Representativeness Heuristic In A Nutshell

The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.

Aspect	Explanation
Representativeness Heuristic	The representativeness heuristic is a cognitive shortcut that individuals use when making judgments or decisions. It involves assessing the likelihood of an event or the category membership of something based on how similar it appears to a typical example or prototype.
Description	– People tend to rely on representativeness when evaluating probabilities or making judgments about uncertain events. – It involves comparing the object or event in question to a mental prototype or stereotype. – This heuristic can lead to biases and errors in judgment.
Prototype	A prototype is a mental image or concept that represents a typical or ideal example of a category. When people use the representativeness heuristic, they assess whether an object or event is similar to this mental prototype.
Biases and Errors	– Base Rate Neglect: People often ignore statistical base rates (prior probabilities) in favor of representativeness. – Conjunction Fallacy: Assuming that specific combinations of events are more likely than single events, even when this defies logic.
Example	If someone sees a person who fits the stereotype of a librarian (e.g., glasses, quiet demeanor), they may assume that this person is indeed a librarian, neglecting the low base rate of librarians in the population.
Impact	The representativeness heuristic can lead to judgments and decisions that are based on stereotypes or surface similarities rather than objective probabilities. This can result in suboptimal decisions and contribute to various cognitive biases.
Applications	The representativeness heuristic is encountered in everyday decision-making, including financial choices, medical diagnoses, and legal judgments. It can affect how people perceive and respond to risk, often leading to overestimation or underestimation.
Mitigation	Critical thinking, statistical education, and awareness of cognitive biases can help individuals recognize and mitigate the influence of the representativeness heuristic. Encouraging a more systematic and analytical approach to decision-making is beneficial.
In Sum	While the representativeness heuristic is a mental shortcut that simplifies decision-making, it can introduce biases and errors when judgments are based on stereotypes or superficial similarities rather than accurate probabilities and data.

Table of Contents

Understanding the representativeness heuristic

They noted that the representativeness heuristic explains the degree to which an event is:

Similar in essential characteristics to the parent population (class), and
Reflective of the important features of the process by which it is generated.

To better explain the heuristic, consider the example of John.

John is a history buff who enjoys visiting museums and other places of cultural significance. He is also a regional chess champion and goes fossicking for gold on the weekend.

Given the information supplied, which is the more likely scenario?

John is an archaeologist in residence for a prestigious university.
John is a truck driver.

When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.

However, the odds that John is a truck driver are far greater because truck drivers make up a higher percentage of the population than archaeologists.

When decisions are made based on the representativeness heuristic, the individual is more likely to overestimate the likelihood of an event occurring. For a given event, there is no correlation between representativeness and a higher probability of that event occurring.

The representativeness heuristic in business and marketing

The representativeness heuristic is common in consumer behavior because products are rarely described completely. As a result, the consumer must form inferences about the information that is missing.

In a 2004 study, researchers found that consumers inferred a higher product quality from a no-name brand if the packaging was designed to mimic a better known global brand.

Representativeness is also seen in finance where investors prefer to buy a stock with unusually high share price appreciation.

Further studies demonstrated that investors misattributed positive company characteristics (such as high-quality products) as an indicator of a good investment.

Applications in marketing

Marketing agencies use the heuristic to convince consumers that products are representative of ideas or concepts they already possess.

Advertisements depicting suave men drinking alcoholic beverages surrounded by women lead consumers into thinking that they must also drink that brand to be popular with the opposite sex.

Marketing campaigns for SUVs and trucks also suggest that their rugged off-road vehicles are only driven by similarly rugged men.

In each case, the consumer makes a buying decision based on comparing their current situation to a representative example.

Principles of the Representativeness Heuristic:

Prototype Matching: Individuals assess the likelihood of an event by comparing it to a mental prototype or stereotype they have in mind.
Simplification: It simplifies complex decision-making processes by relying on familiar patterns and associations.
Overlooking Base Rates: People may ignore statistical base rates in favor of a more representative or vivid mental image.
Influence of Stereotypes: Stereotypes and preconceived notions can strongly influence judgments when using this heuristic.

Advantages of the Representativeness Heuristic:

Quick Decision-Making: It allows for rapid decision-making, which can be advantageous in situations where time is limited.
Intuitive: The heuristic aligns with human intuition and simplifies complex problems.
Efficiency: In some cases, relying on prototypes can lead to accurate judgments when they align with reality.

Challenges of the Representativeness Heuristic:

Biases and Errors: It often leads to systematic biases and errors in judgment, as it oversimplifies complex probabilities.
Neglect of Base Rates: Individuals may ignore statistical base rates, leading to inaccurate assessments.
Stereotype Influence: Stereotypes can reinforce biases and lead to unfair judgments.
Lack of Rationality: The heuristic doesn’t always align with rational decision-making processes.

When to Be Cautious About Using the Representativeness Heuristic:

Complex Probabilities: When dealing with situations involving complex probabilities, where a more thorough analysis is necessary.
Risk Assessment: In contexts where accurate risk assessment is critical, such as financial investments or medical diagnoses.
Avoiding Stereotypes: To avoid reinforcing stereotypes or making unfair judgments based on appearances.
Legal and Ethical Decisions: In legal and ethical decision-making, where fairness and impartiality are essential.

What to Expect from Using the Representativeness Heuristic:

Rapid Judgments: Expect quick and intuitive judgments based on perceived similarities to prototypes.
Biases and Errors: Be aware of the potential for biases and errors, as the heuristic can lead to inaccurate assessments.
Stereotype Influence: Stereotypes may influence judgments and decisions more than factual information.
Influence on Choices: The heuristic can significantly impact choices and preferences.

Long-Term Impact of the Representativeness Heuristic:

Perpetuation of Biases: Over time, relying on this heuristic can reinforce biases and stereotypes.
Learning from Errors: Individuals and organizations may learn to be cautious about its use through recognizing past errors.
Improved Decision-Making: With awareness and training, decision-makers can improve judgment by supplementing the heuristic with more rational analysis.
Cultural and Social Impact: The use of this heuristic can influence cultural and social perceptions and norms.

Case Studies

Product Packaging and Branding: Companies often use the representativeness heuristic in product packaging and branding. For instance:
- Generic Brands: A generic or store-brand product may adopt packaging that resembles a well-known national brand. This tactic leads consumers to perceive the generic product as representative of the higher-quality national brand, even if the actual quality may differ.
- Healthy Product Claims: Food products that display images of fresh fruits and vegetables on their packaging may lead consumers to believe that the product is healthier, even if the actual nutritional content does not align with the representation.
Celebrity Endorsements: Companies frequently use celebrity endorsements in marketing campaigns. The representativeness heuristic comes into play when consumers associate positive qualities or characteristics of the celebrity with the endorsed product:
- Athlete Endorsements: Sports beverage companies often use famous athletes in their ads. Consumers may believe that consuming the product will make them more athletic or fit, based on the representation of the athlete’s performance.
- Actor Endorsements: Perfume or cologne advertisements featuring well-known actors may lead consumers to associate the product with the attractiveness and charm of the actor.
Target Audience Portrayal: Companies tailor their marketing strategies to represent and appeal to their target audience. This often involves using imagery, settings, or scenarios that consumers can relate to:
- Youth-Oriented Brands: Brands targeting younger consumers may use imagery of vibrant, energetic, and socially active individuals in their advertisements. This representation aligns with the youthful aspirations and self-image of the target audience.
- Luxury Brands: Luxury brands, on the other hand, may use imagery of opulence, exclusivity, and elegance to represent their products. This appeals to consumers who seek to associate themselves with these qualities.
Financial Services Advertising: In the financial industry, the representativeness heuristic can influence investment decisions:
- Successful Investor Portrayals: Investment firms may depict scenarios where successful investors enjoy financial prosperity due to their investment choices. Prospective investors might be swayed by the representation and believe they can achieve similar success by choosing the advertised financial services.
Product Comparisons: When companies compare their products to competitors’, they often use the representativeness heuristic to their advantage:
- Product A vs. Product B: A detergent brand may claim that its product is “just like Brand X but at half the price.” Consumers may perceive the product as representative of the higher-priced brand’s quality, making it an attractive choice.
Customer Testimonials: Companies feature customer testimonials in their marketing materials to represent the positive experiences of their products or services:
- Health Supplements: Dietary supplement companies might showcase testimonials from customers who claim to have experienced significant health improvements. These representations aim to convince potential buyers that they, too, can achieve similar results.
Influencer Marketing: Brands often collaborate with social media influencers who align with their target audience. The representativeness heuristic comes into play when consumers associate the influencer’s lifestyle or persona with the endorsed product:
- Beauty Products: Cosmetic companies may partner with beauty influencers who showcase makeup application. Consumers may perceive the product as representative of the influencer’s flawless appearance.
Testimonials and Case Studies: B2B (business-to-business) companies leverage the representativeness heuristic in marketing to other businesses:
- Success Stories: Software companies may share case studies featuring successful clients who achieved significant business growth using their solutions. Prospective clients may believe that implementing the software will lead to similar success.
E-commerce Product Recommendations: Online retailers use algorithms to recommend products to customers based on their browsing and purchase history. These recommendations are often based on the representativeness heuristic:
- “Customers Also Bought” Section: When an e-commerce site suggests that customers who bought a specific product also purchased another related item, it leverages the representativeness heuristic. Consumers may believe that the recommended product is representative of what they need.
Travel and Hospitality Industry: In the travel and hospitality sector, companies often use the representativeness heuristic to create aspirational experiences:
- Vacation Packages: Travel agencies may promote vacation packages with imagery of idyllic beaches and luxury accommodations. This representation aligns with consumers’ desires for a relaxing and enjoyable getaway.
Technology Product Descriptions: When describing technology products or services, companies may use terminology that aligns with consumers’ preconceived notions of quality:
- Smartphones: Smartphone manufacturers may emphasize features like “cutting-edge technology” and “high-performance processors.” These descriptions appeal to consumers who associate these qualities with superior devices.
Real Estate Listings: In real estate, property listings often use the representativeness heuristic to attract potential buyers:
- Luxury Home Descriptions: Real estate agents may describe a property as “an executive’s dream home” or “fit for a celebrity.” These descriptions create a representation of opulence and exclusivity to appeal to upscale buyers.
Food and Beverage Product Descriptions: Food and beverage companies use descriptive language to influence consumers’ perceptions of taste and quality:
- Artisanal or Craft Products: Brands may label their products as “artisanal” or “handcrafted,” implying a higher level of quality and uniqueness. Consumers may associate these terms with superior taste.
Sustainability Claims: Companies seeking to promote their commitment to sustainability may use the representativeness heuristic to convey eco-friendliness:
- Product Labeling: Food companies may use packaging with images of lush forests or clean oceans to represent environmentally conscious practices, even if the product’s impact is limited.
Vehicle Marketing: Car manufacturers often use the representativeness heuristic to create associations between their vehicles and desirable lifestyles:
- Adventure and Exploration: SUV advertisements may depict off-road adventures in scenic landscapes, connecting the vehicle with a sense of adventure and exploration.
Personal Finance and Retirement Planning:
- Financial advisors often rely on the representativeness heuristic when recommending investment strategies or retirement plans to clients.
- They may base their advice on past market trends, assuming that historical patterns will repeat themselves, potentially overlooking potential shifts or unforeseen economic changes.
Political Advertising and Campaign Messaging:
- Political candidates strategically employ the representativeness heuristic in their campaign messaging to resonate with voters.
- They emphasize past achievements or align themselves with symbols and slogans that evoke positive associations, shaping voters’ perceptions based on familiar narratives or stereotypes.
College Admissions and Selection Criteria:
- Admissions committees at colleges and universities sometimes use the representativeness heuristic when evaluating applicants.
- They may prioritize candidates who fit a certain profile or display characteristics typically associated with academic success, potentially overlooking diverse talents or unique backgrounds.
Social Media Influencer Culture:
- Influencers on platforms like Instagram or YouTube leverage the representativeness heuristic to curate their online personas and content.
- They present an idealized version of their lives or conform to popular trends to attract followers and sponsorships, shaping audience perceptions based on aspirational representations.
Online Dating and Relationship Matching:
- Users of online dating platforms often employ the representativeness heuristic when selecting potential partners.
- They may rely on superficial attributes or profile information to make snap judgments about compatibility, potentially overlooking important factors for long-term relationships.
Academic Publishing and Citation Practices:
- Researchers and scholars sometimes use the representativeness heuristic when citing previous studies or literature in academic papers.
- They may prioritize well-known or widely cited sources, assuming that popularity or familiarity equates to reliability or relevance, potentially perpetuating biases in scholarly discourse.
Legal Precedent and Court Decisions:
- Judges and legal scholars may utilize the representativeness heuristic when interpreting legal precedent or making court decisions.
- They may lean on past rulings or case law that aligns with familiar patterns or established norms, potentially influencing outcomes without considering evolving societal values or changing circumstances.
Cross-Cultural Communication and Stereotyping:
- Individuals from different cultural backgrounds may rely on the representativeness heuristic when interacting with people from other cultures.
- They may use stereotypes or generalizations to make assumptions about behavior or communication styles, leading to misunderstandings or misinterpretations in cross-cultural exchanges.
Environmental Conservation and Sustainability Initiatives:
- Environmental organizations often leverage the representativeness heuristic when promoting conservation efforts or sustainability initiatives.
- They may highlight iconic species or habitats to rally support or funding, relying on familiar symbols or narratives to evoke emotional responses from the public.
Global Conflict and Diplomatic Relations:
- Political leaders and diplomats may employ the representativeness heuristic when engaging in international relations or negotiations.
- They may draw on historical alliances or conflicts to predict the behavior of other countries or leaders, shaping foreign policy decisions based on familiar geopolitical dynamics or power structures.

Key takeaways

The representativeness heuristic occurs when individuals estimate the likelihood of an event based on a broad and typical example of an event or object.
The representativeness heuristic causes the individual to overestimate the chances of an event occurring. This is caused by incorrectly correlating representativeness with higher probability.
The representativeness heuristic is prevalent in marketing campaigns where product qualities, concepts, or themes are matched with those the consumer believes they already possess.

Representativeness Heuristic Highlights:

Definition: The representativeness heuristic is a cognitive bias described by psychologists Daniel Kahneman and Amos Tversky. It involves estimating the likelihood of an event based on how much it resembles a broader class or category, often leading to judgments that don’t necessarily align with statistical probabilities.
Key Aspects of Representativeness:
1. Similarity to Parent Population: Judging an event’s probability based on how similar it is to a broader category or stereotype.
2. Reflection of Important Features: Assessing whether the event reflects the essential characteristics of the process that generates it.
Example: Consider the case of John, who enjoys history, chess, and gold fossicking. Most people would incorrectly choose the option of John being an archaeologist because his characteristics align with the stereotype of an archaeologist, even though the probability of him being a truck driver is higher statistically.
Effect in Decision-Making: The representativeness heuristic often leads to overestimation of the likelihood of an event occurring. People make judgments based on similarity rather than actual probabilities.
Business and Marketing Application:
- Consumer Behavior: Consumers infer qualities about products or brands based on incomplete information. Packaging resembling well-known brands can lead consumers to perceive higher product quality.
- Finance and Investing: Investors may prefer stocks with unusually high appreciation, even if this isn’t a reliable indicator of good investment potential.
Marketing Usage:
- Marketers use the representativeness heuristic to align products with consumers’ existing concepts or ideas. Advertisements may depict scenarios that consumers believe they can relate to, leading to purchasing decisions based on representativeness.
Examples:
- Marketing campaigns showcasing certain types of people using products to convey that the product aligns with the consumer’s self-concept or aspirations.
- Financial advertising portraying successful investors to attract potential investors who aspire to be similarly successful.
Key Takeaway: The representativeness heuristic influences decision-making by leading individuals to judge events or situations based on how well they match established categories or stereotypes, rather than considering actual statistical probabilities. This can have significant implications in various aspects of life, including business and marketing.

Connected Thinking Frameworks

Convergent vs. Divergent Thinking

Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. Whereas divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. Where convergent thinking might work for larger, mature organizations where divergent thinking is more suited for startups and innovative companies.

Critical Thinking

Critical thinking involves analyzing observations, facts, evidence, and arguments to form a judgment about what someone reads, hears, says, or writes.

Biases

The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.

Second-Order Thinking

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

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.

Bounded Rationality

Bounded rationality is a concept attributed to Herbert Simon, an economist and political scientist interested in decision-making and how we make decisions in the real world. In fact, he believed that rather than optimizing (which was the mainstream view in the past decades) humans follow what he called satisficing.

Dunning-Kruger Effect

The Dunning-Kruger effect describes a cognitive bias where people with low ability in a task overestimate their ability to perform that task well. Consumers or businesses that do not possess the requisite knowledge make bad decisions. What’s more, knowledge gaps prevent the person or business from seeing their mistakes.

Occam’s Razor

Occam’s Razor states that one should not increase (beyond reason) the number of entities required to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century English theologian William of Ockham.

Lindy Effect

The Lindy Effect is a theory about the ageing of non-perishable things, like technology or ideas. Popularized by author Nicholas Nassim Taleb, the Lindy Effect states that non-perishable things like technology age – linearly – in reverse. Therefore, the older an idea or a technology, the same will be its life expectancy.

Antifragility

Antifragility was first coined as a term by author, and options trader Nassim Nicholas Taleb. Antifragility is a characteristic of systems that thrive as a result of stressors, volatility, and randomness. Therefore, Antifragile is the opposite of fragile. Where a fragile thing breaks up to volatility; a robust thing resists volatility. An antifragile thing gets stronger from volatility (provided the level of stressors and randomness doesn’t pass a certain threshold).

Ergodicity

Ergodicity is one of the most important concepts in statistics. Ergodicity is a mathematical concept suggesting that a point of a moving system will eventually visit all parts of the space the system moves in. On the opposite side, non-ergodic means that a system doesn’t visit all the possible parts, as there are absorbing barriers

Systems Thinking

Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.

Vertical Thinking

Vertical thinking, on the other hand, is a problem-solving approach that favors a selective, analytical, structured, and sequential mindset. The focus of vertical thinking is to arrive at a reasoned, defined solution.

Metaphorical Thinking

Metaphorical thinking describes a mental process in which comparisons are made between qualities of objects usually considered to be separate classifications. Metaphorical thinking is a mental process connecting two different universes of meaning and is the result of the mind looking for similarities.

Maslow’s Hammer

Maslow’s Hammer, otherwise known as the law of the instrument or the Einstellung effect, is a cognitive bias causing an over-reliance on a familiar tool. This can be expressed as the tendency to overuse a known tool (perhaps a hammer) to solve issues that might require a different tool. This problem is persistent in the business world where perhaps known tools or frameworks might be used in the wrong context (like business plans used as planning tools instead of only investors’ pitches).

Peter Principle

The Peter Principle was first described by Canadian sociologist Lawrence J. Peter in his 1969 book The Peter Principle. The Peter Principle states that people are continually promoted within an organization until they reach their level of incompetence.

Straw Man Fallacy

The straw man fallacy describes an argument that misrepresents an opponent’s stance to make rebuttal more convenient. The straw man fallacy is a type of informal logical fallacy, defined as a flaw in the structure of an argument that renders it invalid.

Google Effect

The Google effect is a tendency for individuals to forget information that is readily available through search engines. During the Google effect – sometimes called digital amnesia – individuals have an excessive reliance on digital information as a form of memory recall.

Streisand Effect

The Streisand Effect is a paradoxical phenomenon where the act of suppressing information to reduce visibility causes it to become more visible. In 2003, Streisand attempted to suppress aerial photographs of her Californian home by suing photographer Kenneth Adelman for an invasion of privacy. Adelman, who Streisand assumed was paparazzi, was instead taking photographs to document and study coastal erosion. In her quest for more privacy, Streisand’s efforts had the opposite effect.

Compromise Effect

Single-attribute choices – such as choosing the apartment with the lowest rent – are relatively simple. However, most of the decisions consumers make are based on multiple attributes which complicate the decision-making process. The compromise effect states that a consumer is more likely to choose the middle option of a set of products over more extreme options.

Butterfly Effect

In business, the butterfly effect describes the phenomenon where the simplest actions yield the largest rewards. The butterfly effect was coined by meteorologist Edward Lorenz in 1960 and as a result, it is most often associated with weather in pop culture. Lorenz noted that the small action of a butterfly fluttering its wings had the potential to cause progressively larger actions resulting in a typhoon.

IKEA Effect

The IKEA effect is a cognitive bias that describes consumers’ tendency to value something more if they have made it themselves. That is why brands often use the IKEA effect to have customizations for final products, as they help the consumer relate to it more and therefore appending to it more value.

Ringelmann Effect

The Ringelmann effect describes the tendency for individuals within a group to become less productive as the group size increases.

The Overview Effect

The overview effect is a cognitive shift reported by some astronauts when they look back at the Earth from space. The shift occurs because of the impressive visual spectacle of the Earth and tends to be characterized by a state of awe and increased self-transcendence.

House Money Effect

The house money effect was first described by researchers Richard Thaler and Eric Johnson in a 1990 study entitled Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice. The house money effect is a cognitive bias where investors take higher risks on reinvested capital than they would on an initial investment.

Heuristic

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.

Recognition Heuristic

The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.

Representativeness Heuristic

Take-The-Best Heuristic

The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.

Bundling Bias

The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.

Barnum Effect

The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.

Anchoring Effect

The anchoring effect describes the human tendency to rely on an initial piece of information (the “anchor”) to make subsequent judgments or decisions. Price anchoring, then, is the process of establishing a price point that customers can reference when making a buying decision.

Decoy Effect

The decoy effect is a psychological phenomenon where inferior – or decoy – options influence consumer preferences. Businesses use the decoy effect to nudge potential customers toward the desired target product. The decoy effect is staged by placing a competitor product and a decoy product, which is primarily used to nudge the customer toward the target product.

Commitment Bias

Commitment bias describes the tendency of an individual to remain committed to past behaviors – even if they result in undesirable outcomes. The bias is particularly pronounced when such behaviors are performed publicly. Commitment bias is also known as escalation of commitment.

First-Principles Thinking

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.

Ladder Of Inference

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.

Goodhart’s Law

Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.

Six Thinking Hats Model

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.

Mandela Effect

The Mandela effect is a phenomenon where a large group of people remembers an event differently from how it occurred. The Mandela effect was first described in relation to Fiona Broome, who believed that former South African President Nelson Mandela died in prison during the 1980s. While Mandela was released from prison in 1990 and died 23 years later, Broome remembered news coverage of his death in prison and even a speech from his widow. Of course, neither event occurred in reality. But Broome was later to discover that she was not the only one with the same recollection of events.

Crowding-Out Effect

The crowding-out effect occurs when public sector spending reduces spending in the private sector.

Bandwagon Effect

The bandwagon effect tells us that the more a belief or idea has been adopted by more people within a group, the more the individual adoption of that idea might increase within the same group. This is the psychological effect that leads to herd mentality. What in marketing can be associated with social proof.

Moore’s Law

Moore’s law states that the number of transistors on a microchip doubles approximately every two years. This observation was made by Intel co-founder Gordon Moore in 1965 and it become a guiding principle for the semiconductor industry and has had far-reaching implications for technology as a whole.

Disruptive Innovation

Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.

Value Migration

Value migration was first described by author Adrian Slywotzky in his 1996 book Value Migration – How to Think Several Moves Ahead of the Competition. Value migration is the transferal of value-creating forces from outdated business models to something better able to satisfy consumer demands.

Bye-Now Effect

The bye-now effect describes the tendency for consumers to think of the word “buy” when they read the word “bye”. In a study that tracked diners at a name-your-own-price restaurant, each diner was asked to read one of two phrases before ordering their meal. The first phrase, “so long”, resulted in diners paying an average of $32 per meal. But when diners recited the phrase “bye bye” before ordering, the average price per meal rose to $45.

Groupthink

Groupthink occurs when well-intentioned individuals make non-optimal or irrational decisions based on a belief that dissent is impossible or on a motivation to conform. Groupthink occurs when members of a group reach a consensus without critical reasoning or evaluation of the alternatives and their consequences.

Stereotyping

A stereotype is a fixed and over-generalized belief about a particular group or class of people. These beliefs are based on the false assumption that certain characteristics are common to every individual residing in that group. Many stereotypes have a long and sometimes controversial history and are a direct consequence of various political, social, or economic events. Stereotyping is the process of making assumptions about a person or group of people based on various attributes, including gender, race, religion, or physical traits.

Murphy’s Law

Murphy’s Law states that if anything can go wrong, it will go wrong. Murphy’s Law was named after aerospace engineer Edward A. Murphy. During his time working at Edwards Air Force Base in 1949, Murphy cursed a technician who had improperly wired an electrical component and said, “If there is any way to do it wrong, he’ll find it.”

Law of Unintended Consequences

The law of unintended consequences was first mentioned by British philosopher John Locke when writing to parliament about the unintended effects of interest rate rises. However, it was popularized in 1936 by American sociologist Robert K. Merton who looked at unexpected, unanticipated, and unintended consequences and their impact on society.

Fundamental Attribution Error

Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.

Outcome Bias

Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.

Hindsight Bias

Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.

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