There are several old-school decision-making approaches that are used in numerous applications. Many of them are semi-automatic, rely too much on subjective fill-in by humans, and have a limited number of functions. The Eisenhower matrix, for example, is a reliable and straightforward method for decision making. It is particularly useful for questions that fall into two categories: "urgent" and "important" However, when a more complicated decision needs to be made, additional features may need to be considered.

The ID3 algorithm implemented in the Decision tree app can use the additional features to make more weighted decisions. For example, the algorithm could consider whether the new decision is profitable, expensive, difficult, or successful. It could weigh these characteristics and their values against the potential risks and benefits of the option to decide whether or not you should pursue it. In this way, you could make more informed and educated decisions about which strategy to pursue and avoid costly mistakes.

Include your historical data for several decisions you have made and give a value for each characteristic such as Urgent: true, Expensive: false, Delegated: false, Successful: true, and so on. The app will create a valid decision tree based on your data.

In practice, this all takes only about five minutes. To make sure you do not make the same mistake twice, take these five minutes to create your decision tree. This can save you a lot of time and money. It's a small investment that can pay off in the long run.

All the information you enter and all the trees you create are yours alone. The Decision tree app is a small piece of artificial intelligence that works exclusively for you and never searches the Internet for an answer. It is completely private and works without an internet connection.

Build a decision tree manually.

When time pressures are high and available information is limited, do not rely too much on your gut as a decision-making shortcut. While you need to tune into your intuition, your also need to critically self-reflect and realize that sometimes “acting on your gut” really means being driven by your personal biases. Making decisions driven by emotions you may fall into the confirming evidence trap (seeking out evidence that justifies our choices rather than looking at the whole picture).

By applying the decision tree app in production (use) mode, you can strive to be more objective. Start from the root. Evaluate a feature and select one of the two branches Repeat this procedure is repeated until a final leaf is reached.

Pose the problem in terms of a binary tree of decisions. The decision tree shows the routes by which the various possible outcomes are achieved. The decision tree is made up of a series of nodes and branches. Each branch represents an alternative course of action or decision.

In “edit” mode build the decision tree of a series of nodes and branches. At the first node on the top begin with one main idea or decision. After adding your main idea to the tree, continue adding chance or decision nodes after each decision to expand your tree further.
Do not try to identify all the events that can happen or all the decisions you will have to make on a subject under analysis. In the decision tree you lay out only those decisions and events or results that are important to you and have consequences you wish to compare.
The more choices you have, the more complex your decision-making process. With the decision tree application consider just the true and false (yes/no) options at a time, so you make a more informed decision. Think critically when considering the remaining options.

Create a Decision Tree using the ID3 algorithm Import raw data from CSV files or fill in manually.