Decision Trees

TM TOOL: DECISION TREES

Introduction

A large part of the technology strategy is the selection process which involves looking into the future and make difficult decisions because of the uncertainty. A decision tree, as its name implies, generates a tree-like graph of decisions that can be made by a business to decide the alternative choices and their potential consequences. Decision trees enable solving those problems step by step in a sequence. Therefore by using a decision tree, the decision maker can identify the most suitable option in a particular circumstance.

The process of decision tree allows companies to assign quantifiable values to the assumed consequences and choose the best option. By quantifying the uncertainty, decision makers are able to model a variety of outcomes and react appropriately.

Where and why the tool is used?

The decision tree is a decision support tool. Decision trees can be applied to many situations. A decision maker in a business, has many alternative choices to decide on. The aim of the decision maker is to choose the best one among those alternatives. Decision trees help to calculate the expected values or the expected utilities of those competing alternatives in a simple way. In addition to this, decision trees permit the consideration of the actions of more than one decision maker. Also they can be combined with other decision tools.

However calculations can become complex if many values are linked and/or uncertain.

As an example, decisions about whether to make R&D or not, cary a high risk potential due to the uncertain nature of technology and the markets. Therefore approaching such decisions solely in terms of risk would be misleading. While deciding, risk and expected return relationship should be taken as a basis. One of the tools which makes the decision easier is the decision tree technique.

Such like important decisions can not be taken in one go, on the contrary they are usually carried our step by step. The sequential nature of decision trees are therefore useful in uncertain fields such as technology.

How is the process? / How to use the tool?

The decision tree graph consists of two parts: nodes and connecting branches. The nodes are displayed as circles or squares and they represent different decisions. The connecting branches represent the alternative outcomes related to the nodes to which they are connected. For example a company must choose a contractor and has two different alternatives; low bidder but risky and reliable but high bidder. The first alternative has two outcomes in terms of being late; it can complete the project on time or it can be late for four months. On the other hand, the second alternative can also complete the project on time but the delay