“Information
is a source of learning. But unless it is organized, processed, and available
to the right people in a format for decision making, it is a burden, not a
benefit”- William Pollard
We are faced with several decisions each day in our life – both personal and professional. There are times when making an important decision can seem daunting and even paralyze one into indecision. Of course, there are informal methods such as seeking the advice of a loved one, using the experience of another in similar situations, or even drawing out a pros and cons list. In the business scenario however, these informal methods might not prove effective or accurate. The good news is that there are several formalized decision-making methods that one can use to visualize a number of outcomes based on an action that one might choose – one such tool is the decision tree flowchart. We will delve into why a decision tree flowchart is a robust method of making informed and effective decisions.
To begin, a decision tree is a flowcharting style that allows the user to examine / investigate the several possible courses of action for a problem and the outcomes and effects of each course of action. A decision tree consists of a root node, leaf nodes, and branches, which enable this method to be highly useful while mapping a course of action after measuring risk versus returns. Flowcharts are a visual tool and as a decision tree this visualization is what makes it possible to include several possible actions and their outcomes, thereby alleviating the risks of unanticipated and unknown consequences.
The essence of a decision tree flowchart is that it allows the user to include minute details and put together a step by step plan as a path, which can be followed easily. It is a tool that supports the important process of decision making with the help of a graph that resembles a tree, and is the sole method of displaying an algorithm containing only conditional control statements.
Within this flowchart each node is representative of a trial or experiment on a part / point, each branch represents the possible outcomes of the trial, and the leaf node represents the decision made post putting together all the elements. Decision tree algorithms are considered as one of the best and commonly used learning methods, given their ability to produce predictive models that are highly stable, accurate and easy to interpret. They have the ability to map non-linear associations as well, making them more flexible and agile to solve any type of problem or perplexing situation. The algorithms of a decision tree flowchart are known as classification and regression trees or CART, and users may apply this type of flowchart to predict an outcome and or to explain a process.
Whether used to predict outcomes or describe processes, a decision tree flowchart is constructed to visualize every possible decision point and their outcomes. This type of flowchart is extremely useful and hence commonly used in the financial realm to monitor spending, manage portfolios, and even provide approvals for loans. In the retail industry, a decision tree flowchart can help to examine the practicability and sustainability of a new product, as also to accurately find new markets for an already existing successful product.
As mentioned, there are several companies that specialize in preparing high quality decision tree flowcharts, and there are readily available online templates as well. For a novice, here are some tips to creating a decision tree flowchart. Starting from left to right, the creator must draw a rectangle that would represent a node, and within this shape the creator must write the question / idea / criterion, which would lead onward to a decision. The next step is ‘adding branches’ – which would essentially be the possible alternatives, connected to the node using separate lines. As mentioned, left to right would be the flow. Leaf nodes form the bulk in a decision tree flowchart and are added at the end of a branch, and another question / idea / criterion would need to be written in each of the leaf nodes. The process is then repeated – that is more branches and leaf nodes are to be added until each question / criterion has ‘found’ an answer / outcome. Post preparing the ‘tree’, all those involved in the process / decision making must be able to verify the accuracy of the outcomes / decisions appearing at the end of the decision tree.
The popularity of decision tree flowcharts is due to the many benefits they afford to the users. The most basic advantage is the ease of understanding and interpreting, and in addition once the decision path is put down, reaching the point to success becomes a lot easier. Of course, calculations are involved when creating decision tree flowcharts, and using the software available to create these diagrams helps to draw better decision trees. Assigning value and possibilities to each branch and making an analysis of each option is a faster and more accurate process when using the decision tree software.
Another major advantage of a decision tree flowchart is the transparency it affords – unlike any other decision making tool. The flowchart lays out in a single document all the possible alternatives, with probable conclusions, enabling easy comparison by the user of all the options. Individual nodes add additional clarity, ensuring unambiguous decision making.
Using a decision tree flowchart, it is possible to designate / allot values to ideas and problems and their related decisions and outcomes. This ensures complete clarity for those involved in the process of making decisions, especially in the case of financial decisions where cost and benefits can be explicitly put down. A decision tree flowchart as a predictive model enables a detailed analysis of the effects of each decision such as knowing whether there is a conclusive ending, or whether other issues will develop, requiring the entire process to be repeated. The segregation of data is possible at a deeper level making it one of the top decision making tools.
Despite the intensity and specificity possible with decision tree flowcharts, the ease of use adds to its stature. The easy to understand format ensures that those viewing the graphical illustrations of problems and the many possibilities, will need no further explanations. It enables data classification without calculations, and is able to support several variables while ensuring complete clarity of the points that lead to prediction or categorization. The decisions and their explanations can easily be simulated using simple mathematical calculations. The fact that they are able to provide easy classification also makes them a highly flexible tool, not requiring detailed quantitative data to become meaningful.
Users find decision tree flowcharts extremely useful to resolve myriad business related issues, making it a highly versatile tool, especially when conditions may be uncertain / undefined. The algorithms of these flowcharts are easily integrated with other tools that manage the analysis of data. It is explicitly clear that businesses can gain immense value by using a decision tree flowchart for any business process – constructing the simpler ones manually or using software to put together more complex ones. They are the common sense tools to bring certainty to decisions of problems that may seem insurmountable or without a solution.
