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Mastering the best of what other people have already figured out

Mental Models: The Best Way to Make Intelligent Decisions (~100 Models Explained)

What are mental models.

A mental model is a compression of how something works. Any idea, belief, or concept can be distilled down. Like a map, mental models reveal key information while ignoring irrelevant details. Models concentrate the world into understandable and useable chunks.

Mental models help us understand the world. For example, velocity is a mental model that helps you understand that both speed and direction matter. Reciprocity is a mental model that helps you understand how going positive and going first gets the world to do most of the work for you. Margin of Safety is a mental model that helps you understand that things don’t always go as planned. Relativity is a mental model that shows us we have blind spots and how a different perspective can reveal new information. The list goes on.

Coming October 2024: Pre-order all 4 volumes of The Great Mental Models now.

Eliminating Blind Spots

In life and business, the person with the fewest blind spots wins.

The source of all poor choices is blind spots. Think about it. If you had perfect information, you would always make the best decision. You’d play your hand perfectly in a poker game where you could see everyone’s cards. You wouldn’t make any mistakes.

How do we eliminate blind spots?

The best way to reduce our blind spots is to change our perspective. Just as knowing where to stand can turn a good photo into a great one, changing your perspective on a situation reveals critical information and offers new solutions.

Think of each model as a lens through which you can see the world. Each lens offers a different perspective, revealing new information. Looking through one lens lets you see one thing, and looking through another reveals something different. Looking through them both reveals more than each one individually.

While there are a lot of specific mental models, only a handful of general ones come from the big disciplines. Understanding them positions you to make fewer errors, see things others miss, and take better actions.

Let’s take a look at the best general models.

You’ve got to have models in your head and you’ve got to array you experience – both vicarious and direct – onto this latticework of mental models. Charlie munger

A Latticework of Mental Models

Worldly wisdom is not simply memorizing things and repeating them back. The people that do that fail at work and fail in life. Wisdom is knowing the consequences of your actions, which comes from the alignment between facts and reasoning.

The world is not divided into distinct disciplines. For example, business professors won’t discuss physics in their lectures, but they should. Velocity teaches us that speed and direction matter. Kinetic energy teaches us that velocity matters more than mass when creating a force. Understanding these insights helps you outperform.

In the real world, everything is connected like a latticework. Just because our teachers didn’t show us how to use the big ideas from all the disciplines in life and business doesn’t mean we can’t learn them ourselves. That’s why we created The Great Mental Models project.

Here are the big ideas that can help you make better decisions, avoid problems, and spot opportunities others miss.

• Core Thinking Concepts
• Physics and Chemistry
• Microeconomics
• Military and War
• Human Nature and Judgment

The Core Mental Models

1. The Map is Not the Territory

The map is not the territory is a reminder that our mental models of the world are not the same as the world itself. It’s a caution against confusing our abstractions and representations with the complex, ever-­shifting reality they aim to describe.

Mistaking the maps for the territory is dangerous. Consider the person who has a great résumé and checks all the boxes on paper but can’t do the actual job. Updating our maps is a difficult process of reconciling what we want to be true with what is true.

In many areas of life, we are offered maps by other people. We are reliant on the maps provided by experts, pundits, and teachers. In these cases, the best we can do is to choose our mapmakers wisely, to seek out those who are rigorous, transparent, and open to revision.

Ultimately, the map/territory distinction is an invitation to engage with the world as it is, not just as we imagine it to be. And remember, when you don’t make the map yourself, choose your cartographer wisely.

2. Circle of Competence

The first rule of competition is, you are more likely to win if you play where you have an advantage. Doing so requires a firm understanding of what you know and what you don’t know. Your circle of competence is your personal sphere of expertise, the area where your knowledge and skills are concentrated. It’s the domain where you have a deep understanding, where your judgments are reliable, and your decisions are sound. 

The size of your circle isn’t as important as knowing the boundaries. The wise person is the one who knows the limits of their knowledge, who can say with confidence, “This falls within my circle,” or “This is outside my area of expertise.” 

Operating within your circle of competence is a recipe for confidence and effectiveness. But venturing outside your circle of competence is a recipe for trouble. You’re like a sailor navigating unfamiliar waters without a map, at the mercy of currents and storms you don’t fully understand. This isn’t to say that you should never venture outside your circle. Learning new things, gaining new skills, and mastering new domains is one of the most beautiful things about life. 

Celebrate your expertise, but also acknowledge your limitations.

3. First Principles Thinking First-principles thinking is one of the best ways to reverse-engineer complicated situations and unleash creative possibility. Sometimes called reasoning from first principles, it’s a tool to help clarify complicated problems by separating the underlying ideas or facts from any assumptions based on them. What remains are the essentials. If you know the first principles of something, you can build the rest of your knowledge around them to produce something new.

4. Thought Experiment Thought experiments can be defined as “devices of the imagination used to investigate the nature of things.” Many disciplines, such as philosophy and physics, make use of thought experiments to examine what can be known. In doing so, they can open up new avenues for inquiry and exploration. Thought experiments are powerful because they help us learn from our mistakes and avoid future ones. They let us take on the impossible, evaluate the potential consequences of our actions, and re-examine history to make better decisions. They can help us both figure out what we really want and the best way to get there.

5. Second-Order Thinking Almost everyone can anticipate the immediate results of their actions. This type of first-order thinking is easy and safe, but it’s also a way to ensure you get the same results that everyone else gets. Second-order thinking is thinking farther ahead and thinking holistically. It requires us to consider not only our actions and their immediate consequences but the subsequent effects of those actions as well. Failing to consider the second and third-order effects can unleash disaster.

6. Probabilistic Thinking Probabilistic thinking is essentially trying to estimate, using some tools of math and logic, the likelihood of any specific outcome coming to pass. It is one of the best tools we have to improve the accuracy of our decisions. In a world where each moment is determined by an infinitely complex set of factors, probabilistic thinking helps us identify the most likely outcomes. When we know these, our decisions can be more precise and effective.

7. Inversion Inversion is a powerful tool to improve your thinking because it helps you identify and remove obstacles to success. The root of inversion is “invert,” which means to upend or turn upside down. As a thinking tool, it means approaching a situation from the opposite end of the natural starting point. Most of us tend to think one way about a problem: forward. Inversion allows us to flip the problem around and think backward. Sometimes it’s good to start at the beginning, but it can be more useful to start at the end.

8. Occam’s Razor Simpler explanations are more likely to be true than complicated ones. This is the essence of Occam’s Razor, a classic principle of logic and problem-solving. Instead of wasting your time trying to disprove complex scenarios, you can make decisions more confidently by basing them on the explanation that has the fewest moving parts.

9. Hanlon’s Razor Hard to trace in its origin, Hanlon’s Razor states that we should not attribute to malice that which is more easily explained by stupidity. In a complex world, using this model helps us avoid paranoia and ideology. By not generally assuming that bad results are the fault of a bad actor, we look for options instead of missing opportunities. This model reminds us that people do make mistakes. It demands that we ask if there is another reasonable explanation for the events that have occurred. The explanation most likely to be right is the one that contains the least amount of intent.

The Mental Models of Physics and Chemistry

1. Relativity Relativity has been used in several contexts in the world of physics, but the important aspect to study is the idea that an observer cannot truly understand a system of which he himself is a part. For example, a man inside an airplane does not feel like he is experiencing movement, but an outside observer can see that movement is occurring. This form of relativity tends to affect social systems in a similar way.

2. Reciprocity If I push on a wall, physics tells me that the wall pushes back with equivalent force. In a biological system, if one individual acts on another, the action will tend to be reciprocated in kind. And of course, human beings act with intense reciprocity demonstrated as well.

3. Thermodynamics The laws of thermodynamics describe energy in a closed system. The laws cannot be escaped and underlie the physical world. They describe a world in which useful energy is constantly being lost, and energy cannot be created or destroyed. Applying their lessons to the social world can be a profitable enterprise.

4. Inertia An object in motion with a certain vector wants to continue moving in that direction unless acted upon. This is a fundamental physical principle of motion; however, individuals, systems, and organizations display the same effect. It allows them to minimize the use of energy, but can cause them to be destroyed or eroded.

5. Friction and Viscosity Both friction and viscosity describe the difficulty of movement. Friction is a force that opposes the movement of objects that are in contact with each other, and viscosity measures how hard it is for one fluid to slide over another. Higher viscosity leads to higher resistance. These concepts teach us a lot about how our environment can impede our movement.

6. Velocity Velocity is not equivalent to speed; the two are sometimes confused. Velocity is speed plus vector: how fast something gets somewhere. An object that moves two steps forward and then two steps back has moved at a certain speed but shows no velocity. The addition of the vector, that critical distinction, is what we should consider in practical life.

7. Leverage Most of the engineering marvels of the world were accomplished with applied leverage. As famously stated by Archimedes, “Give me a lever long enough and I shall move the world.” With a small amount of input force, we can make a great output force through leverage. Understanding where we can apply this model to the human world can be a source of great success.

8. Activation Energy A fire is not much more than a combination of carbon and oxygen, but the forests and coal mines of the world are not combusting at will because such a chemical reaction requires the input of a critical level of “activation energy” in order to get a reaction started. Two combustible elements alone are not enough.

9. Catalysts A catalyst either kick-starts or maintains a chemical reaction but isn’t itself a reactant. The reaction may slow or stop without the addition of catalysts. Social systems, of course, take on many similar traits, and we can view catalysts in a similar light.

10. Alloying When we combine various elements, we create new substances. This is no great surprise, but what can be surprising in the alloying process is that 2+2 can equal not 4 but 6 – the alloy can be far stronger than the simple addition of the underlying elements would lead us to believe. This process leads us to engineer great physical objects, but we understand many intangibles in the same way; a combination of the right elements in social systems or even individuals can create a 2+2=6 effect similar to alloying.

The Mental Models of Biology

1. Evolution Part One: Natural Selection and Extinction Evolution by natural selection was once called “the greatest idea anyone ever had.” In the 19th century, Charles Darwin and Alfred Russel Wallace simultaneously realized that species evolve through random mutation and differential survival rates. If we call human intervention in animal breeding an example of “artificial selection,” we can call Mother Nature deciding the success or failure of a particular mutation “natural selection.” Those best suited for survival tend to be preserved. But of course, conditions change.

2. Evolution Part Two:  Adaptation and The Red Queen Effect   Species tend to adapt to their surroundings in order to survive, given the combination of their genetics and their environment – an always-unavoidable combination. However, adaptations made in an individual’s lifetime are not passed down genetically, as was once thought:  Populations of species adapt through the process of evolution by natural selection, as the most-fit examples of the species replicate at an above-average rate.

The evolution-by-natural-selection model leads to something of an arms race among species competing for limited resources. When one species evolves an advantageous adaptation, a competing species must respond in kind or fail as a species. Standing still can mean falling behind. This arms race is called the Red Queen Effect for the character in Alice in Wonderland who said, “Now, here, you see, it takes all the running you can do, to keep in the same place.”

3. Ecosystems An ecosystem describes any group of organisms coexisting with the natural world. Most ecosystems show diverse forms of life taking on different approaches to survival, with such pressures leading to varying behavior. Social systems can be seen in the same light as the physical ecosystems and many of the same conclusions can be made.

4. Niches Most organisms find a niche: a method of competing and behaving for survival. Usually, a species will select a niche for which it is best adapted. The danger arises when multiple species begin competing for the same niche, which can cause an extinction – there can be only so many species doing the same thing before limited resources give out.

5. Self-Preservation  Without a strong self-preservation instinct in an organism’s DNA, it would tend to disappear over time, thus eliminating that DNA. While cooperation is another important model, the self-preservation instinct is strong in all organisms and can cause violent, erratic, and/or destructive behavior for those around them.

6. Replication A fundamental building block of diverse biological life is high-fidelity replication. The fundamental unit of replication seems to be the DNA molecule, which provides a blueprint for the offspring to be built from physical building blocks. There are a variety of replication methods, but most can be lumped into sexual and asexual.

7. Cooperation  Competition tends to describe most biological systems, but cooperation at various levels is just as important a dynamic. In fact, the cooperation of a bacterium and a simple cell probably created the first complex cell and all of the life we see around us. Without cooperation, no group survives, and the cooperation of groups gives rise to even more complex versions of organization. Cooperation and competition tend to coexist at multiple levels.

The Prisoner’s Dilemma is a famous application of game theory in which two prisoners are both better off cooperating with each other, but if one of them cheats, the other is better off cheating. Thus the dilemma. This model shows up in economic life, in war, and in many other areas of practical human life. Though the prisoner’s dilemma theoretically leads to a poor result, in the real world, cooperation is nearly always possible and must be explored.

8. Hierarchical  Organization Most complex biological organisms have an innate feel for how they should organize. While not all of them end up in hierarchical structures, many do, especially in the animal kingdom. Human beings like to think they are outside of this, but they feel the hierarchical instinct as strongly as any other organism. This includes the Stanford Prison Experiment and Milgram Experiments, which demonstrated what humans learned practically many years before: the human bias towards being influenced by authority. In a dominance hierarchy such as ours, we tend to look to the leader for guidance on behavior, especially in situations of stress or uncertainty. Thus, authority figures have a responsibility to act well, whether they like it or not.

9. Incent ives All creatures respond to incentives to keep themselves alive. This is the basic insight of biology. Constant incentives will tend to cause a biological entity to have constant behavior to an extent. Humans are included and are particularly great examples of the incentive-driven nature of biology; however, humans are complicated in that their incentives can be hidden or intangible. The rule of life is to repeat what works and has been rewarded.

10. Tendency to Minimize Energy Output (Mental and physical) In a physical world governed by thermodynamics and competition for limited energy and resources, any biological organism that was wasteful with energy would be at a severe disadvantage for survival. Thus, we see in most instances that behavior is governed by a tendency to minimize energy usage when at all possible.

The Mental Models of Systems Thinking

1. Feedback L oops  All complex systems are subject to positive and negative feedback loops whereby A causes B, which in turn influences A (and C), and so on – with higher-order effects frequently resulting from the continual movement of the loop. In a homeostatic system, a change in A is often brought back into line by an opposite change in B to maintain the balance of the system, as with the temperature of the human body or the behavior of an organizational culture. Automatic feedback loops maintain a “static” environment unless and until an outside force changes the loop. A “runaway feedback loop” describes a situation in which the output of a reaction becomes its own catalyst (auto-catalysis).

2. Equilibrium Homeostasis is the process through which systems self-regulate to maintain an equilibrium state that enables them to function in a changing environment. Most of the time, they over or undershoot it by a little and must keep adjusting. Like a pilot flying a plane, the system is off course more often than on course. Everything within a homeostatic system contributes to keeping it within a range of equilibrium, so it is important to understand the limits of the range.

3. Bottlenecks A bottleneck describes the place at which a flow (of a tangible or intangible) is stopped, thus constraining it from continuous movement. As with a clogged artery or a blocked drain, a bottleneck in the production of any good or service can be small but have a disproportionate impact if it is in the critical path. However, bottlenecks can also be a source of inspiration as they force us to reconsider if there are alternate pathways to success.

4. Scale One of the most important principles of systems is that they are sensitive to scale. Properties (or behaviors) tend to change when you scale them up or down. In studying complex systems, we must always be roughly quantifying – in orders of magnitude, at least – the scale at which we are observing, analyzing, or predicting the system.

5. Margin of Safety   Similarly, engineers have also developed the habit of adding a margin for error into all calculations. In an unknown world, driving a 9,500-pound bus over a bridge built to hold precisely 9,600 pounds is rarely seen as intelligent. Thus, on the whole, few modern bridges ever fail. In practical life outside of physical engineering, we can often profitably give ourselves margins as robust as the bridge system.

6. Churn Churn is the silent killer of businesses. It’s the slow leak, the constant drip of customers slipping away, of users drifting off to find something new. It’s the attrition that eats away at your growth, that forces you to keep running just to stay in place. The thing about churn is that it’s often hidden. It’s not like a sudden crisis that grabs your attention. It’s a slow, quiet process that happens in the background.

Churn can present opportunity. Like a snake shedding its skin, replacing components of a system is a natural part to keeping it healthy. New parts can improve functionality.

When we use this model as a lens, we see that new people bring new ideas, and counterintuitively, some turnover allows us to maintain stability. Replacing what is worn out also allows us to upgrade and expand our capabilities, creating new opportunities. 

Some churn is inevitable. Too much can kill you.

7. Algorithms Algorithms are recipes. A list of crisp, unambiguous steps that tell you how to get from point A to point B. But they’re more than just directions. Algorithms are if‑then machines for tuning out the noise and zeroing in on the signal. Have the specs been met? Follow the algorithm and find out. Thinking algorithmically means searching for processes that reliably spit out the results you want, like a vending machine dispensing the same candy bar every time someone punches in E4. 

8. Critical mass Critical mass isn’t just a science term; it’s a guide for understanding that often things happen slowly and then all at once. It’s the moment when a system goes from sputtering along to explosive growth. Like a nuclear chain reaction, once you hit critical mass, the reaction becomes self-sustaining.

Through this lens we gain insight into the amount of material needed for a system to change from one state to another. Material can be anything from people and effort to raw material. When enough material builds up, systems reach their tipping point. When we keep going, we get sustainable change.

Using critical mass as a lens for situations in which you want different outcomes helps you identify both the design elements you need to change and the work you need to put in. 

9. Emergence Nearly everything is an emergent effect— table, a space shuttle, even us— combinations of ingredients that come together in a specific way to create something new. Emergence is the universe’s way of reminding us that when we combine different pieces in new ways, we get results that are more than the sum of their parts, often in the most unexpected and thrilling ways. 

Using this mental model is not about trying to predict emergent properties but rather acknowledging they are possible. There is no need to stick with what you know; mix it up and see what happens. Learn new skills, interact with new people, read new things.

10. Irreducibility  Irreducibility is about essence. It’s the idea that some things can’t be broken down into smaller parts without losing what makes them tick. It’s the idea that not everything can be explained by looking at its components. Emergent properties arise from complex systems that can’t be predicted by studying the individual parts.

Grappling with irreducibility requires a shift in thinking. Instead of trying to break things down, sometimes you have to zoom out. Look at the big picture. Embrace the complexity. Because some problems don’t have neat, modular solutions. They’re irreducibly messy.

Using irreducibility as a lens helps you focus on what you can change by understanding what really matters. 

11. Law of Diminishing Returns Diminishing returns is the idea that the easy wins usually come first. The more you optimize a system, the harder it gets to eke out additional improvements. Like squeezing juice from a lemon. The first squeeze is easy. The second takes a bit more work. By the tenth squeeze, you’re fighting for every last drop.

When you’re a beginner, every bit of effort translates into significant gains. But as you level up, progress becomes more incremental. It takes more and more work to get better and better. That’s why going from good to great is often harder than going from bad to good.

Understanding diminishing returns is crucial for allocating resources efficiently. You want to focus on the areas where you can get the biggest bang for your buck. Sometimes, that means knowing when to stop optimizing and move on to something else. 

The Mental Models of Numeracy

1. Distributions The normal distribution is a statistical process that leads to the well-known graphical representation of a bell curve, with a meaningful central “average” and increasingly rare standard deviations from that average when correctly sampled. (The so-called “central limit” theorem.) Well-known examples include human height and weight, but it’s just as important to note that many common processes, especially in non-tangible systems like social systems, do not follow this pattern. Normal distributions can be contrasted with power law, or exponential, distributions.

2. Compounding Compounding is the magic of exponential growth. It’s the idea that small, consistent gains can snowball into massive results over time. Like a tiny snowball rolling down a hill, picking up more and more snow until it’s an avalanche.

Compounding requires us to think long- term about our knowledge, experiences, and relationships. It tells us that the small stuff we learn, the people we meet, and the connections we deepen, when reinvested into our lives, build up our fortunes in wisdom and relationships, not by chance, but by the steady, patient accumulation of efforts. The majority of success doesn’t happen by accident, and the lens of compounding illuminates the investments we need to make to get there.

Compounding is how you turn ordinary into extraordinary, one tiny gain at a time. 

3. Sampling When we want to get information about a population (meaning a set of alike people, things, or events), we usually need to look at a sample (meaning a part of the population). It is usually not possible or even desirable to consider the entire population, so we aim for a sample that represents the whole. As a rule of thumb, more measurements mean more accurate results, all else being equal. Small sample sizes can produce skewed results.

4. Randomness Though the human brain has trouble comprehending it, much of the world is composed of random, non-sequential, non-ordered events. We are “fooled” by random effects when we attribute causality to things that are actually outside of our control. If we don’t course-correct for this fooled-by-randomness effect – our faulty sense of pattern-seeking – we will tend to see things as being more predictable than they are and act accordingly.

5. Regression to the Mean In a normally distributed system, long deviations from the average will tend to return to that average with an increasing number of observations: the so-called Law of Large Numbers. We are often fooled by regression to the mean, as with a sick patient improving spontaneously around the same time they begin taking an herbal remedy, or a poorly performing sports team going on a winning streak. We must be careful not to confuse statistically likely events with causal ones.

6. Multiplying by Zero Any reasonably educated person knows that any number multiplied by zero, no matter how large the number, is still zero. This is true in human systems as well as mathematical ones. In some systems, a failure in one area can negate great effort in all other areas. As simple multiplication would show, fixing the “zero” often has a much greater effect than does trying to enlarge the other areas.

7. Equivalence The introduction of algebra allowed us to demonstrate mathematically and abstractly that two seemingly different things could be the same. By manipulating symbols, we can demonstrate equivalence or inequivalence, the use of which led humanity to untold engineering and technical abilities. Knowing at least the basics of algebra can allow us to understand a variety of important results.

8. Surface Area The surface area of a three dimensional object is the amount of space on the outside of it. Thus, the more surface area you have, the more contact you have with your environment. Sometimes a high surface area is desirable: Our lungs and intestines have a huge surface area to increase the absorption of oxygen and nutrients. Other times we want to reduce our exposure, such as limiting our internet exposure to reduce the attack surface.

9. Global and Local Maxima The maxima and minima of a mathematical function are the largest and smallest values over its domain. Although there is one maximum value, the global maximum, there can be smaller peaks of value in a given range, the local maxima. Global and local maxima help us identify peaks, and if there is still potential to go higher or lower. It also reminds us that sometimes we have to go down to go back up.

The Mental Models of Microeconomics

1. Opportunity Costs Doing one thing means not being able to do another. We live in a world of trade-offs, and the concept of opportunity cost rules all. Most aptly summarized as “there is no such thing as a free lunch.”

2. Creative Destruction Coined by economist Joseph Schumpeter, the term “creative destruction” describes the capitalistic process at work in a functioning free-market system. Motivated by personal incentives (including but not limited to financial profit), entrepreneurs will push to best one another in a never-ending game of creative one-upmanship, in the process destroying old ideas and replacing them with newer technology. Beware getting left behind.

3.  Comparative Advantage The Scottish economist David Ricardo had an unusual and non-intuitive insight: Two individuals, firms, or countries could benefit from trading with one another even if one of them was better at everything. Comparative advantage is best seen as an applied opportunity cost: If it has the opportunity to trade, an entity gives up free gains in productivity by not focusing on what it does best.

4. Specialization (Pin Factory) Another Scottish economist, Adam Smith, highlighted the advantages gained in a free-market system by specialization. Rather than having a group of workers each producing an entire item from start to finish, Smith explained that it’s usually far more productive to have each of them specialize in one aspect of production. He also cautioned, however, that each worker might not enjoy such a life; this is a trade-off of the specialization model.

5. Seizing the Middle In chess, the winning strategy is usually to seize control of the middle of the board, so as to maximize the potential moves that can be made and control the movement of the maximal number of pieces. The same strategy works profitably in business, as can be demonstrated by John D. Rockefeller’s control of the refinery business in the early days of the oil trade and Microsoft’s control of the operating system in the early days of the software trade.

6. Trademarks, Patents, and Copyrights These three concepts, along with other related ones, protect the creative work produced by enterprising individuals, thus creating additional incentives for creativity and promoting the creative-destruction model of capitalism. Without these protections, information and creative workers have no defense against their work being freely distributed.

7. Double-Entry Bookkeeping One of the marvels of modern capitalism has been the bookkeeping system introduced in Genoa in the 14th century. The double-entry system requires that every entry, such as income, also be entered into another corresponding account. Correct double-entry bookkeeping acts as a check on potential accounting errors and allows for accurate records and thus, more accurate behavior by the owner of a firm.

8. Utility (Marginal, Diminishing, Increasing) The usefulness of additional units of any good tends to vary with scale. Marginal utility allows us to understand the value of one additional unit, and in most practical areas of life, that utility diminishes at some point. On the other hand, in some cases, additional units are subject to a “critical point” where the utility function jumps discretely up or down. As an example, giving water to a thirsty man has diminishing marginal utility with each additional unit, and can eventually kill him with enough units.

9. Bribery Often ignored in mainstream economics, the concept of bribery is central to human systems: Given the chance, it is often easier to pay a certain agent to look the other way than to follow the rules. The enforcer of the rules is then neutralized. This principal/agent problem can be seen as a form of arbitrage.

10. Arbitrage Given two markets selling an identical good, an arbitrage exists if the good can profitably be bought in one market and sold at a profit in the other. This model is simple on its face, but can present itself in disguised forms: The only gas station in a 50-mile radius is also an arbitrage as it can buy gasoline and sell it at the desired profit (temporarily) without interference. Nearly all arbitrage situations eventually disappear as they are discovered and exploited.

11. Supply and Demand The basic equation of biological and economic life is one of limited supply of necessary goods and competition for those goods. Just as biological entities compete for limited usable energy, so too do economic entities compete for limited customer wealth and limited demand for their products. The point at which supply and demand for a given good are equal is called an equilibrium; however, in practical life, equilibrium points tend to be dynamic and changing, never static.

12. Scarcity Game theory describes situations of conflict, limited resources, and competition. Given a certain situation and a limited amount of resources and time, what decisions are competitors likely to make, and which should they make? One important note is that traditional game theory may describe humans as more rational than they really are. Game theory is theory, after all.

13. Mr. Market Mr. Market was introduced by the investor Benjamin Graham in his seminal book The Intelligent Investor to represent the vicissitudes of the financial markets. As Graham explains, the markets are a bit like a moody neighbor, sometimes waking up happy and sometimes waking up sad – your job as an investor is to take advantage of him in his bad moods and sell to him in his good moods. This attitude is contrasted to an efficient-market hypothesis in which Mr. Market always wakes up in the middle of the bed, never feeling overly strong in either direction.

The Mental Models of Military and War

1. Seeing the Front One of the most valuable military tactics is the habit of “personally seeing the front” before making decisions – not always relying on advisors, maps, and reports, all of which can be either faulty or biased. The Map/Territory model illustrates the problem with not seeing the front, as does the incentive model. Leaders of any organization can generally benefit from seeing the front, as not only does it provide firsthand information, but it also tends to improve the quality of secondhand information.

2. Asymmetric Warfare The asymmetry model leads to an application in warfare whereby one side seemingly “plays by different rules” than the other side due to circumstance. Generally, this model is applied by an insurgency with limited resources. Unable to out-muscle their opponents, asymmetric fighters use other tactics, as with terrorism creating fear that’s disproportionate to their actual destructive ability.

3. Two-Front War The Second World War was a good example of a two-front war. Once Russia and Germany became enemies, Germany was forced to split its troops and send them to separate fronts, weakening their impact on either front. In practical life, opening a two-front war can often be a useful tactic, as can solving a two-front war or avoiding one, as in the example of an organization tamping down internal discord to focus on its competitors.

4. Counterinsurgency Though asymmetric insurgent warfare can be extremely effective, over time competitors have also developed counterinsurgency strategies. Recently and famously, General David Petraeus of the United States led the development of counterinsurgency plans that involved no additional force but substantial additional gains. Tit-for-tat warfare or competition will often lead to a feedback loop that demands insurgency and counterinsurgency.

5. Mutually Assured Destruction Somewhat paradoxically, the stronger two opponents become, the less likely they may be to destroy one another. This process of mutually assured destruction occurs not just in warfare, as with the development of global nuclear warheads, but also in business, as with the avoidance of destructive price wars between competitors. However, in a fat-tailed world, it is also possible that mutually assured destruction scenarios simply make destruction more severe in the event of a mistake (pushing destruction into the “tails” of the distribution).

The Mental Models of Human Nature and Judgment

1. Trust Fundamentally, the modern world operates on trust. Familial trust is generally a given (otherwise we’d have a hell of a time surviving), but we also choose to trust chefs, clerks, drivers, factory workers, executives, and many others. A trusting system is one that tends to work most efficiently; the rewards of trust are extremely high.

2. Bias from Incentives Highly responsive to incentives, humans have perhaps the most varied and hardest to understand set of incentives in the animal kingdom. This causes us to distort our thinking when it is in our own interest to do so. A wonderful example is a salesman truly believing that his product will improve the lives of its users. It’s not merely convenient that he sells the product; the fact of his selling the product causes a very real bias in his own thinking.

3. Pavlovian Association Ivan Pavlov very effectively demonstrated that animals can respond not just to direct incentives but also to associated objects; remember the famous dogs salivating at the ring of a bell. Human beings are much the same and can feel positive and negative emotion towards intangible objects, with the emotion coming from past associations rather than direct effects.

4.  Tendency to Feel Envy & Jealousy Humans have a tendency to feel envious of those receiving more than they are, and a desire “get what is theirs” in due course. The tendency towards envy is strong enough to drive otherwise irrational behavior, but is as old as humanity itself. Any system ignorant of envy effects will tend to self-immolate over time.

5.  Tendency to Distort Due to Liking/Loving or  Disliking/Hating Based on past association, stereotyping, ideology, genetic influence, or direct experience, humans have a tendency to distort their thinking in favor of people or things that they like and against people or things they dislike. This tendency leads to overrating the things we like and underrating or broadly categorizing things we dislike, often missing crucial nuances in the process.

6. Denial  Anyone who has been alive long enough realizes that, as the saying goes, “denial is not just a river in Africa.” This is powerfully demonstrated in situations like war or drug abuse, where denial has powerful destructive effects but allows for behavioral inertia. Denying reality can be a coping mechanism, a survival mechanism, or a purposeful tactic.

7.  Availability Heuristic One of the most useful findings of modern psychology is what Daniel Kahneman calls the Availability Bias or Heuristic: We tend to most easily recall what is salient, important, frequent, and recent. The brain has its own energy-saving and inertial tendencies that we have little control over – the availability heuristic is likely one of them. Having a truly comprehensive memory would be debilitating. Some sub-examples of the availability heuristic include the Anchoring and Sunk Cost Tendencies.

8. Representativeness Heuristic The three major psychological findings that fall under Representativeness, also defined by Kahneman and his partner Tversky, are:

a. Failure to Account for Base Rates An unconscious failure to look at past odds in determining current or future behavior.

b. Tendency to Stereotype  The tendency to broadly generalize and categorize rather than look for specific nuance. Like availability, this is generally a necessary trait for energy-saving in the brain.

c. Failure to See False Conjunctions Most famously demonstrated by the Linda Test, the same two psychologists showed that students chose more vividly described individuals as more likely to fit into a predefined category than individuals with broader, more inclusive, but less vivid descriptions, even if the vivid example was a mere subset of the more inclusive set. These specific examples are seen as more representative of the category than those with the broader but vaguer descriptions, in violation of logic and probability.

9.  Social Proof (Safety in Numbers) Human beings are one of many social species, along with bees, ants, and chimps, among many more. We have a DNA-level instinct to seek safety in numbers and will look for social guidance of our behavior. This instinct creates a cohesive sense of cooperation and culture which would not otherwise be possible but also leads us to do foolish things if our group is doing them as well.

10.  Narrative Instinct Human beings have been appropriately called “the storytelling animal” because of our instinct to construct and seek meaning in narrative. It’s likely that long before we developed the ability to write or to create objects, we were telling stories and thinking in stories. Nearly all social organizations, from religious institutions to corporations to nation-states, run on constructions of the narrative instinct.

11. Curiosity Instinct We like to call other species curious, but we are the most curious of all, an instinct which led us out of the savanna and led us to learn a great deal about the world around us, using that information to create the world in our collective minds. The curiosity instinct leads to unique human behavior and forms of organization like the scientific enterprise. Even before there were direct incentives to innovate, humans innovated out of curiosity.

12. Language Instinct The psychologist Steven Pinker calls our DNA-level instinct to learn grammatically constructed language the Language Instinct. The idea that grammatical language is not a simple cultural artifact was first popularized by the linguist Noam Chomsky. As we saw with the narrative instinct, we use these instincts to create shared stories, as well as to gossip, solve problems, and fight, among other things. Grammatically ordered language theoretically carries infinite varying meaning.

13. First-Conclusion Bias As Charlie Munger famously pointed out, the mind works a bit like a sperm and egg: the first idea gets in and then the mind shuts. Like many other tendencies, this is probably an energy-saving device. Our tendency to settle on first conclusions leads us to accept many erroneous results and cease asking questions; it can be countered with some simple and useful mental routines.

14.  Tendency to Overgeneralize from Small Samples It’s important for human beings to generalize; we need not see every instance to understand the general rule, and this works to our advantage. With generalizing, however, comes a subset of errors when we forget about the Law of Large Numbers and act as if it does not exist. We take a small number of instances and create a general category, even if we have no statistically sound basis for the conclusion.

15. Relative Satisfaction/Misery Tendencies The envy tendency is probably the most obvious manifestation of the relative satisfaction tendency, but nearly all studies of human happiness show that it is related to the state of the person relative to either their past or their peers, not absolute. These relative tendencies cause us great misery or happiness in a very wide variety of objectively different situations and make us poor predictors of our own behavior and feelings.

16.  Commitment & Consistency Bias As psychologists have frequently and famously demonstrated, humans are subject to a bias towards keeping their prior commitments and staying consistent with our prior selves when possible. This trait is necessary for social cohesion: people who often change their conclusions and habits are often distrusted. Yet our bias towards staying consistent can become, as one wag put it, a “hobgoblin of foolish minds” – when it is combined with the first-conclusion bias, we end up landing on poor answers and standing pat in the face of great evidence.

17.  Hindsight Bias Once we know the outcome, it’s nearly impossible to turn back the clock mentally. Our narrative instinct leads us to reason that we knew it all along (whatever “it” is), when in fact we are often simply reasoning post-hoc with information not available to us before the event. The hindsight bias explains why it’s wise to keep a journal of important decisions for an unaltered record and to re-examine our beliefs when we convince ourselves that we knew it all along.

18.  Sensitivity to Fairness Justice runs deep in our veins. In another illustration of our relative sense of well-being, we are careful arbiters of what is fair. Violations of fairness can be considered grounds for reciprocal action, or at least distrust. Yet fairness itself seems to be a moving target. What is seen as fair and just in one time and place may not be in another. Consider that slavery has been seen as perfectly natural and perfectly unnatural in alternating phases of human existence.

19. Tendency to Overestimate Consistency of Behavior ( Fundamental Attribution Error ) We tend to over-ascribe the behavior of others to their innate traits rather than to situational factors, leading us to overestimate how consistent that behavior will be in the future. In such a situation, predicting behavior seems not very difficult. Of course, in practice this assumption is consistently demonstrated to be wrong, and we are consequently surprised when others do not act in accordance with the “innate” traits we’ve endowed them with.

20. Influence of Stress (Including Breaking Points) Stress causes both mental and physiological responses and tends to amplify the other biases. Almost all human mental biases become worse in the face of stress as the body goes into a fight-or-flight response, relying purely on instinct without the emergency brake of Daniel Kahneman’s “System 2” type of reasoning. Stress causes hasty decisions, immediacy, and a fallback to habit, thus giving rise to the elite soldiers’ motto: “In the thick of battle, you will not rise to the level of your expectations, but fall to the level of your training.”

21. Survivorship Bias A major problem with historiography – our interpretation of the past – is that history is famously written by the victors. We do not see what Nassim Taleb calls the “silent grave” – the lottery ticket holders who did not win. Thus, we over-attribute success to things done by the successful agent rather than to randomness or luck, and we often learn false lessons by exclusively studying victors without seeing all of the accompanying losers who acted in the same way but were not lucky enough to succeed.

22.  Tendency to Want to Do Something (Fight/Flight, Intervention, Demonstration of Value, etc.) We might term this Boredom Syndrome: Most humans have the tendency to need to act, even when their actions are not needed. We also tend to offer solutions even when we do not have knowledge to solve the problem.

23. Falsification / Confirmation Bias What a man wishes, he also believes. Similarly, what we believe is what we choose to see. This is commonly referred to as the confirmation bias. It is a deeply ingrained mental habit, both energy-conserving and comfortable, to look for confirmations of long-held wisdom rather than violations. Yet the scientific process – including hypothesis generation, blind testing when needed, and objective statistical rigor – is designed to root out precisely the opposite, which is why it works so well when followed.

The modern scientific enterprise operates under the principle of falsification: A method is termed scientific if it can be stated in such a way that a certain defined result would cause it to be proved false. Pseudo-knowledge and pseudo-science operate and propagate by being unfalsifiable – as with astrology, we are unable to prove them either correct or incorrect because the conditions under which they would be shown false are never stated.

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Mental models: 13 thinking tools to boost your problem-solving skills

Imagine you've gone out to dinner with friends. You’ve just sat down at your favorite table at your favorite restaurant, looking forward to the evening ahead.

The waiter brings over your menus and tells you about the specials. It sounds like one of the dishes is really good — you've always wanted to try it, and the way they've described it sounds amazing.

You're mulling it over in your mind while the others order, and then it's your turn — and you just ask for the same meal you always get.

Sound familiar?

Whether it’s your favorite meal or the perfectly worn-in pair of jeans in your closet, this tendency to fall back on what we know rather than risk something unknown is the result of a common thinking tool called a mental model.

Mental models, like the status quo bias in the scenario above, represent how we perceive something to operate in the world based on what we have learned in our lives. We all use them to help us understand complex situations and predict what will happen. If leveraged well, they can be powerful thinking tools.

This article will explore the concept of mental models as thinking tools and uncover 13 mental models you can add to your toolkit of thinking skills.

Mental models as thinking tools

Most of the time, we're not as thoughtful as we think. While many of us consider ourselves capable of critical thinking, researchers say we tend to make snap judgments without using our knowledge.

For example, let’s try an exercise. Take a look at this image:

Did you immediately react based on what you think is about to happen?

Although there isn’t a picture showing what takes place next, most of us made a guess using a tool we weren't even aware of — a mental model. Through our mental model, we could predict a possible outcome (which hopefully didn’t involve any scratches or falls).

Many of our snap judgments and reactions — whether about a photo we see or a problem we encounter — are shaped by the mental models we use to view the world. We begin to develop mental models as soon as we are born and continue to develop them throughout our lives, using them as a thinking tool to make sense of life, solve problems, and make decisions.

We all start out with different sets of mental models — after all, we all have different experiences that shape our early lives. As we gain experiences and knowledge, we add more models to our toolkit and learn to see things in new ways.

Sometimes our mental models work against us. If we limit our thinking to only a few mental models, we can suffer from critical thinking barriers . However, when we actively pursue thoughtful learning and collect many mental models, they can be extremely valuable tools for critical and creative thinking.

Munger's Latticework of Mental Models

Mental models as thinking tools were first made popular by Charlie Munger in his 1995 " The Psychology of Human Misjudgment " speech at Harvard University. Entrepreneurs and thinkers have since embraced mental models to achieve success.

According to Munger's Latticework of Mental Models theory, we can use various thinking tools to see problems from several points of view. Combining mental models increases original thinking, creativity, and problem-solving skills instead of relying on one frame of reference.

As Munger said , "All the wisdom of the world is not to be found in one little academic department ... 80 or 90 important models will carry about 90 percent of the freight in making you a worldly-wise person. And, of those, only a mere handful really carry very heavy freight."

This is why we need to keep learning — to expand our toolbox. The more mental models we have in our toolkit, the easier it is to find one that works for the situation.

A well-stocked toolbox is more effective at solving a problem than a single nail.

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13 valuable tools for your thinking skills toolkit

There are hundreds of mental models and thinking tools available, which can be overwhelming. Most of us are familiar with concepts like the Eisenhower Matrix and brainstorming. However, we can use many other mental models for creative and critical thinking. Here are 13 thinking tools to boost decision-making, problem-solving, and creative thinking skills.

1. First Principles

First principle thinking is a mental model that can be used for problem-solving by breaking things down to the most basic level. This thinking tool is based on the idea that all complex problems can be reduced to more specific, fundamental parts. Using first-principles thinking, you identify the underlying causes of a problem and then find the best solutions that address those root causes.

For instance, it would be impossible to pack up your entire house at once if you were moving. To pack efficiently and safely, you’d need to go room by room, tackling one room at a time.

2. Inversion

Inversion is a technique used to generate ideas of creative solutions to problems by imagining the opposite of them. Inversion is higher-order thinking that requires thinking about the solution you don't want. With inverted thinking, you consider how something might fail and then try to avoid those mistakes. This approach differs from "working backward," another way of doing things that encourages you to begin with the desired end solution in mind.

3. Occam's Razor

Occam's Razor is a mental model that can simplify complex problems and situations by determining which explanation is most likely. This thinking tool is based on the principle that the simplest answer is usually correct. When using Occam's Razor, you should look for the most obvious, straightforward reasoning that fits all facts.

4. Bloom's Taxonomy

Bloom's Taxonomy is a mental model used for categorizing the knowledge levels of learners. The cognitive, affective, and psychomotor learning domains are grouped into three hierarchical levels, with each level encompassing the previous one. In a hierarchical structure, areas of knowledge begin with simple skills and progress to higher-order thinking.

The six levels of Bloom's Taxonomy are:

• Knowledge: Recalling or recognizing facts and information
• Comprehension: Understanding the meaning of information
• Application: Using information in new ways
• Analysis: Breaking down information into smaller parts
• Synthesis: Putting pieces of information together to form a new whole
• Evaluation: Making judgments about the value of information

By applying the actions from each level of this tool, we can analyze situations from different angles and find more comprehensive solutions.

5. Incentives

Incentives are a model that can be used to encourage desired behavior. Based on a cause and effect concept, people will be more likely to act if they are given an incentive to do so. The incentives can be monetary, such as a bonus or commission, or non-monetary, such as recognition or privileges.

6. Fundamental Attribution Error

The fundamental attribution error is characterized by the tendency to focus too much on personal characteristics and not enough on circumstances when judging others. This mental model believes that people's actions reflect who they are without considering their point of view. This can lead to misunderstanding and conflict.

For example, it's easy to get angry and lash out at someone who cuts you off in traffic without considering that maybe they are rushing to the hospital for an emergency. Keeping this model in mind can help us avoid over-simplifying behavior.

7. Law of Diminishing Returns

The Law of Diminishing Returns provides a way to determine when it’s no longer efficient to continue investing in something. This thinking tool is based on the idea that there’s a point at which additional investment in something will result in diminishing returns.

The law of diminishing returns is often used in higher-level business decisions to determine when to stop investing in a project, but it’s also used in other forms of decision-making. Research has found that decision-makers tend to use a "matching" strategy in which they make their choice based on the relative value each option has.

8. Redundancy

The redundancy theory suggests that learners retain less new knowledge if the same information is presented in multiple ways or if it’s unnecessarily elaborate. Studies have shown that using several sources to relay information, such as text, visuals, and audio can create a lack of focus and less learning. Integrating the redundancy model can help teachers and leaders make learning more efficient.

9. Hanlon's Razor

Hanlon's Razor is a mental model that suggests most mistakes are not made maliciously. The purpose of this tool is to remind us not to assume the worst in the actions of others. Hanlon's Razor can help us see the situation from another's point of view and have more empathy, therefore avoiding making wrong assumptions.

For example, friends who aren't answering their mobile phones most likely aren't mad at you. Maybe they're just busy, or perhaps there are various other reasons to explain their delay.

10. Common Knowledge

We usually think of common knowledge as universal facts most people understand. However, the mental model of common knowledge is a little different. Used as a thinking tool, it focuses on pooling together the knowledge we don't share and taking into account the wisdom of others to help us make better decisions. Brainstorming, creating concept maps, and integrating feedback are useful tools we can use to share common knowledge.

11. Survivorship Bias

Survivorship bias refers to the tendency to focus on successful people, businesses, and strategies while overlooking failed ones.

For example, the idea that all 21st-century Hollywood stars got there through hard work may underestimate the amount of networking used to achieve fame. The idea dismisses the millions of other actors who worked just as hard but didn't have the same connections.

This thinking process can lead to decision-making errors because it causes people to overestimate their chances of success. However, when used to frame thinking, understanding the survivorship bias can help us consider other points of view and avoid making incorrect decisions.

12. The Ladder of Inference

The Ladder of Inference is a mental model that helps explain why we make judgments quickly and unconsciously. The ladder illustrates the rapid steps our minds go through to make decisions and take action in any given situation. The seven steps are:

• Observations: The data or information that we carry in through our senses
• Selected Data: The process of our brain choosing which information is important and which to ignore
• Meanings: Making interpretations and judgments based on our experiences, beliefs, and values
• Assumptions: The views or beliefs that we hold that help us interpret the facts
• Conclusions: The decision or opinion that we form based on our assumptions
• Beliefs: The convictions that we have about ourselves and the world around us
• Actions: The way we act or respond based on our thoughts

Using the Ladder of Inference as a thinking tool can help us avoid rash judgments based on assumptions and ensure sound thinking.

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13. 80/20 Rule

The 80/20 Rule is a thinking tool that we can use to understand the relationship between inputs and outputs. This model is based on the idea that 80% of the results come from 20% of the effort. The 80/20 rule can be used to decide how to allocate resources.

Thinking tools are essential for a learner's toolkit

Every lifelong learner should have a toolbox of thinking tools. Mental models are helpful thinking tools that can enhance the creative and critical thinking processes. By having more tools at your disposal, you can approach any situation from various angles, increasing the probability of finding a successful solution.

Remember — building your thinking toolkit is an ongoing process. Keep learning, and you'll soon find that you're making better decisions consistently and solving problems more quickly.

I hope you have enjoyed reading this article. Feel free to share, recommend and connect 🙏

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Erin E. Rupp

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Mental Models: Learn How to Think Better and Gain a Mental Edge

Definition: what are mental models.

Let’s start with a definition. What are mental models? A mental model is an explanation of how something works. The phrase “mental model” is an overarching term for any sort of concept, framework, or worldview that you carry around in your mind.

Mental models help you understand life. For example, supply and demand is a mental model that helps you understand how the economy works. Game theory is a mental model that helps you understand how relationships and trust work. Entropy is a mental model that helps you understand how disorder and decay work.

Mental models also guide your perception and behavior. They are the thinking tools that you use to understand life, make decisions, and solve problems. Learning a new mental model gives you a new way to see the world—like Richard Feynman learning a new math technique.

Mental models are imperfect, but useful. There is no single mental model from physics or engineering, for example, that provides a flawless explanation of the entire universe, but the best mental models from those disciplines have allowed us to build bridges and roads, develop new technologies, and even travel to outer space. As historian Yuval Noah Harari puts it, “Scientists generally agree that no theory is 100 percent correct. Thus, the real test of knowledge is not truth, but utility.”

The best mental models are the ideas with the most utility. They are broadly useful in daily life. Understanding these concepts will help you make wiser choices and take better actions. This is why developing a broad base of mental models is critical for anyone interested in thinking clearly, rationally, and effectively.

Mental Models Example

How to Train Your Brain to Think in New Ways – This article shares some useful examples of how mental models work (and how the right mental model can make a big difference).

The Big Mental Models

There are thousands of mental models, but the best ones apply broadly to life and are useful in a wide range of situations.

Of all the mental models humankind has generated throughout history, there are just a few dozen that you need to master to have a firm grasp of how the world works. To quote Charlie Munger, “80 or 90 important models will carry about 90% of the freight in making you a worldly-wise person. And, of those, only a mere handful really carry very heavy freight.”

After many hours of research, I have sorted through more than 1,000 mental models and distilled them into a short list of the most important mental models for daily life.

I am only included the most important and useful mental models on this page. I have separated them out by industry below.

Mental Models in Business

• Common Knowledge
• Comparative Advantage
• Diversification
• Economies of Scale
• Efficient Market Hypothesis
• Game Theory
• Incentives (Reward and Punishment)
• Supply and Demand
• Classical Conditioning (Pavlov)
• Commitment and Consistency Bias
• Hyperbolic Discounting
• Illusion of Control
• Loss Aversion
• Maslow’s Hierarchy of Needs
• Mere Exposure Effect
• Operant Conditioning (Skinner)
• Reciprocity
• Status Quo Bias
• Survivorship Bias
• The Scientific Method
• Surfing or “Riding the Wave”
• Working Backward

Mental Models in Science

• Evolution by Natural Selection
• Equilibrium (Homeostasis)
• Activation Energy
• Atomic Theory
• Autocatalysis
• Entropy (The Second Law of Thermodynamics)
• Critical Mass

Mental Models in Math and Engineering

Engineering

• Break Points
• Margin of Safety

Mathematics

• Normal Distribution (Bell Curve)
• Permutations and Combinations

Best Mental Models Books

• Seeking Wisdom by Peter Bevelin
• Poor Charlie’s Almanack by Charles Munger
• The Personal MBA by Josh Kaufman
• The Fifth Discipline by Peter Senge

Want more? Browse my full list of the best business books .

All Mental Models Articles

• First Principles: Elon Musk on the Power of Thinking for Yourself
• Mental Models: How to Train Your Brain to Think in New Ways
• Entropy: Why Life Always Seems to Get More Complicated
• Inversion: The Crucial Thinking Skill Nobody Ever Taught You
• A Margin of Safety: How to Thrive in the Age of Uncertainty
• All Models Are Wrong, Some Are Useful
• How to Spot a Common Mental Error That Leads to Misguided Thinking

Or, browse my best articles .

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Mental Models (Part 1)

Use these mental models to improve your problem-solving and decision-making skills and overcome common [smoov.bra.in2023] reasoning errors. 

As an economist by way of education (not profession), I was introduced to Charlie Munger’s now famous speech, The Psychology of Human Misjudgment (which is quite arguably the magnum opus on why we behave the way we do) in grad school, and this introduced me to behavioral economics, which then led me to discover mental models and how to use them to dominate the competition.

Or, in more formal (less hostile) terms: how to apply the models to business, investing, and personal growth 🙂

Its been a while since grad school, but the more I read and learn, the more I’ve come to realize that these models have near infinite possibilities and can be applied in a variety of areas, from basic life choices to solving the unanswered complex questions of the universe.

But before we get into the meat, what exactly is a mental model?

A mental model is just a fancy word for a principle that you can use to try to explain things and/or make better decisions.

It’s a simplified “cognitive framework” that can help you understand and interact with the world by providing a structured way to organize information and make good choices.

There are tens of thousands of mental models out there (every discipline has their own set), but you don’t need to know all of them.

You just need to know the basics.

As Munger says, “80 or 90 important models will carry about 90% of the freight in making you a worldly‑wise person.”

This post will discuss a few of the mental models that have been repeatedly useful to me over the years.

I use quite a few of them every day at the office (from spaceflight probability to hiring decisions to general strategy) and others outside the office (e.g. investing, personal life, and, of course fantasy football).

Note: as you read through this post you will come across various links to books that I personally recommend reading/studying to increase you knowledge of the topic currently in discussion.

Disclaimer: this is an incomplete list and biased from my own experience and knowledge, this is not financial or life advice, use at your own risk 🙂

Ok, let’s dive into it.

Mental Models to Help You Think Like A Genius:

1. Probabilistic Thinking

The modern world is facing a severe crisis of critical thinking and cognitive reasoning.

We exist in a culture of irrationality, fear, doubt, and uncertainty.

Nobody knows how to think anymore.

People are lost.

The confusion leads to anxiety and stress.

And stress leads to bad decisions.

Bad decisions are everywhere.

To make things worse, there are scammers, fraudsters, and hucksters lurking in the shadows.

Lurking and waiting to prey on the insecurity and fear that arises from a world full of uncertainty and unknowns.

Many times they come across as nice, helpful, and innocent.

They’ll offer you interesting remedies to “fix” your anxiety and stress.

They offer the answers to all of your problems and confusion.

Often by promoting courses or “mantras” or selling supplements, potions and elixirs.

Or by telling you to simply “think positive” and that everything will be OK.

“Have faith, little one.”

You can sell anything to fools if you market it properly.

They are wolves in sheep’s clothing.

And now “uncertainty” has become a dirty word.

We’re only allowed to think “positive”.

Everything else is “negative”.

So we default to the Binary.

What is the Binary, you ask?

Binary thinking is the tendency to see things in terms of absolutes (good versus bad or right versus wrong).

The Binary is simplified mindset where a person sees issues in terms of two options that are often mutually exclusive.

In the Binary, everything is either black or white, left or right, yes or no, on or off, hot or cold.

And using Binary Thinking to make sense of the world and solve hard problems often leads to bad outcomes.

Especially in a stressful world full of irrationality, anxiety, fear, doubt, and uncertainty.

Will you get struck by lightning today?

Hit by a car?

Robbed by bandits?

Win the Powerball lottery?

Maybe you will, maybe you won’t.

We’ll never totally know the outcome until the day is over, which is not particularly useful when we have to make our decisions in the morning.

Sure, Binary Thinking works in certain situations (sometimes), but for the most part, especially in the cold reality of our dynamic, complex, uncertain world, Binary Thinking is often subpar.

Using the Binary is a common [smoov.bra.in2023] runtime error. This happens when you use your brain on default settings.

Using default settings makes it easier to fall into the trap of optimism bias (more on this later), risk miscalculation, and self-destruction.

You see, in the real world, the future is inherently unpredictable because not all variables can be known — and even the tiniest error imaginable in the data can quickly throw off your predictions.

And because the future is not 100% deterministic, we need to figure out a way to navigate uncertainty and complexity so we can have a better understanding of the events that could impact us in a positive or negative way (and their likelihood).

This is where Probabilistic Thinking comes in.

In the office , we use probability theory just about every day to solve hard problems.

We’re a team of nerds who are deep in the mud with predictive modeling/analysis every day (building predictive algorithms, tinkering with AI and machine learning and the likes).

And from being knee deep in it on a day-to-day basis, I know firsthand just how difficult it is to predict the future .

Even if you’re a data science genius, predicting the future is incredibly difficult.

Most of the time the best you can do is just create “estimates” by coming up with simple, realistic, useful probabilities.

“So, how do I do that?”

And what is probabilistic thinking?

Probabilistic Thinking is when you try to estimate (using logic and math ) the likelihood of any specific outcome.

This can help improve decision making accuracy.

If you live on Earth (Solar System 1) and are not some alien reading this from some far away planet, you should be aware that every moment in our world is determined by an infinitely complex set of factors.

This complexity can lead to uncertainty, anxiety, and fear.

Feelings that most humans experience every day (to a certain degree).

Probabilistic thinking, on the other hand, can reduce uncertainty, anxiety, and fear, and help you solve some very hard problems — because probabilistic thinking can give you the ability to see through the dense fog of madness and uncertainty and show you the most likely outcomes.

When you know the outcomes (holy sh*t can you predict the future now?) not only will your decisions be more accurate and effective, but you’ll also be able to avoid pitfalls like recency bias and emotional decision-making suboptimality.

You see, the right answer is like two people. Quant is the nice one. Logic causes all the trouble. They fight.” —Jamin Thompson

Probabilistic Thinking is a much more scientific and quantitative approach (as opposed to Binary Thinking) when it comes to making difficult decisions in uncertain or unpredictable situations because it considers the odds, probabilities, and likelihoods of a multitude of various outcomes.

It acknowledges that many real-world situations are characterized by inherent variability and unknowns — and it seeks to quantify and manage this uncertainty through the use of probability theory.

Are you lost in the woods?

Decision forest too thick?

How do you get out of here?

Do you take this path or that one?

Each choice could lead to a different outcome.

How do you figure out the probability of each one?

Are there complex formulas?

What does probability even mean anyway?

That’s a great question. I’m glad you asked that question.

Probability means POSSIBILITY.

Probability is a measure of the likelihood that an event will occur in a random experiment.

The value is expressed as a number between 0 and 1, where 0 means the event is an impossible one and 1 indicates a certain event.

You see, many events cannot be predicted with absolute certainty. We can only predict the chance an event has to occur (or how likely they are going to happen).

The higher the probability of an event, the more likely it is that the event will occur.

Take a coin toss, for example. When you toss a coin, you will either get heads or tails. These are the only two possible outcomes (H, T). But, if you toss two coins, then there will be four possible outcomes [(H, H), (H, T), (T, H), (T, T)].

Note: this is basic probability theory (also used in the probability distribution) where you learn the possibility of outcomes for a random experiment. To find the probability of a single event, first we need to know the total number of possible outcomes. 

That said, when it comes to Probabilistic Thinking, there are two critical factors to consider: 

• The probability of a certain outcome.
• The magnitude of a certain outcome.

But, how do I calculate the probability of an outcome?

Without turning this into a very boring math essay full of complex formulas that make no sense, here is all you really need to know.

Probabilistic thinking pretty much boils down to the following three critical aspects:

• Bayesian thinking
• Fat-tailed curves
• Asymmetries

Let us begin with Bayesian Thinking.

(aka The Bayesian view of probability or Bayes’ Theorem)

Bayes’ Theorem is a fundamental concept in probability theory and statistics.

Named after 18th-century statistician, philosopher and minister Thomas Bayes, Bayes’ theorem describes the probability of an event, based on prior knowledge or conditions that may be related to the event.

It works by giving you a way to update and improve your probability estimates when new evidence becomes available.

In simple terms: Bayes Theorem measures the plausibility of an event when you have incomplete information.

It starts with a statement of knowledge prior (usually this comes in the form of a prediction).

*yes, this can really come in handy if you are trying to win your fantasy football league*

For example: to improve the state of knowledge, an experiment is designed and executed to “get new evidence”.

Both the prior and the experiment’s results have a joint distribution (the probability of two events happening together) that leads to a new and improved belief.

This is demonstrated in the following equation:

P(A|B) = [P(B|A) P(A)] / P(B)

Where P = probability, A = prior knowledge, and B = new evidence.

And where P(A) = probability the prior belief is true.

P(B) = probability that the new evidence is true.

P(A|B) = probability of the prior belief if the new evidence is true.

P(B|A) = probability of the evidence if the prior belief is true.

It’s a deceptively simple calculation, although it can be used to easily calculate the conditional probability of events where intuition often fails.

Unrelated, intuition usually fails.

Side note for the AI enthusiasts: although Bayes Theorem is widely used in the field of probability, it is also heavily used in machine learning as well.

The core concept of Bayes focuses on the fact that as we encounter new information, we should probably take into account what we already know when we learn something new.

This helps us use all relevant prior information as we make decisions.

It’s particularly useful when dealing with conditional probability, where the likelihood of an event is dependent on the occurrence of another event.

Poker players and entrepreneurs both embrace the probabilistic nature of decisions. When you make a decision, you’ve defined the set of possible outcomes, but you can’t guarantee that you’ll get a particular outcome. — Annie Duke (Poker Champion)

As mentioned previously, we live in a world that is full of uncertainty.

And uncertainty leads to stress.

Stress leads to bad results.

These are critical points to understand if you truly want to make better decisions.

A huge part of Probabilistic Thinking involves befriending uncertainty, which can be incredibly hard.

To overcome this, we need to acknowledge that uncertainty exists, that it is everywhere, and make it our friend.

To do this you must learn to live in “chaos” and embrace the unknown.

Let go of your ego and your biases and accept the conditions of the situation.

Let your mind be free.

Be ok with saying “I’m not sure”.

Accept that you will never (even if you are a data science genius or fantasy football expert) know all the facts in any given situation and that there are no guarantees of a specific outcome.

Next, after you figure out what you think may happen, ask yourself, “what else might happen?” and then decouple from notions of ‘good’ and ‘bad’ in decisions from those outcomes.

It’s also important to keep in mind that when you are swimming in the deep waters of uncertainty and complexity, there is also (very likely) a degree of luck involved, so it’s possible for you to make a ‘bad’ decision that leads to a positive outcome.

And that’s OK.

It’s MUCH easier to accept randomness when things don’t go our way.

So, with that in mind, instead of focusing on outcomes/results, learn to trust the process and try to reflect on your previous decisions from a probabilistic perspective.

Got all that?

Now, the next thing to remember is to never (for any reason) express 100% certainty.

This is the ultimate rookie move, and if you have made it this far, you definitely aren’t a rookie anymore.

So, start doing this today: if you want to make a prediction (fantasy football, the weather, stock market, economy, world war 3, whatever), get in the habit of assigning levels of certainty to your predictions, rather than boldly claiming something will just ‘simply happen’.

Always do your due diligence and estimate the percentage chance it will happen based on your available data/facts.

Note: it’s important that when you’re confronted with the possibility that you’re wrong that you don’t engage in any sort of cognitive gymnastics to try to hold onto that false belief (even though you want to). To become a true mental master, you’ll have to come to terms with the fact that there are countless things you’re not right about in our present moment in spacetime. 

If you’ve got all that, the next step is to update your probabilities.

You have been presented with new information. What should you do?

You must be open to it and consider any emerging facts.

Then, use the data to update your predictions.

Note: this process can be painful and difficult and involves challenging and disrupting your biases. 

And then, FINALLY, after you have made your predictions and updated them, THEN you must find the confidence to act (based on your current knowledge) to run the numbers and understand all the probable outcomes, while also accepting the fact that you could always be wrong.

Artist depiction of a Deimos-One Data Scientist Modeling Simplicity in a Stochastic Environment

And that’s (mostly) it in a nutshell.

Probabilistic Thinking (or Bayes’ theorem) is a powerful tool for making informed decisions and updating beliefs in the face of uncertainty and changing evidence.

It’s a pragmatic approach to decision-making that recognizes the limitations of certainty and embraces the tools of probability to navigate uncertainty.

Using it will help you avoid common [smoov.bra.in2023] reasoning errors and empower you to make more informed decisions.

As an added bonus, you’ll also get better at managing risk and developing strategies that can hedge against uncertainty and complexity.

If you master this style of analysis, you’ll have a new weapon in your war chest that will help you understand not only the world, but also yourself (decisions, thoughts, emotions, etc.).

That is true power.

Next up, fat-tailed curves.

So, what exactly is a “fat-tail”?

The statistical term ‘fat tails’ refers to probability distributions that have a relatively high probability of extreme outcomes.

Just think: your last relationship.

Or, that memecoin you put your whole savings in.

A fat-tailed distribution exhibits a large skewness, which consists of a thick end or “tail” toward the edges of the distribution curve.

Fat-tails also imply strong influence of extreme observations on expected future risk.

Fat-tails are similar (but slightly different) to its more traditional “do-gooder” older brother, the normal distribution curve.

The normal distribution curve is shaped like a bell (it’s also known as the bell curve), and it typically involves two basic terms: (1) the mean (the average) and; (2) the standard deviation (the amount of dispersion or variation).

Usually the values here cluster in the mean and the rest symmetrically taper off towards either extreme.

Kind of like ordering “hot wings” with the mildest sauce there is.

The fat-tail, on the other hand, is sort of like wild and crazy hot wings with Carolina reaper peppers and homemade hot sauce from the back of someone’s barn.

You know that sh*t is gonna be SPICY.

But hey, let’s compare wings, shall we?

At first glance both types of wings (mild/extreme hot) seem similar enough (common outcomes cluster together bla bla) but when you look closely (can you identify a Carolina reaper without Googling?) they always have very distinctive traits to tell them apart.

If you want to use comic books as a reference instead of hot wings, take Loki and Thor, for example. They are “brothers” but their difference is usually in the physical difference (Thor is the jacked one).

With these distribution curves, it is also appearance based — the difference is in the tails.

Here are some important distinctions: 

In a bell curve the extremes are predictable. There can only be so much deviation from the mean.

Fat tails have positive excess leptokurtosis (fatter tails and a higher peak at the mean), which means there is no real cap on extreme events (positive or negative).

In a normal distribution (bell curve), on the other hand, the extremes are more predictable.

The more extreme events that are possible, the longer the tails of the curve get.

Does that make sense?

You’re doing so great.

Sure, you could make the argument that any one extreme event is still unlikely, but due to the massive number of options, you probably won’t be able to confidently rely on the most common outcomes as a representation of the average.

And the more extreme events that are possible (think millions or even billions) the higher the probability that one of them will occur.

When it comes to fat-tails, you know crazy things are going to happen (with near certainty), like your fantasy football team having multiple starters sent to IR on the same day, you just have no idea of knowing when.

So, how can a common pleb like myself use this knowledge to my advantage?

That’s a great question, I’m glad you asked that question.

Suppose you hear on the news that you had a greater risk of falling out of bed and cracking your head open than being killed by war.

The stats, the priors (seem) to back it up: over 30,000 people died from falling injuries last year in your country and only 200 or so died from war.

Should you be more worried about falling out of bed or World War 3?

A lot of hucksters and actors who play economists on TV use examples like these to “prove” that the risk of war (World War 3 in this case) is low.

They say things like “there are very few deaths from this in the past and the numbers back this up so why even worry?”

Looking at it on the surface, it may appear (to the untrained eye) that the risk of war is low since death data shows recent deaths to be low, and that you have a greater risk of dying from falling, it all makes sense, right?

The problem is in the fat tails.

The shape of the curves often tell a very different story.

Think of it like this: the risk of war is more like your bank account, while falling deaths are more like weight and height. In the next ten or twenty years, how many outcomes/events are possible?

How fat is the tail?

Think about it.

If the risk of World War 3 is high, it would follow a more fat-tailed curve where a greater chance of extreme negative events exists.

On the other hand, dying from falling (like the time I fell out of the top bunk of my bunkbed as a kid) should follow more of a bell curve, where any outliers should have a well-defined scope.

It may take a bit of practice, thinking, and application, but trust me, it’s simple once you get it.

If you don’t understand it now, keep studying and you will.

Remember, the important thing to do when you are trying to solve a hard problem is not just sit around and try to imagine every possible scenario/outcome in the tail. This is an impossible task for any human running [smoov.bra.in2023] to figure out.

Instead, use the power of the fat-tail to your advantage.

Doing this will not only put you in a great position to survive and thrive in the wildly unpredictable future — but it will also help you think clearly and make good decisions — so you can always stay one step ahead in a world we don’t fully understand.

Finally, that leaves Asymmetries.

Now that you have basic probability under your belt, it’s time to embrace a more advanced concept that many experts call “metaprobability” — aka the probability that your probability estimates are any good.

Let’s be honest, your probability estimates probably suck (at least right now because you’re just starting out) but for the purposes of this exercise let’s pretend that they are brilliant.

For argument’s sake, let us consider the possibility.

You are a common plebeian genius who has access to brain tools and weapons only possessed by super advanced civilizations.

The internet, advanced machine learning, AI, GPT-4, Amazon Books , and many other tools from the wonderful world of advanced data science wizardry are all at your fingertips.

Look at us.

Who would have thought?

But with all these advanced tools is it now possible to accurately predict the future?

Let us see.

First, we evaluate the known params:

-I exist -The world exists -The world is chaos -Chaos leads to war -War is unpredictable -Unpredictability leads to uncertainty -Uncertainty leads to stress -Stress kills

bla bla bla

Now, let us consider a function of a complex variable f(z) = wut + tf where we assign falling out of bed, world war 3, nuclear attack, terrorism, disease, famine, global warming, AI, a specific weight to form a probabilistic argument to estimate the chance that a violent kinetic event will occur, and/or the event’s place in spacetime.

Let us import the vars into our shitty bathroom formula:

tf² [(x²) + (y²) + y(z²)] + ded P = —————————————— Σi (7x – war + wut²)

Solving for wut + tf we can conclude with a 69.699% probability that shit happens and that shit will continue to happen until shit happening ceases to occur.

We have discussed economic hucksters and Decepticon intellectuals in previous posts.

Bold predictions.

Fancy charts.

Long exposition.

Pseudo quant.

Devoid of logic.

Immovably committed to bold positions because it makes you sound smarter than being humbly realistic.

They make bold predictions but are wrong more often than they are right.

Bla bla bla.

The reason these guys are wrong so often has to do with asymmetries.

For example, if you observe a common huckster in action: the expensive suit, the nicely polished pitch deck, the fancy charts, the slick haircuts, etcetera…

These guys will look you right in the eye in a pitch meeting and tell you you can expect to “achieve a rate of return of 30% or more per year” or even more.

And most of them never hit their projections.

Not because they don’t have ANY of their projections correct, it’s because they got so many incorrect.

They overestimated their confidence in their probabilistic estimates — and they do this consistently, meeting after meeting, year after year.

A common [smoov.bra.in2023] runtime error.

Note: we all know the stock market usually only returns about 7% a year in the United States, but for some reason (unexplained by modern science) we continue to listen to and bet on the smooth talking 30% guy. 

With that in mind, here is what you need to do.

Write this down:   my probability estimates and predictions are more likely to be wrong when I am “over-optimistic” instead of “under-optimistic”.

And a lot more probability estimates are wrong on the “over-optimistic” side than the “under-optimistic” side.

Remember this fact.

Put it on the fridge so you never forget it.

Why is this so important, you ask?

The reason for is simple: a lot of uncertain outcomes are inherently asymmetric.

They have longer downside tails than upside.

And a common [smoov.bra.in2023] runtime error is to lock in and focus on the “obvious” or “most likely” outcome — and then forget to crunch the numbers to figure out the real expect impact of multiple asymmetries together.

Image: Sketchplanations.com

Things that never happen (or rarely happen): an investor who wanted to hit a 30% annual return but instead hit 45% over multiple years.

When you do the analysis (you can go crunch the numbers yourself) you’ll find that most guys end up closer to 9 or 10 percent.

Maybe 12 percent if they’re lucky.

Remember, your estimation errors are asymmetric, skewing in a single direction — this is often the case with probabilistic decision-making .

Whew, that was a lot.

You got all that?

To sum things up, just remember: when you get too over-confident and fall into the trap of blind “over-optimism” it often leads to errors and bad outcomes.

But, if you can build your data analysis skills up to a ’99 Madden awareness level’ you’ll be able to recognize overestimations in your probabilistic estimates so you can plan more carefully during high-stake situations and make rational (winning) decisions when you are faced with high levels of uncertainty, ambiguity, and incomplete knowledge.

You will be a god among men.

2. Second-Order Thinking 

These days, it can be tempting to make emotional decisions with small upside that provide instant gratification.

This is often referred to as first-level thinking, which is simplistic and superficial by nature.

First-level thinking does not consider the negative future consequences of a decision made today.

First-level thinking focuses on solving an immediate problem, with little or no consideration of the potential consequences.

But most decisions require a much deeper level of thought and mental exploration. They require you to look beyond the immediate and the obvious; to dig deeper.

For example:

An investor with first-level thinking may think that a crypto company with a rapidly growing online following will lead to an inevitable (somehow correlated) rise in share price.

On a similar note, a person on a diet may conclude that the best choice for a hungry stomach is a delicious bacon cheeseburger (I’ve done this).

In both cases, the potentially negative future consequences of each choice have not been fully thought out and evaluated.

It happens all the time: some decisions seem like dubs at first, but then turn out to be huge L’s as time goes on.

What seems like a good memecoin to buy today turns out to be a huge dud months later.

What looked like a good decision before is now a bad one.

Most people stop at first level thinking, but you don’t have to.

Instead, give second-order thinking a shot and see if your decision making can improve.

So, what exactly is Second Order Thinking?

In his exceptional book, The Most Important Thing , Howard Marks explains the concept of second-order thinking, which he calls second-level thinking:

“First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in “The outlook for the company is favorable, meaning the stock will go up.”

First-level thinking is very linear.

It’s fast and easy.

Simplistic and superficial.

Just about anyone can do it.

It is based on default settings.

It is the result of looking for something that solves the problem at hand without considering the tradeoffs or consequences.

For example, you’re thirsty so let’s drink an ice cold beer .

First-level thinking is very basic, and just about everyone can do it (a bad sign for anything involving an attempt at superiority).

Second-order thinking is a lot deeper, more complex and convoluted.

More deliberate.

It requires a much deeper engagement of the mind.

Second-order thinkers analyze the statistics, facts, and information, but also question the reasoning behind them.

Second-order thinkers have a strong understanding of bias.

Second-order thinkers have strong metacognition.

Second-order thinkers think about their own thinking — and then think about thinking about the thinking they are thinking — often analyzing multiple variable at the same time.

Second-order thinking is a mental model that can help you properly assess the implications of your decisions by considering future possibilities/consequences. It encourages you to think outside the box and prepare for every eventuality.

So, how do I start thinking in the second order?

A good place to start would be asking yourself the following:

• What is the probability that I’m right?
• What is the range of likely future outcomes?
• Which outcome do I think will occur?
• What does the consensus think?
• How does my expectation differ from the consensus?
• And then what?
• What do the consequences look like in 10 minutes? 10 months? 10 Years?

Key Point: While first-level thinking evaluates the direct outcomes of a single decision, second-order thinking delves into the broader and deeper implications that can arise as a result of those outcomes.

Unlike first-level thinking, where everyone reaches the same conclusions, second-order thinking gives you the ability to navigate complex situations with greater perspective and insight.

It’s a model that that considers all future possibilities.

It can prepare you for any eventuality.

It goes beyond simple cause-and-effect reasoning.

It considers the entire chain of reactions and unintended consequences and shields you from the human default tendency to make the most obvious choice.

When you look beyond the immediate and obvious, you’ll be able to make better decisions that will lead to more positive outcomes, both now and in the future.

Looking back at some of your past decisions in a new light (from the lens of having just read through this) first-level thinking may sound really stupid, but our minds are programmed (aka [smoov.bra.in2023] default settings) to search for the easiest solution and/or the solution that usually appears obvious.

For this reason, most people really struggle to look beyond their initial assumptions to make the optimal decision.

This is especially true when we are stressed, in a time crunch, inexperienced in the field at hand, over-optimistic (see mental model #1 again), experiencing strong emotions, have psychological biases, or are isolated from other points of view.

At the end of the day, second-order thinking can help you step outside your comfort zone and objectively analyze and assess the implications of your decisions by considering the future consequences.

It will help you make sure you’re certain and comfortable with the long-term consequences of your decisions today.

This mental model is particularly useful in times of uncertainty and/or in rapidly changing environments, where the ability to foresee multiple potential outcomes can help you avoid disaster and lead to more successful outcomes.

Bonus Chance: second-order thinkers typically outperform first-level thinkers because they can see solutions to problems that others can’t.

3. Opportunity Cost

There is no such thing as absolute victory, there is no perfect solution, there are only trade-offs. All you can do is try to get the best trade-off you can get.

We live in a world of trade-offs.

There is no such thing as a perfect outcome.

And the concept of opportunity cost (e.g. there is no such thing as a free lunch) is the king of all trade-offs.

This is a fundamental concept that’s taught in Basic Economics .

So, what exactly is an opportunity cost?

In economics, opportunity cost refers to the loss of potential gain a person could have received but passed up in pursuit of another option.

Opportunity cost is a fundamental concept in economics and decision-making.

When making a choice between two or more alternatives, the cost of that decision is not just the immediate financial expense but also the potential value or benefits you lose by not choosing the next best alternative.

In other words, opportunity cost is the value of the next best option that you give up when you make a decision.

It helps you evaluate the trade-offs involved in your choices.

For the nerds, you can express opportunity cost conceptually as follows:

Opportunity Cost = FO – CO where: FO = Return on best forgone option CO = Return on chosen option

Let us consider an example of opportunity cost in the context of selling a stock now or waiting to sell it in three months.

Suppose you have 1,000 shares of Deimos-One stock, and the current market price per share is $100.

You have two options:

Option 1: Sell the stock today at $100 per share. Option 2: Wait and sell it in three months hoping that the stock price will go up.

To calculate the opportunity cost, we will need to compare the returns of both options.

Option 1: 1,000 shares x $100 per share = $100,000 (current value)

Option 2: 1,000 shares x $120 per share = $120,000 (future value) *let’s assume the stock price has increased*

Now, calculate the opportunity cost:

Opportunity Cost = Future Value (Option 2) – Current Value (Option 1) Opportunity Cost = $120,000 – $100,000 = $20,000

So, if you choose Option 1 and sell the stock today, your opportunity cost is $20,000.

This means that by selling now, you’re giving up the potential $20,000 in profit you could have earned if you had waited for three months and sold the stock at the higher price.

This opportunity cost scenario shows the trade-off between realizing immediate gains and waiting for potentially higher returns.

Opportunity cost is a powerful mental model to help you make more informed decisions as it encourages you to consider not only the benefits of your chosen option but also what you’re sacrificing by not choosing an alternative.

It’s always a wise move to think about the potential costs that arise because you chose in favor of one option and thus against every other option.

4. Randomness 

There aren’t always cause-effect relationships.

A lot of stuff is just random.

For some reason (unexplained by modern science), the human brain has a lot of trouble comprehending this fact (another common runtime error?) but the truth is: a lot of the world is made up of random, non-sequential, non-ordered events.

Humans are often “fooled” by randomness.

A function of [smoov.bra.in2023]  perchance?

A common plebian reasoning error?

This needs to be studied further.

We attribute causality to things we have zero control over.

And if you get fooled by randomness and get tricked into a false sense of pattern seeking — you will get finessed into seeing things as being more predictable than they actually are, and eventually make a critical error.

It happens all the time.

So, what exactly is “randomness”?

In previous blogs , we have discussed how hucksters and posers do not understand probabilistic processes, or how to model simplicity in stochastic environments.

Randomness is a mental model/cognitive framework that recognizes the inherent uncertainty and unpredictability present in various aspects of life and decision-making.

Here’s the thing: we live in an unpredictable world.

It’s a world with a dense decision forest.

There are many steps/variables/tricks/outcomes.

It can be thick and hard to see.

There is complexity.

Stochasticity.

Uncertainty.

But, the winners are often able to see 2-3 steps ahead.

They can see through the trees to infinity.

The losers can barely see what’s in front of them.

You see, many outcomes are not entirely deterministic — a lot of it is subject to chance and probability.

The winners just know how to calculate it.

Here are a few key principles to understand when it comes to randomness:

Probabilistic Thinking: Embracing randomness and uncertainty (see model #1 above) means thinking in terms of probabilities. Instead of expecting deterministic outcomes, we must consider the likelihood a situation can have multiple possible outcomes, each with its own chance of occurring. Understanding these probabilities is critical for understanding the distribution of possible outcomes and making informed decisions based on that information.

Statistical Reasoning: Randomness often follows statistical patterns. Finding these patterns can help successfully navigate through a dense decision forest. By applying statistical methods to analyze data, considering patterns and distributions rather than relying on intuition or a “gut feeling” can help you make informed judgments even when faced with uncertainty.

Stochastic Processes: One must recognize that many processes are driven by stochastic, or random, elements, and it helps to study, understand, and be able to model complex systems.

Irrationality Awareness: Randomness highlights human biases and irrational tendencies when dealing with uncertainty. In order to navigate through the decision forest, we must be aware of these biases and encourage ourselves to make rational decisions.

Uncertainty Awareness: Nobody knows it all. Many events are inherently uncertain and cannot be predicted with certainty. Recognizing this can help avoid overconfidence, not only in your predictions but also in your decisions.

Decision Under Uncertainty: As mentioned above, not only must we have uncertainty awareness, but we must be able to make decisions when outcomes are uncertain. It helps to make decisions based on expected value or risk-reward analysis.

Risk Assessment / Prediction Limits: Every decision you make can have a range of outcomes, and randomness often adds risk and uncertainty into decision-making processes. So, one must calculate risk probability. But not all events can be accurately predicted, some degree of uncertainty will always be present. Recognizing the limits of prediction is key.

We use Monte Carlo (MC) Simulation (a basic mathematical technique that predicts possible outcomes of uncertain events) in the office quite often to simplify randomness and predict future outcomes.

MC can be a very useful tool to identify all the possible outcomes of an event (e.g. spacecraft launch, payload drops, landing, etc.) making it a lot easier to measure risk so we can make good decisions under uncertain initial conditions.

We can run MC simulations millions of times (it generates a bunch of “what-if” test scenarios) by treating every input variable and its intrinsic uncertainty as a probability distribution function.

This allows us to get precise, quantitative risk analyses of incredibly complex projects (such as a payload drop over a distant planet) and mission critical risk assurance for the spacecraft.

What we usually end up with is a comprehensive and quantifiable statistical picture of what could happen, its likelihood of happening, and any errors associated with such an occurrence.

It is a great tool to hedge your bets against the cruel pimp slap of an unforeseen random event.

That said, MC also kicks ass due to the fact that unlike normal forecasting models (or traditional single-point risk estimates) MC is able to build a model of possible results by leveraging a probability distribution (like a uniform or normal distribution) for any variable that has inherent uncertainty.

Then, it recalculates the results over and over (thousands and thousands of times) each time using a different set of random numbers between the minimum and maximum values, generating a large number of likely outcomes.

And thanks to the internet and tools like YouTube and GPT4, you don’t have to be a master data scientist to set up and run basic MC simulations.

This is a very simple method/experiment that you can learn quickly and use to solve any problem that includes an element of uncertainty or randomness in its prediction.

Or, problems that may have a probabilistic interpretation or be deterministic in principle.

At the end of the day, we live in a confusing world with tons of uncertainty, and understanding randomness is essential if you want to manage risk and navigate uncertainty.

The basic framework is built on rational decision-making, statistical thinking, probability and risk analysis that you can use to make better decisions in all aspects of life, from everyday choices to complex financial and life decisions.

Put it in your war chest and use it to your advantage.

5. Occam’s Razor 

“Never multiply unnecessarily.”

Occam’s razor (also known as the “law of parsimony”) is a foundational mental model in reasoning and problem-solving. It underscores the principle of simplicity as a guiding criterion for choosing among competing hypotheses or explanations.

It states that one should not increase (beyond reason) the number of entities that are necessary to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century philosopher/theologian William of Ockham .

It can be summarized as follows:

Among competing hypotheses, the one with the fewest assumptions should be selected.

Simple explanations are preferrable to complex ones.

Simple theories are easier to verify.

Simple solutions are easier to execute.

Always choose the less complex explanation/option.

Occam’s razor mirrors the colloquial phrase “KISS” (Keep It Simple Stupid).

The general idea behind “KISS” is that if you have two or more explanations that work equally well (ceteris paribus) in answering a question, the simplest hypothesis is generally the most optimal.

As discussed in previous articles , we live in an era where we have more knowledge and technical capabilities to ask and answer more questions than ever before.

The more questions we ask, the more answers we get.

And, the more answers we get, the more questions arise.

Every day we are asking and answering more questions, in more fields, and arriving at even more questions.

And we’re doing it at unprecedented speeds.

We are, at an alarming rate, asking and answering more and more questions , which in turn, allows us to make more decisions and have more agency.

The problem is, you and I (and just about every human on this planet) is still running [smoov.bra.in2023] which severely limits our cognitive abilities and decision making skills.

Our core programming does not have the capacity to process information at this volume and scale.

Note: if this does not make sense to you, it’s likely a runtime error… [smoov.bra.in2023] needs more CPU and RAM to process fully but the sim params have prevented this.

Sure, we have a lot more options now (and that’s a good thing).

But, with more options come more choices.

And with more choices come more decisions to make.

And with more decisions to make, the more complex the solutions become.

So, paradoxically, in an attempt to gain more knowledge and understanding by building the technologies we thought would help make our lives easier, we seem to be doing the opposite of Occam’s Razor.

The question of utility seems to be getting farther and farther away.

We live in a world where we have unprecedented choice freedom and agency.

But with all of these options (multiplied unnecessarily) are we causing more work for our brains?

Are we wasting hours of our lives pondering over trivial decisions?

Just think about the amount of time it takes to find a TV show to watch on Netflix, or how long it takes to figure out what food you want to order on Uber Eats.

As a self-described deep thinker myself, I’m not going to sit here and chastise you for thinking but sometimes thinking can be suboptimal.

Alan Watts may have said it best when he said: “Don’t think too much.”

A person who thinks all the time has nothing to think about except thoughts. So, he loses touch with reality, and lives in a world of illusions.

By thoughts, I mean specifically, chatter in the skull. Perpetual and compulsive repetition of words, of reckoning and calculating.

I’m not saying that thinking is bad. Like everything else, it’s useful in moderation.

A good servant but a bad monster.

And all so-called civilized peoples have increasingly become crazy and self-destructive because, through excessive thinking, they have lost touch with reality.

We are wasting our brain power on trivial matters and useless activities.

This is causing decreased cognitive ability and mental exhaustion.

Occam’s Razor, on the other hand, encourages clarity, parsimony, and simplicity in reasoning.

It encourages you to choose straightforward, elegant explanations that minimize unnecessary complexities and assumptions.

It promotes rationality and economy in the formation of hypothesis.

It aids in prediction and empirical testing and contributes to the efficiency and progress of scientific inquiry.

This mental model’s power lies in its capacity to foster clarity of thought, drive scientific progress, and help you make informed and rational choices when faced with uncertainty and complexity.

Use it to your advantage.

Final Thoughts

Mental models (especially in the way presented here) can be a mouthful to take in at first, but if you spend some time with them, studying them, and using them in application (not just theory) you’ll eventually get the hang of them.

It’s all about the application and the context, you have to use them in the right way at the right time. It’s a science; you’ll have to understand them well and practice using them for them to have full effect.

Personally, I find mental models to be particularly useful when I’m trying to come up with cool ideas or trying to solve hard problems.

That said, I’ve rambled on enough for today.

I hope you gained some valuable insight from the words written here.

It’s my hope that you can leave the internet somehow smarter than you were when you first logged on.

So, what Mental Model has helped you the most?

Let me know on X/Twitter.

Follow me for more shitty analysis: twitter.com/jaminthompson.

Click Here to read Mental Models Part 2.

Best Mental Model Books for further study: 

Poor Charlie’s Almanac by Charles Munger

The Most Important Thing by Howard Marks

The Personal MBA by Josh Kaufmann

The Fifth Discipline by Peter Senge

Thinking in Bets by Annie Duke

Against the Gods by Peter Bernstein

Basic Economics by Thomas Sowell

Math for Machine Learning by Richard Han

Click to learn how to make $300 a day with an Automated Sales Machine .

Unleash Your Inner Problem-Solver: Adopting Mental Models for Success

Unlocking your problem-solving potential.

When it comes to problem-solving, embracing mental models can be a game-changer. Mental models are frameworks or structures that help us make sense of the world and navigate complex situations. By adopting these models, you can enhance your problem-solving abilities and approach challenges with a fresh perspective.

Embracing Mental Models for Success

To unlock your problem-solving potential, it’s important to embrace the power of mental models . These models provide you with a set of tools and frameworks that can help you analyze problems, generate creative solutions, and make informed decisions.

Mental models are derived from various disciplines, including psychology, cognitive science, and philosophy. They are cognitive constructs that represent how we understand and interpret the world around us. By utilizing mental models, you can tap into a wealth of cognitive processes and decision-making models that have been developed and refined over time.

How Mental Models Can Enhance Problem-Solving Abilities

Mental models can significantly enhance your problem-solving abilities in several ways. First, they provide cognitive strategies and thinking frameworks that help you break down complex problems into manageable chunks. These models allow you to see patterns, connections, and relationships that may not be immediately apparent.

Second, mental models enable you to leverage cognitive shortcuts and mental shortcuts to quickly evaluate options and make effective decisions. By relying on these established frameworks, you can save time and mental energy, allowing you to focus on finding innovative solutions.

Third, mental models encourage critical thinking by challenging assumptions and biases. They provide a structured approach to problem-solving, helping you to identify potential blind spots and consider alternative perspectives. This promotes a more comprehensive and balanced analysis of the problem at hand.

By adopting mental models, you will expand your cognitive toolbox and develop a repertoire of mental frameworks that can be applied to various problem-solving scenarios. These models will sharpen your analytical skills, foster creativity, and ultimately empower you to overcome obstacles and achieve success.

In the following sections, we will explore specific mental models that are particularly useful for problem-solving. These models include Occam’s Razor, the Pareto Principle, and the Circle of Influence. By understanding and applying these mental models to real-life scenarios, you will gain practical insights on how to approach problems with clarity and efficiency.

Understanding Mental Models

To become a more effective problem-solver, it’s important to understand the concept of mental models . Mental models are cognitive frameworks or representations that help you make sense of the world and navigate complex situations. They are the mental constructs you use to interpret information, analyze problems, and make decisions. By adopting and utilizing mental models, you can enhance your problem-solving abilities and improve your decision-making process.

What are Mental Models?

Mental models are like mental tools that you can use to understand, explain, and predict various phenomena. They are the lenses through which you perceive the world around you. These models are derived from your experiences, knowledge, beliefs, and cognitive processes. They provide you with a structured way of thinking and reasoning about problems and situations.

Mental models can take various forms, such as logical reasoning models, thinking frameworks, critical thinking models, or problem-solving models. They help you simplify complex problems, identify patterns, and make connections between different pieces of information. By internalizing these models, you develop a set of mental shortcuts or cognitive strategies that enable you to approach problems more efficiently and effectively.

The Power of Mental Models in Decision Making

The power of mental models lies in their ability to facilitate decision making. They provide you with a systematic approach to problem-solving, allowing you to evaluate options, anticipate consequences, and weigh potential outcomes. Mental models help you organize your thoughts, analyze information, and make informed choices.

By adopting mental models, you can overcome cognitive biases and avoid common pitfalls in decision making. These models enable you to consider multiple perspectives, challenge assumptions, and think critically. They also help you to identify relevant information, filter out noise, and focus on the key factors that influence the problem at hand.

Internalizing mental models is a continuous process that requires practice and exposure to diverse problem-solving scenarios. As you develop your mental model toolkit, you can explore additional models that align with your specific interests or areas of expertise. Check out our article on cognitive processes for more insights into the cognitive strategies involved in problem-solving.

In the next section, we will explore some popular mental models that can enhance your problem-solving abilities and provide practical applications in real-life scenarios. By incorporating these models into your decision-making process, you can unleash your inner problem-solver and achieve greater success in various aspects of your life.

Popular Mental Models for Problem-Solving

When it comes to problem-solving, mental models can serve as invaluable tools to help you navigate challenges and find effective solutions. In this section, we will explore three popular mental models that can enhance your problem-solving abilities: Occam’s Razor , the Pareto Principle , and the Circle of Influence .

Occam’s Razor

Occam’s Razor is a mental model that encourages simplicity in problem-solving. According to this principle, the simplest explanation is often the most likely one. When faced with a complex problem, Occam’s Razor suggests that you should prioritize explanations or solutions that require the fewest assumptions or elements.

By applying Occam’s Razor, you can streamline your problem-solving process and avoid unnecessary complexity. This mental model helps you focus on the key factors and underlying causes of a problem, enabling you to arrive at a more efficient solution. To learn more about critical thinking models and other cognitive tools, check out our article on cognitive tools .

The Pareto Principle

The Pareto Principle, also known as the 80/20 rule, states that approximately 80% of the effects come from 20% of the causes. This mental model suggests that a small number of factors or actions often have a disproportionately significant impact on the outcome of a situation.

By understanding and applying the Pareto Principle, you can prioritize your efforts and resources to focus on the most influential aspects of a problem. This allows you to maximize efficiency and achieve optimal results. To explore more mental models for decision-making and problem-solving, visit our article on mental models for decision-making .

The Circle of Influence

The Circle of Influence is a mental model introduced by Stephen Covey in his book “The 7 Habits of Highly Effective People.” This model encourages individuals to focus their time and energy on things they can control or influence, rather than wasting resources on things beyond their control.

When applying the Circle of Influence to problem-solving, it’s important to identify the aspects of a problem that you have the power to change or influence. By directing your efforts towards these areas, you can make meaningful progress and increase your chances of finding successful solutions. To explore more mental models for self-improvement and success, check out our article on mental models for self-improvement .

By incorporating these popular mental models into your problem-solving process, you can enhance your ability to tackle challenges effectively. Remember to apply Occam’s Razor to simplify complex problems, leverage the Pareto Principle to focus on the most impactful factors, and utilize the Circle of Influence to direct your efforts towards areas within your control. These mental models will empower you to approach problem-solving with a strategic mindset, leading to more efficient and successful outcomes.

Applying Mental Models to Real-Life Scenarios

Now that you have a good understanding of mental models and their significance in problem-solving, it’s time to explore how you can apply these models to real-life scenarios. Let’s dive into three popular mental models: Occam’s Razor , the Pareto Principle , and the Circle of Influence .

Problem-Solving with Occam’s Razor

Occam’s Razor is a useful mental model that suggests the simplest explanation is often the correct one. When faced with a problem, applying Occam’s Razor encourages you to prioritize the solution that requires the fewest assumptions or steps. By eliminating unnecessary complexity, you can streamline your problem-solving process and increase your chances of finding an effective solution.

To apply Occam’s Razor, start by identifying the core issue and focusing on the most straightforward explanation or solution. Avoid overcomplicating the problem by introducing unnecessary elements. This mental model helps you avoid getting lost in intricate details and guides you towards a more efficient problem-solving approach.

Maximizing Efficiency with the Pareto Principle

The Pareto Principle, also known as the 80/20 rule, is a mental model that suggests that approximately 80% of the effects come from 20% of the causes. Applied to problem-solving, the Pareto Principle reminds us to focus on the vital few factors that have the most significant impact.

When faced with a problem, consider identifying the key factors or causes that contribute to the issue. By focusing your efforts on addressing these critical elements, you can maximize efficiency and achieve more impactful results. This mental model helps you prioritize your resources and avoid wasting time and energy on less influential aspects of the problem.

Focusing on What You Can Control with the Circle of Influence

The Circle of Influence is a mental model that emphasizes focusing on what you can control rather than what you cannot. When encountering a problem, it is essential to distinguish between factors within your control and those outside of it. By directing your attention and efforts towards the aspects you can influence, you can increase your effectiveness in problem-solving.

To apply the Circle of Influence, evaluate the various elements of the problem and identify the ones you have the power to change or influence. By focusing on these areas, you can take proactive steps and make a meaningful impact. This mental model helps you avoid expending unnecessary energy on factors beyond your control and empowers you to take charge of the problem-solving process.

By integrating these mental models into your problem-solving approach, you can enhance your ability to tackle challenges effectively. Remember, mental models are tools that can help guide your thinking and decision-making, but they should be used in conjunction with your own judgment and experience. Explore additional mental models to expand your problem-solving toolkit and incorporate them into your daily life.

Developing Your Mental Model Toolkit

Now that you have a solid understanding of mental models and their application in problem-solving, it’s time to expand your toolkit by exploring additional mental models and incorporating them into your daily life.

Exploring Additional Mental Models

There are numerous mental models available, each with its own unique perspective and benefits. By exploring a variety of mental models, you can enhance your critical thinking skills and approach problem-solving from different angles. Here are a few additional mental models that you may find useful:

Cognitive Processes : Understanding the underlying cognitive processes involved in decision-making and problem-solving can provide valuable insights into how our minds work. Dive deeper into the intricacies of cognitive processes by exploring articles on cognitive processes .

Decision-Making Models : Decision-making models offer structured frameworks for making sound decisions. These models provide a systematic approach to evaluate options and consider various factors. Learn more about decision-making models by visiting our article on decision-making models .

Cognitive Strategies : Cognitive strategies help optimize our mental processes and improve our problem-solving abilities. They involve techniques such as goal setting, brainstorming, and organizing information. Discover effective cognitive strategies in our article on cognitive strategies .

By exploring these additional mental models, you can gain a broader perspective and develop a diverse set of tools to tackle various challenges.

Incorporating Mental Models into Your Daily Life

To make the most of mental models, it’s essential to incorporate them into your daily life. Here are some practical ways to do so:

Practice Awareness : Start by cultivating awareness of the mental models you have learned. Recognize when and how you can apply them in different situations.

Reflect and Evaluate : Take time to reflect on past experiences and evaluate how specific mental models could have been applied to improve your problem-solving outcomes.

Seek New Perspectives : Continuously seek out new mental models and perspectives. Explore articles and resources on topics such as cognitive frameworks and mental patterns to expand your understanding.

Experiment and Iterate : Apply mental models in various scenarios and assess their effectiveness. Adjust your approach as needed and refine your problem-solving skills over time.

Remember, the key to mastering mental models is consistent practice and application. The more you incorporate them into your thinking process, the more natural they will become. With time and experience, mental models will become an integral part of your problem-solving toolkit, empowering you to unleash your inner problem-solver.

Continue to explore different mental models and their applications in various aspects of life, such as self-improvement , productivity , creativity , leadership , and communication . The more you delve into these concepts, the more equipped you will be to tackle challenges and achieve success in your endeavors.

You want to build a $300/day business. Here's how...

In today's world, anyone can build a business that makes at least $300 a day. But you don't want to work 24/7 doing it.

So you need a system.

You need to know the whole system to make your business flourish.

This is why you build an Automated Sales Machine . Not only because you need a system that you can maximize, but also a system that allows you to walk away when you need it.

What would you do if you had a business that was making $300 a day every day?

Mental Models: Unlocking the power of effective thinking

Introduction.

As an ardent consumer of investment and decision-making content, I have come across numerous articles, books, and podcasts where the concept of mental models is hailed as a favorite among investors and experts in the field. Time and time again, the term would pique my interest, yet I never truly grasped the idea in its entirety. While I managed to piece together a vague understanding based on the contexts in which it was mentioned, I couldn't shake the nagging feeling that I was missing out on a powerful tool for enhancing my ability to think effectively and make good decisions.

Fueled by curiosity and a desire to broaden my thinking tools, I decided to do some research and reading on the world of mental models to arrive at a better understanding of what mental models are and why they are so important. In this article, I share my findings on the importance of mental models, discuss useful examples, and provide tips on how to apply them to improve your thinking and decision-making.

Where does the idea come from?

The investment community's fascination with mental models can be traced in part to Berkshire Hathaway's long-time Vice Chairman Charlie Munger's enthusiasm for them. Munger often attributes his extraordinary investment success to his ability to evaluate investments using multiple "mental models," a concept he famously discussed in a 1994 speech at the USC Business School .

Although Munger popularized the term, mental modeling theory dates back to the early 1940s and has been extensively studied across various fields, including psychology, cognitive science, and system dynamics, in the decades since it was first introduced.

What is a mental model?

The concept of mental models varies across disciplines, leading to a vast and intricate literature on their definition, presence, understanding, and application. An in-depth account of this vast literature is not possible within the space of this article, but worth acknowledging that it exists. Bearing that in mind, what follows a somewhat cursory definition which I've pieced together from a brief review of the literature. Fortunately, at least in my experience, a precise scientific definition isn't necessary for understanding the importance of mental models and how to use them to enhance your thinking.

A cursory definition

Mental models are cognitive constructs that help us understand the world around us and make effective decisions. They are frameworks that simplify complex systems, provide context for new information, and help us process, analyze, and interpret experiences. Mental models can be thought of as mental shortcuts or "rules of thumb" that help us navigate our everyday lives.

Why are they important?

A broad base of mental models improves your ability to think clearly, rationally, and effectively. Mental models do this by:

• Enhancing problem-solving skills: Mental models enable us to approach problems from different perspectives, identify patterns, and develop innovative solutions. They allow us to break down complex situations into smaller, more manageable parts, making it easier to evaluate options and determine the best course of action.
• Facilitating better decision-making: Mental models assist in filtering relevant information and minimizing cognitive biases. By incorporating diverse mental models, we can analyze situations more objectively and make informed decisions.
• Improving learning and retention: By providing a structure to organize and interpret new information, mental models promote better understanding and memory retention. They help us link new experiences to existing knowledge, facilitating faster and more effective learning.

What are some examples of useful mental models?

Some mental models I've found particularly useful include:

• The Pareto Principle (80/20 Rule): The Pareto Principle, also known as the 80/20 Rule, is a mental model that can be applied across various fields, including business, economics, and time management. The principle posits that 80% of the outcomes are derived from 20% of the causes. In a business context, this may mean that 80% of a company's profits come from 20% of its customers, or 80% of a project's progress can be attributed to 20% of the tasks. By identifying and concentrating on the critical 20% of tasks or inputs, individuals and organizations can maximize their productivity, effectiveness, and resource allocation. The Pareto Principle can also help in prioritizing and streamlining decision-making processes, allowing people to focus on the most significant factors that will yield the most considerable impact.
• First Principles Thinking: First Principles Thinking is a mental model that involves deconstructing complex problems into their most basic elements and questioning the underlying assumptions. By analyzing a problem from the ground up, individuals can gain a deeper understanding of the core principles and develop innovative, creative solutions that are not constrained by conventional wisdom or established practices. This approach can be applied in various fields, including science, technology, and business, to foster critical thinking and problem-solving skills. First Principles Thinking can help individuals overcome cognitive biases, question the status quo, and identify novel approaches or perspectives that may have been overlooked in traditional problem-solving methods.
• Circle of Competence: The Circle of Competence is a mental model that emphasizes the importance of focusing on areas where an individual possesses expertise or deep understanding. By acknowledging one's limitations and concentrating on domains within one's circle of competence, individuals can make more informed decisions, minimize the risk of costly mistakes, and increase the likelihood of success. This concept can be applied to investing, career development, and personal growth, among other areas. To expand one's circle of competence, it is essential to engage in continuous learning, skill development, and knowledge acquisition. By understanding and respecting the boundaries of one's circle of competence, individuals can develop self-awareness, avoid overconfidence, and ultimately make better decisions in both personal and professional settings.

How should you apply them?

• Develop a mental model toolbox: Expose yourself to various mental models across different disciplines to build a diverse cognitive toolkit. Reading books, articles, and attending workshops can help you acquire new models.
• Choose the right model for the situation: Different mental models are better suited for different situations. Assess the problem at hand and select the appropriate model to guide your thinking and decision-making.
• Practice using mental models: Apply mental models to everyday situations and challenges to strengthen your understanding and improve your ability to use them effectively.
• Challenge your assumptions: Regularly question your beliefs and assumptions, and consider alternative perspectives. This helps to reduce cognitive biases and improve the accuracy of your mental models.

Mental models are powerful cognitive tools that can help us make better decisions, solve complex problems, and enhance our learning capabilities. By developing a diverse set of mental models and applying them effectively, we can unlock the full potential of our minds and achieve greater success in both our personal and professional lives.

Publications

• Béland, F., & Cox, R. H. (2021). The Importance of Mental Models in Implementation Science. Frontiers in Public Health, 9, 680316. https://doi.org/10.3389/fpubh.2021.680316
• Jones, N. A., Ross, H., Lynam, T., Perez, P., & Leitch, A. (2011). Mental Models: An Interdisciplinary Synthesis of Theory and Methods. Ecology and Society, 16(1). https://doi.org/10.5751/es-03802-160146
• World Bank. (2015). Mind, Society, and Behavior. Retrieved from https://www.worldbank.org/content/dam/Worldbank/Publications/WDR/WDR%202015/Chapter-3.pdf
• Rook, L. (2013), Mental Models: A robust definition, The Learning Organization, Vol. 20 No. 1, pp. 38-47. https://doi.org/10.1108/09696471311288519
• Doyle, J.K. and Ford, D.N. (1998), Mental models concepts for system dynamics research. Syst. Dyn. Rev., 14: 3-29.  https://doi.org/10.1002/(SICI)1099-1727(199821)14:1<3::AID-SDR140>3.0.CO;2-K
• Groesser, S.N. (2012). Mental Model of Dynamic Systems. In: Seel, N.M. (eds) Encyclopedia of the Sciences of Learning. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1428-6_1838
• Clear, J. (n.d.). Mental Models: How to Train Your Brain to Think in New Ways. Retrieved from https://jamesclear.com/mental-models
• Farnam Street. (n.d.). Mental Models. Retrieved from https://fs.blog/mental-models/
• Ness Labs. (n.d.). Mental Models: A Beginner's Guide. Retrieved from https://nesslabs.com/mental-models
• Vikhornova, A. (2018, March 1). What We Can Learn from the History of Systems Thinking. Medium. Retrieved from https://medium.com/systems-thinking-for-non-systems-thinkers/what-we-can-learn-from-the-history-of-systems-thinking-79852d8955c4
• Egan, C. (2021). Mental Models: How Peter Senge's Theory Can Change Your Life. Shortform. Retrieved from https://www.shortform.com/blog/mental-models-peter-senge/
• Weiss, R. J. (2021). Charlie Munger's Mental Models Explained. The Ways to Wealth. Retrieved from https://www.thewaystowealth.com/investing/charlie-munger-mental-models-explained/
• Model Theory. (n.d.). What are Mental Models? Retrieved from https://www.modeltheory.org/about/what-are-mental-models/
• NDSU (2022). The Importance of Mental Models. NDSU Career and Advising Center. Retrieved from https://career-advising.ndsu.edu/blog/2022/11/01/the-importance-of-mental-models/
• McKinsey & Company. (n.d.). The beginning of system dynamics. Retrieved from https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/the-beginning-of-system-dynamics#/
• LessWrong. (n.d.). An overview of the mental model theory. Retrieved from https://www.lesswrong.com/posts/YKCoj7DxDMktr4qKP/an-overview-of-the-mental-model-theory
• The Systems Thinker. (n.d.). What are mental models? Retrieved from https://thesystemsthinker.com/what-are-mental-models/

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Mental Models: The Ultimate Guide

Updated: October 17, 2018

Published: September 13, 2018

Have you ever wondered why two heads are better than one -- and four heads are better than two? It's because we're all limited by our own experiences, biases, and areas of expertise.

These areas of expertise give rise to "mental models," assets we're using all the time but might not realize we have.

Your coworker in sales has a different background than you, which means she can bring different ideas to the table. You might spend most of your time creating content on a daily basis, giving you a unique understanding of your brand's voice and position in the industry. Meanwhile, your coworker might spend most of her time speaking to customers, giving her visibility into what your industry really wants right now.

Put you and your sales-minded coworker in a room together, and your combined insights can crack a challenging problem.

But it's just not feasible to host a roundtable discussion every time you need to make an important decision. As individuals, we need to be able to think about our business's problems differently every time we encounter a new one.

Luckily, there's a way to hack the decision-making process and reap the "two heads" effect by yourself: mental models.

What is a mental model?

A mental model is the specific thought process you use to examine a problem. There are many types of known mental models, and each one takes a unique view of a foreign concept in order to reduce its complexity. In short, it is the mind's way of making sense of something.

A mental model is a way of examining a problem. As James Clear explains , "Each mental model offers a different framework that you can use to look at life ... If you develop a bigger toolbox of mental models, you'll improve your ability to solve problems because you'll have more options for getting to the right answer. This is one of the primary ways that truly brilliant people separate themselves from the masses of smart individuals out there."

Charlie Munger's Latticework of Mental Models

To really understand mental models today, take a page from Charlie Munger , Vice Chairman of Berkshire Hathaway, Inc. -- a conglomerate holding company that owns such companies as Geico, Dairy Queen, and Helzberg Diamonds.

A close friend and colleague of Warren Buffet, Munger is known for his interest in psychology. On the subject of decision-making -- primarily in business -- he suggests there are numerous mental models that can help us dismantle and solve difficult problems. Says Munger:

"You can't really know anything if you just remember isolated facts and try and bang 'em back. If the facts don't hang together on a latticework of theory, you don't have them in usable form."

It's this latticework of mental models that allows us to adjust our view of a challenge if we need to. After all, not every dilemma is presented to us the same way, or can be decided on from the same vantage point. The more mental models you experiment with, the more adaptable you'll become to the challenges that come your way.

So, where do you even begin to build your own "latticework" of mental models? Take a look at some of the most common mental models below -- a few of them you might be practicing without realizing it.

14 Examples of Mental Models to Practice (and Avoid)

1. bayes' theorem.

This describes the probability of something happening based on potentially relevant factors. These factors include evidence from past results and current conditions that could affect a new outcome.

To give you an idea of how this theorem might look in the marketing industry, imagine you launched an email marketing campaign four months ago that had a 20% open rate. The following month, you launched a similar email marketing campaign with the goal of a 20% open rate, but instead received a 25% open rate. In the third month, your email campaign saw a 26% open rate. Then, last month, you purged your mailing list of contacts who haven't opened an email from your business in the last 60 days -- and subsequently launched another email campaign.

Given the steady increase in your open rate over the last four months, and the fact that you removed your most inactive emails from your contact list, a realistic open rate goal under Bayes' Theorem might be 30%.

2. Circle of Competence

We can thank Warren Buffett for this mental model . In 1996, Buffett told his shareholders, "You don't have to be an expert on every company, or even many. You only have to be able to evaluate companies within your circle of competence. The size of that circle is not very important; knowing its boundaries, however, is vital."

Concentrate on your area of expertise, and don't be afraid to say "I don't know" when you're dealing with someone else's circle of competence.

For example, a HubSpot content creator can write an article that teaches realtors how to use the inbound methodology to attract homebuyers, but she shouldn't try to write about the real estate industry itself. Realtors know far more about their customers and how the industry operates than HubSpot content creators do.

3. Confirmation Bias

This is a human tendency to look for and interpret information in a way that reinforces or confirms what you already believe.

For instance, if you're confident your website's organic traffic for December will exceed its traffic from November, you might focus too much on December's promising traffic level after just the first week, and not enough on the fact that the holidays later into December often cause B2B website traffic to decrease.

To protect yourself against confirmation bias, accept the idea that your perception doesn't always (or even frequently) equal reality. Challenge yourself to find different interpretations of what's happening.

In the above example, you might think, "Is there anything to suggest our organic traffic for December will drop before the month's over? What might stand in the way of our goal?"

Being more skeptical will lead you to probe more deeply for objections -- which, in turn, will help you set more realistic expectations before it's too late.

4. Inversion Mental Model

The inversion perspective is one of the most powerful mental models. Rather than thinking about your desired outcome, consider the outcome you'd like to avoid.

For example, say you want to be promoted to senior marketing manager. Instead of asking yourself, "What are the top five things I could do to get promoted?" ask yourself, "What are the top 10 things that would prevent my promotion?"

Then, you'd make sure to do none of those things.

As Shane Parrish says , "Avoiding stupidity is easier than seeking brilliance." While you won't always find the answer by inverting the problem, you'll definitely improve.

5. Fundamental Attribution Error

We're more likely to believe someone is acting a certain way because of their character than the situation.

In other words, if your social media strategist doesn't show up to a marketing team meeting, you'll probably think, "They're flakey," not "They must have gotten stuck in traffic."

Challenge yourself to give people the benefit of the doubt. Behavior is usually situational, so your predictions of how people will act will be more accurate if you don't chalk things up to "how they are."

6. Hanlon's Razor

If a marketing qualified lead (MQL) goes dark at a critical point in the acquisition process, you're probably going to assume they were "kicking tires" or decided the information they had wasn't good enough to continue the conversation. Hanlon's Razor, however, asks us to "Never attribute to malice what could be explained by carelessness." In other words, it's more realistic to assume the person is busy instead.

7. Jealousy Tendency

There are two types of envy. The productive type is "inferiority," or the desire to raise yourself up to another person's level. Do you want to become as successful as your team's marketing director? You're motivated by this kind of envy.

The unproductive type is malicious envy, or the desire to take something valuable away from someone else -- not for your own means, but so they don't have it.

These motivators are worth remembering when, for example, you're writing website copy for your online visitors. Your visitors might be personally invested in a particular goal because they want to do as well -- or better -- than another person at their company, or beat someone else's record. Identifying your visitors' desires will help you craft landing page copy that seeks to solve their personal goals.

You should also be conscious of the jealousy tendency in your own decision-making process. While a competitive streak (inferiority envy) might benefit you in a fast-moving startup, wanting other people to fail (malicious envy) will only distract you. Overcome envy by reminding yourself of your similarities to this person, which will trigger your empathy, and avoid the temptation to sabotage them. Turn those impulses into growth opportunities: What skill or habit can you improve to get their results?

8. Law of Diminishing Returns

At a certain point, the incremental benefits you get from an investment get increasingly smaller. The first month you go on a diet, for example, you might lose six pounds. The second month you might lose three. The third month you might lose two.

This concept applies to marketing in several ways. First, make sure you're focusing on the most valuable activities. Let's say you've spent a week researching your buyer persona before launching a blog dedicated to them. As crucial as a detailed buyer persona is to your business, know when to call it complete. You're probably not going to double your results by spending another week sizing up your ideal buyer, and the more trivial the details get, the less those details will actually benefit your content. Instead, use that time to research a different buyer and establish multiple audience segments.

To ensure you spend your time on the things that offer the biggest returns, recognize what you need to know to be successful. Developing a brand voice and a series of calls-to-actions for your blog might be more productive than mastering the entire AP stylebook cover to cover.

There are diminishing returns to memorizing obscure details, and the sooner you notice them, the sooner you can jump on the projects that are more valuable to your business's growth.

9. Margin of Safety

A bridge might theoretically handle up to 15,000 pounds, but it would be wise to cap the weight limit at 14,000. It would be a major disaster if the bridge wasn't actually that strong -- and the risk isn't worth it.

The margin of safety is the idea that we should leave ourselves room for mistakes or failures. For instance, when creating your website's conversion goals, you might not count a downloaded ebook as a lead until they've responded to a follow-up email or sought more information from you, just in case they change their mind.

Think of this model as a safety net. It's better to be pleasantly surprised than proven right.

10. Occam's Razor

This principle states the simplest explanation is usually the correct one. If you're trying to understand what happened, develop the most basic hypothesis possible.

11. Opportunity Costs

Every choice comes at the cost of another. If you decide to send emails after lunch, you can't use that time to write a blog post. If you pursue one large, unpredictable lead-generation campaign, you won't have the bandwidth or the risk tolerance to pursue another at the same time.

Keep this in the back of your mind every time you're deciding what to do. What's the alternative? Are you willing to give that up?

12. Pareto Principle

The Pareto Principle, also known as the 80/20 rule, means most results aren't distributed equally. In other words:

• 20% of the work generates 80% of the returns
• 20% of your traffic yields 80% of your leads
• 20% of features are responsible for 80% of your usage
• 20% of your time produces 80% of your results

If you can hone in on your top customers, selling activities, and so forth, you'll be dramatically more successful.

At my former company, for example, we analyzed our customers and found those who spent the most (i.e., the 20% who created 80% of our revenue) worked in HR. Once we knew that, our sales and marketing teams could target HR professionals. As a result, the company's revenue increased by 230%.

13. Preferential Attachment

Imagine two runners competing in a race. The first runner to pass the one-mile mark gets water and a protein bar. The slower one gets nothing.

This describes the preferential attachment, where the leader is given more resources than their competitors. Those resources give them an even greater advantage.

As a marketer, you see this effect in the lead-nurturing process. It can be tempting to spend all your time serving content to your most qualified leads. But in the process, you might be neglecting the people who are in the early stages of learning about your business, or take a bit more time to open their emails and download certain resources.

No matter how much you might "prefer" getting your furthest-along leads into the hands of a salesperson, it's important not to develop preferential attachment to these people at the expense of other website visitors.

14. Redundancy

Along similar lines, redundancy describes what good engineers do to put back-up systems in place to protect against failure. This drastically reduces your chances of total failure.

As a marketer, you can use this strategy to create a campaign that keeps your readers, subscribers, leads, and existing customers happy and educated while also making a bet on a brand new offering. Maybe you're promoting a huge product right now and have an ambitious lead-generation goal to hit next month. Pursue four or five smaller, low-risk content campaigns at the same time to ensure your lead-gen pipeline remains stable while also rolling out your new product.

With these mental models at your disposal, your analytical and decision making skills will exponentially improve.

Don't forget to share this post!

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These 10 Mental Models Will Make You Smarter

Explore how mental models like first principles thinking, intellectual humility, and other related concepts can foster innovation, creativity, and effective problem-solving.

Csaba Okrona

In a world brimming with complexity and constant change, the ability to think clearly and make well-informed decisions is more valuable than ever. Mental models, which are frameworks or lenses through which we can view and understand the world, play a crucial role in enhancing our cognitive capabilities. They are the tools that shape how we perceive, interpret, and respond to the myriad of challenges and opportunities that life presents. In this blog post, I delve into ten powerful mental models, each offering a unique perspective and strategy for smarter thinking, decision-making, and problem-solving.

From the age-old wisdom of Aristotle’s First Principles Thinking to the modern-day insights of Charlie Munger’s Inversion, these models provide a rich tapestry of thought that can guide us through the complexities of modern life. Whether you’re a business leader making strategic decisions, a student grappling with academic concepts, or an individual navigating personal choices, these mental models offer invaluable guidance.

As we explore each model, we’ll uncover how they can be applied in various aspects of life and work, providing a comprehensive toolkit for anyone seeking to enhance their cognitive abilities. These models aid in solving specific problems and contribute to a broader understanding of how to approach challenges in a more thoughtful, informed, and effective manner.

First Principles Thinking

First principles thinking finds its genesis in ancient Greek philosophy, particularly in the work of Aristotle. Aristotle, in his approach to understanding the world,  emphasized  the importance of breaking down complex concepts into their most basic and undeniable truths or ‘first principles.’ This method was a radical departure from relying on analogy or comparison, which were prevalent in the thought processes of his time. Instead, Aristotle proposed that by understanding the fundamental truths of a subject, one could reconstruct knowledge or solve problems from the ground up, free from the constraints of existing assumptions or beliefs.

This approach has a timeless appeal, as it encourages critical thinking and a profound understanding of the underlying nature of things. In an era where information overload is common, first principles thinking offers a way to cut through the noise and focus on what is most essential.

The Utility of First Principles Thinking in Modern Problem-Solving

The utility of first principles thinking in contemporary contexts is vast. This method is particularly valuable in:

• Innovation and Creativity : By breaking down problems to their fundamental elements, it allows thinkers to sidestep conventional wisdom and develop original solutions.
• Complex Problem-Solving : In complex systems or problems, first principles thinking helps identify the core issues, leading to more effective solutions.
• Learning and Understanding : This approach promotes a deeper understanding of subjects by encouraging individuals to build knowledge from the ground up.
• Decision-Making : First principles thinking aids in making clear, rational decisions by focusing on fundamental truths rather than assumptions or biases.

In business and technology, for instance, this approach helps leaders and entrepreneurs navigate rapidly changing landscapes by fostering innovative solutions that are not merely incremental improvements but rather groundbreaking leaps in thinking and execution.

Real-World Applications: From Elon Musk to Julia Child

Several prominent figures have applied first principles thinking with notable success:

• Elon Musk and SpaceX : Elon Musk, CEO of SpaceX, is perhaps one of the most famous contemporary advocates of first principles thinking. When faced with the high cost of rocket components, instead of looking for cheaper suppliers, Musk and his team broke down the rocket into its fundamental materials and functions. This analysis revealed that the raw materials of rockets were significantly cheaper than the rockets themselves, leading to the idea of building rockets in-house, drastically reducing costs.
• Julia Child and Culinary Arts : Julia Child, the celebrated chef,  applied first principles thinking  to the art of French cooking. She deconstructed complex French recipes to their basic elements, making them accessible and understandable to the American public. This approach not only demystified French cuisine but also revolutionized home cooking in the United States.
• Steve Jobs and Apple : Steve Jobs, co-founder of Apple, applied first principles thinking in product design. By focusing on the fundamental aspects of user experience and aesthetics, Jobs guided Apple to create products that were not just incremental improvements on existing technology but were innovative and set new industry standards.

Harnessing the Power of First Principles Thinking as a mental model

To effectively apply first principles thinking, one must:

• Identify and Challenge Assumptions : Recognize the existing assumptions about a problem or situation and question their validity.
• Break Down Problems into Basic Elements : Deconstruct the problem into its most fundamental parts.
• Rebuild from the Ground Up : Use these basic elements to explore new solutions and approaches.
• Apply Across Contexts : Utilize this method in various fields — from business and technology to personal decision-making.

In conclusion, first principles thinking is more than a mere problem-solving tool; it’s a mindset that encourages deep understanding and innovative solutions. Its origins in ancient philosophy, its utility in modern contexts, and its application by contemporary innovators all attest to its enduring value. By embracing this approach, individuals and organizations can foster a culture of creativity, critical thinking, and groundbreaking innovation.

Intellectual Humility as a mental model

Intellectual humility, a concept rooted in the recognition of our cognitive limitations, is a cornerstone of effective learning, communication, and decision-making. By questioning our own knowledge and being open to changing our beliefs based on new information, we foster a mindset that is not only adaptable but also profoundly honest and self-aware. This approach to thinking and learning revolves around several key elements: recognizing our blind spots, admitting our errors, tempering our convictions, and being open to altering our beliefs.

Recognizing Our Blind Spots: The First Step to Wisdom

The journey towards intellectual humility begins with an acknowledgment of our blind spots. These are areas in our understanding or knowledge where we may be either uninformed or misinformed but remain unaware of these gaps. The recognition of blind spots is crucial because it opens us to the possibility that what we think we know might not be complete or accurate. This self-awareness is the first step in cultivating a mindset that seeks to understand more deeply and broadly.

In professional and personal contexts, recognizing blind spots can lead to more inclusive and comprehensive decision-making. It allows us to consider perspectives and data that we might have otherwise overlooked, leading to more informed and effective solutions.

The Courage to Say, “I Was Wrong”: Embracing Vulnerability

Admitting when we are wrong is a powerful demonstration of intellectual humility. This admission not only signifies a commitment to truth over ego, but also fosters a culture of learning and growth. In environments where individuals can openly acknowledge their mistakes without fear of judgment, there is a greater opportunity for collective learning and progress.

The ability to say “I was wrong” is particularly vital in leadership. It creates an atmosphere of trust and respect, encouraging others to also be open about their uncertainties and errors. This leads to more honest conversations and a deeper collective understanding.

Exercising Caution with Our Convictions: The Balance of Belief and Inquiry

Being careful with our convictions means maintaining a balance between what we believe and our willingness to question those beliefs. It involves understanding that our current knowledge and perspectives are, at best, incomplete, and being open to the possibility that they may be challenged or disproven by new evidence or arguments.

This cautious approach to convictions doesn’t imply a lack of confidence or commitment to our beliefs. Rather, it suggests a form of intellectual flexibility – a readiness to refine or revise our understandings in the light of new information. Such an approach is invaluable in a world where knowledge and contexts are constantly evolving.

The Willingness to Change Our Own Beliefs: A Dynamic Mindset

The hallmark of intellectual humility is the willingness to change our own beliefs when presented with new evidence or compelling arguments. This doesn’t mean being fickle or easily swayed but having a mindset that is both critical and open. It’s about being anchored in evidence and reason, rather than in pride or tradition.

This willingness to change beliefs is essential for continuous learning and adaptation. It enables us to grow both personally and professionally, as we are not confined by the limitations of our past understanding but are always moving towards a more nuanced and comprehensive view of the world.

The Pareto Principle

The Pareto Principle, commonly known as the 80/20 rule, is a powerful mental model that can significantly enhance decision-making and efficiency. By understanding and applying this principle, individuals and organizations can make smarter choices, prioritize more effectively, and achieve better outcomes with less effort. Let’s explore how the Pareto Principle functions as a mental model and examine some real-world examples of its application.

Understanding the Pareto Principle as a Mental Model

The Pareto Principle, initially observed by economist Vilfredo Pareto, states that roughly 80% of effects come from 20% of causes. This principle has been found applicable in various domains, suggesting that a small proportion of inputs often leads to a majority of the results. As a mental model, the Pareto Principle encourages us to identify and focus on the most effective set of actions that yield the greatest benefits. It aids in recognizing the imbalance in effort and reward and leveraging this knowledge for strategic planning and execution.

Examples Demonstrating the Pareto Principle in Action

• Business Operations and Sales : In many businesses, it’s observed that 80% of sales come from 20% of customers. This insight is invaluable for marketing and customer relationship strategies. By focusing on the needs and preferences of this key customer segment, businesses can maximize their sales and customer satisfaction with relatively less effort.
• Personal Productivity and Time Management : On a personal level, the Pareto Principle can be applied to productivity. Often, 20% of our tasks contribute to 80% of our productivity. By identifying and prioritizing these tasks, individuals can enhance their efficiency, focusing on what truly matters and achieving more significant results in less time.
• Software Development and Bug Fixing : In software engineering, it’s often found that 20% of the code contains 80% of the bugs. Recognizing this can help teams prioritize their debugging efforts, focusing on the most problematic areas of the code to improve software quality more efficiently.
• Health and Fitness : In the realm of health and fitness, the Pareto Principle can be observed in how a small number of lifestyle changes can lead to significant health improvements. For instance, 20% of exercise routines or dietary changes might contribute to 80% of an individual’s health benefits, suggesting a more targeted approach to fitness and nutrition.
• Inventory Management : In inventory management, a common observation is that 20% of products account for 80% of sales or inventory costs. This insight helps businesses in optimizing their inventory, focusing on the most profitable or cost-intensive items for better financial management.
• Environmental Conservation Efforts : When addressing environmental issues, often a small number of sources are responsible for a large proportion of pollution or environmental degradation. By targeting these key sources, conservation efforts can be more effective and impactful.

The Mediocrity Principle as a mental model

The Mediocrity Principle, a mental model rooted in the idea that our personal experiences and the events around us are not exceptional but rather the result of natural, universal laws, offers a unique perspective for enhancing our thinking and emotional well-being. By accepting that we are not inherently special or unique, we can approach life with greater humility, reduced anxiety, and a more realistic understanding of our place in the world. This principle can be a liberating framework, aiding us in navigating life’s challenges with a grounded and balanced mindset.

The Core of the Mediocrity Principle: A Perspective of Humility

The essence of the Mediocrity Principle lies in the recognition that our experiences, while personally significant, are not unique or extraordinary in the grand scheme of things. This realization is not meant to diminish our individual value or experiences but to place them in a broader, more realistic context. By acknowledging that we are part of the vast tapestry of life governed by universal laws and shared experiences, we can shed the burden of believing that our challenges or successes are singularly unique.

This perspective is beneficial in several ways:

• Reducing Anxiety and Stress : Understanding that our experiences are often shared can alleviate feelings of isolation and anxiety. Knowing that others have faced similar challenges and prevailed can provide comfort and a sense of shared humanity.
• Fostering Humility : The Mediocrity Principle encourages a humble approach to life. It reminds us that our knowledge and experiences are just a small part of a much larger world, promoting a mindset that is open to learning and growth.
• Encouraging a Realistic Outlook : This principle helps us view our achievements and setbacks in a realistic light. It promotes a balanced perspective where we neither overestimate our successes nor undervalue our struggles.

Practical Applications of the Mediocrity Principle

• Personal Growth and Self-Reflection : When facing personal challenges or successes, the Mediocrity Principle reminds us that these experiences are not unique to us. This understanding can lead to a more objective and less self-centered approach to self-reflection and growth.
• Interpersonal Relationships : In relationships, this principle helps in understanding that many conflicts or dynamics are not unique but part of common human interactions. This can lead to more empathy and less ego-centric reactions.
• Professional Life : In the workplace, the Mediocrity Principle can help in dealing with competition, failure, or success. Recognizing that our professional journey is influenced by common factors experienced by many can guide more rational career decisions and interactions.
• Coping with Life’s Ups and Downs : In dealing with life’s various ups and downs, this principle offers a grounding perspective. It helps in realizing that many of life’s events are part of the common human experience, which can be comforting and enlightening.

Probabilistic Thinking

Probabilistic thinking, a mental model that employs mathematics and logic to estimate the likelihood of various outcomes, is a fundamental tool for making smarter decisions. By continuously updating our expectations based on new information and systematically questioning our assumptions, we can approach problems and decisions with a more nuanced and informed perspective. This method not only enhances our understanding of potential outcomes but also improves our ability to make decisions in uncertain and complex situations.

The Essence of Probabilistic Thinking: Navigating Uncertainty with Logic and Math

At its core, probabilistic thinking is about understanding and working with uncertainty. It involves estimating the likelihood of different outcomes based on available information and recognizing that these estimates may change as new information emerges. This approach stands in contrast to deterministic thinking, where outcomes are seen as fixed and certain. Probabilistic thinking acknowledges that the world is complex and that outcomes are often influenced by a variety of factors, many of which are uncertain.

This mental model is particularly valuable in scenarios where decisions need to be made with incomplete information. By quantifying uncertainty and considering a range of possible outcomes, we can make more informed and rational choices.

Implementing Probabilistic Thinking: Key Questions to Ask

To effectively apply probabilistic thinking, it’s helpful to regularly ask ourselves several critical questions:

• What Else Might Happen? : This question encourages us to consider a range of possible outcomes, not just the ones that are most apparent or desirable. By thinking about alternative scenarios, we can better prepare for a variety of possibilities.
• What If You’re Wrong? : This question prompts us to challenge our assumptions and consider the implications if our current understanding or predictions are incorrect. It’s a crucial step in developing a more robust and resilient decision-making process.
• What Could Be Next? : This forward-looking question helps us anticipate future developments and trends. By considering what might happen next, we can make decisions that are not just reactive but proactive, taking into account potential future changes.

Real-World Applications of Probabilistic Thinking

• Investment and Financial Planning : In finance, probabilistic thinking helps investors assess risks and potential returns of different investment options. By estimating the probabilities of various market movements and economic scenarios, investors can make more informed decisions about where to allocate their resources.
• Business Strategy and Planning : Businesses use probabilistic thinking to evaluate the risks and potential outcomes of different strategic choices. This might involve estimating the likelihood of success for a new product launch or the impact of changing market conditions on business operations.
• Healthcare and Medical Diagnosis : Doctors often use probabilistic thinking when diagnosing patients. Based on symptoms, medical history, and test results, they estimate the likelihood of various diseases or conditions.
• Personal Decision-Making : On a personal level, probabilistic thinking can be used for decisions like planning a career move or making major life choices. By considering the probabilities of various outcomes and continually updating these estimations as new information becomes available, individuals can make more informed and rational decisions.

Projective Thinking

Projective Thinking is a mental model that champions the suspension of disbelief by currently accepted views, encouraging a mindset that is open, speculative, and creative. This approach to thinking is not just about challenging the status quo but about envisioning new possibilities and contexts that transcend conventional boundaries. By integrating intellectual humility, Projective Thinking enables us to explore uncharted territories of thought and innovation. It involves creating new contexts, concepts, and objectives, thus fostering a rich environment for groundbreaking ideas and solutions.

The Dynamics of Projective Thinking: Beyond the Conventional

At its essence, Projective Thinking requires us to step outside our comfort zones and established belief systems. It’s about imagining ‘what could be’ rather than just accepting ‘what is.’ This form of thinking is particularly potent in scenarios where traditional approaches have failed to solve complex problems, or where new challenges demand innovative solutions.

Projective Thinking is distinguished by several key characteristics:

• Suspension of Disbelief : This is the fundamental step in Projective Thinking. It involves setting aside our preconceived notions and the limitations of current knowledge to explore new possibilities.
• Intellectual Humility : Recognizing that our current understanding is limited and being open to radically different ideas is crucial in Projective Thinking. It’s about acknowledging that there might be many things we don’t know or understand yet.
• Open-Ended Exploration : Projective Thinking is inherently speculative. It’s about asking ‘what if’ and exploring a range of potential scenarios without being constrained by existing models or theories.

Implementing Projective Thinking: Context, Concepts, Objectives

• Creating Context : This involves understanding the broader environment in which a problem or situation exists. It’s about looking at the bigger picture and considering factors that might not be immediately apparent.
• Developing Concepts : In this stage, new ideas and theories are formulated. These concepts don’t have to be fully formed or immediately practical; they are starting points for further exploration and refinement.
• Establishing Objectives : Setting objectives in Projective Thinking is about defining what we want to achieve with our speculative ideas. These objectives can be ambitious and forward-looking, guiding our exploration towards meaningful and impactful outcomes.

Examples of Projective Thinking in Action

• Technology and Innovation : Consider the development of the smartphone. Before its invention, the idea of a single device handling communication, entertainment, and information was speculative. Projective Thinking enabled innovators to envision a new context where all these functionalities converge in one device.
• Urban Planning and Sustainability : Urban planners using Projective Thinking might envision cities of the future. They create contexts where sustainability, technology, and human-centric design converge, leading to innovative concepts in urban living.
• Scientific Research : In science, Projective Thinking can lead to groundbreaking theories. For instance, considering the possibility of multiverses or new dimensions in physics requires a speculative approach that goes beyond current scientific understanding.
• Art and Creative Fields : Artists and writers often use Projective Thinking to create new worlds, characters, and stories. They build contexts and concepts that challenge the viewer’s or reader’s understanding of reality.

The Law Of Large Numbers

The Law of Large Numbers is a fundamental mental model in the realm of probability and statistics, serving as a crucial tool for understanding and predicting outcomes in various contexts. This law posits that as the size of a sample increases, the sample average tends to converge towards the theoretical or expected average of the population. This principle is not only central to probabilistic thinking but also forms the foundation of many business models and decision-making processes. Understanding the Law of Large Numbers helps in distinguishing between reliable and unreliable data, especially in the context of studies or business strategies.

The Law of Large Numbers: Bridging Theory and Reality

The essence of the Law of Large Numbers lies in its ability to link theoretical predictions with empirical observations. In probability theory, this law reassures us that with a sufficiently large sample size, the average of the results obtained will be close to the expected value, and will tend to become closer as more trials are performed. This principle is vital in fields where outcomes are subject to randomness or uncertainty.

Two versions of this law are often discussed:

• The Weak Law of Large Numbers : This version states that for a large number of trials, the sample average will be approximately equal to the expected value with a high probability.
• The Strong Law of Large Numbers : This stronger version asserts that the sample average will almost surely converge to the expected value as the sample size goes to infinity.

Practical Applications: From Casinos to Research Studies

• Casinos and Gambling Industries : Casinos are a classic example of a business model built on the Law of Large Numbers. They rely on the statistical certainty that over a large number of bets, the outcomes will average out to a predictable percentage in favor of the house. This ensures profitability in the long run, despite individual variations and wins.
• Insurance and Risk Assessment : Insurance companies use this law to predict loss averages over a large number of clients. By understanding that individual variations will average out, they can set premiums and payouts that are profitable over time.
• Scientific and Medical Research : In research, the Law of Large Numbers underscores the importance of large sample sizes in studies and experiments. Larger samples lead to more reliable and generalizable results, reducing the impact of anomalies or outliers.
• Financial Markets and Investing : Investors and analysts often rely on this principle to predict market trends and risks. Understanding that short-term fluctuations may not reflect long-term realities, they use large data sets to make more informed decisions.

The Law of Small Numbers: A Cautionary Note

Conversely, the Law of Small Numbers warns against over-relying on small samples. Small sample sizes can lead to misleading results, as they may not accurately represent the larger population. This is crucial in evaluating research studies, business pilots, or any scenario where conclusions are drawn from limited data. A small sample might yield results that are significantly different from the true population average, leading to incorrect assumptions or decisions.

Bottom-Up Thinking

Bottom-Up Thinking is a mental model that emphasizes starting from the most fundamental principles or elements and building upwards to form a comprehensive understanding or solution. Contrasting with top-down thinking, where ideas or hypotheses are accepted as a given and then validated, bottom-up thinking encourages a more exploratory and foundational approach. This method, akin to constructing a house from the ground up, ensures a solid and well-thought-out framework for ideas and solutions, often leading to innovative and more robust outcomes.

The Essence of Bottom-Up Thinking: From First Principles to Complex Ideas

Bottom-Up Thinking is grounded in the concept of first principles — the most basic, foundational elements or truths of a given subject or problem. By identifying and understanding these first principles, bottom-up thinkers can construct complex ideas, solutions, and mental models that are rooted in fundamental truths rather than assumptions or preconceived notions.

This approach offers several advantages:

• Clarity and Depth of Understanding : Starting from the basics ensures a thorough comprehension of the underlying factors or principles of a subject, leading to a clearer and more profound understanding.
• Innovation and Creativity : Since bottom-up thinking is not constrained by existing models or theories, it often leads to novel insights and innovative solutions that might not be evident when using a top-down approach.
• Flexibility and Adaptability : This method allows for greater adaptability, as the foundational understanding can be reassembled or adjusted to accommodate new information or insights.

Practical Applications: Bottom-Up Thinking in Action

• Problem-Solving in Business and Technology : In business and technology, bottom-up thinking can lead to innovative product designs and solutions. For instance, a company may start by understanding the fundamental needs and behaviors of its customers before developing a product, ensuring that the final design is closely aligned with user requirements.
• Scientific Research and Discovery : Scientists often employ bottom-up thinking. They start with basic observations and experiments, gradually building up to more complex theories. This method ensures that theories are solidly grounded in empirical evidence.
• Learning and Education : In education, a bottom-up approach involves starting with foundational concepts before moving to more advanced topics. This approach ensures that students have a solid understanding of the basics, which is essential for comprehending more complex ideas.
• Programming and Software Development : In software development, a bottom-up approach might involve starting with writing small, functional modules or components of code before integrating them into a larger system. This ensures that each part of the system is robust and well-functioning on its own.

The Shifting Baseline Syndrome

The Shifting Baseline Syndrome is a mental model that highlights the often unnoticed change in our baseline assumptions or perceptions over time. This concept, particularly relevant in the context of environmental and social changes, suggests that each generation accepts their current state as the norm, often overlooking the changes from previous generations. This syndrome can lead to a gradual acceptance of deteriorating conditions or standards. By regularly reassessing and updating our baselines, akin to the approach in probabilistic thinking, we can maintain a more accurate and informed perspective.

Understanding the Shifting Baseline Syndrome: The Subtlety of Change

The core idea of the Shifting Baseline Syndrome is that our perception of normality evolves, often without our conscious awareness. This change can happen due to gradual alterations in our environment, society, or personal lives. Over time, what was once considered extraordinary or unacceptable may become the new norm, and vice versa. This shift can have significant implications, especially when it leads to complacency or a failure to recognize detrimental changes.

Applications and Implications of Shifting Baselines

• Environmental Conservation : In ecology, this syndrome is often discussed in the context of environmental degradation. For instance, each successive generation might perceive the level of biodiversity or environmental quality they experience in childhood as normal, not realizing the degradation from previous generations. This perception can lead to a lack of urgency in addressing environmental issues.
• Social and Cultural Norms : Shifting baselines also occur in societal and cultural contexts. What is considered socially acceptable or normal can change over time, impacting laws, policies, and social behaviors. Regularly reassessing these norms is crucial for social progress and ethical decision-making.
• Personal Development and Goals : On a personal level, shifting baselines can impact our goals and standards. For example, as one advances in their career, their baseline for what constitutes success may change, affecting their satisfaction and motivation.
• Health and Lifestyle Standards : In health, perceptions of what is normal in terms of lifestyle, diet, and physical activity can shift, influencing public health outcomes and personal well-being.

Counteracting the Shifting Baseline Syndrome: Strategies for Maintaining Awareness

• Regularly Ask Questions : Regularly questioning and reassessing our assumptions helps in maintaining an accurate understanding of changes. Asking questions like “Has this always been the norm?” or “How has this situation changed from 10 years ago?” can provide perspective.
• Challenge Your Assumptions : Actively challenging our current beliefs and assumptions is crucial. This involves seeking information from a variety of sources and perspectives to understand broader changes and trends.
• Reset Your Baselines Regularly : Consciously updating our baselines in light of new information and changes ensures that our perceptions and decisions are based on current realities rather than outdated norms.
• Historical Comparisons : Looking back at historical data or experiences can provide a clear contrast to current conditions, highlighting changes that might have gone unnoticed.

Inversion, a mental model popularized by Charlie Munger, vice chairman of Berkshire Hathaway, encourages approaching problems from the opposite end of the traditional forward-thinking perspective. This model is rooted in the idea of understanding and avoiding the actions or decisions that could lead to negative outcomes. As Munger famously advised, rather than solely focusing on what would lead to success, it is equally, if not more important, to consider what would prevent or impede it. Inversion is about visualizing the opposite of what you want to achieve and working backward to understand and avoid potential pitfalls.

The Power of Inverse Thinking: Averting Failure to Pave the Path to Success

The principle of inversion revolves around the concept of thinking backward or in reverse. Instead of directly aiming for success, this approach prompts us to consider all the ways in which we could fail and then strategically avoid those paths. This reverse analysis often reveals insights and considerations that might be overlooked in conventional forward-thinking processes.

Key aspects of this approach include:

• Identifying Potential Pitfalls : By imagining scenarios where things go wrong, we can identify potential risks and challenges that might not be obvious at first glance.
• Risk Mitigation : Understanding what could lead to failure allows us to take proactive steps to mitigate these risks.
• Clearer Goal Definition : Sometimes, knowing what we don’t want can be as important as knowing what we do want. Inversion helps in clarifying objectives by framing them in terms of what to avoid.

Practical Applications of Inversion

• Business Strategy and Decision-Making : Businesses can use inversion to avoid strategies that could lead to failure. For example, a company might consider all the factors that could lead to a product’s failure in the market and work to mitigate these issues during the development stage.
• Personal Goals and Self-Improvement : On a personal level, inversion can be applied to goal setting and habit formation. For instance, rather than just focusing on the habits that lead to good health, one might consider the habits that contribute to poor health and actively avoid them.
• Financial Planning and Investment : Investors often use inversion to avoid significant losses. By considering the factors that could lead to a bad investment, they can make more informed decisions that safeguard their assets.
• Project Management and Planning : In project management, envisioning what could cause a project to fail helps in developing more robust and risk-averse planning.

Embracing Inversion: A Guiding Quote from Charlie Munger

Charlie Munger’s advice, “Don’t focus on success; focus on not making mistakes,” encapsulates the essence of inversion. It’s about shifting the focus from solely pursuing success to also understanding and avoiding the paths that lead to failure. This perspective encourages thorough analysis, risk awareness, and strategic planning.

In this exploration of ten diverse and powerful mental models, we have journeyed through a range of strategies that can profoundly enhance our thinking, decision-making, and problem-solving abilities. Each model, from the time-tested wisdom of First Principles Thinking to the innovative approach of Inversion, offers unique insights and practical methods for navigating the complex challenges of the modern world.

• First Principles Thinking  grounds us in the fundamental truths, enabling us to build knowledge and solutions from the base up.
• Intellectual Humility  reminds us to acknowledge our limitations and be open to new perspectives and information.
• The Pareto Principle  guides us to focus on the most effective actions that yield the greatest benefits.
• The Mediocrity Principle  helps in maintaining a realistic perspective, understanding that our experiences are often shared and not unique.
• Probabilistic Thinking  encourages us to embrace uncertainty and make decisions based on likelihoods and informed estimations.
• Projective Thinking  invites us to envision novel possibilities and think beyond the conventional frameworks.
• The Law of Large Numbers  underlines the importance of large sample sizes in making accurate predictions and decisions.
• Bottom-Up Thinking  emphasizes building complex ideas from simple, foundational elements.
• The Shifting Baseline Syndrome  warns of the gradual, often unnoticed shifts in our baseline assumptions and perceptions.
• Inversion  challenges us to think in reverse, focusing on avoiding failures to pave the way for success.

Each of these mental models, with their unique lenses and approaches, equips us with the tools to think more deeply, act more wisely, and adapt more effectively to an ever-changing world. By integrating these models into our cognitive toolkit, we can enhance our ability to make smarter decisions, foster innovation, and navigate life’s complexities with greater acumen and success.

In essence, these mental models are not just techniques for thought; they are guides for a more insightful, effective, and fulfilled life. As we continue to face new challenges and opportunities, the application of these models can be our compass, leading us to more informed and enlightened paths. Let us embrace these models as we endeavor to understand our world better and craft a future marked by wisdom, creativity, and thoughtful action.

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Mental Models

What are mental models.

Mental models are representations of the world that help us understand complex concepts and make better decisions.

They provide a framework for thinking and problem-solving, allow us to view problems from different angles and generate creative solutions, and help us become more effective thinkers and problem solvers. 

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We create mental models based on past experiences, beliefs, and assumptions to understand how the world works. Mental models can be conscious or unconscious, varying in accuracy and usefulness depending on the context. 

Mental models are essential for decision-making, problem-solving, and learning, as well as effective communication and collaboration in group settings. However, mental models can also lead to bias and errors if they are incomplete, inaccurate, inflexible, or resistant to change.

Mental Models in UX Design

“Users spend most of their time on other sites. This means that users prefer your site to work the same way as all the other sites they already know." — Jakob’s Law (Jakob Nielsen)

Mental models are important in creating user-friendly interfaces. Designers research users' mental models to create designs that align with their expectations and beliefs. Research takes various forms, such as ethnographic research through surveys or observation. If interfaces match users’ expectations, they do not have to learn new concepts or behaviors. For example, a shopping cart icon is a standard mental model for e-commerce websites. Skeuomorphic design elements, like virtual buttons that resemble real-world buttons, also help users. 

Mental models help people understand the world—they simplify complex concepts. Every individual forms their own mental model, and different people might form different models for the same interface. This is why we cannot rely on any one mental model to solve problems. Designers know this and have developed principles and methodologies like Jakob's Law and design thinking to understand their users' mental models better.

Jakob's Law emphasizes consistency in user experience design. Users may need support with unfamiliar design patterns, leading them to abandon tasks. Designs that align with users' mental models can address this issue. For example, if the designer places the navigation menu in an unexpected location, users may struggle to find it.

Design thinking is a problem-solving approach that aims to understand users' needs and preferences by involving them in every stage of the design process. Designers using this method often conduct user research, create personas, and then conduct user testing to identify potential problems with their designs.

How to Communicate Mental Models

As mental models are abstract, we can use different formats to communicate them. Each form has its unique advantages and applications: 

Conceptual Models: Conceptual models are used in HCI and interaction design as a way for designers to communicate how they interpret users' mental models to stakeholders, team members, and developers. Some examples of conceptual models are diagrams, flowcharts, or narratives. They are often used in science, engineering, and design to develop and test hypotheses, communicate complex ideas, and guide decision-making.

For example, a conceptual model of a forest could include wildlife, insects, trees, etc., their roles, how they interact and the different life stages they go through. This model can predict the effects of, say, introducing a new species or climate change.

Visual Models: Visual models describe data, concepts, or processes, such as diagrams, charts, graphs, maps, infographics, and animations. Visual models are often used in science, engineering, education, and business to simplify and make information more accessible . Compared to conceptual models, visual models provide more detailed and specific information.

A user flow is a visual representation of a user's path to accomplish a task on a website or app. It shows the steps involved in the process, including any user's decision points or actions.

© Interaction Design Foundation, CC BY-SA 4.0

Applications of Mental Models in Everyday Life

We can use mental models in everyday life to understand our environment better and make more informed decisions. 

Problem-solving: An example of problem-solving through mental models is the 5 Whys. The 5 Whys can help you understand how a user thinks and diagnose the cause of a problem with a series of "why" questions.

Decision-making: Mental models help us analyze the potential consequences of different decisions and identify which is most likely to lead to a desirable outcome. An example is the "cost-benefit analysis," which evaluates the costs and benefits of different options regarding financial, social, or environmental impacts.

Critical thinking: Methods like the scientific or Socratic methods help you question your assumptions and challenge commonly held beliefs.

The Five Whys method is a problem-solving technique that involves asking "Why?" five times to uncover the root cause of an issue. It helps to understand the underlying mental models that inform decision-making process

Learn More about Mental Models

Learn how to use Mental Models in Mobile UX .

Read more about the importance of mental models in decision-making and critical thinking, using Charlie Munger's approach as an example.

Discover how to create user-friendly designs that align with users' mental models by applying Jakob's Law . 

Don’t miss this excellent masterclass to learn How To Design For The Way Your Users Think .

Learn about mental models and their role in user experience design in this informative article.

Read more about transforming Mental Models into Conceptual Models for Mobile UX .

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What are mental models?

• Representations of how the world works
• Representations of physical objects
• Scientific theories

Why do UX designers research users' mental models?

• To align designs with users' expectations
• To create physical objects based on digital designs
• To develop scientific theories

What does Jakob’s Law state about users' behavior?

• Users dislike consistency in design
• Users prefer interfaces that work like other familiar ones
• Users prefer new and unique interfaces

What is a common issue when designers rely on their own mental models?

• It always aligns with users' expectations.
• It can cause a mismatch with users' mental models.
• It leads to innovative designs.

What is the purpose of visual models in UX design?

• To create physical high-fidelity prototypes
• To replace conceptual models completely
• To simplify and communicate complex concepts

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Literature on Mental Models

Here’s the entire UX literature on Mental Models by the Interaction Design Foundation, collated in one place:

Learn more about Mental Models

Take a deep dive into Mental Models with our course Mobile UX Strategy: How to Build Successful Products .

All open-source articles on Mental Models

An introduction to usability.

• 4 years ago

How to Use Mental Models in UX Design

Mental models

How to Transform Mental Models into Conceptual Models for Mobile UX

Understand the Elements and Thinking Modes that Create Fruitful Ideation Sessions

How to Design for Ease of Use

• 3 years ago

Three Common Models of the Brain to Help You Develop Better User Experiences

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Mental Models: The Secret Weapons for Intelligent Decision-Making

Sudarshan Somanathan

Head of Content

February 13, 2024

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From something as simple as choosing what to wear for work to as complex as what business strategy to implement to achieve a competitive advantage, making decisions is an integral part of our everyday lives. The human brain is wired in such a way that we make many of these choices subconsciously, without even being aware of it! 🧠

However, not all decisions are (or should be) made subconsciously—sometimes, they result from proper thought, analysis, and planning. In such situations, a structured decision-making approach is necessary to make the right calls or have a winning strategy.

That structured approach to thinking and reasoning is what the term mental models is all about. In this all-encompassing article, we’ll introduce the 10 most well-known mental model examples and see how they can help you get your desired outcome at a certain point. We’ll also introduce you to a powerful productivity tool to help you implement any mental model in your personal and professional life.

What Are Mental Models?

1. baye’s theorem, 2. opportunity cost, 3. redundancy, 4. backward chaining, 5. pareto principle (80/20 rule), 6. law of diminishing returns (or diminishing marginal utility), 7. margin of safety, 8. confirmation bias, 9. preferential attachment, 10. hanlon’s razor.

In the simplest possible terms, mental models are thinking tools. They’re structured cognitive frameworks that allow a human being to critically and rationally analyze any situation or problem at hand and make informed decisions .

Think of a mental model as a simplified representation of reality that helps you process complex systems and information to solve problems efficiently. 

A prominent thinker and Warren Buffett’s partner, Charlie Munger, was among the first proponents of mental models. He argued that until you see the facts hanging together through a “ latticework of theory ,” you can’t make sense of them. To overcome these blind spots, you must consciously develop and apply various mental models to the data and facts to comprehend them and understand your options in any given situation.

Keep in mind that certain mental models can also be negative and should be avoided. It’s human nature to develop the wrong mental routines during stressful situations—for example, a fight-or-flight response in the face of danger.

Now, let’s take a look at the 10 most prominent frameworks for interpreting information, understanding how the world works, and making the best possible decisions, every time! 

10 Mental Models to Implement (or Avoid!) in Your Everyday Life

There are dozens of mental models that can help you make all types of decisions . But for the sake of brevity, we’ve hand-picked the 10 most prominent ones for improving your thinking and reasoning in both personal and professional realms.

We’ll also explore how ClickUp , a platform designed to improve work performance and get things done , can help you apply these mental models with its various project management and productivity features. 

Baye’s theorem tries to predict the possibility of any event or situation by analyzing the relevant and historical data and other situational factors that may lead to them. It’s the mathematical way of predicting an event’s probability rather than relying on assumptions, which are often incorrect or biased. Here’s what the Baye’s theorem formula looks like: 

After you’ve evaluated the mathematical probability of multiple outcomes using Baye’s theorem, you can use ClickUp Whiteboards —ClickUp’s digital whiteboarding feature—to analyze the potential impact of each event.

If you’re not used to whiteboards, you can get a head start with the ClickUp Probability and Impact Matrix Template to plot the probability and impact of each outcome on an XY-plane for easy analysis. This can help you maintain realistic expectations and make informed decisions regardless of what the future holds. 

There’s a cost to every decision we make in terms of the abandoned alternatives . The opportunity cost analysis provides insight into what you may be missing out on by selecting a particular option in a given situation. This understanding enables you to evaluate the comparative advantage of your choices in an impartial and unbiased manner. 

You can quickly analyze opportunity costs of any choice with the ClickUp Gantt Chart view . Use it to build detailed visual roadmaps of each important aspect of your workload and easily identify the tasks that may get delayed or abandoned if you decide to take on additional work. 

And since Gantt charts also visualize dependencies , you can get a clear picture of every activity that may be affected by a delay in the completion of any particular task. 

You may already be familiar with this one—redundancy refers to having an extra quantity of some crucial resource (i.e., an additional machine or employee). It provides a backup plan if the essential resource you need breaks down before completing its intended job. 

Here’s what it looks like—if you assess that you’ll need 10 people to manage a project , onboard 11-12. Ensure that the 10 members of the new team are experts in their respective fields, and that the other two have a general understanding of everything that goes into the project. Those two people can fill in if another team member falls sick, gets moved to another project, or leaves the team.

ClickUp’s built-in task management features can help you implement a redundancy mindset in your projects. With ClickUp Tasks , you can create multiple subtasks within each task and assign them to different team members. When a task is split between multiple team members, it becomes less dependent on a single individual for its completion, which is what redundancy is all about.

You can also add a priority level to each task and maintain a backup team for handling high-priority tasks in case the original assignees cannot complete them.

If you tend to get bogged down in detail while pursuing a goal, a simple mental model called backward chaining might be just what you need. Instead of starting from step one and moving forward, backward chaining suggests that you kick things off with your end goal . 

Start by jotting down all the steps necessary to complete a goal—but in reverse order. What would typically be the last step now tops your to-do list , while the nominally first step comes at the very end of the line.

While a forward-looking process may feel familiar and more intuitive, it can sometimes drown you in all the detail and individual steps that you lose sight of the big picture. In contrast, backward chaining always keeps your eyes on the prize . It also offers a vantage point to reach your goals more creatively and efficiently.

ClickUp can help you implement the backward chaining mental model with its native goal-tracking feature called ClickUp Goals . Use it to define a target you want to achieve, then break it down into tasks necessary for completing it. To work backward from your goal, rearrange the tasks in descending order with simple drag-and-drop actions. 

The Pareto principle claims that, in most cases, 80% of the effects come from just 20% of causes . Therefore, according to this rule, you should focus your resources and energy output on those activities that bring the most value.

If you’re running a business, ClickUp CRM can help you weave the Pareto principle into your workflows by allowing insights into the potential value of your customer interactions in real time. This helps you quickly identify high-value leads or customers who deserve the most attention and effort. You can also easily track the position of those leads and customers in your sales pipeline and see who is in charge of them under the “Assignee” section.

There’s a limit to everything, including the ability of an investment to generate returns. The returns will get more and more modest until they eventually turn zero or even harmful in some cases.

The law of diminishing returns tells us that rather than stressing over activities that bring progressively less value, we should focus our time, energy, and resources on opportunities that can generate new value.

To identify the efforts whose returns are starting to diminish, you should have a mechanism that allows a comparative study of returns over a period of time. Fortunately, you can use the ClickUp Dashboards feature to track and visualize the returns of all your investments with the help of line charts. 📊

For instance, if you want to analyze which of your sales channels are giving diminishing returns month-on-month, simply import the sales data of each channel for the last six months into ClickUp and visualize it using line charts on your Dashboard.

You can add separate charts for data for each sales channel and then easily spot which marketing channel’s ROI has been going down sequentially for months. 

While redundancy asks you to keep an extra supply as a precaution against potential failures or unavailability of vital resources, the margin of safety advocates for incorporating a buffer in your planning . This measure ensures your efforts are resilient and can withstand setbacks, thus reducing the risk of failure or, in the worst cases, a catastrophe. 🧨

There are different ways the margin of safety is implemented in different situations. For instance:

• While building public infrastructure (i.e., bridges, railroads, etc.), the maximum limits are set at a level that’s lower than the total capacity of the structure
• When setting project deadlines, savvy project managers leave some room for rescheduling or reassigning the tasks to another member in case someone falls sick
• When making financial plans, companies include some margin of safety in their sales and cost estimates

Unlocking the potential of this mental model depends on the art of forecasting . You can determine the margin of safety only by anticipating various outcomes through data analysis. ClickUp simplifies this process by offering a range of forecasting templates, including:

• ClickUp Sales Forecast Template
• ClickUp Project Cost Management Template
• ClickUp Demand Planning and KPI Tracking Template

Confirmation bias is the tendency to think and interpret situations in a way that adheres to our existing beliefs and ideas while rejecting everything that goes against them. 

Under the influence of this negative mental model, we may discard all the data and scientific evidence that contradicts our preconceived notions and accept facts selectively to create an illusion of reality. Sometimes, people invent a rationale out of the blue to justify their views.

The solution to avoid this cognitive bias is two-fold:

• First is humility. You need to remind yourself that there are no universal truths constantly, and no matter how educated and informed you are, there’s still a lot you don’t know
• The second is to make data-driven decisions. Establish processes to collect and analyze data without flaws and then rely on that data in your decision-making

While the first part of the solution is more of a skill you need to practice, ClickUp can help you with the second part. ClickUp Dashboards can help you easily understand the patterns and trends hidden in your data with the help of visual elements known as cards. 

While you can automatically track project data on team performance and finished tasks, you can also import data from external sources to visualize and analyze. With dozens of supported card types, you can choose a visualization that presents your data in the best possible way. 

This mental model is somewhat at odds with the Pareto principle. While the latter suggests that you should focus on those 20% of actions that lead to 80% of results, the former advocates for the opposite approach.

The preferential attachment model claims that by allocating more resources to efforts already driving the majority of the results, you further amplify their ability to generate results while not giving other activities a fair chance to do the same. 

So, how do you choose between these two approaches? Well, balance is the key. Before fully embracing the Pareto principle and dedicating your best efforts to a handful of leads or activities, ensure you allocate a fair amount of time, effort, and resources to test the potential of other revenue streams.

Self-doubt is deeply ingrained in human nature. A good example is how managers and sales team leaders look for faults when they don’t close a potential deal or there’s radio silence from a promising lead in the negotiating stage. You might assume there’s something wrong with your sales process or with your product/service that made the lead back out. 🤔

While that may be true sometimes, it’s certainly not the case every single time. Leads might stop responding because they’re busy or testing the waters before making a financial commitment. That’s what Hanlon’s Razor tells us: Never attribute to malice what could be explained by carelessness.

ClickUp can help you determine whether your marketing qualified leads (MQLs) are dropping out due to some shortcomings on your part or because of their indecision or irresponsibility. By collecting conversion data from ClickUp CRM and analyzing it with ClickUp Dashboards, you can determine if there’s a consistent trend of leads dropping out or if these occurrences are just isolated incidents. 

If there’s a trend, you need to figure out the reason(s) behind it and improve your product or marketing strategy. Sometimes, your strategy will be good, and you may have to optimize your processes instead. But if you’re faced with isolated facts here and there, don’t worry too much about them!

Implement Any Mental Model into Your Decision-Making with ClickUp

The mental models we’ve introduced can help you make smart moves and wiser choices. You can even make your own mental models—the key is to make sure that they use accurate data and logical theory to help make sense of something. Because when making crucial decisions, the last thing you want is to rely on guesswork. 

ClickUp’s visualization, reporting, task management, and information organization features (i.e., dedicated project Spaces, Docs, multiple views, etc.) can help you discover elusive patterns or insights you can use to fully implement the best mental models into your everyday life and work. 

Sign up for ClickUp today and unlock the doors to superior decision-making and problem-solving. You’ll thank us later! 💪

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What’s a mental model? Your shortcut to being more productive, more often

Contributing writer

Everyone has their own way of looking at the world.

The way you view your world and everything in it (yourself, your job, your relationships, your goals…literally everything) is unique—you’re experiencing it through a lens typically constructed from a mix of your beliefs, experiences, biases, and opinions.

But that lens? It’s not always the clearest way to look at things.

For example, when you encounter a problem you’ve never faced before, you’re not going to have the experience to solve it—so looking at the problem through your unique lens isn’t going to get you any closer to a solution.

And that’s where mental models come in.

Mental models allow you to view the world through more tried, tested, and unbiased lenses, and help find solutions to problems that might be out of your personal sphere of experience.

Not only can they be incredibly helpful in giving you deeper insights into the world around you, they can also be extremely useful at taking your career to the next level.

But what, exactly, are mental models? How do they work? And how can you use mental models to reexamine your own thoughts, beliefs, and behaviors, as well as improve your professional life in the process?

We talked to Thomas Oppong , founder of AllTopStartups and creator of Thinking in Models , a course on how to apply mental models for career growth, to get his expert insights on all things mental models—including which mental models you should adopt to thrive in your career.

What Are Mental Models?

First things first, before we jump into how mental models can completely change your career game, let’s quickly cover what, exactly, mental models are. Thomas Oppong explains:

“I think the basic definition of mental models would be just tools, ideas, principles, and perceptions that we consistently use to solve better decisions or to understand life. So every principle…that we use in our daily lives, either in business, career, or in life, [can be considered] mental models.”

So that lens we were talking about earlier, the unique one through which you view the world?

Think of that as your own, personal mental model. But there are other mental models (or other lenses through which you can view things) that you can apply to specific situations that will give you a deeper level of understanding and insight than you’d be able to pull from your own personal experience. This in turn, can help you make better decisions and easily solve a problem.

I’ll use myself as an example. I’m a writer, and I’m pretty good with words (if I do say so myself). But numbers? Not so much. So, if I was to try to figure out how much I need to save each month in order to comfortably retire 30+ years from now—strictly by using my own background and experience—I wouldn’t even know where to begin ($50 a month, cross my fingers, and hope for the best?).

But luckily, I don’t have to approach that problem through my own lens of experience; there’s a mental model for that!

Compounding is an existing mental model that, when applied to investment situations (like retirement), can be used to calculate how much interest will accrue over a specific period of time.

So instead of banging my head against a wall, trying to figure out how much to put aside each month, I can apply the compounding mental model and voila! Retirement planning problem solved.

Simply put, mental models are explanations of how things work.

They guide our thinking, giving us access to these “lenses” or formulas we might not otherwise have had access to, which we can use to supercharge our problem-solving abilities and make the decision-making process easier and faster. Oppong explains:

“Mental models have a lot to offer because…there are so many people who have experimented with different ways to make things better, different ways to make better decisions. And then, they’ve shared these principles [and] ideas with the rest of us. So, as people in their daily lives continue to find them and apply them, [mental models] shorten the decision process and make it easier for us to even do better or make better assumptions or make better decisions.”

In a nutshell, mental models can help us think beyond our own personal experience and provide a kind of mental “shortcut,” making it easier, faster, and more efficient to find solutions for problems.

What’s The Connection Between Mental Models, Productivity, And Success?

Alright, so now that you know what mental models are, let’s talk about how they work—and, in particular, how they’re connected to your career, success, and productivity

There are a few different ways mental models can help you level up your productivity, get more done , and take your career to the next level, including:

• Cutting down on problem-solving time. Imagine if you had to start from scratch to figure out every problem you encountered during the day? By applying mental models, you can more quickly and easily understand the problem at hand—and, more importantly, get to the best and more productive solution.
• Opening your mind to new and different ways of thinking. As mentioned, we all have our own unique way of looking at things—but sometimes, that unique way of looking at things can hold us back. By applying mental models, you can remove yourself from the equation and approach things from a more objective place. And that willingness to open your mind and see things through a new lens? It’s a key to growth—both personal and professional.“Once you’re open to learning [and using different mental models], you probably would be able to identify your own biases or your own traps or your own mental biases that are preventing you from growing,” says Oppong.
• Helping you become more adaptable. The most successful people are the ones who can roll with the punches and adapt to things as they come. The more mental models you understand, the more you’re able to look at things from a variety of different perspectives—and the more adaptable and flexible you’ll be when solving problems.

The Mental Models That Can Help You Take Your Career To The Next Level

You know what mental models are. You know how they can make you more productive. Now, let’s take a look at the specific mental models you need to adopt to thrive in your career.

Circle Of Competence

The circle of competence mental model was developed by Warren Buffet—and while it was originally used as a way to guide investment decisions, it’s also extremely relevant to business.

Your circle of competence is the areas in which you excel. You should always stick within that circle. If you try to move outside of that circle (and focus on tasks where you have a limited understanding or experience), you’re not going to be as effective—and your productivity will tank as a result.

Source: Farnam Street

So, for example, let’s say you’re the CEO of a startup, and your circle of competence includes pitching investors, mentoring your team, and coming up with big-picture strategies.

If you want your business to succeed, that’s where you need to spend your time; if your focus is on tasks outside of your circle of competence (so, for example, managing budgets or writing social media copy), your productivity is going to suffer—and so will your startup.

Take the time to identify your circle of competence. Ask yourself:

• What am I good at?
• What do I love doing?
• Where do I excel?

Then, spend your time and energy there—and figure out how to get rid of the tasks outside of your circle of competence (for example, by hiring an assistant).

Incentives (AKA Reward And Punishment)

The incentives mental model says that all living things (including humans) are inherently incentive-driven—when you understand this principle, you can apply it to your work and incentivize yourself to get things done.

For example, is there a task on your to-do list that you dread every day? If you respond to more positive incentives (or rewards), you could tell yourself: “If I get XYZ task done by 12pm, I can treat myself to an iced coffee at lunch.”

If you’re the kind of person who responds better to more negative incentives (AKA punishment), you could tell yourself “If I don’t get XYZ task done by 12pm, no iced coffee with lunch today.”

Either way, the reward or punishment is the incentive you need to tackle your dreaded work task, making it easier to get it done—increasing your productivity in the process.

Regret Minimization Framework

Sometimes, the decision that provides a sense of instant gratification isn’t the best or most productive—and that’s where the regret minimization framework comes in.

“One [mental model] that I’ve found to also be very helpful is… the Regret Minimization Framework ,” says Oppong.

Developed by Amazon CEO Jeff Bezos, the regret minimization framework allows you to think beyond the present moment and assists in making the best decision for your future.

Oppong explains:

“Whenever you’re taking an action, instead of just making a choice that would benefit you in the short term, you focus on the long term. Long term not just in the next five or ten years but…the next 15 or 20 years.”

This mental model gives you a framework for evaluating your decisions and how those decisions are going to impact your success and well-being in the long term.

So, for example,  you get offered a promotion at work, but it would require you to put in longer hours at the office. If you were only thinking about your short-term benefit, you might be tempted to say no (who wants to work late when there’s Netflix to watch?!). But by applying the regret minimization framework, you can assess how the decision is going to impact you in the long-term and come to the realization that, 10 years from now, you’d probably come to regret turning down a promotion for more time with your Netflix queue.

Law Of Diminishing Returns

The law of diminishing returns is defined as “the point at which the level of profits or benefits gained is less than the amount of money or energy invested”—you can use this mental model to maximize your efficiency and make sure you’re getting the most productivity bang for your buck.

The key to successfully using the law of diminishing returns?

Identifying the “point” where the energy outweighs the benefit and making sure to work up to that point, but never past it.

Here’s a great example of the law of diminishing returns: The number of hours you work every day.

Everyone hits a point where the juice is no longer worth the squeeze, where they’re technically “working,” but they’re so mentally exhausted, they’re not actually getting things done.

Identifying the time of day when you hit that point—and working until then, but not a minute after—will help you maximize your productivity every day (without veering into burnout territory ).

Fixed And Growth Mindset

According to this mental model, pioneered by Stanford psychologist and researcher Carol S. Dweck in her book, Mindset , there are two ways to view yourself: With a fixed mindset or a growth mindset.

If you have a fixed mindset, you believe who you are—including your skills, talents, and abilities—are set in stone. You are who you are, and really? There’s no changing.

A growth mindset is just the opposite, it’s the belief that your skills, talents, and abilities are constantly evolving. There’s always the possibility for change and, as the name implies, growth.

When you approach your career with a growth mindset, you’ll always leave the door open for new opportunities to learn, grow, and change—no matter how successful you are.

“If you have a growth mindset, then you’ll be able to [grow]…wherever you find yourself, even if you find yourself at the top of the corporate ladder, you will still be able to grow,” says Oppong.

Adopting a growth mindset will not only make for a more successful and productive career—but it will also make for a more exciting one When you’re open to growing, learning, changing, and evolving, who knows where you’ll end up?

Use Mental Models To Skyrocket Success

Everyone has their own way of looking at the world. But mental models allow you widen that perspective and find new, different, and more efficient ways to think and work—which is a key factor in skyrocketing your productivity and career and claiming the success you deserve!

Next: How To Beat Decision Fatigue With Better Brain Habits

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View the high resolution version of today’s graphic by clicking here .

The level of a person’s raw intelligence, as measured by aptitude tests such as IQ scores, is generally stable for most people during the course of their adulthood.

While it’s true that there are things you can do to fine tune your natural capabilities, such as doing brain exercises, solving puzzles, and getting optimal sleep—the amount of raw brainpower you have is difficult to increase in any meaningful or permanent way.

For those of us who constantly strive to be high-performers in our fields, this seems like bad news. If we can’t increase our processing power, then how can we solve life’s bigger problems as we move up the ladder?

The Key: Mental Models

The good news is that while raw cognitive abilities matter, it’s how you use and harness those abilities that really makes the difference.

The world’s most successful people, from Ray Dalio to Warren Buffett , are not necessarily leagues above the rest of us in raw intelligence—instead, they simply develop and learn to apply better mental models of how the world works, and they use these principles to filter their thoughts, decisions, strategies, and execution.

This infographic comes from best-selling author and entrepreneur Michael Simmons , who has collected over 650 mental models through his work. The infographic, in a similar style to one we previously published on cognitive biases , synthesizes these models down to the most useful and universal mental models that people should learn to master first.

Concepts such as the 80/20 rule (Pareto’s principle), compound interest, and network building are summarized in the visualization, and their major components are broken down further within the circle.

Mental Model Examples

Example #1: Pareto’s Principle (80/20 Rule for Prioritization)

In a recent Medium post by Simmons, he highlights a well-known mental model that is the perfect bread crumb to start with.

The 80/20 rule (Pareto’s principle) is named after Italian economist Vilfredo Pareto, who was likely the first person to note the 80/20 connection in an 1896 paper.

In short, it shows that 20% of inputs (work, time, effort) often leads to 80% of outputs (performance, sales, revenue, etc.), creating an extremely vivid mental framework for making prioritization decisions.

The 80/20 rule represents a power law distribution that has been empirically shown to exist throughout nature, and it also has huge implications on business.

If you focus your effort on these 20% of tasks first, and get the most out of them, you will be able to drive results much more efficiently than wasting time on the 80% “long-tail” shown below.

Example #2: Metcalfe’s Law (Network Building)

Metcalfe’s Law is one of network effects, stating that a network’s value is proportional to the square of the number of nodes in the network.

From a mental model perspective, this is a useful way to understand how certain types of technology-driven businesses derive value.

If you have a smart grid that is only connected to one power source, that’s alright—but one connected to many different energy sources and potential consumers is much more useful for everyone on the grid. Each additional node provides value for the rest of the connections.

This mental model can be applied outside of strict technology or business terms as well.

For example, if you build a personal network of connections, each additional relationship can provide more value to the other people in your network. It’s the same principle that Harvard or other prestigious universities operate on: the more value a student can get from the alumni network, the higher price they can charge for tuition.

It’s hard to compete with a fully formed network at scale, as they create massive economic moats for the owner. Modern social networks and messaging apps like Facebook, Instagram, LinkedIn, TikTok, WhatsApp, and Snapchat all operate with this in mind.

The Power of Mental Models

These are just two examples of how powerful mental models can be effective in making you think clearer and work smarter.

If you want to be a top performer, it’s worth looking into other mental models out there as well. They can help you better frame reality, so that you can harness your intelligence and effort in the most effective way possible—and it’ll allow you to deliver results along the way.

This post was first published in 2018. We have since updated it, adding in new content for 2021.

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Overview of the Problem-Solving Mental Process

• Identify the Problem
• Define the Problem
• Form a Strategy
• Organize Information
• Allocate Resources
• Monitor Progress
• Evaluate the Results

Frequently Asked Questions

Problem-solving is a mental process that involves discovering, analyzing, and solving problems. The ultimate goal of problem-solving is to overcome obstacles and find a solution that best resolves the issue.

The best strategy for solving a problem depends largely on the unique situation. In some cases, people are better off learning everything they can about the issue and then using factual knowledge to come up with a solution. In other instances, creativity and insight are the best options.

It is not necessary to follow problem-solving steps sequentially, It is common to skip steps or even go back through steps multiple times until the desired solution is reached.

In order to correctly solve a problem, it is often important to follow a series of steps. Researchers sometimes refer to this as the problem-solving cycle. While this cycle is portrayed sequentially, people rarely follow a rigid series of steps to find a solution.

The following steps include developing strategies and organizing knowledge.

1. Identifying the Problem

While it may seem like an obvious step, identifying the problem is not always as simple as it sounds. In some cases, people might mistakenly identify the wrong source of a problem, which will make attempts to solve it inefficient or even useless.

Some strategies that you might use to figure out the source of a problem include :

• Asking questions about the problem
• Breaking the problem down into smaller pieces
• Looking at the problem from different perspectives
• Conducting research to figure out what relationships exist between different variables

2. Defining the Problem

After the problem has been identified, it is important to fully define the problem so that it can be solved. You can define a problem by operationally defining each aspect of the problem and setting goals for what aspects of the problem you will address

At this point, you should focus on figuring out which aspects of the problems are facts and which are opinions. State the problem clearly and identify the scope of the solution.

3. Forming a Strategy

After the problem has been identified, it is time to start brainstorming potential solutions. This step usually involves generating as many ideas as possible without judging their quality. Once several possibilities have been generated, they can be evaluated and narrowed down.

The next step is to develop a strategy to solve the problem. The approach used will vary depending upon the situation and the individual's unique preferences. Common problem-solving strategies include heuristics and algorithms.

• Heuristics are mental shortcuts that are often based on solutions that have worked in the past. They can work well if the problem is similar to something you have encountered before and are often the best choice if you need a fast solution.
• Algorithms are step-by-step strategies that are guaranteed to produce a correct result. While this approach is great for accuracy, it can also consume time and resources.

Heuristics are often best used when time is of the essence, while algorithms are a better choice when a decision needs to be as accurate as possible.

4. Organizing Information

Before coming up with a solution, you need to first organize the available information. What do you know about the problem? What do you not know? The more information that is available the better prepared you will be to come up with an accurate solution.

When approaching a problem, it is important to make sure that you have all the data you need. Making a decision without adequate information can lead to biased or inaccurate results.

5. Allocating Resources

Of course, we don't always have unlimited money, time, and other resources to solve a problem. Before you begin to solve a problem, you need to determine how high priority it is.

If it is an important problem, it is probably worth allocating more resources to solving it. If, however, it is a fairly unimportant problem, then you do not want to spend too much of your available resources on coming up with a solution.

At this stage, it is important to consider all of the factors that might affect the problem at hand. This includes looking at the available resources, deadlines that need to be met, and any possible risks involved in each solution. After careful evaluation, a decision can be made about which solution to pursue.

6. Monitoring Progress

After selecting a problem-solving strategy, it is time to put the plan into action and see if it works. This step might involve trying out different solutions to see which one is the most effective.

It is also important to monitor the situation after implementing a solution to ensure that the problem has been solved and that no new problems have arisen as a result of the proposed solution.

Effective problem-solvers tend to monitor their progress as they work towards a solution. If they are not making good progress toward reaching their goal, they will reevaluate their approach or look for new strategies .

7. Evaluating the Results

After a solution has been reached, it is important to evaluate the results to determine if it is the best possible solution to the problem. This evaluation might be immediate, such as checking the results of a math problem to ensure the answer is correct, or it can be delayed, such as evaluating the success of a therapy program after several months of treatment.

Once a problem has been solved, it is important to take some time to reflect on the process that was used and evaluate the results. This will help you to improve your problem-solving skills and become more efficient at solving future problems.

A Word From Verywell​

It is important to remember that there are many different problem-solving processes with different steps, and this is just one example. Problem-solving in real-world situations requires a great deal of resourcefulness, flexibility, resilience, and continuous interaction with the environment.

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You can become a better problem solving by:

• Practicing brainstorming and coming up with multiple potential solutions to problems
• Being open-minded and considering all possible options before making a decision
• Breaking down problems into smaller, more manageable pieces
• Asking for help when needed
• Researching different problem-solving techniques and trying out new ones
• Learning from mistakes and using them as opportunities to grow

It's important to communicate openly and honestly with your partner about what's going on. Try to see things from their perspective as well as your own. Work together to find a resolution that works for both of you. Be willing to compromise and accept that there may not be a perfect solution.

Take breaks if things are getting too heated, and come back to the problem when you feel calm and collected. Don't try to fix every problem on your own—consider asking a therapist or counselor for help and insight.

If you've tried everything and there doesn't seem to be a way to fix the problem, you may have to learn to accept it. This can be difficult, but try to focus on the positive aspects of your life and remember that every situation is temporary. Don't dwell on what's going wrong—instead, think about what's going right. Find support by talking to friends or family. Seek professional help if you're having trouble coping.

Davidson JE, Sternberg RJ, editors.  The Psychology of Problem Solving .  Cambridge University Press; 2003. doi:10.1017/CBO9780511615771

Sarathy V. Real world problem-solving .  Front Hum Neurosci . 2018;12:261. Published 2018 Jun 26. doi:10.3389/fnhum.2018.00261

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Ten mental models for learning.

A mental model is a general idea that can be used to explain many different phenomena. Supply and demand in economics, natural selection in biology, recursion in computer science, or proof by induction in mathematics—these models are everywhere once you know to look for them.

Just as understanding supply and demand helps you reason about economics problems, understanding mental models of learning will make it easier to think about learning problems.

Unfortunately, learning is rarely taught as a class on its own—meaning most of these mental models are known only to specialists. In this essay, I’d like to share the ten that have influenced me the most, along with references to dig deeper in case you’d like to know more.

1. Problem solving is search.

Herbert Simon and Allen Newell launched the study of problem solving with their landmark book, Human Problem Solving . In it, they argued that people solve problems by searching through a problem space.

A problem space is like a maze: you know where you are now, you’d know if you’ve reached the exit, but you don’t know how to get there. Along the way, you’re constrained in your movements by the maze’s walls.

Problem spaces can also be abstract. Solving a Rubik’s cube, for instance, means moving through a large problem space of configurations—the scrambled cube is your start, the cube with each color segregated to a single side is the exit, and the twists and turns define the “walls” of the problem space.

Real-life problems are typically more expansive than mazes or Rubik’s cubes—the start state, end state and exact moves are often not clear-cut. But searching through the space of possibilities is still a good characterization of what people do when solving unfamiliar problems—meaning when they don’t yet have a method or memory that guides them directly to the answer.

One implication of this model is that, without prior knowledge, most problems are really difficult to solve. A Rubik’s cube has over forty-three quintillion configurations —a big space to search in if you aren’t clever about it. Learning is the process of acquiring patterns and methods to cut down on brute-force searching.

2. Memory strengthens by retrieval.

Retrieving knowledge strengthens memory more than seeing something for a second time does. Testing knowledge isn’t just a way of measuring what you know—it actively improves your memory. In fact, testing is one of the best study techniques researchers have discovered.

Why is retrieval so helpful? One way to think of it is that the brain economizes effort by remembering only those things that are likely to prove useful. If you always have an answer at hand, there’s no need to encode it in memory. In contrast, the difficulty associated with retrieval is a strong signal that you need to remember.

Retrieval only works if there is something to retrieve. This is why we need books, teachers and classes. When memory fails, we fall back on problem-solving search which, depending on the size of the problem space, may fail utterly to give us a correct answer. However, once we’ve seen the answer, we’ll learn more by retrieving it than by repeatedly viewing it.

3. Knowledge grows exponentially.

How much you’re able to learn depends on what you already know. Research finds that the amount of knowledge retained from a text depends on prior knowledge of the topic . This effect can even outweigh general intelligence in some situations.

As you learn new things, you integrate them into what you already know. This integration provides more hooks for you to recall that information later. However, when you know little about a topic, you have fewer hooks to put new information on. This makes the information easier to forget. Like a crystal growing from a seed, future learning is much easier once a foundation is established.

This process has limits, of course, or knowledge would accelerate indefinitely. Still, it’s good to keep in mind because the early phases of learning are often the hardest and can give a misleading impression of future difficulty within a field.

4. Creativity is mostly copying.

Few subjects are so misunderstood as creativity. We tend to imbue creative individuals with a near-magical aura, but creativity is much more mundane in practice.

In an impressive review of significant inventions, Matt Ridley argues that innovation results from an evolutionary process . Rather than springing into the world fully-formed, new invention is essentially the random mutation of old ideas. When those ideas prove useful, they expand to fill a new niche.

Evidence for this view comes from the phenomenon of near-simultaneous innovations. Numerous times in history, multiple, unconnected people have developed the same innovation, which suggests that these inventions were somehow “nearby” in the space of possibilities right before their discovery.

Even in fine art, the importance of copying has been neglected. Yes, many revolutions in art were explicit rejections of past trends. But the revolutionaries themselves were, almost without exception, steeped in the tradition they rebelled against. Rebelling against any convention requires awareness of that convention.

5. Skills are specific.

Transfer refers to enhanced abilities in one task after practice or training in a different task. In research on transfer, a typical pattern shows up:

• Practice at a task makes you better at it.
• Practice at a task helps with similar tasks (usually ones that overlap in procedures or knowledge).
• Practice at one task helps little with unrelated tasks, even if they seem to require the same broad abilities like “memory,” “critical thinking” or “intelligence.”

It’s hard to make exact predictions about transfer because they depend on knowing both exactly how the human mind works and the structure of all knowledge. However, in more restricted domains, John Anderson has found that productions—IF-THEN rules that operate on knowledge—form a fairly good match for the amount of transfer observed in intellectual skills .

While skills may be specific, breadth creates generality. For instance, learning a word in a foreign language is only helpful when using or hearing that word. But if you know many words, you can say a lot of different things.

Similarly, knowing one idea may matter little, but mastering many can give enormous power. Every extra year of education improves IQ by 1-5 points , in part because the breadth of knowledge taught in school overlaps with that needed in real life (and on intelligence tests).

If you want to be smarter, there are no shortcuts—you’ll have to learn a lot. But the converse is also true. Learning a lot makes you more intelligent than you might predict.

6. Mental bandwidth is extremely limited.

We can only keep a few things in mind at any one time. George Miller initially pegged the number at seven, plus or minus two items . But more recent work has suggested the number is closer to four things .

This incredibly narrow space is the bottleneck through which all learning, every idea, memory and experience must flow if it is going to become a part of our long-term experience. Subliminal learning doesn’t work. If you aren’t paying attention, you’re not learning.

The primary way we can be more efficient with learning is to ensure the things that flow through the bottleneck are useful. Devoting bandwidth to irrelevant elements may slow us down.

Since the 1980s, cognitive load theory has been used to explain how interventions optimize (or limit) learning based on our limited mental bandwidth. This research finds:

• Problem solving may be counterproductive for beginners. Novices do better when shown worked examples (solutions) instead.
• Materials should be designed to avoid needing to flip between pages or parts of a diagram to understand the material.
• Redundant information impedes learning.
• Complex ideas can be learned more easily when presented first in parts.

7. Success is the best teacher.

We learn more from success than failure . The reason is that problem spaces are typically large, and most solutions are wrong. Knowing what works cuts down the possibilities dramatically, whereas experiencing failure only tells you one specific strategy doesn’t work.

A good rule is to aim for a roughly 85% success rate when learning. You can do this by calibrating the difficulty of your practice (open vs. closed book, with vs. without a tutor, simple vs. complex problems) or by seeking extra training and assistance when falling below this threshold. If you succeed above this threshold, you’re probably not seeking hard enough problems—and are practicing routines instead of learning new skills.

8. We reason through examples.

How people can think logically is an age-old puzzle. Since Kant, we’ve known that logic can’t be acquired from experience. Somehow, we must already know the rules of logic, or an illogical mind could never have invented them. But if that is so, why do we so often fail at the kinds of problems logicians invent?

In 1983, Philip Johnson-Laird proposed a solution : we reason by constructing a mental model of the situation.

To test a syllogism like “All men are mortal. Socrates is a man. Therefore, Socrates is mortal,” we imagine a collection of men, all of whom are mortal, and imagine that Socrates is one of them. We deduce the syllogism is true through this examination.

Johnson-Laird suggested that this mental-model based reasoning also explains our logical deficits. We struggle most with logical statements that require us to examine multiple models. The more models that need constructing and reviewing, the more likely we will make mistakes.

Related research by Daniel Kahneman and Amos Tversky shows that this example-based reasoning can lead us to mistake our fluency in recalling examples for the actual probability of an event or pattern. For instance, we might think more words fit the pattern K _ _ _ than _ _ K _ because it is easier to think of examples in the first category (e.g., KITE, KALE, KILL) than the second (e.g., TAKE, BIKE, NUKE).

Reasoning through examples has several implications:

• Learning is often faster through examples than abstract descriptions.
• To learn a general pattern, we need many examples.
• We must watch out when making broad inferences based on a few examples. (Are you sure you’ve considered all the possible cases?)

9. Knowledge becomes invisible with experience.

Skills become increasingly automated through practice. This reduces our conscious awareness of the skill, making it require less of our precious working memory capacity to perform. Think of driving a car: at first, using the blinkers and the brakes was painfully deliberate. After years of driving, you barely think about it.

The increased automation of skills has drawbacks, however. One is that it becomes much harder to teach a skill to someone else. When knowledge becomes tacit, it becomes harder to make explicit how you make a decision. Experts frequently underestimate the importance of “basic” skills because, having long been automated, they don’t seem to factor much into their daily decision-making.

Another drawback is that automated skills are less open to conscious control. This can lead to plateaus in progress when you keep doing something the way you’ve always done it, even when that is no longer appropriate. Seeking more difficult challenges becomes vital because these bump you out of automaticity and force you to try better solutions.

10. Relearning is relatively fast.

After years spent in school, how many of us could still pass the final exams we needed to graduate? Faced with classroom questions, many adults sheepishly admit they recall little.

Forgetting is the unavoidable fate of any skill we don’t use regularly. Hermann Ebbinghaus found that knowledge tapers off at an exponential rate —most quickly at the beginning, slowing down as time elapses.

Yet there is a silver lining. Relearning is usually much faster than initial learning. Some of this can be understood as a threshold problem. Imagine memory strength ranges between 0 and 100. Under some threshold, say 35, a memory is inaccessible. Thus if a memory dropped from 36 to 34 in strength, you would forget what you had known. But even a little boost from relearning would repair the memory enough to recall it. In contrast a new memory (starting at zero) would require much more work.

Connectionist models , inspired by human neural networks, offer another argument for the potency of relearning. In these models, a computational neural network may take hundreds of iterations to reach the optimal point. And if you “jiggle” the connections in this network, it forgets the right answer and responds no better than if by chance. However, as with the threshold explanation above, the network relearns the optimal response much faster the second time. 1

Relearning is a nuisance, especially since struggling with previously easy problems can be discouraging. Yet it’s no reason not to learn deeply and broadly—even forgotten knowledge can be revived much faster than starting from scratch.

What are the learning challenges you’re facing? Can you apply one of these mental models to see it in a new light? What would the implications be for tackling a skill or subject you find difficult? Share your thoughts in the comments!

• These networks are trained via gradient descent. Gradient descent works by essentially rolling downhill. Correct knowledge is like the gently-sloping bottom of a steep canyon—the correct direction is down the canyon, but the sides are quite high. Unlike a three-dimensional space, as would describe a physical canyon, most networks are in an extremely high-dimensional space. That means any imprecision in the direction results in running up the side of the canyon. The result is that networks typically slosh around a lot before getting to the bottom of the long canyon. However, when you add any noise to the system, the “downhill” direction usually goes straight back to the optimal point.

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10 Best Problem-Solving Therapy Worksheets & Activities

Cognitive science tells us that we regularly face not only well-defined problems but, importantly, many that are ill defined (Eysenck & Keane, 2015).

Sometimes, we find ourselves unable to overcome our daily problems or the inevitable (though hopefully infrequent) life traumas we face.

Problem-Solving Therapy aims to reduce the incidence and impact of mental health disorders and improve wellbeing by helping clients face life’s difficulties (Dobson, 2011).

This article introduces Problem-Solving Therapy and offers techniques, activities, and worksheets that mental health professionals can use with clients.

Before you continue, we thought you might like to download our three Positive Psychology Exercises for free . These science-based exercises explore fundamental aspects of positive psychology, including strengths, values, and self-compassion, and will give you the tools to enhance the wellbeing of your clients, students, or employees.

This Article Contains:

What is problem-solving therapy, 14 steps for problem-solving therapy, 3 best interventions and techniques, 7 activities and worksheets for your session, fascinating books on the topic, resources from positivepsychology.com, a take-home message.

Problem-Solving Therapy assumes that mental disorders arise in response to ineffective or maladaptive coping. By adopting a more realistic and optimistic view of coping, individuals can understand the role of emotions and develop actions to reduce distress and maintain mental wellbeing (Nezu & Nezu, 2009).

“Problem-solving therapy (PST) is a psychosocial intervention, generally considered to be under a cognitive-behavioral umbrella” (Nezu, Nezu, & D’Zurilla, 2013, p. ix). It aims to encourage the client to cope better with day-to-day problems and traumatic events and reduce their impact on mental and physical wellbeing.

Clinical research, counseling, and health psychology have shown PST to be highly effective in clients of all ages, ranging from children to the elderly, across multiple clinical settings, including schizophrenia, stress, and anxiety disorders (Dobson, 2011).

Can it help with depression?

PST appears particularly helpful in treating clients with depression. A recent analysis of 30 studies found that PST was an effective treatment with a similar degree of success as other successful therapies targeting depression (Cuijpers, Wit, Kleiboer, Karyotaki, & Ebert, 2020).

Other studies confirm the value of PST and its effectiveness at treating depression in multiple age groups and its capacity to combine with other therapies, including drug treatments (Dobson, 2011).

The major concepts

Effective coping varies depending on the situation, and treatment typically focuses on improving the environment and reducing emotional distress (Dobson, 2011).

PST is based on two overlapping models:

Social problem-solving model

This model focuses on solving the problem “as it occurs in the natural social environment,” combined with a general coping strategy and a method of self-control (Dobson, 2011, p. 198).

The model includes three central concepts:

• Social problem-solving
• The problem
• The solution

The model is a “self-directed cognitive-behavioral process by which an individual, couple, or group attempts to identify or discover effective solutions for specific problems encountered in everyday living” (Dobson, 2011, p. 199).

Relational problem-solving model

The theory of PST is underpinned by a relational problem-solving model, whereby stress is viewed in terms of the relationships between three factors:

• Stressful life events
• Emotional distress and wellbeing
• Problem-solving coping

Therefore, when a significant adverse life event occurs, it may require “sweeping readjustments in a person’s life” (Dobson, 2011, p. 202).

• Enhance positive problem orientation
• Decrease negative orientation
• Foster ability to apply rational problem-solving skills
• Reduce the tendency to avoid problem-solving
• Minimize the tendency to be careless and impulsive

D’Zurilla’s and Nezu’s model includes (modified from Dobson, 2011):

• Initial structuring Establish a positive therapeutic relationship that encourages optimism and explains the PST approach.
• Assessment Formally and informally assess areas of stress in the client’s life and their problem-solving strengths and weaknesses.
• Obstacles to effective problem-solving Explore typically human challenges to problem-solving, such as multitasking and the negative impact of stress. Introduce tools that can help, such as making lists, visualization, and breaking complex problems down.
• Problem orientation – fostering self-efficacy Introduce the importance of a positive problem orientation, adopting tools, such as visualization, to promote self-efficacy.
• Problem orientation – recognizing problems Help clients recognize issues as they occur and use problem checklists to ‘normalize’ the experience.
• Problem orientation – seeing problems as challenges Encourage clients to break free of harmful and restricted ways of thinking while learning how to argue from another point of view.
• Problem orientation – use and control emotions Help clients understand the role of emotions in problem-solving, including using feelings to inform the process and managing disruptive emotions (such as cognitive reframing and relaxation exercises).
• Problem orientation – stop and think Teach clients how to reduce impulsive and avoidance tendencies (visualizing a stop sign or traffic light).
• Problem definition and formulation Encourage an understanding of the nature of problems and set realistic goals and objectives.
• Generation of alternatives Work with clients to help them recognize the wide range of potential solutions to each problem (for example, brainstorming).
• Decision-making Encourage better decision-making through an improved understanding of the consequences of decisions and the value and likelihood of different outcomes.
• Solution implementation and verification Foster the client’s ability to carry out a solution plan, monitor its outcome, evaluate its effectiveness, and use self-reinforcement to increase the chance of success.
• Guided practice Encourage the application of problem-solving skills across multiple domains and future stressful problems.
• Rapid problem-solving Teach clients how to apply problem-solving questions and guidelines quickly in any given situation.

Success in PST depends on the effectiveness of its implementation; using the right approach is crucial (Dobson, 2011).

Problem-solving therapy – Baycrest

The following interventions and techniques are helpful when implementing more effective problem-solving approaches in client’s lives.

First, it is essential to consider if PST is the best approach for the client, based on the problems they present.

Is PPT appropriate?

It is vital to consider whether PST is appropriate for the client’s situation. Therapists new to the approach may require additional guidance (Nezu et al., 2013).

Therapists should consider the following questions before beginning PST with a client (modified from Nezu et al., 2013):

• Has PST proven effective in the past for the problem? For example, research has shown success with depression, generalized anxiety, back pain, Alzheimer’s disease, cancer, and supporting caregivers (Nezu et al., 2013).
• Is PST acceptable to the client?
• Is the individual experiencing a significant mental or physical health problem?

All affirmative answers suggest that PST would be a helpful technique to apply in this instance.

Five problem-solving steps

The following five steps are valuable when working with clients to help them cope with and manage their environment (modified from Dobson, 2011).

Ask the client to consider the following points (forming the acronym ADAPT) when confronted by a problem:

• Attitude Aim to adopt a positive, optimistic attitude to the problem and problem-solving process.
• Define Obtain all required facts and details of potential obstacles to define the problem.
• Alternatives Identify various alternative solutions and actions to overcome the obstacle and achieve the problem-solving goal.
• Predict Predict each alternative’s positive and negative outcomes and choose the one most likely to achieve the goal and maximize the benefits.
• Try out Once selected, try out the solution and monitor its effectiveness while engaging in self-reinforcement.

If the client is not satisfied with their solution, they can return to step ‘A’ and find a more appropriate solution.

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Positive self-statements

When dealing with clients facing negative self-beliefs, it can be helpful for them to use positive self-statements.

Use the following (or add new) self-statements to replace harmful, negative thinking (modified from Dobson, 2011):

• I can solve this problem; I’ve tackled similar ones before.
• I can cope with this.
• I just need to take a breath and relax.
• Once I start, it will be easier.
• It’s okay to look out for myself.
• I can get help if needed.
• Other people feel the same way I do.
• I’ll take one piece of the problem at a time.
• I can keep my fears in check.
• I don’t need to please everyone.

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PST practitioners have many different techniques available to support clients as they learn to tackle day-to-day or one-off trauma.

5 Worksheets and workbooks

Problem-solving self-monitoring form.

Ask the client to complete the following:

• Describe the problem you are facing.
• What is your goal?
• What have you tried so far to solve the problem?
• What was the outcome?

Reactions to Stress

It can be helpful for the client to recognize their own experiences of stress. Do they react angrily, withdraw, or give up (Dobson, 2011)?

The Reactions to Stress worksheet can be given to the client as homework to capture stressful events and their reactions. By recording how they felt, behaved, and thought, they can recognize repeating patterns.

What Are Your Unique Triggers?

Helping clients capture triggers for their stressful reactions can encourage emotional regulation.

When clients can identify triggers that may lead to a negative response, they can stop the experience or slow down their emotional reaction (Dobson, 2011).

The What Are Your Unique Triggers ? worksheet helps the client identify their triggers (e.g., conflict, relationships, physical environment, etc.).

Problem-Solving worksheet

Imagining an existing or potential problem and working through how to resolve it can be a powerful exercise for the client.

Use the Problem-Solving worksheet to state a problem and goal and consider the obstacles in the way. Then explore options for achieving the goal, along with their pros and cons, to assess the best action plan.

Getting the Facts

Clients can become better equipped to tackle problems and choose the right course of action by recognizing facts versus assumptions and gathering all the necessary information (Dobson, 2011).

Use the Getting the Facts worksheet to answer the following questions clearly and unambiguously:

• Who is involved?
• What did or did not happen, and how did it bother you?
• Where did it happen?
• When did it happen?
• Why did it happen?
• How did you respond?

2 Helpful Group Activities

While therapists can use the worksheets above in group situations, the following two interventions work particularly well with more than one person.

Generating Alternative Solutions and Better Decision-Making

A group setting can provide an ideal opportunity to share a problem and identify potential solutions arising from multiple perspectives.

Use the Generating Alternative Solutions and Better Decision-Making worksheet and ask the client to explain the situation or problem to the group and the obstacles in the way.

Once the approaches are captured and reviewed, the individual can share their decision-making process with the group if they want further feedback.

Visualization

Visualization can be performed with individuals or in a group setting to help clients solve problems in multiple ways, including (Dobson, 2011):

• Clarifying the problem by looking at it from multiple perspectives
• Rehearsing a solution in the mind to improve and get more practice
• Visualizing a ‘safe place’ for relaxation, slowing down, and stress management

Guided imagery is particularly valuable for encouraging the group to take a ‘mental vacation’ and let go of stress.

Ask the group to begin with slow, deep breathing that fills the entire diaphragm. Then ask them to visualize a favorite scene (real or imagined) that makes them feel relaxed, perhaps beside a gently flowing river, a summer meadow, or at the beach.

The more the senses are engaged, the more real the experience. Ask the group to think about what they can hear, see, touch, smell, and even taste.

Encourage them to experience the situation as fully as possible, immersing themselves and enjoying their place of safety.

Such feelings of relaxation may be able to help clients fall asleep, relieve stress, and become more ready to solve problems.

We have included three of our favorite books on the subject of Problem-Solving Therapy below.

1. Problem-Solving Therapy: A Treatment Manual – Arthur Nezu, Christine Maguth Nezu, and Thomas D’Zurilla

This is an incredibly valuable book for anyone wishing to understand the principles and practice behind PST.

Written by the co-developers of PST, the manual provides powerful toolkits to overcome cognitive overload, emotional dysregulation, and the barriers to practical problem-solving.

Find the book on Amazon .

2. Emotion-Centered Problem-Solving Therapy: Treatment Guidelines – Arthur Nezu and Christine Maguth Nezu

Another, more recent, book from the creators of PST, this text includes important advances in neuroscience underpinning the role of emotion in behavioral treatment.

Along with clinical examples, the book also includes crucial toolkits that form part of a stepped model for the application of PST.

3. Handbook of Cognitive-Behavioral Therapies – Keith Dobson and David Dozois

This is the fourth edition of a hugely popular guide to Cognitive-Behavioral Therapies and includes a valuable and insightful section on Problem-Solving Therapy.

This is an important book for students and more experienced therapists wishing to form a high-level and in-depth understanding of the tools and techniques available to Cognitive-Behavioral Therapists.

For even more tools to help strengthen your clients’ problem-solving skills, check out the following free worksheets from our blog.

• Case Formulation Worksheet This worksheet presents a four-step framework to help therapists and their clients come to a shared understanding of the client’s presenting problem.
• Understanding Your Default Problem-Solving Approach This worksheet poses a series of questions helping clients reflect on their typical cognitive, emotional, and behavioral responses to problems.
• Social Problem Solving: Step by Step This worksheet presents a streamlined template to help clients define a problem, generate possible courses of action, and evaluate the effectiveness of an implemented solution.

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While we are born problem-solvers, facing an incredibly diverse set of challenges daily, we sometimes need support.

Problem-Solving Therapy aims to reduce stress and associated mental health disorders and improve wellbeing by improving our ability to cope. PST is valuable in diverse clinical settings, ranging from depression to schizophrenia, with research suggesting it as a highly effective treatment for teaching coping strategies and reducing emotional distress.

Many PST techniques are available to help improve clients’ positive outlook on obstacles while reducing avoidance of problem situations and the tendency to be careless and impulsive.

The PST model typically assesses the client’s strengths, weaknesses, and coping strategies when facing problems before encouraging a healthy experience of and relationship with problem-solving.

Why not use this article to explore the theory behind PST and try out some of our powerful tools and interventions with your clients to help them with their decision-making, coping, and problem-solving?

We hope you enjoyed reading this article. Don’t forget to download our three Positive Psychology Exercises for free .

• Cuijpers, P., Wit, L., Kleiboer, A., Karyotaki, E., & Ebert, D. (2020). Problem-solving therapy for adult depression: An updated meta-analysis. European P sychiatry ,  48 (1), 27–37.
• Dobson, K. S. (2011). Handbook of cognitive-behavioral therapies (3rd ed.). Guilford Press.
• Dobson, K. S., & Dozois, D. J. A. (2021). Handbook of cognitive-behavioral therapies  (4th ed.). Guilford Press.
• Eysenck, M. W., & Keane, M. T. (2015). Cognitive psychology: A student’s handbook . Psychology Press.
• Nezu, A. M., & Nezu, C. M. (2009). Problem-solving therapy DVD . Retrieved September 13, 2021, from https://www.apa.org/pubs/videos/4310852
• Nezu, A. M., & Nezu, C. M. (2018). Emotion-centered problem-solving therapy: Treatment guidelines. Springer.
• Nezu, A. M., Nezu, C. M., & D’Zurilla, T. J. (2013). Problem-solving therapy: A treatment manual . Springer.

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Mental Models and Lifelong Learning

• Reference work entry
• pp 2205–2211
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• Philip Barker 2 &
• Paul van Schaik 2  

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Cognitive structures ; Human development ; Learning ; Learning community ; Learning resources ; Problem solving

The development of mental models is an important aspect of living and learning. These complex cognitive structures capture records of human experience and store them in the mind. They can subsequently be used for problem solving and goal-seeking activity. An individual’s collection of mental models starts to develop at an early age and is continually modified during that person’s lifetime. The set of mental models that are developed in early life may not be fully applicable to situations that arise in later life. During a person’s life span, continual learning is therefore necessary in order to fine-tune these models – thereby ensuring their currency.

Theoretical Background

The theoretical background issues underlying the work described in this contribution falls within two distinct, but closely related and overlapping domains: mental models and lifelong...

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Barker, P., van Schaik, P. (2012). Mental Models and Lifelong Learning. In: Seel, N.M. (eds) Encyclopedia of the Sciences of Learning. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1428-6_604

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