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Improve Your Decision Making Skills With These 2 'Mental Models'

Intelligent decision making requires more than just introspection. Here's why, as well as how you can improve.

By Mark Travers, Ph.D. | October 08, 2024

Mental models are cognitive frameworks or representations that help individuals understand and interpret the world around them. They are the mental shortcuts or simplified versions of reality that people use to process information, make decisions and solve problems. Mental models influence how we perceive situations, predict outcomes and decide on courses of action.

Here are two essential mental models for making intelligent decisions and how to use them effectively.

1. Probabilistic Thinking

Probabilistic thinking is a mental model that involves making decisions based on the likelihood of various outcomes rather than certainty. Instead of thinking in absolute terms (e.g., something will or will not happen), probabilistic thinking assesses the probability or chance of different scenarios occurring. It involves:

Assessing likelihoods. Estimating the probability of various outcomes based on available data or past experiences.
Considering multiple scenarios. Evaluating several possible futures rather than focusing on a single expected result.
Weighing risks and benefits. Making decisions by comparing the potential gains and losses of different actions, accounting for their likelihood.
Avoiding certainty bias. Recognizing that few things are guaranteed and embracing uncertainty as a part of decision-making.

For instance, a manager estimates a 70% chance of completing a challenging project on time but acknowledges a 30% risk of delays due to potential issues. By evaluating these probabilities, the manager chooses to proceed with the project while implementing contingency plans, such as reallocating resources or adjusting timelines, to mitigate risks and increase the likelihood of success.

Even after years of studying probability, individuals struggle to apply probabilistic thinking in real-life situations, suggests a 2023 study published in the International Journal of Studies in Education and Science. It reveals that people often struggle with correctly applying probabilistic reasoning in uncertain situations, leading to errors such as:

Overconfidence. Participants often relied on their previous experiences without critically analyzing all possibilities. They assumed that they had equal chances of winning or making the right choice without considering the actual probabilities.
Habitual decision-making. Many decisions were made based on habit or past experiences rather than a rational evaluation of the options available. This led them to make choices without assessing the consequences of each possibility.
Equiprobability fallacy. Participants exhibited a common misconception that all random events or outcomes have an equal probability of occurring, even when this was not the case.
Difficulty in analyzing probabilities. Participants struggled to identify and evaluate all possible outcomes in uncertain situations, which affected their ability to make informed decisions.

The study suggests a cross-examination approach that involves using targeted, critical questions to assess and challenge individuals' reasoning and decision-making processes.It requires participants to explain and justify their choices in uncertain situations, often prompting them to reconsider their initial assumptions and explore all possible outcomes.

2. Second-Order Thinking

Second-order thinking is a mental model that involves looking beyond the immediate effects of a decision to consider its longer-term and indirect consequences. Instead of just asking, "what will happen if I do this?" it also asks, "and then what?"

This approach helps anticipate potential ripple effects, make more intelligent, strategic decisions that others might overlook and avoid unintended consequences. It involves:

Assessing long-term impacts and avoiding short-term traps. Assessing how a decision will affect future outcomes and scenarios over time and focusing on choosing options that may not provide immediate rewards but may lead to better long-term results.
Recognizing chain reactions. Understanding that one action can set off a chain of interconnected events or outcomes.
System interactions. Considering how various elements within a system will respond and interact with each other due to a decision.

When it comes to decision-making, choose options that not only have immediate benefits (first-order effects) but also continue to provide positive outcomes when you consider the long-term and indirect consequences (second-order and third-order effects).

In other words, a good decision remains beneficial even when you think through its future impacts and ripple effects over time. For instance, hiring unsuitable employees may solve immediate staffing needs (first-order effect), but it can lead to significant long-term issues.

Poor hires often result in lower productivity, reduced team morale and increased turnover, which disrupts business operations (second-order effect). Over time, this can damage the company's reputation, making it harder to attract top talent and increasing hiring and training costs (third-order effect). Ultimately, these compounded issues can hinder the company's growth and profitability in the long term.

By integrating these mental models into your daily decision-making, you'll not only make more intelligent choices but also develop a deeper understanding of the complexities behind each decision and what it entails.

Discover whether you rely more on logic or intuition when making big decisions. Take the science-backed Intuitive Decision Style Scale to find out.

A similar version of this article can also be found on Forbes.com, here.