A decision tree mimics the mental process behind the game of 20 Questions: Are you famous? Yes. Are you Marie of Romania? No. Are you an athlete? No.
The simplest decision tree in consumer lending, for instance, might start with the age of the applicant lender and progress through a series of “if, then” decision points to determine their creditworthiness:
- If the borrower is younger than 18, then the decision to lend is “no.”
- If the borrower is between 18 and 64, has no children and has an income greater than $20,000, then the decision is “yes.” On the other hand, if a person is in that age range, has children and earns less than $30,000, then the decision is “no.”
- If the borrower is older than 65 and has an income greater than $40,000, then the decision is “yes.”
However, consumer lending is much more complicated than assessing applicants’ age, family status and income. Other factors include an applicant’s credit history, outstanding debt, repayment history and the number of loan accounts and whether they are revolving or term. Each element creates its own branch of the decision tree, all interrelated.
The decision tree gets extremely complicated when decision-makers consider all the “if, then” scenarios flowing from those additional parameters. Managing a decision tree becomes impossible for humans to keep up with as increasingly complex datasets pour in and change the conditionals. This is where information science specialists use resources like machine learning.
What Role Does Machine Learning Play in the Development of Effective Learning Trees?
Machine learning (ML) software uses mathematical algorithms to analyze data in real-time without human intervention. As new data arrives, a smart machine mines existing data and uses the new information to recalculate its algorithms and identify changing trends and patterns. As a result, decision trees powered by ML algorithms can provide business leaders with statistically accurate predictive models that enable them to make decisions quickly and more accurately.
“When it comes to making decisions about a business, data is always going to be vital, but with machine learning, we have so many ways in which we can use them and find out more and more about customers,” according to Comidor, a digital-transformation consultant.
How Do Businesses Use Decision Trees?
Graphic visualizations of ML-powered decision trees — flowcharts and diagrams — are easy-to-digest models that support data-driven decision-making by enabling leaders to evaluate, interpret and explore alternatives.
Businesses typically use decision trees to help them manage projects and plan for complex changes and how they impact other operations, including:
- Reducing the workforce
- Farming out critical functions
- Entering new markets
- Pricing products and services
- Relocating
- Selling the business
- Adding or removing product offerings
- Investing in research and development
“A decision tree is a critical part of strategic planning because it allows decisionmakers to analyze the effects of a significant change throughout different areas of the business,” according to CFO Selections, a financial and accounting services provider.
How Do Business Professionals Acquire Advanced Decision-Making Expertise?
A Master of Science (M.S.) in Information Science, such as the online program through Texas A&M International University, equips graduates with the knowledge and insights to manage complex networks, databases, advanced data analytics, data mining and project management. Courses include:
- Advanced Programming
- Networks and Distributed Systems
- Data Mining and Business Analytics
Candidates for career advancement and job seekers will gain significant advances over their competition by mastering advanced manipulation of data and programming of sophisticated, data-intensive applications and file structures that connect business leaders with the technologies that enrich their companies. Understanding the benefits of decision trees allows business professionals to assess applicants who can fulfill their information science needs.
Learn more about Texas A&M International University’s online M.S. in Information Science program.
