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.
Aspect
Explanation
What is the Ladder of Inference?
The ladder of inference is a decision-making process where individuals move from collecting facts to making decisions or taking actions. It illustrates how personal beliefs and biases influence this process.
Purpose
To understand how our mental models, assumptions, and biases impact the way we perceive information and make decisions, and to promote more informed and unbiased decision-making.
Mental Models
Mental models are unique assumptions and generalizations that individuals hold based on their past experiences, values, and beliefs. These models shape how we interpret information.
Stages of the Ladder
There are seven stages in the ladder of inference, each representing a step in the decision-making process: Available Data, Select Data, Paraphrase Data, Name What Is Happening, Explain or Evaluate, Develop Beliefs, and Take Action.
Stage 1 – Available Data
Collecting facts and reality; the foundation of the ladder.
Stage 2 – Select Data
Choosing which data to pay attention to, often influenced by subconscious decisions.
Stage 3 – Paraphrase Data
Adding personal meaning and biases to the selected data, without necessarily evaluating its validity.
Stage 4 – Name What Is Happening
Labeling situations based on a combination of interpreted facts and personal assumptions.
Stage 5 – Explain or Evaluate
Seeking reasons or judgments by considering causal theories and evaluating them based on personal values and beliefs.
Stage 6 – Develop Beliefs
Forming beliefs based on conclusions drawn from previous stages, which then shape future judgments and actions.
Stage 7 – Take Action
Making decisions and taking actions based on the beliefs and assumptions developed throughout the process.
Improving Decision Making
Recognizing biases and consciously adjusting one’s position on the ladder to promote more objective and informed decision-making.
Examples of Biases
Various biases, such as Maslow’s Hammer (over-reliance on familiar tools), Pygmalion Effect (higher expectations leading to improved performance), and Ringelmann Effect (reduced productivity in larger groups), can affect decision-making at different stages of the ladder.
Mental models encapsulate assumptions and generalizations and are unique to everyone.
They explain why two people can witness the same event but experience it in two vastly different fashions.
Fundamentally, the ladder of inference encourages informed decision making based on fact and not on personal biases that characterize mental models.
By acting without bias, the individual or business experiences growth. Indeed, the ladder is often equated with the cycle of growth, where completion of each cycle results in improvement based on continuous learning.
Climbing the rungs of the inference ladder
The ladder of inference can be thought of as a visual representation of the decision-making thought process.
Seven rungs exist, with each rung representing one of the seven stages of thinking.
Let’s look at each stage:
Stage 1 – available data
At the bottom of the ladder exists information about the reality and facts of daily life.
This includes everything from the body language of a colleague to the results from a marketing campaign.
Stage 2 – select data
Given the richness and abundance of available data, people cannot pay attention to all of it simultaneously.
Instead, mostly subconscious choices are made regarding what data is selected and what data is ignored.
Stage 3 – paraphrase data
In the third stage, the individual adds meaning to the data based on unique past experiences, values, beliefs, or biases.
Often, there is no consideration regarding whether the meaning applied is valid or true.
Stage 4 – name what is happening
Here, the individual names the situation based on a combination of interpreted fact and personal assumptions.
Stage 5 – explain or evaluate what is happening
Having just explained what is happening, the individual then seeks to explain why it is happening.
This is performed by considering a list of causal theories that are judged as either good or bad according to the individual’s values.
Stage 6 – develop beliefs based on conclusions
These beliefs then shape future judgments in scenarios with similar contexts.
The classic example is an employee who is consistently late to work in the belief that they will not be reprimanded by management.
This belief then leads the employee to be late to meetings and other formal engagements.
Stage 7 – take action
In the final stage, the individual takes what they believe is the right course of action. Of course, their actions are always based on beliefs and assumptions.
Using the ladder of inference to make better decisions
Many assume that the ladder of inference is a systematic guide to making better decisions.
However, the ladder merely outlines the natural thought process that every individual experiences.
To improve decision making, an individual must know where they sit on the ladder and adjust accordingly.
Indeed, one of the key steps within the process is to recognize the biases that might be affecting our judgement.
The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman since 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.
Perhaps counterintuitively, it is preferable to occupy the lower rungs of the ladder or descend where possible.
An individual who tends to paraphrase data (Stage 3) to their detriment should be more selective about the data they select from their environment (Stage 2).
An individual who tends to select data to suit their own agenda (Stage 2) should consider incorporating a broader subset of available data (Stage 1).
In both cases, the individual is encouraged to question the validity of their assumptions and beliefs.
This helps them break free of the reflexive loop – where assumptions and beliefs impact the data that will be selected in similar future scenarios.
This can often lead to a toxic cycle where actions are reinforced by limited or flawed information and vice versa.
Thus, the ladder of inference is the first step toward understanding and recognizing which biases might be limiting our understanding of the world and, based on that, what mental models we can use as effective ways to make decisions.
Ladder of inference and biases in decision making
Take the case of interpreting the world based on the tools that we know, thus falling into the trap of Maslow’s Hammer.
We might select the tools and frameworks that we’re familiar with, thinking that those are the tools that work in every scenario, thus impairing our ability to be effective in specific situations.
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).
Or take the case of the Pygmalion effect within organizations and how it might affect the decision-making process.
The Pygmalion effect is a psychological phenomenon where higher expectations lead to an increase in performance. The Pygmalion effect was defined by psychologist Robert Rosenthal, who described it as “the phenomenon whereby one person’s expectation for another person’s behavior comes to serve as a self-fulfilling prophecy.”
Or how decision-making is affected within large groups.
The Ringelmann effect describes the tendency for individuals within a group to become less productive as the group size increases.
All these sorts of biases need to be identified within the ladder of inference to be able to make effective decisions, based on reliable mental models!
Case studies
Stage 1 – Available Data
A scientist collects temperature and humidity readings from a weather station.
A salesperson reviews monthly sales figures for a product.
Stage 2 – Select Data
A news editor decides which news stories to feature on the front page.
A job applicant highlights specific achievements on their resume for a job interview.
Stage 3 – Paraphrase Data
A manager interprets an employee’s frequent absences as a lack of dedication.
A chef perceives a customer’s preference for spicy food based on their previous orders.
Stage 4 – Name What Is Happening
An event planner labels a decrease in RSVPs as “low interest” without investigating further.
A teacher describes a student’s behavior as “disruptive” without considering external factors.
Stage 5 – Explain or Evaluate What Is Happening
A financial analyst attributes a drop in stock prices to economic instability, leading to a negative evaluation.
A coach believes a team’s success is due to their training methods and evaluates them positively.
Stage 6 – Develop Beliefs Based on Conclusions
An employee believes they won’t be promoted due to past rejections, leading to reduced ambition.
A student who consistently receives praise develops a belief in their own intelligence, boosting confidence.
Stage 7 – Take Action
An investor sells their stocks based on the belief that a recession is imminent.
A manager implements a new project management approach because they believe it will increase team productivity.
Maslow’s Hammer Bias
A graphic designer exclusively uses one design software for all projects, overlooking other potentially more suitable tools.
An architect relies on the same building materials for all projects, regardless of unique client needs.
Pygmalion Effect Bias
A teacher with high expectations for students’ success sees improved academic performance in their class.
A coach who believes in the team’s potential motivates players to achieve better results.
Ringelmann Effect Bias
In a large brainstorming session, individual participants contribute less as the group size increases.
In a massive organization, employees become less engaged and productive as the company expands.
Key takeaways
The ladder of inference describes how people form and sustain mental models in the decision-making process.
The ladder of inference has seven rungs, with each rung representing a particular stage of decision making based on personal assumptions, beliefs, or biases.
The ladder of inference is not intended to provide advice on optimal decision making. Instead, it allows individuals to identify where their process is flawed and move down the ladder to correct it.
Ladder of Inference Highlights:
Definition: The ladder of inference is a cognitive process where individuals move from facts to decisions or actions. It was introduced by Chris Argyris to illustrate how people form and utilize mental models to make decisions.
Mental Models and Diversity: Mental models are individual assumptions and generalizations that influence how people perceive events. They explain why different people can experience the same event differently due to their unique mental frameworks.
Bias-Free Decision Making: The ladder of inference encourages unbiased decision-making based on facts rather than personal biases inherent in mental models. By minimizing bias, individuals and businesses can achieve growth and continuous learning.
Stages of the Ladder: The ladder of inference represents a seven-stage decision-making process:
Stage 1: Available data (facts).
Stage 2: Selection of data based on attention and relevance.
Stage 3: Paraphrasing data with personal meaning and biases.
Stage 4: Naming the situation based on interpretations.
Stage 5: Explaining or evaluating the situation based on causal theories.
Stage 6: Developing beliefs based on conclusions.
Stage 7: Taking action guided by beliefs and assumptions.
Improving Decision Making: The ladder of inference does not provide a formula for optimal decision-making but helps individuals recognize biases in their process. By identifying biases, individuals can adjust their decision-making and strive to make more objective choices.
Cognitive Biases and Mental Models: Cognitive biases, systematic errors in decision-making, are intertwined with mental models and ladder of inference stages. Understanding biases within the ladder’s framework is crucial for effective decision-making.
Examples of Biases: Various biases, such as Maslow’s Hammer (over-reliance on familiar tools) and the Pygmalion Effect (higher expectations leading to improved performance), can affect decision-making. The Ringelmann Effect (reduced productivity in larger groups) is another bias that influences decision-making.
Key Takeaway: The ladder of inference provides a framework for understanding how personal assumptions, beliefs, and biases influence decision-making. By recognizing biases within the ladder’s stages, individuals can make more informed and unbiased decisions based on reliable mental models.
Related Framework
Description
When to Apply
Ladder of Inference
The Ladder of Inference is a model that illustrates how people make sense of the world and form beliefs based on incomplete and often biased information. It describes a process where individuals select data, interpret it based on their existing beliefs and assumptions, draw conclusions, and take action. Understanding the Ladder of Inference can help individuals and organizations recognize their mental models, challenge assumptions, and improve decision-making by considering a broader range of perspectives and data.
When analyzing decision-making processes or facilitating communication, utilizing the Ladder of Inference can improve awareness and enhance critical thinking skills by identifying underlying assumptions and evaluating inference chains, thus promoting reflective practice and mitigating cognitive biases in problem-solving sessions, team meetings, or conflict resolution, ultimately improving decision quality and fostering collaboration through mindful inquiry and evidence-based reasoning.
Cognitive Bias
Cognitive Bias refers to systematic patterns of deviation from rationality in judgment and decision-making. These biases often stem from heuristics or mental shortcuts that individuals use to simplify complex information processing tasks. Cognitive biases can lead to errors in judgment, affecting various aspects of decision-making, from risk assessment to problem-solving. Understanding cognitive biases can help individuals and organizations recognize and mitigate their impact, leading to more objective and effective decision-making processes.
When evaluating decision outcomes or conducting risk assessments, addressing Cognitive Bias can improve decision quality and reduce errors by recognizing common biases and implementing decision safeguards, thus enhancing problem-solving and minimizing decision errors in strategic planning, project management, or organizational leadership, ultimately improving performance and fostering a culture of learning through cognitive awareness and bias mitigation strategies.
Reflective Practice
Reflective Practice involves deliberate reflection on experiences, actions, and outcomes to gain insights and improve future performance. It encourages individuals to critically examine their assumptions, beliefs, and behaviors, fostering continuous learning and growth. Reflective practice can enhance self-awareness, promote empathy, and facilitate adaptive decision-making by encouraging individuals to consider multiple perspectives and challenge their mental models.
When promoting learning culture or developing leadership skills, engaging in Reflective Practice can enhance self-awareness and improve decision-making by encouraging critical reflection and learning from experiences, thus fostering personal growth and building resilience in professional development, team dynamics, or organizational change initiatives, ultimately empowering individuals and enhancing organizational effectiveness through continuous improvement and adaptive learning processes.
Systems Thinking
Systems Thinking is an approach to problem-solving that emphasizes understanding the interconnectedness and dynamics of complex systems. It encourages individuals to consider the broader context and relationships between elements within a system rather than focusing solely on individual parts. Systems thinking helps identify feedback loops, unintended consequences, and leverage points for intervention, enabling more holistic and effective solutions to complex problems.
When tackling complex challenges or designing interventions, applying Systems Thinking can improve problem understanding and facilitate system-level analysis by identifying interdependencies and uncovering leverage points, thus enhancing decision effectiveness and promoting sustainable solutions in policy development, organizational change, or community development, ultimately optimizing system performance and fostering resilience through holistic thinking and collaborative problem-solving.
Critical Thinking
Critical Thinking involves systematically analyzing and evaluating information to form reasoned judgments and make informed decisions. It requires individuals to question assumptions, consider evidence, and weigh alternative perspectives before reaching conclusions. Critical thinking skills enable individuals to identify biases, recognize logical fallacies, and differentiate between fact and opinion, leading to more objective and well-founded decision-making.
When evaluating arguments or assessing evidence, applying Critical Thinking can enhance analytical skills and improve decision quality by challenging assumptions and evaluating reasoning, thus facilitating sound judgment and minimizing errors in research projects, strategic planning, or policy analysis, ultimately strengthening decision processes and fostering intellectual rigor through evidence-based inquiry and logical reasoning.
Metacognition
Metacognition refers to the awareness and understanding of one’s own thought processes, including how individuals monitor, regulate, and evaluate their cognitive activities. It involves reflecting on one’s thinking, planning strategies, and adapting approaches based on feedback and outcomes. Metacognitive skills enable individuals to become more effective learners and decision-makers by actively managing their cognitive resources and optimizing their problem-solving strategies.
When developing learning strategies or improving decision-making, fostering Metacognition can enhance cognitive flexibility and promote self-regulated learning by encouraging reflection and strategic planning, thus improving learning outcomes and facilitating adaptive decision processes in education, training programs, or professional development, ultimately empowering individuals and enhancing performance through metacognitive awareness and strategic self-management.
Emotional Intelligence
Emotional Intelligence (EI) refers to the ability to recognize, understand, and manage one’s own emotions as well as those of others. It involves skills such as self-awareness, self-regulation, empathy, and social skills, which are essential for effective communication, relationship building, and decision-making. Emotional intelligence enables individuals to navigate complex social dynamics, resolve conflicts, and make decisions that consider both rational and emotional factors.
When promoting interpersonal skills or enhancing team collaboration, leveraging Emotional Intelligence can improve communication effectiveness and facilitate conflict resolution by fostering empathy and emotional regulation, thus building trust and strengthening relationships in team settings, leadership development, or customer relations, ultimately enhancing organizational culture and promoting positive outcomes through emotional awareness and interpersonal competence.
Scenario Planning
Scenario Planning is a strategic foresight technique that involves envisioning multiple future scenarios to anticipate uncertainties and prepare for alternative futures. It enables organizations to explore potential challenges, opportunities, and disruptions, allowing them to develop robust strategies and contingency plans. Scenario planning fosters resilience by encouraging proactive thinking and adaptive decision-making in the face of uncertainty.
When anticipating future trends or developing strategic plans, employing Scenario Planning can enhance preparedness and facilitate adaptive strategy formulation by exploring diverse scenarios and assessing potential impacts, thus improving risk management and informing decision choices in business strategy, policy development, or crisis management, ultimately enhancing organizational agility and fostering strategic resilience through strategic foresight and contingency planning.
Complexity Theory
Complexity Theory is a framework for understanding the behavior of complex systems, emphasizing self-organization, emergence, and nonlinear dynamics. It explores how simple rules and interactions among components can lead to the emergence of complex phenomena. Complexity theory recognizes that complex systems are inherently unpredictable and adaptive, requiring a flexible, adaptive approach to decision-making and problem-solving. Understanding complexity theory can help individuals navigate uncertain and dynamic environments by embracing complexity and leveraging emergent patterns to inform decision-making.
When dealing with complex systems or dynamic environments, applying Complexity Theory can enhance understanding and inform decision-making by recognizing emergent patterns and navigating nonlinear dynamics, thus facilitating adaptive responses and promoting innovation in organizational strategy, economic policy, or ecosystem management, ultimately fostering resilience and sustainability through flexible, responsive approaches and emergent strategies.
SWOT Analysis
SWOT Analysis is a strategic planning tool used to identify an organization’s strengths, weaknesses, opportunities, and threats. It involves assessing internal factors such as resources, capabilities, and vulnerabilities, as well as external factors such as market trends, competition, and regulatory changes. SWOT analysis helps organizations develop strategic priorities, mitigate risks, and capitalize on opportunities by aligning their strengths with external opportunities and addressing weaknesses and threats.
When conducting strategic assessments or formulating business strategies, utilizing SWOT Analysis can inform decision-making and guide strategic planning by assessing internal capabilities and external market dynamics, thus identifying strategic priorities and allocating resources in market entry strategies, product development, or risk management, ultimately enhancing organizational competitiveness and improving performance through strategic alignment and evidence-based planning.
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.
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 is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.
Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.
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.
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 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.
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 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, 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, 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).
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.
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.
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.
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.
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.
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.
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.
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 – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.
The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.
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.
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.
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.
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 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 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 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.
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 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.”
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 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 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 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.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
