How to Make Decision Trees to Better Utilize Your Current Data
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There’s an old saying, you can’t see the forest for the leaves, which means you do not see the substance of something because you are looking at all the details. In the case of businesses, those details are the huge amounts of data that you collect and analyze on a daily basis. The forest is the procedures or processes that may produce different outcomes.
Given that old saying, it’s somewhat ironic that knowing how to make decision trees could be the ideal solution. Just, what are decision trees, and how can knowing how to make decision trees better utilize your data?
What Is a Decision Tree?
A decision tree is a diagram that can visually illustrate the different steps in any process or procedure. It can show the potential outcomes of each step and how differing paths can affect the final outcome to decide which path is the optimum. The format the diagram takes can depend on how complex the process is and could be anything from a flowchart to a series of bulleted lists.
Why is it called a tree, then? It’s given that name as it shows the user the different branches that may occur as a result of any decisions made. For example, if you’re working in data engineering, you could construct a decision tree to show what happens when you choose different methods of data collection or analysis.
In the realm of data-driven decision-making, businesses will often use decision trees alongside document collection software to provide a visual guide for their staff when involved in any task where decisions at different stages can lead to different outcomes.
Businesses will often use decision trees so that there is a visual guide for their staff when working on any process where decisions at different stages can lead to different outcomes. It allows those staff to evaluate the potential impact of their decisions on the overall process.
5 Stages in How To Make Decision Trees
1. Choose your method
The first thing to do is to decide what method you will use to make your decision tree. Your decision may be influenced by how complex the process is and how much data you will be utilizing. There are two main types of decision trees.
Flow chart. You may need to use specialist software to construct a decision tree in the form of a flow chart. The advantage of this method is that employees can follow a clearly marked path that leads to the best outcomes. They can be very useful in areas such as data quality management, where you need workers to check the quality of data and look for errors.
Bullet list. This format may be better suited to simpler processes as it can get unwieldy when you have long lists of points (and sub-bullets). However, that simplicity means that you don’t need special software and can use a program such as Word.
2. Identify prompts
If you want to know how to make decision trees, then you need to know the different prompts at each stage of the process. What triggers a step? And how do different triggers affect outcomes?
Every journey needs a starting point, and each branch of your decision tree is the same. Even a process as simple as sending a virtual fax has a starting point and, depending on the material being sent, different steps to ensure a positive outcome.
List each of your primary prompts so that you have those necessary starting points. You can then move on to constructing any branches that will be connected to those prompts or affected by them.
3. List your questions
In essence, you have a starting point, and you have an ideal destination (or even destinations). Your next step is to list the questions that enable movement through the process and any variables that may affect the questions and answers. By identifying all pertinent questions, you can ensure that the process is easier for anyone following the tree in the future.
For example, your boss has tasked you with identifying a Test IO alternative. You would look at the testing process itself and how you would approach it. Looking at the various steps and how questions would be answered can help identify the most viable alternative. While your end aim is to have all the answers, you need the questions first.
4. Work out the answers
What comes after questions? Answers, of course. For every question you’ve listed, you need an answer (or answers). Each question may have simple ‘yes or no’ answers, or it may have several answers that create new branches. The answers on your decision tree should lead to the next question/step in the process, and the answers to that lead to the next step and so on.
Keep your questions as simple as you can and, where possible, be able to answer any question with ‘yes or no’. A good decision tree is going to include every possible question and answer involved in any process so you can ensure the process itself is as efficient as possible.
5. Determine your outcomes
The important thing to remember is that business processes may have several possible outcomes. Even a process as simple as a product exchange or refund has two potential outcomes: you agree to the customer request, or you don’t. These outcomes can be conditional on some of the questions and answers that appear on your decision tree.
You also need to note that processes may be interlinked and that the successful completion of one process then may automatically lead to the next process in sequence. Being able to connect these processes – in sequence – is an integral part of knowing how to make decision trees work for you.
Processes can be incredibly complex or glaringly simple. Either way, a decision tree can help clarify the different steps in any process and can provide an easy-to-follow visual guide for any staff undertaking that process. Highlighting steps where potential issues may arise can also help prevent logjams and can streamline the entire process.
Each business will have its own processes that need to be followed. These processes can sometimes be repetitive and thus prone to human error. Decision trees can reduce the likelihood of human error and can help your business achieve the outcomes it wants.
Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.