Decision Tree Analysis

Decision Tree Analysis:
A decision tree is a map of the possible outcomes of a series of related choices.
Allows weighing possible actions against one another based on their costs, probabilities, and benefits. Used to map out an algorithm to predict the best choice mathematically.

3 types of nodes:
Chance nodes - Circle; shows the probabilities of certain results.
Decision nodes - Square; shows a decision to be made.
End nodes - Triangle; shows the final outcome of a decision path.


Process:
Start with the main decision. Draw a small box to represent this point, then draw a line from the box to the right for each possible solution or action. Label them accordingly.

Add chance and decision nodes to expand the tree as follows:
If another decision is necessary, draw another box.
If the outcome is uncertain, draw a circle (circles represent chance nodes).
If the problem is solved, leave it blank (for now).

From each decision node, draw possible solutions. From each chance node, draw lines representing possible outcomes. If you intend to analyze your options numerically, include the probability of each outcome and the cost of each action.

With a complete decision tree, you’re now ready to begin analyzing the decision you face.


By calculating the EMV expected monetary value of each choice in the tree, you can minimize risk and maximize the likelihood of reaching a desirable outcome.