Complex problems often require decisions at different levels. These decisions cannot be made in isolation or sequence. Instead, they are best presented as a tree of decisions.
Developed in the 1960s, the Decision Tree is a mathematical model and graphic representation for making decisions on complex issues. It contains action choices (at each decision point), outcomes or results of each action, and the probability and value (costs and returns) of each result [@mageeDecisionTreesDecisionMaking1964]. We can compare the value of each outcome (branch) mathematically by multiplying all the factors (the mathematical model) for the branch and determine which alternative will yield the most expected gain with the information available at that given point.
Decision Tree allows complex factors, such as the timeframe of each alternative (DCF, NPV, etc.), strategy alignment, etc., to be built into the mathematical model and update the tree as new information becomes available.
However, the decision tree does not guarantee the optimal final decision, as the gains must be viewed with who bears what risks for each branch.
References
- Magee, J.F. (1964) Decision Trees for Decision-Making. Harvard Business Review. https://hbr.org/1964/07/decision-trees-for-decision-making.