What is a Decision Tree?

By Deepak Palasamudram3 min read · Posted May 10, 2023

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A decision tree is a tool used in business to explore all of the alternatives in decision-making and to make the best possible outcome in business projects. Decision trees are classified into two types: categorical variable decision trees and continuous variable decision trees. A categorical variable decision tree has a target that is divided into categories, such as yes/no responses, whereas a continuous variable decision tree has a target that is continuous, which means there are multiple responses rather than a limited number. Now you may wonder, why should I create a decision tree instead of other tools, and how can I make one? Well, read on to find out!

Benefits of Decision Trees

Improves Decision-Making

A decision tree visually represents the decision-making process, making it easier to understand and interpret. This allows companies to consider all options in their decision-making and choose the best possible outcome for their project.

Identifies Key Variables

Decision trees can be used to identify the most important variables that influence decision outcomes. This allows organizations to focus resources and effort on the most critical factors and ignore irrelevant factors, saving time and resources.

Reduces Errors

Decision trees help reduce errors, improve accuracy by identifying essential predictors, and reduce overfitting. This enables more reliable and accurate decision-making that benefits businesses regarding profitability, customer satisfaction, and operational efficiency.

Explains Decisions

Decision trees provide a clear and understandable description of the decision-making process. This helps to justify decisions to stakeholders such as customers, investors, and regulators.

Saves Time and Resources

Decision trees require little data preparation and can handle numerical and categorical data. This means businesses can save time and resources by using decision trees instead of other techniques requiring more data preparation. As said before, it also focuses on important variables and ignores irrelevant information.

Steps to Make a Decision Tree

State the main idea

The first step of creating a decision tree is to define the main problem or question that you want to explore and decide upon. This is called a root node, and it is on the top of the decision tree.

Add potential decisions and outcomes

Connect each decision to the root node using branches, and write down the possible outcomes of each decision.

Expand until you reach endpoints

Keep expanding upon the tree using branches building off potential decisions until you reach an endpoint. Ensure it is 100% looked over, the endpoints are solid, and that all outcomes/decisions are accounted for.

Calculate risk and reward

Use quantitative data to calculate the expected value of each decision. This will help find potential risks and benefits of each decision and will allow you to choose the best decision among the decision tree based on risk and reward.

Evaluate Outcomes

By calculating risk and reward, determine the best action based on your business project needs, goals, and targets. The highest value decision may not be the best, as it could come with increased risk. You should also consider your business' budget, time, and other factors.

Conclusion

A decision tree is an effective way to ensure your decision-making within your business is the best decision. As said before, there are two types of decision trees, categorical variable decision trees and continuous variable decision trees, which can be used based on your business targets. There are many benefits involved with decision trees, and it is a simple design that is also very effective.

References

About The Author

Deepak Palasamudram

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Hello, I am Deepak, a high school student and an Article Writer for Pitch Labs. Along with my love of writing and teaching others, I am passionate about entrepreneurship, finance, and coding. I plan to delve more into these subjects in the future.

See more posts by Deepak Palasamudram

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