The Purpose for Decision Trees
Decision trees are algorithms organizations use to assist them in making the best decision for their given objective (5). This approach is recommended for problems that have several solutions or contains several nested decisions (7). By using decision trees, organizations have a visual illustration of their decision's affects allowing them to picture what the costs and benefits will be for each possible outcome (7). Benefits associated with decision trees include that they "are simple to understand and interpret, have value even with little hard data, possible scenarios can be added [to them], worst, best and expected values can be determined for different scenarios, [they] use a white box model, and [they] can be combined with other decision techniques" (5).
How are Decision Trees Used?
Decision trees are methods used for solving complex operations research problems (5). They are used in several career fields, including business and healthcare, to help companies make better decisions (5). In business, decision trees are used to help a company make decisions in areas such as developing their business and investing in new projects (8). For example, a company may need to decide whether or not to hire a new employee. When doing this they need to consider the extra cost of the new hire and whether or not they will be successful (8). In healthcare, decision trees are used to determine what type of treatment to use for a patient and how the patient may respond to the treatment (9). For example, if a patient has cancer the doctors take in to consideration whether or not the patient wants treatment and if they do what type of treatment the patient is a candidate for. The patient will need different treatment depending on the type and stage of the cancer. If they choose treatment, doctors must consider how the patient will respond to the treatment and they must also look at the chances of the cancer reoccurring with each decision (9).