What Is Decision Tree Analysis: Definition, Benefits & How To

As a project manager, you make important decisions every day. But how can you be sure that the choices you’re making are the best ones for both your individual career and your company as a whole? The answer is found through decision tree analysis.

In this article, you’ll learn exactly what decision tree analysis is and why this exercise can be so beneficial for project managers. We’ll then show you a four-step system you can use to make effective decision trees. Let’s dive in!

What’s a Decision Tree?

A decision tree is a type of diagram that clearly defines potential outcomes for a collection of related choices. In project management, a decision tree analysis exercise will allow project leaders to easily compare different courses of action against each other and evaluate the risks, probabilities of success, and potential benefits associated with each.

It’s important to note that a proper decision tree has four main elements : decision nodes, chance nodes, end nodes, and branches. Let’s briefly explore each of these individually.

In general, a decision tree analysis exercise begins with a single decision node, AKA a square. From there, branches are drawn representing various choices and resulting in potential outcomes (i.e. chance nodes).

When the full potential scenario has been played out, an end node is used to signify the final outcome. As you’ll see later in this article, a completed decision tree analysis graph looks like a tree, hence the name.

The Benefits of Decision Tree Analysis

As a project manager, every decision you make presents both new threats and fresh opportunities. The decision tree analysis technique allows you to be better prepare for each eventuality and make the most informed choices for each stage of your projects.

There are other benefits as well:

Have we convinced you yet of the importance of decision tree analysis? Great! Let’s move on to the next section where we’ll show you how to use this decision-making strategy in your own project management pursuits.

How to Use a Decision Tree in Project Management

You’re now familiar with what a decision tree is and why decision tree analysis can be so beneficial to your project management efforts. Now, let’s take a look at the four steps you need to master to use decision trees effectively.

1. Identify Each of Your Options

The first step is to identify each of the options before you. Every project has multiple roads to completion. Your initial job is to recognize each of them so that you can add them to your decision tree and make the wises choices about which to take and when.

For example, Mary owns a fabric manufacturing plant in Los Angeles, California. Though they’ve only been in business for a few years, they’re growing rapidly and Mary needs to find a larger vendor to source materials from. She identifies two legitimate options: a U.S. based company that sits just a few hours away from Mary’s plant, and a vendor that operates overseas.

2. Forecast Potential Outcomes for Each Option

Now that each of your project options has been realized, it’s time to identify potential outcomes for each of them. This step isn’t full proof. You’ll need to make predictions and best-guesses and estimations — some of which could prove to be inaccurate. But that’s okay! The point of this exercise is to identify the option with the highest probability of success.

Returning to our previous example, Mary needs to decide whether to partner with a U.S. based vendor or the one situated overseas. Both options present their fair share of risks and rewards. So, in order to make the right choice, Mary begins crafting a decision tree. It looks like this:

Decision tree analysis example

Now, Mary needs to add potential outcomes for each choice so that she can accurately predict which materials vendor will best suit her growing company’s needs and budget. On the one hand, the U.S. based vendor will allow her to visit more often in person and check up on operations. But it’s also the more expensive option.

On the other hand, the overseas vendor is much cheaper and Mary could use the money saved to improve other areas of her business. But there are downsides too. Mary won’t be able to make as many trips to see this vendor, there will be a language barrier, and shipping times will be longer.

What’s the best option? Mary takes into account every bit of information she can get her hands on and estimates the probability of success for both paths. She then adds these details to her decision tree to help her make the best choice possible. Her tree now looks like this:

Decision tree analysis example

Mary can now move onto step three and analyze her decision tree to figure out which vendor is her best option.

3. Thoroughly Analyze Each Potential Result

At this point, you should have a full decision tree made. Congratulations! This is a big first step, but the hard work is just getting started. Now you need to analyze each potential result and assess which option will be the best fit for your unique project. If you’re working with monetary amounts, you can use the expected value (EV) formula .

Expected value is found by multiplying a potential outcome by the likelihood that it will occur. For example, if you anticipate that your project will earn your company $1,000 and it has a 50% chance of success. Your EV score is 500.

Let’s get back to Mary and her search for the right vendor. Based on her research, she predicts that working with a U.S. based vendor has an 80% chance of success and will produce a profit of $100,000. Using the formula described above, Mary gets an EV score of 80,000.

But she also needs to run the calculations for failure. So Mary multiplies $20,000 by 20% and ends up with 4,000. Finally, she just needs to subtract the failure score from the success score to get her total EV, which is 76,000 for the U.S. based vendor.

Mary goes through the same exact process for the overseas vendor and realizes that her EV, should she go that route, amounts to a score of 52,500. Based on EV alone, Mary’s best option is to work with the U.S. based vendor.

While EV scores aren’t everything, they will help you make a more qualified decision. We suggest you memorize this formula and use it in your decision tree analysis exercises.

4. Optimize Your Actions Accordingly

The final step is to optimize your actions. Once you know which option provides the greatest chance of success for your project, as well as the one that presents the greatest value, you can confidently make project decisions.

In Mary’s case, she decided to go with the U.S. based vendor. Not only did that vendor score a higher EV, but it also represents only $5,000 more dollars in losses should the relationship fail. Those two things plus the fact that Mary can visit the vendor regularly and they both speak the same language made it a very clear choice for her.

The Right Tools for Your Decision Tree Analysis Exercise

You now know how to create a decision tree! But before we let you go, we want to quickly go over the physical tools you can use to illustrate your different project options.