Quantitative Decision Making Tools: Decision Trees, Payback Analysis & Simulations

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Successful managers use decision-making tools to analyze a problem and try to determine the best solution for that problem. Here, we will discuss three main decision-making tools and help you to understand their function and implementation.

Decision Making Tools

Good managers do not simply just make decisions. Instead, they use tools to determine the best course of action, making it possible for the manager to make an informed decision. That does not mean that good managers always make the right decisions, but they certainly are making decisions that are more informed than they would be based purely on guesswork.

There are many different tools managers use to make decisions, but the ones that we see the most are the decision tree, payback analysis and simulation. While there are more, these are the three we see the most, and it's important to understand them and know how to use them before you start making decisions.

The Decision Tree

The first tool we will look at is the decision tree. This tool has us write down an issue or problem, and then, as we think through the problem, we draw solutions or steps that branch out from the original issue. You start your decision tree by taking a piece of paper and drawing a small square to represent the decision you need to make. It could look something like this:

'Should we decide to continue to produce dress shoes only, or should we look at making sneakers as well?'

This first block represents the issue that requires you to make a decision. From there, just like the name 'decision tree' implies, branches start to sprout out with your thoughts for different solutions or directions for this issue.

You can make any number of branches, and there is no set pattern to the decision tree - it is defined more by its functionality than its form. Using a decision tree, you can capture your thoughts, review them and, if needed, add more branches, hopefully continuing on until you find your answer. Each decision you make leads you to another decision (or would/could choice) and that choice leads you to another.

Payback Analysis

I'm happy to say that payback analysis is much easier and much more finite than the decision tree. This tool will help you analyze financial investments. When we use payback analysis, we look at an investment and the anticipated savings or cost increase that will result from that investment. Then, we use a calculation that gives us a time frame for us to make back the money spent in the initial investment.

For example, let's say we are going to invest in energy-efficient lighting. We know that the initial investment would be $15,000, but we also know that our energy cost savings would be $5,000 a year. We can simply use some basic math to understand how long it would take for us to earn back our initial investment of $15,000. Did he say math? Nooo! Don't worry though - it's pretty simple.

We can divide $15,000 (our investment) by the amount we would save each year ($5,000), and from that basic calculation, we can see that it would take 3 years to make back our investment. If that time frame is something that is good for you, then you decide to make the investment. If not, see if you can come up with some other investment or savings to change the calculation. Either way, you will have used the payback analysis tool to make a well-informed decision.

Simulation

I wish I could say simulation was as easy, but it is not. When we think of simulation, we think of video games or flight simulators, and fortunately for us, that is exactly how this tool is used for decision making. There are many software programs out there to simulate what could happen in a given situation, and those software programs are typically designed specifically for specific industries.

For example, if a nuclear power plant wanted to simulate what would happen in the event of an emergency, they obviously would not create the emergency in the plant to see what happens. And, as you could guess, they would also not use tools like a decision tree because an emergency is of a much more important scale than, say, a business struggling to get its new product line off the ground. The manager of this nuclear power plant would want to work through the problem in a simulated environment to see what would happen and how they should react.

This is where the software comes into play. They can simulate an emergency and see how they react to it to help them make decisions in the event of an actual emergency. An easier way to look at this is to think of pilots in a flight simulator, simulating that both your engines have gone out. By doing this in a simulator, the pilot can see how to handle the problem without actually having a plane have its engines go out. This not only allows the pilot to experience the situation and make decisions accordingly, but it also helps the airline to make decisions about training pilots and other employees to handle emergencies.

Lesson Summary

In the end, no matter what tool we use to make a decision, we want to be somewhat like a Boy Scout. We want to be as prepared as possible by using decision-making tools to reach the best possible conclusion before you have to make a final decision. What tool you use depends on the situation, and it really is your choice. Does the situation require a decision tree so you can think through different possible aspects of the situation? Are you looking at some type of monetary investment and want to see what your payback will be? Or do you need to simulate an event or emergency to see how your team will handle it?

Just remember, using a tool has a much better outcome than not using one. For example, you would not drive a nail with your head (well, you could, but it would really hurt) - instead you use a tool (a hammer) to do a better job.

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