The GOOD, The BAD & The UGLY of Using Decision Trees - DeciZone
"If a picture is worth a thousand words, then a flowchart is worth a thousand sentences." - Flowchartenator
Should you be using a decision tree instead? Here are the advantages, disadvantages and considerations to help you decide.
I used to play a simple game with my daughter when she was in elementary school. She had to pick an animal and I had to guess it by asking her a series of questions like ‘Can it climb on a tree?’ or ‘does it run fast?’ and she would answer a simple ‘yes’ or ‘no’. You scored higher if you answer it correctly in the least number of questions. Its a fun educational game and it can teach even adults a thing or two about thinking out of the box. Try it at your own risk.
That simple game closely resembles how we humans often think about the process of eliminating alternative outcomes and deciding on the final conclusion when faced with a major decision. Only difference is that the alternatives and the questions are not that simple when you grow up. That game practically represents what we call decision tree logical structures. The whole game can be represented in the form of a really big decision tree with a large number of leaf nodes, but the most amazing thing is that you can reach the final leaf node of that game by answering just a few questions. Amazing, isn’t it?
"Always make new mistakes.” - Esther Dyson
Much has been said about decision trees and their close cousins, flowcharts. Decision trees have become so ubiquitous that we sometimes don’t even realize that we are traversing in a decision tree at that moment, i.e. find your own adventure games, hierarchical menu systems, product selection interfaces on many websites, phone support IVR systems, self help troubleshooters, and many more. When the utility of the decision tree perfectly matches with the requirement of a specific use case, the final experience is so amazing that the user completely forgets that they are experiencing a basic decision tree. Below we take a detailed look at what the advantages and disadvantages are in using decision trees for your specific use cases.
The GOOD (advantages of using decision trees)
Comes naturally: A big advantage of using decision trees is that it closely resembles how people think about confusing choices. So using a product or service that employs a decision tree might feel natural when implemented carefully.
Faster: It is often said that in business a quick decision is better than a good decision taken late. A decision tree with the decision making framework can enable your people to make quick decisions that are informed by your guidance and best practices while certainly avoiding expensive mistakes. Navigable decision trees make it super easy and accessible from any mobile device.
Understand: The whole process of creating a decision tree gives you a better understanding of that particular topic because you might feel the need to clearly articulate and logically organize all the alternatives.
"Simplicity is the glory of expression." - Walt Whitman
Optimize: You will realize which aspect of the main topic you are least familiar with. Better yet, you might just uncover an opportunity to better optimize the outcomes.
Comprehensive: A decision tree keeps the author more honest because every decision tree branch represents an exclusive logical space where they are compelled to propose their insightful recommendation. Compare that with writing an article about the same topic where it might be relatively easy to emphasize on the easy well known options while the less known options may just get a passing mention.
Documentation: Decision trees serve as a great way to document most processes and algorithms.
Expectations: The goal of a decision tree may be very clearly stated for you (i.e. How to qualify a new customer?). Depending on your experience about that topic, you might need to set the right expectations for the viewer from the beginning. Often you may not have all the details on the topic, but a clearly set expectations from the beginning might earn some appreciation from the viewer.
Flexible: You will think of many new criteria/questions and will be tempted to include all of them in the same decision tree. A better approach is to write the ideas down on post-it notes, arrange them on the wall and then find the most appropriate logical position in the decision tree for introducing that new question. This way you can also move the post-it notes around till you get the right logical structure. You have enough flexibility to be able to shape a better user experience in your decision tree.
Strategic: Creating a decision tree is not just creating a diagram - it is strategic thinking at its best for a given goal. Imagine being able to grow the same strategically thought out decision tree over time to address more and more scenarios. It can potentially become your competitive strength and a unique differentiator.
Resolution: It feels good when you get to present your recommendation or conclusion at the end of a branch. In fact, you have taken someone through a conversational interview and based on your best judgement and knowledge, delivered a 'here is what I would have done if I were you' style recommendation.
Genuine: Its difficult to bluff in a decision tree without smelling foul. Most decision trees break down a big decision into many simple mini decisions. These mini-decisions are simple decisions that viewers are most familiar with and can easily decide on - and so its not easy to just blow smoke.
Details: If done properly, the number of recommendations/branches of your decision tree directly correlates with your level of understanding of that topic. More detailed and insightful thought process almost always gets rewarded with compliance.
Simple: It is effortless for your audience to answer simple yes/no questions and that also happens to be the most convenient structure for designing your decision trees. When given too many choices, you are adding to the cognitive load your audience has to deal with.
Automatic: You can save yourself and your audience lots of time. You just create your decision tree once and then a million people can get to your customized and insightful recommendations in less than 30 seconds in a fairly automated manner.
Improve: You can keep updating your thought process by adding more details, criteria and scenarios to your decision trees as you get more feedback from your audience.
Effective: You will realize that you spend less time in the repeatedly answering the same questions and are spending more time in researching, analyzing and strategy activities, just so that your audience can have it easy. With less repeated work, you experience better job and become more effective at your real work.
Satisfaction: Your audience will love it when your decision tree takes them through a insightful thought process and delivers well reasoned recommendations in a convincing manner.
The BAD (disadvantages of using decision trees)
Changes: When trying to represent a complicated topic with a decision tree, you might find that it becomes large and difficult to maintain. You should look for tools that allow you to version control your decision trees.
Subjectivity: A decision tree is best used in situations where the decision criteria / choices are fairly constant and the thought process is generally applicable in most cases. In cases where the choices depend on emotions or other subjective factors, creating a decision tree might be a challenge. And then there may be use cases where creating a decision tree just does not make sense.
“Life is too complicated not to be orderly.” – Martha Stewart
Evolve: Your decision tree may evolve in its logic over time as you get more familiar with the topic and as you get more feedback from its audience. Unless you have tools designed to facilitate continuous improvement, your decision tree may lose its effectiveness over time.
Repeat: Often you find that the same logical pattern repeats in multiple branches of the same decision tree. This might mean that you are repeating the same logic at multiple places in your decision tree. In this situation, if you need to change the repeating logic, it can be a nightmare to make sure you made that change in all the places that pattern repeats. You need tools that allow you to clone your logic and easily manage cloned elements.
Complexity: Any decision tree created with detailed thought process might look complicated when you see it in a diagram. Most people do not like complicated things and have a strong preference for simpler alternatives. You might be better off using decision treeing platforms that have a clean and simple interface with an awesome user experience.
Familiarity: At times people use obscure elements/features inside their decision trees. This creates a problem for the audience that is not familiar with those elements/features. You need a standardized approach at creating and accessing decision trees.
The UGLY (problems with conventional approach)
Usability: A good decision tree might take a lot of work to create. Last thing you want is that it becomes this big diagram poster on a wall, frozen in time. Instead you want a solution that makes it easy for everyone to collaborate, share feedback and continuously improve the decision tree over time.
Mobile: Conventional diagramming tools allow you to create a big diagram and then share that diagram document with others. But most people are not comfortable following complex diagrams. On the contrary, a well thought out decision tree can almost behave like a dynamic application that can guide its audience to the most appropriate recommendation. Look for solutions that allow you to easily create a simple decision tree and then allow your audience to access that decision tree from any mobile browser, any time and from anywhere in the world.
“It is not enough to be busy, so are the ants. The question is: What are we busy about?” – Henry David Thoreau
Everywhere: Most conventional solutions need a laptop/desktop size screen to create or modify decision trees. But today we do everything on our mobile phones and so it naturally makes sense in looking for solutions that allow you to create/edit decision trees on any mobile browser.
Coding: Decision trees form the basic foundation for building the ever so popular chatbots today. But to create a chatbot today you almost always need a developer with advanced coding skills which makes it a big challenge. That is why you should look for a solution that allows anyone without coding skills to just create a decision tree which then becomes a dynamic conversational application serving their audience using the right tone and language. The fact that no coding skills are required in creating or modifying these decision trees means that it is easy for anyone to create and maintain these decision trees for the long term.
Features: Conventional tools to create decision trees are very limited in scope when it comes to the interactive and multimedia features. You are so much better of with a solution that allows you to attach files, show images, upload files, attach links and share feedback specific to each and every node in your decision tree.
Measure: Most decision tree solutions today cannot give you meaningful metrics and reports about how your decision tree is being used. Look for a solution that allows you to download raw data between the start and end dates of your choice so that you can analyze and find opportunities for improvement.
Integrate: Today most tools need to talk to other tools in the ecosystem. Your decision tree solution better be capable to integrate with popular CRM, Ticketing, ERP and other platforms.
The good news is that by leveraging a advanced platforms like DeciZone.com, you can streamline most of your operations and best practices using simple decision trees. Even if you do not know coding or programming, you can create a interactive decision tree based on your business rules and guidelines. You can share your decision tree and allow anyone to get customized recommendations from your decision tree in just a few clicks on any size browser.
Frequently Asked Questions (FAQ)
Frequent Mistakes
The information in this article may be devired from the following sources and may have been enhanced using artificial as well as real intelligence technologies: