Fast-And-Frugal Trees In A Nutshell

Fast-and-frugal trees are classification trees with sequentially ordered cues that aid in decision making. Fast-and-frugal trees (FFTs) are very simple illustrations of heuristic decision making. Each tree is comprised of sequentially ordered cues – or questions. In turn, each cue has two branches according to how the question can be answered:

  1. If the answer to the question is yes, then the branch leads to the next question in the sequence.
  2. If the answer to the question is no, then the branch leads to an exit point in the sequence.

At the final cue in the sequence, both branches lead to an exit point to ensure that a decision is made either way.

Why is the fast-and-frugal tree useful in business?

Fast-and-frugal trees are particularly useful when decisions need to be made quickly. They are well suited to binary classification problems – or problems with elements occupying two possible outcomes.

FFTs have been trialed in emergency room scenarios to help physicians triage patients. During a peer-reviewed study, a classification tree of just three cues enabled doctors to diagnose and then direct patients to either a regular nursing bed or the coronary care unit. 

Cues were based on historical acute heart disease data, allowing high-risk patients to be identified quickly and accurately. In fact, the process was so accurate that it was a better predictor of heart disease than the clinical judgment of the physicians themselves.

Constructing fast-and-frugal trees

There are several ways to construct fast-and-frugal trees.

In the emergency room example, physicians had historical data on factors that lead to acute heart disease. Chest pain was one such predisposition, leading to the creation of a cue entitled “Chest pain chief symptom?” with a yes or no answer.

Although FFTs were designed to be simple, they have nonetheless been adapted by using more complex methods. Primarily, this is seen in FFTs that are constructed using a zig-zag algorithm.

Here, the tree is created using positive and negative cue validity. This validity is defined as the proportion of cases with a positive/negative outcome in all cases with a positive/negative cue value. Typically, the first – or “root” – cue of a zig-zag analysis tree is the cue with the greatest positive (or negative) validity. This ensures that the most significant positive and negative decisions are made first. 

Typically, cue validities are determined by using counts and ratios. In more advanced scenarios, they must be estimated using elements of probability theory such as conditional independence. Zig-zag decision trees enhance the already strong fundamentals of FFTs. Given that the tree can be completed with pen and paper, the accuracy of a zig-zag tree is as high as using a logistic regression model.

Fast-and-frugal tree applications

As noted, FFTs are useful in any situation requiring fast and accurate decisions or risk assessment. 

Beyond medical applications, these trees have been used in the military to identify enemy threats and also in courtrooms to decide whether to bail or jail a defendant.

In recent times, fast-and-frugal trees have also shone a light on how customer management decisions are made. Retail banking sales managers who embodied fast, frugal, and adaptive decision making were able to better anticipate client needs.

Key takeaways:

  • Fast-and-frugal trees are heuristic models that are useful for tasks where binary decisions or classifications need to be made.
  • Fast-and-frugal trees are made of sequentially ordered cues, otherwise known as questions. Each cue has a binary answer, with one answer leading to a subsequent question and the other leading to an exit point.
  • Fast-and-frugal trees are simple and effective decision-making tools. However, the decision-making process is enhanced by using historical data and aspects of probability theory.

Connected Thinking Tools

First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.
The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.
The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.
Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.
Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.
Moonshot thinking is an approach to innovation, and it can be applied to business or any other discipline where you target at least 10X goals. That shifts the mindset, and it empowers a team of people to look for unconventional solutions, thus starting from first principles, by leveraging on fast-paced experimentation.
Tim Brown, Executive Chair of IDEO, defined design thinking as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Therefore, desirability, feasibility, and viability are balanced to solve critical problems.
The CATWOE analysis is a problem-solving strategy that asks businesses to look at an issue from six different perspectives. The CATWOE analysis is an in-depth and holistic approach to problem-solving because it enables businesses to consider all perspectives. This often forces management out of habitual ways of thinking that would otherwise hinder growth and profitability. Most importantly, the CATWOE analysis allows businesses to combine multiple perspectives into a single, unifying solution.

Read Next: BiasesDecision-MakingBounded Rationality.

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