What Is A Heuristic And Why Heuristics Matter In Business

As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.

Aspect	Explanation
Definition	A heuristic is a mental shortcut or a simplified strategy that individuals use to make judgments, decisions, or solve problems efficiently. It’s a rule or guideline that simplifies complex tasks.
Purpose	The primary purpose of heuristics is to speed up decision-making and problem-solving processes by reducing the cognitive load. They provide quick and practical solutions in situations where in-depth analysis may be time-consuming or impractical.
Types of Heuristics	There are several types of heuristics commonly used: – Availability Heuristic: People judge the likelihood of events based on their availability in memory. If something is more easily recalled, it’s perceived as more common or likely. – Representativeness Heuristic: This involves categorizing something based on how similar it is to a prototype. If an object or event closely resembles a known prototype, it’s judged as more representative. – Anchoring and Adjustment Heuristic: People tend to rely on initial information (the anchor) and adjust from there when making judgments. – Satisficing Heuristic: Rather than seeking the best solution, individuals settle for a satisfactory one. – Confirmation Bias: People seek information that confirms their existing beliefs or decisions.
Pros	Heuristics offer several advantages: – Speed: They allow for quick decision-making and problem-solving. – Cognitive Efficiency: Heuristics reduce mental effort and simplify complex tasks. – Adaptability: They can be applied in various situations. – Simplicity: Heuristics are easy to understand and apply.
Cons	Despite their benefits, heuristics have limitations: – Biases: They can lead to cognitive biases, causing errors in judgment. – Inaccuracy: Heuristics may not always yield accurate or optimal solutions. – Oversimplification: They can oversimplify complex problems, leading to suboptimal decisions.
Common Examples	Everyday examples of heuristics include: – Choosing the shortest line at the grocery store checkout. – Making snap judgments based on first impressions. – Relying on past experience to make decisions. – Using stereotypes to assess people or situations.
In Decision-Making	Heuristics play a significant role in decision-making processes. They help individuals make choices in situations with limited time and information. However, they can also lead to biases, such as confirmation bias or overconfidence.
In Problem-Solving	Heuristics simplify complex problem-solving tasks by breaking them down into manageable steps or focusing on the most relevant information. While this speeds up the process, it may result in suboptimal solutions.
Bounded Rationality	Heuristics are closely linked to bounded rationality, a concept that suggests that individuals make decisions within the limits of their knowledge, cognitive resources, and time. Heuristics are used to cope with these limitations.
Criticisms	Critics argue that heuristics can lead to systematic errors and irrational judgments, especially when individuals rely on them excessively. They may not always lead to the best or most rational decisions.
Improvement	To mitigate the potential drawbacks of heuristics, individuals can: – Be aware of cognitive biases associated with heuristics. – Seek additional information and consider multiple perspectives. – Use heuristics as a starting point and then engage in more thorough analysis when necessary.
In Artificial Intelligence	Heuristics are also used in artificial intelligence and computer science to create algorithms and search strategies that solve problems more efficiently. They help computers make decisions and navigate complex tasks.

What is a Heuristic? Beyond biases and the prevailing narrowed vision of the mind

In a 1996 paper entitled “Reasoning the Fast and Frugal Way: Models of Bounded Rationality” psychologists Gerd Gigerenzer and Daniel G. Goldstein highlighted:

Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might.

This is a very important concept to start with. Where modern psychologists and theorists of mind manufacture experiments in the lab, those experiments are tied to specific scenarios, that are hardly replicable in the real world.

Why is that? It all starts with a narrow theory of mind.

A narrow definition of rationality

Experiments are manufactured and often based on assumptions around how our minds work. For instance, if a psychologist will label rationality as the ability to optimize during a decision-making process (just like a machine would do) this requires the mind to gather all the possible information to come to a logical decision.

However, in the real world, decisions are made with incomplete information, a high degree of uncertainty and little to no understanding of what’s coming next. Therefore, when the psychologist mutters about the inability of the human brain to understand statistics or logic. In the real world, that means survival.

If surviving means losing some efficiency or avoiding optimization to prevent massive failure, our mind is working as it should.

Risk vs. Uncertainty

Another component that the conventional or prevailing school of thought is the lack of understanding of the domain in which the human mind is operating. That’s a key point to understand the difference between risk and uncertainty.

Risk is computable

Risk is a concept that analysts love. Why? It’s something that can be modeled. Thus, circumscribed to scenarios that have definite rules, like games. You often see in business books how game theory helped businessmen to be successful.

But that is a story crafted in hindsight. Game theory or your skills as a chess player might help you (in impressing others) in normal circumstances (assuming those exist) but they won’t help you much in the real world. Unless you have an alternative toolbox made of heuristics.

Uncertainty is not computable

When financial analysts evaluate risks they fall into the trap of thinking that we can understand the real world by modeling it. The modern approaches to entrepreneurship try to bring this same logic to the business world, with nefast consequences.

When there is a high variability of outcomes, it’s impossible to model the risk. If at all you need a simple set of rules of thumb to avoid the worst-case scenario because if that materializes that will be no risk-model that will help with that.

Indeed the consequences of an uncertain scenario might be too bad for you to actually even see its outcome because survival is at stake.

Unmodeling the real world

When psychological experiments are made in the lab, often times the psychologist starts with a preconceived idea of the human mind and she works her way back to prove it with an experiment.

When that happens experiments are “manufactured” (in many cases unconsciously) to produce a certain result (in short, biases are more a domain applicable to psychologists than of laypeople dealing with real-world uncertainty).

This has come up recently with what is called a Replication Crisis, which as highlighted on Wikipedia:

The replication crisis (or replicability crisis or reproducibility crisis) is, as of 2019, an ongoing methodological crisis in which it has been found that many scientific studies are difficult or impossible to replicate or reproduce. The replication crisis affects the social sciences and medicine most severely.

Part of this trend is in the use of statistical tools that are not proper for real-world analyses, and the fact that research sometimes turns into an attention-driven activity. As pointed out by Noah Smith in Bloombergs’ “Why ‘Statistical Significance’ Is Often Insignificant:”

In psychology, in medicine, and in some fields of economics, large and systematic searches are discovering that many findings in the literature are spurious. John Ioannidis, professor of medicine and health research at Stanford University, goes so far as to say that “most published research findings are false,” including those in economics. The tendency research journals have of publishing anything with p-values lower than 5 percent — the arbitrary value referred to as “statistical significance” — is widely suspected as a culprit.

To be sure, this is not to say those experiments aren’t valid. Worse than that, in some instances, they carry from the beginning assumptions about the psyche of the subjects that are biased themselves.

In short, the biases that we all talk about nowadays, especially in the business world, in reality, might easily be explained with a theory of mind that goes beyond the conventional definition of rationality.

This definition starts by thinking of our mind as an easily tricked machine, that due to its survival mechanisms isn’t well-adapted anymore to modern times. Thus, it can easily fall prey to dozens if not hundreds of biases that affect our daily lives.

That is we see anywhere today in business publications massive lists of cognitive biases that make us more “aware.”

Heuristics: dirt and quick? Not really!

As highlighted in “Heuristic Decision Making:”

The goal of making judgments more accurately by ignoring information is new. It goes beyond the classical assumption that a heuristic trades off some accuracy for less effort.

The main perspective for which heuristics have been studied and communicated to a mass business audience is through the fact that by definition a heuristic is quick and dirty. In short, our error-prone mind generates biases because we use heuristics that made us sacrifice efficiency for speed in the face of a sort la lazy mechanism of the mind.

According to this view, the mind might ignore important information in an efficiency-driven way, almost like it was optimizing for computing power.

In reality, the mind might have learned that ignoring useless information is a more effective survival mechanism in that specific context. Therefore, focusing on one key data point is way more reliable than taking more information. This completely changes the paradigm.

Where a lazy-driven mind avoids too much information because it’s not computably able to process it (thus sacrificing efficiency for speed almost like it was a computer). In a new paradigm, where heuristics and rules of thumbs become central as a necessary filtering mechanism of the mind that learns ho to ignore useless and irrelevant information.

In short, what matters is the outcome of the action, not the process neither the motivation that drives the process.

Conflict of interests, marketing, and manipulation

New media have enabled companies to communicate at large scale. When this communication is done right we can call it marketing. When that’s done wrong we can call it a conflict of interest or at worst manipulation.

Thus, many of what we call biases are also the consequence of the way the message gets framed to us. In short, it’s like playing a game where one player has to trick the other. As the other player learns the tricks of the first player, new strategies need to be found.

One there is a gap between the trickster and the tricked a bias might emerge as a better ability of the trickster.

Blind faith in technology

While planning a trip back to the city I live in, I was thinking to postpone the trip due to bad weather. While consulting my GPS which optimizes for shorter routes (not certainly for the beauty of the landscape or chances of survival) I risked to get to the end of the trip underwater.

In short, the GPS was giving me the time to destination with a bit of delay but without necessarily mentioning that I was getting there by risking to be flooded!

This blind faith in technology isn’t due to our inability to deal with it. Rather with the way these technologies are framed. When technology is built to optimize, and when it is marketed so that you believe that optimization is what matters in any context (optimization works in narrow ordinary situations) you end up relying too much on it.

The central problem with a two-system thinking model

Theories proposed by psychologists like Kahneman and Tversky have become central in the business world. The book Thinking, Fast And Slow has become a business bible and indeed that is a great read.

Yet the assumptions underlying these theories stand on a hypothetical optimization process humans should follow when making a decision. As highlighted in the paper “Heuristic Decision Making:”

As Kahneman (2003) explained in his Nobel Memorial Lecture: “Our research attempted to obtain a map of bounded rationality, by exploring the systematic biases that separate the beliefs that people have and the choices they make from the optimal beliefs and choices assumed in rational-agent models”

This view might start with a wrong definition and interpretation of bounded rationality formulated by Simon. Bounded rationality is not about systematic biases, it’s about decision-making in the real world, which is unpredictable.

Fast, frugal, yet accurate

Another key concept to internalize to deeply understand this alternative view of bounded rationality is the concept of ecological rationality. Ecological rationality looks for strategies that are better suited for a specific environment and context.

The key point here is that there is no best strategy, or optimization strategy because that would not be possible in a large world made of uncertainty.

Therefore, the rules of thumb we might be able to use for each circumstance will help us take advantage of the structure of the environment we operate within.

Thus in this sort of decision-making process, it is like we do create a small world but highly adapted to context and circumstance, which is the opposite of what classic theories of rationality do, assuming that our mind works in a vacuum, or in a sort of free-context reality.

The two sides of Bounded rationality

Based on what we have said so far, let’s look again at the concept of bounded rationality. According to the definition given by his father, Simon, bounded rationality has two main sides:

ecological
and cognitive

It’s ecological because “the mind is adapted for real-world environments.” Therefore, on the one side, the mind makes decisions based on the structure of the environment. And on the other side, there is the computational capability of the decision-maker (cognitive side).

As highlighted by Gerd Gigerenzer and Wolfgang Gaissmaier in “Heuristic Decision Making modern psychologists have focused their attention on the latter (the cognitive side).

More precisely, the focus on the cognitive side has produced the misunderstanding that as the human mind has limited ability to process information, it produces a set of irreparable biases.

Part of this misunderstanding might be given by the fact that those presumably simple heuristics that the mind uses to solve real-world problems are not sophisticated enough to look interesting to the norms of classical rationality.

The importance of Ecological Rationality

Once you understand the other side of rationality, not the cognitive, but the ecological, it changes everything.

In an ecological rationality sense, less-is-more becomes a powerful heuristic to rely on in many of the real-world scenarios.

Less-is-more is about ignoring cues that not only make us worse decision-makers. It also means that after a certain point more information leads to worse decisions, even when the costs of acquiring that information are zero.

Redefining biases

In the conventional view, a bias is a cognitive error the mind makes, which is due to our lack of understanding of the real world driven by classic rationality. In the alternative way to look at bounded rationality in a decision-making process, it needs to balance out bias and flexibility to produce overall an inference which is more effective than a system that has no biases at all!

In that scenario, less information, ignoring a big chunk of noisy information and make “biased decisions” might lead to better decision-making.

Building an adaptive toolbox for entrepreneurs

Once you understand all the principles highlighted above, you start tinkering with simple algorithms, that we can call heuristics, extremely useful for the businessman who doesn’t want to fall trap of complex thinking for the sake of it.

The FourWeekMBA analysis and study into this adaptive toolbox has just started, and we’ll be looking more and more into a set of simple heuristics to use in different contexts, by starting from when it makes sense to use them in the first place.

There are a few contexts in the business world where gathering more information, data and complex models can indeed help build a successful company (like at an operational level). But there are many other places (strategy and vision) where those complex systems not only do not work but are harmful.

For the sake of having a better toolbox for directing your business in the right direction, we’ll continue our investigation!

Case Studies

Recognition Heuristic: This is a simple rule: If one of two objects is recognized and the other is not, then infer that the recognized object has the higher value with respect to the criterion. For example, if someone has to pick a city to visit and recognizes one city but not the other, they might choose the recognized city assuming it’s more popular or significant.
Take-the-Best Heuristic: When making a decision, this heuristic prompts individuals to select the option that scores highest on the most important criterion, ignoring all others. For instance, when choosing a car, if fuel efficiency is the most important criterion, one might select the car with the best fuel efficiency without considering other factors like price or safety.
Satisficing: This term, coined by Herbert Simon, means searching through available options until an acceptability threshold is met. It’s the middle ground between settling for the first acceptable option and holding out for the best possible option. For instance, when hungry, someone might choose a restaurant that’s “good enough” rather than spending hours looking for the best one.
Anchoring and Adjustment: When making decisions, we often start from an initial value (the anchor) and then adjust away from that anchor. For example, if you’re negotiating a salary and the employer offers $50,000, that number becomes the anchor. You might counter with $55,000, adjusting from the initial anchor, rather than asking for, say, $70,000.
Framing Effect: Decisions can be influenced by how choices are presented. For example, meat labeled “75% lean” is more likely to be chosen than meat labeled “25% fat,” even though they mean the same thing.
Endowment Effect: People tend to overvalue things simply because they own them. For instance, someone trying to sell a used car might price it higher than its market value just because it’s theirs.
Default Effect: People are more likely to choose a default option when one is provided. This is why many software installations come with certain options pre-selected, or why organ donation rates are higher in countries with opt-out systems.
Paralysis by Analysis: Having too much information can lead to decision paralysis, where the individual becomes overwhelmed and struggles to make a choice. This is where the “less-is-more” heuristic can come in handy, prompting one to make a decision based on fewer, more critical factors.
Escalation of Commitment: Sometimes, people continue a behavior or endeavor as a result of previously invested resources (time, money, or effort), even if it’s not the best decision. Recognizing this bias can help individuals avoid throwing good money after bad.
Authority Heuristic: We often trust the judgment of experts or authority figures, even if we haven’t critically evaluated their advice. For instance, someone might buy a product because a celebrity endorsed it.
Consistency Heuristic: People prefer to be consistent in their attitudes and choices. If someone publicly commits to a goal (like losing weight), they’re more likely to stick to it to remain consistent with their commitment.
Contrast Effect: Our perception of a decision can be altered based on a comparison. For example, if you see a shirt for $100 and then see a similar one for $50, the second one seems cheap by contrast.
Mood and Decision Making: Our emotional state can influence our decisions. When happy, people may be more prone to take risks. Recognizing this can help in ensuring decisions aren’t purely emotion-driven.

Key Highlights:

Heuristics are fast and accurate decision-making strategies used in the real world to cope with uncertainty and limited time and knowledge.
The prevailing narrow theory of mind in traditional psychological experiments leads to a narrow definition of rationality, assuming unlimited time, knowledge, and computational capabilities.
In the real world, decisions are made with incomplete information, high uncertainty, and little understanding of future outcomes, which is crucial for survival.
The conventional view distinguishes risk (computable) from uncertainty (uncomputable), but in uncertain scenarios, heuristics become more reliable than attempting to optimize.
Psychological experiments may be influenced by preconceived ideas of how the human mind works, leading to the replication crisis where many scientific studies are difficult to reproduce.
Heuristics are not just quick and dirty shortcuts but can be effective ways of decision-making in specific contexts, following the concept of ecological rationality.
Less-is-more is an important heuristic that suggests ignoring useless information can lead to better decision-making in uncertain environments.
Biases and heuristics can balance out to produce overall better decision-making, challenging the notion that biases are solely cognitive errors.
Building an adaptive toolbox of simple heuristics can help entrepreneurs make effective decisions in various business contexts.
Blind faith in technology can be problematic, as relying solely on optimization-oriented technologies may lead to suboptimal outcomes in uncertain situations.
Bounded rationality has two main sides: ecological (mind adapted for real-world environments) and cognitive (computational capability of the decision-maker).
Understanding ecological rationality allows for better decision-making by relying on heuristics suited for specific environments and contexts.
The alternative view of bounded rationality emphasizes the use of simple heuristics as a necessary filtering mechanism of the mind to ignore useless and irrelevant information.
The mind’s ability to ignore information can be an effective survival mechanism and lead to better decision-making in uncertain situations.
By adopting heuristics and simple rules of thumb, entrepreneurs can develop a more effective decision-making approach in the face of uncertainty.
Recognizing biases and heuristics in communication and marketing can help avoid manipulation and conflict of interests.
Heuristics provide an adaptive toolbox for decision-making that is better suited for uncertain environments than complex models and optimization-oriented approaches.

List of Heuristics

Heuristic	Explanation	Implications	Prevention Strategies	When to Leverage	Examples
Anchoring	Relying on the first piece of information encountered (the “anchor”) when making decisions.	May lead to biased judgments if the anchor is arbitrary.	Be aware of anchoring effects and consider multiple anchors.	In negotiations, set the initial offer.	Setting a high price for a product before discounting.
Availability	Judging likelihood based on ease of recall or availability of related examples in memory.	Overestimating the probability of events that receive more media coverage.	Be critical of media influence and seek diverse sources of information.	When assessing personal experiences.	Believing a plane crash is more common after hearing about one on the news.
Confirmation Bias	Seeking information that confirms existing beliefs while ignoring contradictory information.	Can reinforce stereotypes and hinder objective decision-making.	Actively seek out opposing viewpoints and diverse sources of information.	When conducting research or analyzing data.	Believing a diet works because you only read success stories.
Sunk Cost Fallacy	Continuing an endeavor based on prior investments (e.g., time, money), even when not rational.	Can lead to wasteful decisions and perpetuate failing projects.	Evaluate decisions based on future costs and benefits, not past investments.	When considering whether to continue a project.	Staying in a failing business to “recoup” losses.
Hindsight Bias	Believing an event was predictable or expected after it has already occurred.	Hinders learning from past mistakes and impacts decision-making.	Reflect on decisions without the benefit of hindsight when evaluating outcomes.	During post-project reviews.	Thinking that a stock market crash was predictable after it happens.
Loss Aversion	Preferring to avoid losses over acquiring equivalent gains, leading to risk aversion.	May lead to missed opportunities and conservative decision-making.	Recognize loss aversion tendencies and assess risks objectively.	When considering investment decisions.	Avoiding stock market investments due to fear of losing money.
Overconfidence	Overestimating one’s abilities, knowledge, or the accuracy of one’s beliefs and predictions.	The tendency to overestimate one’s own abilities or the accuracy of one’s beliefs and predictions.	Encourage critical self-assessment and seek external feedback.	When planning and assessing personal skills.	Believing you’re a better driver than others despite data to the contrary.
Recency Effect	Giving more importance to recent events or information when making decisions.	May lead to overlooking long-term trends and making impulsive choices.	Balance recent data with historical context and trends.	In investment decisions, consider long-term performance.	Buying a stock because it performed well recently.
Framing Effect	Decisions can be influenced by how information is presented or framed.	Different framings can lead to varying perceptions and choices.	Be aware of framing effects and consider different perspectives.	When crafting persuasive messages.	A health campaign emphasizing “90% fat-free” vs. “10% fat” yogurt.
Prospect Theory	Evaluating potential outcomes based on perceived gains and losses rather than final states.	People evaluate potential outcomes based on perceived gains and losses rather than final states.	Use objective data and consider outcomes in terms of overall utility.	When designing incentive programs.	Offering insurance with a focus on avoiding potential losses.
Status Quo Bias	The preference for the current state of affairs and the resistance to change.	Can lead to missed opportunities for improvement and innovation.	Encourage regular evaluation and a willingness to consider change.	When assessing organizational processes.	Sticking to an old software system despite better alternatives.
Groupthink	The tendency of a group to make decisions without critical evaluation due to a desire for consensus and conformity.	Can lead to poor decisions when diverse perspectives are not considered.	Encourage open and dissenting opinions within group discussions.	During team decision-making processes.	Going along with a group’s decision to maintain harmony.
Availability Cascade	A self-reinforcing process where a belief or idea becomes more credible and influential simply because it’s repeated frequently.	Can lead to the spread of misinformation and irrational beliefs.	Encourage critical thinking and fact-checking in the face of widely repeated claims.	When evaluating the credibility of information.	Believing a false rumor because it’s widely shared on social media.
Anchoring and Adjustment	People start with an initial estimate (the anchor) and then adjust it to reach a final decision.	Anchors can bias judgment, leading to inaccurate estimates.	Be aware of the anchor’s influence and adjust away from it if necessary.	In negotiations and pricing decisions.	Offering a high-priced item as a starting point for negotiation.
The Planning Fallacy	The tendency to underestimate the time, costs, and risks of future actions and overestimate the benefits.	Can lead to project delays, budget overruns, and disappointment.	Use historical data and consider potential risks when planning projects.	When estimating project timelines and budgets.	Underestimating the time needed to complete a construction project.
Regression to the Mean	The tendency for extreme events or measurements to return to a more average state over time.	Can lead to misinterpretation of natural fluctuations as trends or interventions.	Recognize that extreme results are often followed by more typical ones.	When analyzing performance data.	Assuming a sports team will continue winning after a streak of victories.
Cognitive Dissonance	The discomfort people feel when they hold conflicting beliefs or engage in actions that are inconsistent with their beliefs.	Can lead to rationalization and resistance to changing beliefs or behaviors.	Encourage reflection and openness to adjusting beliefs or behaviors.	When promoting behavior change or diversity of thought.	Smoking despite knowing the health risks because quitting is difficult.
Representativeness Heuristic	Judging the probability of an event based on how similar it is to a prototype.	Can lead to stereotyping and misjudgments if prototypes are not representative.	Use statistical information in addition to resemblance when making judgments.	When making predictions based on patterns.	Assuming a person is a good programmer because they fit the “nerd” stereotype.
Fundamental Attribution Error	The tendency to attribute the behavior of others to their character while attributing our own behavior to external factors.	Can lead to misjudgments about the motivations and intentions of others.	Practice empathy and consider situational factors when judging others.	When evaluating the actions of individuals or groups.	Blaming a coworker for a mistake while attributing your own mistakes to external pressures.
Illusory Correlation	Perceiving a relationship between two variables when none exists or overestimating the strength of a real but weak relationship.	Can lead to superstitions and inaccurate beliefs about cause and effect.	Encourage objective analysis and critical thinking when evaluating correlations.	When interpreting data or research findings.	Believing that a lucky charm improves sports performance based on anecdotal evidence.
The Endowment Effect	The tendency to overvalue items simply because you own them.	Can lead to inflated valuations and resistance to selling or exchanging possessions.	Recognize the bias and consider the objective value of items when making decisions.	When pricing personal belongings for sale.	Valuing a used car much higher just because it’s yours.
Hyperbolic Discounting	The tendency to prioritize immediate rewards over larger, delayed rewards.	Can lead to impulsive decision-making and neglecting long-term goals.	Implement strategies like pre-commitment to make future rewards more salient.	When setting savings or investment goals.	Choosing to spend money on entertainment rather than saving for retirement.
The Curse of Knowledge	Assuming that others have the same level of knowledge or understanding as oneself.	Can lead to ineffective communication and difficulty teaching or explaining concepts.	Practice empathy and adapt your communication to the audience’s level of knowledge.	When explaining complex ideas or concepts.	Using jargon when explaining a technical concept to a non-expert.
Escalation of Commitment	The tendency to continue investing in a decision or project, despite evidence of failure.	Can lead to persistent, irrational investment of resources.	Establish clear criteria for success and be willing to cut losses when those criteria aren’t met.	When managing a failing project.	Pouring more money into a failing business despite declining performance.
The Curse of Sunk Costs	The inability to ignore past costs when making decisions.	Can lead to irrational decisions to justify past investments.	Evaluate decisions based on future costs and benefits, not past investments.	When deciding whether to continue a project.	Continuing to attend an expensive, unenjoyable event to “get your money’s worth.”
Anchoring to Initial Beliefs	The tendency to anchor one’s beliefs or judgments to initial information, even if it’s inaccurate.	Can lead to stubbornness and resistance to changing one’s mind when presented with new evidence.	Encourage open-mindedness and a willingness to adjust beliefs based on new information.	When engaged in debates or discussions.	Holding onto a political belief despite evidence to the contrary because it was your initial stance.
The Just-World Hypothesis	The belief that the world is inherently fair, and people get what they deserve.	Can lead to victim-blaming and insensitivity to the struggles of others.	Recognize that the world is complex, and circumstances often play a significant role in outcomes.	When discussing social justice issues.	Blaming a homeless person for their situation based on the assumption that they must have done something to deserve it.
The Availability Heuristic	Estimating the likelihood of an event based on its ease of recall from memory.	Can lead to misjudgments if memorable events don’t accurately represent probabilities.	Cross-reference information with objective data to reduce reliance on memory alone.	When assessing risk or probabilities.	Overestimating the risk of shark attacks after seeing a news story about one.
The Dunning-Kruger Effect	The cognitive bias where people with low ability at a task overestimate their ability, while those with high ability underestimate their ability.	Can lead to overconfidence and incompetence in some cases.	Encourage self-awareness and humility in assessing one’s own skills and knowledge.	When seeking self-improvement or providing feedback.	Someone with limited knowledge about a subject believing they are an expert.
The Zeigarnik Effect	The tendency to remember uncompleted tasks or interrupted activities better than completed tasks.	Can lead to intrusive thoughts and decreased focus on current tasks.	Use task management strategies to reduce the mental load of unfinished tasks.	When organizing your work or managing your to-do list.	Remembering to buy groceries that you left off your last shopping trip.

References:

Reasoning the Fast and Frugal Way: Models of Bounded Rationality, Gerd Gigerenzer and Daniel G. Goldstein, Max Planck Institute for Psychological Research and University of Chicago, Psychological Review Copyright 1996 by the American Psychological Association, Inc. 1996, Vol. 103. No. 4, 650-669
Heuristic Decision Making, Gerd Gigerenzer and Wolfgang Gaissmaier, Annu. Rev. Psychol. 2011. 62:451–82
Simon, Herbert, 1983. “On the Behavioral and Rational Foundation of Economic Theory,” Working Paper Series 115, Research Institute of Industrial Economics.
Simon, Herbert A., 1978. “Rational Decision-Making in Business Organizations,” Nobel Prize in Economics documents 1978-1, Nobel Prize Committee.

Read Next: Heuristics, Biases.

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