Dunbar’s Number

Dunbar’s Number is a concept that represents the average number of meaningful relationships humans can maintain due to cognitive limits. It finds applications in optimizing organizational size, understanding social networks, and community building. By recognizing Dunbar’s Number, one can enhance social bonding and communication while being mindful of scaling and relationship maintenance challenges.

Introduction to Dunbar’s Number

Dunbar’s Number, also known as the Dunbar’s cognitive limit, refers to the suggested limit to the number of meaningful and stable social relationships an individual can maintain. The concept was first proposed by Robin Dunbar in the early 1990s, based on his research into the social structures of various primate species and their relationship to brain size.

The core idea is that there is a cognitive limit to the number of people with whom we can maintain social relationships that involve a high level of trust, emotional closeness, and cooperation. Beyond this limit, it becomes increasingly challenging for individuals to keep track of the social nuances and emotional connections required for meaningful relationships.

The Science Behind Dunbar’s Number

Dunbar’s Number is rooted in the relationship between brain size and social group size observed in primates, including humans. Dunbar noted a strong correlation between the size of the neocortex, the part of the brain responsible for higher cognitive functions, and the average social group size of various primate species.

By extrapolating these findings, Dunbar estimated that the maximum number of individuals with whom a human can maintain stable social relationships is approximately 150. This number is often cited as “Dunbar’s Number” and represents the upper limit of what is commonly referred to as one’s social network or support group.

Significance in Human Evolution

Dunbar’s Number has important implications for our understanding of human evolution and the development of complex social structures. Here are some key points of significance:

  1. Evolutionary Adaptation: Dunbar suggests that the cognitive limit on social relationships is an evolutionary adaptation. Throughout our evolutionary history, individuals who could form and maintain stable social bonds had advantages in terms of cooperation, protection, and resource sharing, contributing to their survival and reproductive success.
  2. Social Hierarchies: Within larger human communities or societies, social hierarchies and subgroups naturally emerge to maintain social cohesion. These hierarchies allow individuals to manage their social relationships effectively by focusing on a smaller, more manageable subset of connections.
  3. Diverse Relationship Tiers: Dunbar’s research indicates that people have different tiers of social relationships, with the innermost tier (often around 5 close relationships) representing those with the highest level of emotional intimacy and support. As you move outward from this inner circle, the number of relationships increases, but the level of emotional closeness decreases.
  4. Maintaining Social Stability: By recognizing these cognitive limits, individuals and societies can better understand why social networks are structured the way they are and why they tend to have a hierarchical quality. This knowledge can contribute to the stability of social structures.

Dunbar’s Number in Modern Society

In today’s interconnected world, Dunbar’s Number continues to offer valuable insights into human social dynamics and communication:

  1. Online Social Networks: Social media platforms have expanded the reach of our social networks, allowing us to connect with hundreds or even thousands of individuals. However, Dunbar’s Number suggests that only a fraction of these connections can be meaningful and stable relationships. This can help explain why many online connections remain relatively superficial.
  2. Workplace and Organizations: Understanding Dunbar’s Number can also be beneficial in workplace settings and organizations. It highlights the importance of forming close-knit teams and communities within larger organizations to foster effective communication and collaboration.
  3. Community Building: In community building and event planning, organizers often consider Dunbar’s Number when designing social experiences. It underscores the idea that successful gatherings or communities tend to be organized into smaller, more tightly-knit groups within the larger whole.
  4. Relationship Maintenance: On a personal level, acknowledging Dunbar’s Number can help individuals prioritize and allocate time and emotional energy to maintain their most important relationships. It can also explain why, as our social circles grow, we may feel stretched thin in terms of maintaining meaningful connections.

Critiques and Variability

While Dunbar’s Number offers valuable insights into human social relationships, it’s important to note that it is not a rigid, one-size-fits-all limit. There is variability among individuals, and factors such as personality, communication skills, and cultural norms can influence the number of social relationships a person can effectively maintain.

Additionally, Dunbar’s Number represents an average or rough estimate, and some individuals may exceed this limit while others fall below it. Nevertheless, it serves as a useful framework for understanding the general constraints and tendencies that shape our social lives.


Dunbar’s Number, rooted in the relationship between brain size and social group size observed in primates, provides valuable insights into the cognitive limits of human social relationships. It suggests that there is an upper limit to the number of stable and meaningful social connections an individual can maintain effectively. While this limit is not rigid and can vary among individuals, it has important implications for our understanding of human evolution, social dynamics, and communication in both traditional and modern contexts. Recognizing the existence of these cognitive limits can help individuals and societies navigate the complexities of human social networks and prioritize the relationships that matter most.

Examples of Dunbar’s Number:

  • Small Communities: A tight-knit neighborhood or a small village where residents maintain close, meaningful relationships within the community.
  • Work Teams: An efficient project team within a company that comprises members within the Dunbar’s Number range, allowing for effective collaboration and communication.
  • Friend Circles: Groups of friends or acquaintances who naturally fall within the Dunbar’s Number, ensuring that each member can maintain meaningful relationships with others.
  • Online Forums: Some online forums or social media groups may have subgroups or communities that align with Dunbar’s Number, fostering more engaged and meaningful interactions.

Key Highlights of Dunbar’s Number:

  • Cognitive Limit: Dunbar’s Number is based on the cognitive limit of humans to manage stable and meaningful social relationships. It is often estimated to be around 150, although variations exist.
  • Meaningful Relationships: It represents the average number of meaningful relationships an individual can effectively maintain. These relationships go beyond mere acquaintanceships.
  • Social Brain Hypothesis: The concept is linked to the social brain hypothesis, which suggests that our brain’s size limits the size of our social groups. Evolutionarily, humans developed larger brains to handle complex social interactions.
  • Use Cases: Dunbar’s Number finds applications in optimizing organizational size, analyzing social networks, and building cohesive communities.
  • Benefits: Recognizing Dunbar’s Number can lead to enhanced social bonding within smaller groups, more efficient communication, and stronger community cohesion.
  • Challenges: Businesses and communities may face challenges when trying to scale beyond Dunbar’s Number, as maintaining meaningful relationships becomes increasingly difficult. Balancing growth with relationship quality is essential.

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.


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 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).

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.

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.

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.


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

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.

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.

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 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.


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.

Read Next: BiasesBounded RationalityMandela EffectDunning-Kruger EffectLindy EffectCrowding Out EffectBandwagon Effect.

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