmaceutical drugs.
The decision tree is broken down into distinct categories. Root nodes, decision nodes, event nodes and end nodes. A root node is at the beginning and where the decision maker has a decision choice or an uncertain outcome. An event node represents the possible outcomes on a given decision. You have to figure out the possible outcomes and their likelihood for this node. The decision nodes represent choices that can be made by a decision maker. The end nodes represent the final outcomes of the decision tree.
- By linking actions and choices – decision trees give decision makers a framework and make them think about the consequences.
- Value of information – having to think through this process gives the decision maker insight on how valuable this information is.
- Decision trees act as a form of risk management. If the decision doesn’t pass each test – it may be too risky to undertake.
- They are easy to construct and give definitive answers.
- There is no wiggle room or room to maneuver.
- Multiple risks are hard to assess at the same time. This is a linear process at each stage.
- Event nodes require estimates of outcomes. This is subjective in a lot of cases.
- The use of the decision tree depends entirely on the decision makers willingness to stick to it strictly.
Decision tree analysis is particularly useful when there are discrete outcomes. However, as a process becomes more complicated and the number of outcomes increases, it is harder to use this tool effectively. Its ease of use and ability to make decision makers think about the choices and consequences makes this a tool that can be applied to many different situations.
Probabilistic Approaches: Scenario Analysis, Decision Trees and Simulations. Stern. NYU. Retrieved from; http://people.stern.nyu.edu/adamodar/pdfiles/papers/probabilistic.pd