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.
Component
Description
Definition
Systems Thinking is a holistic and analytical approach to problem-solving and decision-making that views complex systems as interconnected and interdependent. It recognizes that actions within a system can have ripple effects and aims to understand the system’s behavior as a whole, rather than focusing on isolated components. Systems Thinking helps identify underlying patterns and relationships to find effective solutions.
Key Principles
– Interconnectedness: Systems Thinking acknowledges that everything in a system is interconnected, and changes in one part can impact the entire system. – Feedback Loops: It considers both reinforcing (positive) and balancing (negative) feedback loops that influence system behavior. – Emergence: Systems Thinking recognizes that system properties and behaviors can emerge from the interactions of its parts. – Hierarchy: It considers systems within systems, recognizing multiple levels of organization. – Boundaries: Defining system boundaries helps delineate what is included in the analysis.
How It Works
1. Identify the System: Define the system of interest and its boundaries. 2. Understand Components: Analyze the individual components or elements within the system. 3. Identify Interconnections: Recognize the relationships and interactions among system components. 4. Feedback Loops: Identify feedback loops and their impact on system behavior. 5. Emergent Properties: Consider how the system’s behavior emerges from these interactions. 6. Analyze Dynamics: Explore how changes affect the system over time. 7. Identify Patterns: Look for recurring patterns and behaviors within the system. 8. Develop Solutions: Use insights gained to develop effective solutions that consider the system as a whole.
Benefits
– Holistic Understanding: Systems Thinking provides a deeper and more comprehensive understanding of complex issues and challenges. – Effective Problem Solving: It helps identify root causes and underlying factors, leading to more effective problem-solving. – Improved Decision-Making: Decision-makers can make more informed and sustainable choices by considering long-term consequences and interdependencies. – Enhanced Planning: Systems Thinking aids in strategic planning and policy development. – Innovation: It can spark creative solutions by exploring unconventional relationships and feedback loops.
Drawbacks
– Complexity: Analyzing complex systems can be challenging and time-consuming. – Data Requirements: Systems Thinking often requires a significant amount of data and information. – Subjectivity: Interpreting system dynamics and feedback loops can involve subjectivity. – Learning Curve: It may take time for individuals or teams to become proficient in Systems Thinking.
Applications
– Business and Management: Used to analyze organizational structures, supply chains, and business processes. – Environmental Science: Applied to study ecosystems, climate change, and resource management. – Public Policy: Used to develop policies addressing complex social issues. – Healthcare: Applied to understand healthcare delivery systems and patient outcomes. – Engineering: Used in product design, quality control, and process optimization. – Education: Applied in curriculum design and improving learning outcomes.
Examples
– Supply Chain Management: Analyzing the entire supply chain to identify bottlenecks and optimize efficiency. – Environmental Conservation: Studying ecosystems to determine the impact of human activity and develop conservation strategies. – Public Health: Understanding the factors influencing public health outcomes, such as disease spread. – Urban Planning: Examining the interconnectedness of urban systems, such as transportation, housing, and infrastructure. – Business Strategy: Considering the interdependencies of various business functions in strategic planning.
Systems thinking is based on systems theory and is responsible for one of the major breakthroughs in the understanding of complex organizations.
Systems theory studies systems from the perspective of the whole system, various subsystems, and the recurring patterns or relationships between subsystems.
The application of this theory in an organizational context is called systems analysis – of which systems thinking is a primary component.
In general terms, systems thinking considers systems in terms of their overall structures, patterns, and cycles.
This broad and holistic perspective enables organizations to identify solutions that address as many problems as possible.
In systems thinking, these solutions are known as leverage points because they leverage improvement throughout the system. Prioritizing leverage points across an entire system is called whole systems thinking.
The approach differs from traditional analysis methods which study systems by separating them into their constituent parts.
In addition to analyzing organizational complexity, systems thinking has also been used in medical, environmental, political, economic, and educational contexts.
Why use systems thinking?
By considering the system as a whole, systems thinking encourages organizations to broaden their perspectives and consider new or innovative solutions. This is particularly important for problems that are:
Chronic – that is, they are not a one-time event.
Familiar – or those that have a known history of repeated occurrences.
Complex – where people have unsuccessfully tried to find a solution in the past and failed.
Perhaps more profoundly, systems thinking promotes the idea that there is no perfect solution to any situation. Every decision the business makes will impact other parts of the system, so the “right” decision may be assumed to be any with the least severe negative impact.
For project teams, systems thinking diagrams are also important in telling compelling user stories. Diagrams that deal with cause and effect force the team to develop shared pictures and stories that can be understood and communicated by every member.
Six key themes of systems thinking
Here are some of the key themes that comprise a systems thinking mindset:
Interconnectedness
Systems thinkers understand that everything is connected. Trees need carbon dioxide, water, and sunlight to thrive.
Humans, in turn, can only survive by eating the food and oxygen that trees and other plants produce.
Systems thinkers see the world as a dynamic, chaotic, and interrelated arrangement of relationships and feedback loops.
Synthesis
In most cases, synthesis means the act of combining things to create something new.
In systems thinking, synthesis means separating complexity into manageable parts to understand the whole and the parts simultaneously.
Emergence
A term used to describe the natural outcome of things interacting with one another.
Key characteristics of emergence include non-linearity and self-organization.
Feedback loops
A natural consequence of interconnectedness are the feedback loops which flow between the elements of a system.
There are two main types: reinforcing and balancing.
Reinforcing feedback loops involve elements in the loop reinforcing more of the same, such as population growth in a large city.
Balancing loops are comprised of elements in some form of harmony, such as the relative abundance of predators and prey in an ecosystem.
Systems mapping
This is one of the key tools in a system thinker’s arsenal.
There are many ways to map a system, including behavior-over-time graphs, iceberg models, causal loop diagrams, and connected circles.
Whatever the method chosen, it should define how the elements within a system behave and how they are related.
Insights can then be used to develop effective shifts, interventions, policy, and project decisions.
Causality
Systems thinking also encourages the individual to consider causality as a dynamic and constantly evolving process.
Most people understand simple cause and effect, but relatively few can apply the concept to gain a deeper understanding of system feedback loops, agency, connections, and relationships.
Systems thinking examples
Subaru
Japanese car maker Subaru operates the only zero-waste automotive manufacturing facility in the United States.
While the EV revolution is now well underway, car manufacturing itself remains a process with a harmful carbon footprint.
This is mostly because the sourcing and processing of raw materials such as steel, aluminum, plastic, and rubber are extremely energy-intensive.
In a 2018 report, for example, it was estimated that the vehicle industry’s GHG emissions exceeded those of the European Union.
Subaru’s approach
Operating in an industry not known for environmental values, Subaru employed systems thinking to radically rethink its operations.
Over a period of just two years, the company transformed its Lafayette, Indiana-based assembly plant into a zero-waste facility.
With assistance from an environmental consultancy firm, Subaru adopted the three Rs of sustainability: reduce, reuse, and recycle.
Underpinning this effort was the kaizen philosophy of continuous improvement with employees rewarded for ideas that promoted environmental stewardship.
The factory itself also sits on an 832-acre site surrounded by forests, prairie grass, and other habitats for some of America’s most iconic plant and animal species.
According to executive vice president Tom Easterday, this includes firms outside of the automotive industry:
“We sometimes joke that we’ve had everything from potato chips to rocket ships visit us – from Frito Lay to Raytheon.”
The National Parks Service (NPS) has also turned to Subaru for assistance with its own zero-waste initiative.
Systems thinking has enabled Subaru to frame issues within the broader contexts in which it operates.
Importantly, the company understands the interconnectedness of business, the environment, and society as a whole.
“We don’t need the government to tell us to be good environmental stewards – it’s good for business”, Easterday explained.
Costco
To meet increased consumer demand for organic food, Costco started to invest in organic farmers in its supply chain.
The move relates to the key systems thinking principle of causality and has a basic but effective premise: If Costco provides the means for producers to transition to organic, the retailer can enter into “first buyer” agreements with them, stock more organic food in its stores, and increase revenue.
While the industry enjoyed grew at an impressive rate of 10%, the fact remained that if there was more organic produce, revenue and growth would be even higher.
Costco’s role in the industry
To some extent, growth in organic food sales has been stifled by structural issues in the agricultural industry.
Namely, the powerful influence of multinationals who control food supply with vast, monoculture farms and the governments that subsidize them.
However, Costco’s initiative shows that companies can use systems thinking and take a more proactive approach to manage their supply chains. This particular retailer improved its bottom line by meeting consumer demand in a rapidly growing industry.
But in the process, Costco also increased ethical and environmental standards in the food industry and made it more attractive as a potential recipient of investment or subsidization.
Key takeaways
Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. In addition to analyzing organizational and project complexity, it is also used in medical, environmental, political, economic, and educational contexts.
Systems thinking promotes the idea that there is no perfect solution to any situation. This helps the organization choose the best course of action by anticipating the potential impact of each option.
The systems thinking mindset is comprised of six key themes: interconnectedness, synthesis, emergence, feedback loops, systems mapping, and causality.
Key Highlights
Systems Thinking: Systems thinking is a holistic approach to investigating the factors and interactions that contribute to potential outcomes. It involves understanding complex organizations by considering the whole system, various subsystems, and the recurring patterns or relationships between them.
Applications: Systems thinking finds applications in diverse fields such as organizational analysis, medical, environmental, political, economic, and educational contexts. It offers a broad and holistic perspective that helps identify solutions to a wide range of problems.
Leverage Points: In systems thinking, solutions are referred to as leverage points. These points are crucial elements that, when targeted, can lead to significant improvements throughout the entire system. Prioritizing leverage points is essential in whole systems thinking.
Six Key Themes: The systems thinking mindset encompasses six key themes:
Interconnectedness: Understanding that everything is connected, and recognizing the dynamic, chaotic, and interrelated arrangement of relationships and feedback loops within a system.
Synthesis: Combining elements to create something new and separating complexity into manageable parts to understand the whole and its parts simultaneously.
Emergence: The natural outcome of things interacting with one another, characterized by non-linearity and self-organization.
Feedback Loops: The consequence of interconnectedness, where feedback flows between elements in a system, leading to reinforcing or balancing loops.
Systems Mapping: Utilizing various tools such as behavior-over-time graphs, iceberg models, causal loop diagrams, and connected circles to map and understand system behavior and relationships.
Causality: Considering causality as a dynamic and constantly evolving process, moving beyond simple cause-and-effect relationships.
Benefits: Systems thinking encourages organizations to broaden their perspectives and consider new or innovative solutions. It is particularly useful for addressing chronic, familiar, and complex problems that have resisted solutions in the past. By recognizing the interconnectedness of systems, it promotes the idea that there is no perfect solution, but rather decisions that minimize negative impacts.
Related Frameworks
Description
When to Apply
Causal Loop Diagrams (CLDs)
– Graphical representations of the feedback loops and causal relationships within a system. Causal Loop Diagrams (CLDs) help visualize the interdependencies and dynamics that influence system behavior over time.
– When analyzing complex systems and their feedback structures. – Creating Causal Loop Diagrams to map out the feedback loops and causal relationships within a system, understand how changes in one part of the system affect other parts, and identify leverage points for intervention, supporting Systems Thinking and strategic decision-making.
Stock and Flow Diagrams
– Graphical representations of stocks (accumulations) and flows (rates of change) within a system. Stock and Flow Diagrams help illustrate the dynamic behavior of systems, including feedback loops, delays, and accumulations.
– When modeling dynamic processes and interactions within a system. – Developing Stock and Flow Diagrams to visualize the stocks, flows, and feedback mechanisms that drive system behavior, simulate scenarios, and analyze the long-term dynamics of complex systems, supporting Systems Thinking and strategic decision-making processes.
Dynamic Systems Modeling
– A quantitative approach to modeling and simulating the behavior of dynamic systems over time. Dynamic Systems Modeling uses mathematical equations and computational tools to analyze system dynamics, forecast future states, and test policy interventions.
– When simulating the behavior of complex systems under different scenarios. – Applying Dynamic Systems Modeling techniques to build computational models of complex systems, simulate system behavior over time, and evaluate the impact of policy interventions or strategic decisions, supporting Systems Thinking and strategic planning processes.
Boundary Critique
– A method for challenging and redefining the boundaries of a system to better understand its interactions and interdependencies with its broader context. Boundary Critique helps identify blind spots and overlooked connections within a system.
– When examining the scope and boundaries of a system. – Conducting Boundary Critique exercises to question and redefine the boundaries of a system, explore its interactions with external factors and stakeholders, and uncover hidden relationships and dependencies, enhancing Systems Thinking and systemic understanding in decision-making processes.
Resilience Thinking
– Focuses on understanding and enhancing the resilience of socio-ecological systems to cope with disturbances, adapt to change, and maintain function and structure over time. Resilience Thinking emphasizes the importance of diversity, redundancy, and adaptive capacity in fostering system resilience.
– When assessing the capacity of systems to withstand and recover from disruptions. – Applying Resilience Thinking principles to analyze the resilience of socio-ecological systems, identify vulnerabilities, and develop strategies to enhance adaptive capacity, supporting Systems Thinking and strategic decision-making in risk management and sustainability planning.
Complex Adaptive Systems (CAS)
– Systems composed of numerous interconnected agents or components that interact with each other and adapt to their environment. Complex Adaptive Systems (CAS) exhibit emergent behavior and self-organization, making them difficult to predict or control.
– When analyzing systems characterized by emergent behavior and self-organization. – Applying Complex Adaptive Systems theory to understand the behavior of dynamic systems composed of autonomous agents, identify patterns of emergence and adaptation, and explore the implications for strategic decision-making and intervention strategies, supporting Systems Thinking and complexity management approaches.
Whole Systems Design
– An approach to designing and managing systems that considers the interactions and interdependencies among all components and stakeholders. Whole Systems Design seeks to optimize system performance, resilience, and sustainability.
– When designing or redesigning complex systems to achieve desired outcomes. – Implementing Whole Systems Design principles to consider the holistic interactions and interdependencies among system components, stakeholders, and external factors, optimize system performance and sustainability, and align with Systems Thinking principles in strategic decision-making and system design processes.
Holistic Management
– A framework for managing complex systems that emphasizes holistic decision-making, adaptive management, and regenerative practices. Holistic Management integrates ecological, social, and economic considerations to achieve sustainable outcomes.
– When managing natural or social systems with interconnected components. – Applying Holistic Management principles to make decisions that consider the holistic impacts on ecological, social, and economic dimensions, foster adaptive capacity, and promote regenerative practices, aligning with Systems Thinking principles in sustainable management and decision-making processes.
Scenario Planning
– A strategic foresight method that involves developing multiple plausible scenarios of the future based on different assumptions and drivers of change. Scenario Planning enables organizations to anticipate and prepare for future uncertainties and develop flexible long-term strategies.
– When planning for future uncertainties and disruptions. – Engaging in Scenario Planning exercises to explore alternative futures, assess their implications, and develop strategic responses that are robust and adaptable, fostering Systems Thinking and resilience in decision-making and organizational strategy.
Stakeholder Systems Analysis
– A method for mapping and analyzing the relationships and interactions among stakeholders within a system. Stakeholder Systems Analysis helps identify key stakeholders, their interests, and their influence on system dynamics and outcomes.
– When considering the perspectives and interests of stakeholders in system design or management. – Conducting Stakeholder Systems Analysis to map out the relationships and interactions among stakeholders, understand their interests and concerns, and incorporate stakeholder perspectives into decision-making processes, supporting Systems Thinking and stakeholder engagement strategies in system governance and management.
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).
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 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.
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, 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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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 competitorproduct and a decoy product, which is primarily used to nudge the customer toward the target product.
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 – 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.
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