Mental Models: The Best Way to Make Intelligent Decisions

How do you think the most rational people in the world operate their minds? How do they make better decisions?

They do it by “chunking” away a massive, but finite amount of fundamental, unchanging knowledge that can be used in evaluating the infinite number of unique scenarios that show up in the real world.

That is how consistently rational and effective thinking is done, and if we want to learn how to think properly ourselves, we need to figure out how it's done. Fortunately, there is a way, and it works.

Before we dig deeper, let's start by watching this short video on a concept called mental models. Then continue on below.

It's not that complicated, right?

The idea for building a “latticework” of mental models comes from Charlie Munger, Vice Chairman of Berkshire Hathaway and one of the finest thinkers in the world.

Munger's system is akin to “cross-training for the mind”—not siloing ourselves in the small, limited area we may have studied in school, but chunking away a broadly useful set of knowledge about the world, which will serve us in all parts of life.

In a famous speech in the 1990's, Munger explained his novel approach to gaining practical wisdom:

Well, the first rule is that 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 a usable form.

You've got to have models in your head. And you've got to array your experience both vicarious and direct on this latticework of models. You may have noticed students who just try to remember and pound back what is remembered. Well, they fail in school and in life. You've got to hang experience on a latticework of models in your head.

What are the models? Well, the first rule is that you've got to have multiple models because if you just have one or two that you're using, the nature of human psychology is such that you'll torture reality so that it fits your models, or at least you'll think it does…

It's like the old saying, “To the man with only a hammer, every problem looks like a nail.” And of course, that's the way the chiropractor goes about practicing medicine. But that's a perfectly disastrous way to think and a perfectly disastrous way to operate in the world. So you've got to have multiple models.

And the models have to come from multiple disciplines because all the wisdom of the world is not to be found in one little academic department. That's why poetry professors, by and large, are so unwise in a worldly sense. They don't have enough models in their heads. So you've got to have models across a fair array of disciplines.

You may say, “My God, this is already getting way too tough.” But, fortunately, it isn't that tough because 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.(1)

Taking Munger's concept as our starting point, we can figure out how to use our brains more effectively by building our own latticework of mental models.

Building the Latticework

The central principle of the mental model approach is that you must have a large number of them, and they must be fundamentally lasting ideas.

As with physical tools, the lack of a mental tool at the crucial moment can lead to a bad result, and the use of a wrong mental tool is even worse.

If this seems self-evident, it's actually a very unnatural way to think. Without the right training, most minds take the wrong approach. They prefer to solve problems by asking: Which ideas do I already love and know deeply, and how can I apply them to the situation at hand? Psychologists call this the “Availability Heuristic” and its power is well-documented.

You know the old adage, to the man with only a hammer, everything starts looking a bit like a nail. Such narrow-minded thinking feels entirely natural to us, but it leads to far too many misjudgments. You probably do it every single day without knowing.

It's not you don't have some good ideas in your head. You probably do! No competent adult is a total klutz. It's just that we tend to be very limited in our good ideas, and we over-use them. This makes our good ideas just as dangerous as bad ones!

The great investor and teacher Benjamin Graham explained it best:

You can get in way more trouble with a good idea than a bad idea, because you forget that the good idea has limits.

Smart people like Charlie Munger realize that the antidote to this sort of “mental overreaching” is to add more models to your mental palette; to expand your repertoire of ideas, making them vivid and available in the problem-solving process.

You'll know you're on to something when ideas start to compete with one another — you'll find situations where Model 1 tells you X and Model 2 tells you Y. Believe it or not, this the sign that you're on the right track: Letting the models compete and fight for superiority and greater fundamental truth is what good thinking is all about! It's hard work, but that's the only way to get the right answers.

It's a little like learning to walk or ride a bike; at first, you can't believe how much you're supposed to do all at once but eventually, you wonder how you ever didn't know how to do it.

As Charlie Munger likes to say, going back to any other method of thinking would feel like cutting off your hands. Our experience confirms the truth of Munger's dictum.

More About Mental Models

What kinds of knowledge are we talking about adding to our repertoire?

It's the Big, Basic Ideas of all the truly fundamental academic disciplines. The stuff you should have learned in the “101” course of each major subject but probably didn't. These are the true general principles that underlie most of what's going on in the world.

Things like: The main laws of physics. The main ideas driving chemistry. The big, useful tools of mathematics. The guiding principles of biology. The hugely useful concepts from human psychology. The central principles of systems thinking. The working concepts behind business and markets.

These are the winning ideas. For all of the “bestselling” crap that is touted as the new thing each year, there is almost certainly a bigger, more fundamental, and more broadly applicable underlying idea that we already knew about! The “new idea” is thus an application of old ideas, packaged into a new format.

Yet we tend to spend the majority of time keeping up with the “new” at the expense of learning the “old”! This is truly nuts.

The mental models approach inverts the process to the way it should be: Learning the Big Stuff deeply and then using that powerful database every single day.

The over-arching goal is to build a powerful “tree” of the mind with strong roots, trunk, and branches, on which to hang the thousands of “leaves” ones assimilates, directly and vicariously, throughout a lifetime: The scenarios, decisions, problems, and solutions that arise in human and biological life.

Now, let's start by exploring the actual models we've found useful in more depth by clicking the links below.

And remember: Building your latticework is a lifelong project. Stick with it, and you'll find that your ability to understand reality, make consistently good decisions, and help those you love will be always be improving.

The Farnam Street Latticework of Mental Models

Mental Models — How to Solve Problems

General Thinking Concepts (10)

1. Inversion

Otherwise known as thinking through in reverse or thinking “backwards,” inversion is a problem solving technique. Often by considering what we want to avoid rather than what we want to get, we come up with better solutions. Inversion works not just in mathematics but in nearly every area of life: As the saying goes, “Just tell me where I’m going to die so I can never go there.”

2. Falsification

Closely related to inversion, and popularized by the philosopher Karl Popper, 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 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 of the conditions under which they would be shown false are never stated.

3. Circle of Competence

An idea introduced by Warren Buffett and Charles Munger in relation to investing, each individual tends to have an area or areas in which they really, truly know their stuff: Their area of special competence. Areas not inside of that circle are problematic because not only are we ignorant, but we may be ignorant of our own ignorance. Thus, when making decisions it becomes important to define and attend to our special circle, so as to act accordingly.

4. The Principle of Parsimony (Occam’s Razor)

Named after the friar William of Ockham, Occam’s Razor is a heuristic by which we select among competing explanations. Ockham derived that we should prefer the simplest explanation with the least moving parts: They are easier to falsify (see: Falsification), easier to understand, and generally more likely, on average, to be correct. It is not an iron law but a tendency and a mindframe: If all else is equal, it’s more likely that the simple solution suffices. Of course, we also keep in mind Einstein’s famous idea (even if apocryphal) that “an idea should be as simple as possible, but not simpler.”

5. Hanlon's Razor

Harder 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, it helps us avoid extreme paranoia and ideology, often very hard to escape from, by not generally assuming that bad results are the fault of a bad actor, although they can be. More likely, a mistake has been made.

6. Second-order thinking

In all human systems and most complex systems, the second layer of effects often dwarf the first, yet many times go unconsidered. In other words, we must consider that effects have effects. Second-order thinking is best illustrated by the idea of standing on your tip-toes at a parade: Once one person does it, everyone will do it in order to see, thus negating the first tip-toer. However now, the whole parade suffers on its toes rather than its feet.

7. Map is Not the Territory

The map of reality is not reality itself. If any map were to represent its actual territory with perfect fidelity, it would be the size of the territory itself. Thus, no need for a map! This tells us that there will always be an imperfect relationship between the models we use to represent and understand reality, and the reality itself: It is a necessity in order to simplify. It is all we can do to accept this reality and act accordingly.

8. Thought Experiment

A technique popularized by Einstein, the thought experiment is a way to logically carry out a “test” in one’s own head that would be very difficult or impossible to perform in real life. With the thought experiment as a tool, we can solve problems with intuition and logic that could not be demonstrated physically, as with Einstein imagining himself traveling on a beam of light in order to solve the problem of Relativity.

9. 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.

10. Probabilistic Thinking (See also: Numeracy/Bayesian Updating)

The unknowable human world is dominated by probabilistic outcomes, as distinguished from deterministic ones. While we cannot predict the future with great certainty, we are wise to ascribe odds to more and less probable events. We do this every day unconsciously as we cross the street and ascribe low, yet not negligible odds of being hit by a

Numeracy (18)

  1. Permutations & combinations
  2. Algebraic equivalence
  3. Randomness
  4. Stochastic processes (Poisson, Markov/random walk)
  5. Asymmetry
  6. Compounding
  7. Inversion
  8. Multiply by Zero
  9. Churn
  10. Law of Large Numbers
  11. Bell Curve/Normal distribution
  12. Variance
  13. Fat-tailed processes (Extremistan)
  14. Bayesian updating
  15. Power-law distribution (Exponentials)
  16. Regression to the Mean
  17. Order of magnitude
  18. Game Theory

Systems (23)

  1. Scale
  2. Law of Diminishing Returns
  3. Pareto Principle
  4. Feedback loops (and Homeostasis)
  5. Chaos dynamics (Sensitivity to initial conditions)
  6. Preferential Attachment (Cumulative Advantage)
  7. Emergence
  8. Irreducibility (Complexity, Minimums, Time, Length)
  9. Tragedy of the Commons
  10. Gresham’s Law
  11. Algorithm
  12. Fragility – Robustness – Antifragility
  13. Backup systems/Redundency
  14. Margin of safety
  15. Criticality
  16. Network Effects
  17. Black Swan
  18. “Via negativa” – Omission/removal/avoidance of harm.
  19. Lindy Effect
  20. Renormalization Group
  21. Spring loading
  22. Recursion/self-similarity
  23. Complex Adaptive Systems

Physical World (11)

  1. Laws of Thermodynamics
  2. Reciprocity
  3. Velocity
  4. Relativity
  5. Criticality
  6. Equilibrium
  7. Activation Energy
  8. Catalysts
  9. Leverage
  10. Inertia
  11. Alloying

Biological world (18)

  1. Incentives
  2. Cooperation (Incl. symbiosis)
  3. Tendency to minimize energy output (mental & physical)
  4. Repeat what works & has been rewarded
  5. Auto-catalysis
  6. Adaption
  7. Evolution by natural selection
  8. Competition over scarce resources
  9. Red Queen Effect (Co-evolutionary arms race)
  10. Replication
  11. Hierarchical/organizing instincts
  12. Self-preservation instincts
  13. Simple physiological reward-seeking
  14. Exaption
  15. Extinction
  16. Ecosystem
  17. Niches
  18. Dunbar’s Number

Human Nature & Judgment (26)

  1. Trust
  2. Bias from Incentives
  3. Pavlovian mere association
  4. Envy & Jealousy Tendency
  5. Tendency to distort due to liking/loving or disliking/hating
  6. Denial Tendency
  7. Availability Heuristic: Recall what is salient, important, frequent, and recent.
  8. Representativeness Heuristic
    a. Failure to account for base rates
    b. Stereotyping Tendency
    c. Failure to see false conjunctions
  9. Social proof (Safety in numbers)
  10. Narrative Instinct
  11. Curiosity Instinct
  12. Language Instinct
  13. First-conclusion Bias
  14. Tendency to Overgeneralize from Small Samples
  15. Relative Satisfaction/Misreaction Tendencies
  16. Commitment & Consistency Bias
  17. Hindsight Bias
  18. Sensitivity to Fairness
  19. Tendency to overestimate consistency of behavior (Fundamental Attribution Error)
  20. Influence from Authority
  21. Anchoring & Sunk Cost Tendencies
  22. Influence from Stress (Incl. Breaking point)
  23. Survivorship bias
  24. Tendency to want to do something (Fight/Flight, Intervention, Demonstration of value, etc.)
  25. Tendency to be Over-Confident 
  26. Tendency to see what we believe

Microeconomics and Strategy (14)

  1. Opportunity Costs
  2. Creative Destruction
  3. Comparative Advantage
  4. Specialization (Pin factory)
  5. Seizing the middle
  6. Trademarks, patents, and copyright
  7. Double-entry book-keeping
  8. Utility (Marginal, Diminishing, Increasing)
  9. Bottlenecks
  10. Prisoner’s Dilemma
  11. Bribery
  12. Arbitrage
  13. Supply and Demand
  14. Scarcity

Military & War (5)

  1. Seeing the Front
  2. Asymmetric Warfare
  3. Two-front War
  4. Counterinsurgency
  5. Mutually Assured Destruction