Decision Trees and Risk Evaluation

Decision Trees and Risk Evaluation
In operations research, specifically in decision analysis, a decision tree (or tree diagram) is a decision support tool that uses a graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. A decision tree is used to identify the strategy most likely to reach a goal. Another use of trees is as a descriptive means for calculating conditional probabilities.

In data mining and machine learning, a decision tree is a predictive model; that is, a mapping from observations about an item to conclusions about its target value. More descriptive names for such tree models are classification tree (discrete outcome) or regression tree (continuous outcome). In these tree structures, leaves represent classifications and branches represent conjunctions of features that lead to those classifications. The machine learning technique for inducing a decision tree from data is called decision tree learning, or (colloquially) decision trees.

---

Some Advices in Decision Making

• Do not make decisions that are not yours to make.
• When making a tough decision, ask yourself what you would do if all parties involved knew your true intentions and your true desires
• When making a decision you are simply choosing from among alternatives. You are not making a choice between right and wrong.
• Avoid snap decisions. Move fast on the reversible ones and slowly on the non-reversible.
• If you are struggling trying to decide between two choices, choice A and choice B, the problem may be that neither is RIGHT for you and what you need to do is discover your other options i.e. choice C, choice D etc.
• Choosing the right alternative at the wrong time is not any better than the wrong alternative at the right time, so make the decision while you still have time.
• Do your decision making on paper. Make notes and keep your ideas visible so you can consider all the relevant information in making this decision.
• Do not rely too much on the results of quantitative decision making tools

Decision Making is the process of making a conscious choice between 2 or more alternatives producing most desirable consequences (benefits) relative to unwanted consequences (costs).

Good decision making is an essential skill for career success generally, and effective leadership particularly. If you can learn to make timely and well-considered decisions, then you can often lead your team to spectacular and well-deserved success. However, if you make poor decisions, your team risks failure and your time as a leader will, most likely, be brutally short.

The techniques help you to make the best decisions possible with the information you have available. There are some tools which help you map out the likely consequences of decisions, work out the importance of individual factors and choose the best course of action to take.

This blog shares teaching experiences, learning resources, techniques, examples related to decision making processes particularly for engineering managers. It is also useful for engineering students who take engineering management or a related course.