Decision Tree

What is a decision tree, how is it visualised and what are advantages?

The graphical representation of decision options

A decision tree represents a multi-level decision process with all decision options. Since the decision paths are represented by individual branches, it is also called a tree diagram.

A decision tree represents a multi-level decision process with all decision options. Since the decision paths are represented by individual branches, it is also called a tree diagram. It is a visualisation and serves as a decision aid. Often you can find examples of decision trees on the Internet that show alternative paths in a process but are not suitable as decision aids. The purpose of a decision tree is to arrive at a final decision based on various visualised answer options to concrete questions.

Even though a decision tree can be visually appealing, it is clearly structured by formal rules. This is also the biggest advantage for users, who can easily follow these rules over several levels – the questions with their answer options – and thus make a decision.

The visualisation of decision trees

A decision tree can be presented from top to bottom as well as from left to right. Rich decision trees know besides

  • the questions
  • and the response options (also referred to as alternatives)
  • additionally environmental conditions.

These environmental conditions are external factors that influence the outcome of a decision but cannot be influenced by the decision maker (e.g. weather in agriculture or opening hours in stationary retail). They are therefore uncertainty factors and represent risks in the decision-making process.

Decision Tree - an abstract example

This decision tree distinguishes between rectangular and round branch nodes.

  • Decision nodes are rectangular (e.g. E1 and E2).
  • State nodes are round.

The first decision E1 leads to a choice of an alternative A1 or A2 and to environmental states Z1 and Z2. This is followed by further decisions with further alternatives and states, providing a decision can be made all the way to the end.

Advantages and disadvantages of decision trees

In principle, a decision tree is suitable for the systematic derivation of decision options. Since the creation of a decision tree does not require specific qualifications apart from technical expertise, working with decision trees is relatively widespread. Working with decision trees offers the following advantages:

  • They are easy to create and easy to read.
  • Dependencies in both chronological and logical sequence are identified.
  • Only pens, paper or the simplest graphics programs are needed to create them.
  • They can be refined and built up step by step.

Another advantage is that they can also be used as a form of documentation; this makes sense whenever organisations want to understand why a decision was made x(A1, A3, Z1, Z3) and not x(A1, A4, Z1, Z3) in the course of a project or development.

Theoretically, a decision tree is suitable for all types of decision making – in corporate or project management practice, however, there are limits when it comes to very complex relationships. The following disadvantages exist when working with decision trees:

  • The representation can quickly become confusing when there is a lot of information and options.
  • Not always all decision options or possible consequences in terms of costs, risks, probability of occurrence etc. are known. Whether information is missing, however, cannot be seen in the presentation.

 

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Notes:

Here you will find additional information from our Smartpedia section:

Smartpedia: What is a Decision Table?

What is a Decision Table?

Smartpedia: What is a Decision Matrix?

What is a Decision Matrix?