What Is a Decision Tree Analysis?

If you have ever been faced with a difficult decision and attempted to weigh the pros and cons of various options, you have undergone the beginning stages of a decision tree analysis. A decision tree analysis is a graphic organizer that helps individuals or groups visually represent the cause-and-effect relationships of various decisions. It provides a distillation of the thought process that decision-making entails and can be quantified or further analyzed to help narrow down choices.

Features

Most decision tree analysis charts begin with a central concept or key options, which serve as the trunk of the tree. These initial concepts are typically placed within a box or a circle to highlight them as the root of the decision-making process. Then, the analysis features branches, represented as lines, illustrating the various effects and outcomes of different decisions. These branches may then contain subsets of smaller branches detailing further outcomes.

Function

A decision tree analysis is a way to objectively present the various options and their potential outcomes. Some of these outcomes might be quantifiable, in the case of cost of money or time, but others might be less concrete. They typically illustrate both the rewards and the risks inherent in a particular plan.

Considerations

Some decision tree analysis charts employ visual shortcuts. For example, a person might use color coding to emphasize more important concepts. Someone might use a broken line to indicate a hypothesis and a solid line to represent a known fact. A common symbolic code is to use a circle to surround uncertain outcomes and a square to represent decisions.

Effects

Once the decision tree analysis is written, it is important to assign values to each end result to attempt to create an objective measure for evaluating each possible decision. There are several approaches to this process. You can assign monetary or labor costs to each end result. Other people create a rubric to give each decision a score based on its feasibility. These scores can be represented as percentages or as fractions, with the total adding up to 100 percent or 1. The node with the highest score represents the best option.

Warning

A decision tree analysis is only as good as the information you input. If you are biased toward a particular outcome, this preference will show up in the analysis and skew the results. Some people attempt to avoid bias by including other people in the formulation of the decision tree analysis.