Deepen your understanding of any subject with these 6 strategies

Always be learning. For professionals today, keeping pace with the changing dynamics of business is an imperative. And the idea that a diploma represents the end of learning is an old fashioned one. Yet knowing that’s true isn’t the same as knowing how to learn effectively, or to manage the growth of your knowledge and skillsets into new specialties and directions.

If continual learning seems daunting, it doesn’t have to be. It’s not necessary—or even desirable—to start from scratch every time you sit down to explore a new subject. There’s one very powerful toolbox on your side: mental models.

The investor Charlie Munger is Warren Buffet’s longtime partner. In a talk at USC Business School in 1994, he laid out the rationale for using mental models to better understand the world. Here’s what he said:

What is elementary, worldly 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.

He goes on to recommend that your own mental models should come from different areas and disciplines, giving you the intellectual flexibility it takes to foster expertise in a particular subject. Mental models serve a similar function as that of the pilot’s preflight checklist. There are many dozens of things that have to be confirmed to ensure a safe flight. Sure, you can just try and remember the list mentally but consistent use of preflight checklists improves safety dramatically. 

Similarly, when considering a situation, there are many ways of looking at that event. There is a scientific view, an economic view, a social view, a sustainability perspective, and so on. The more complex and consequential the topic, the more worthwhile it is to have a cognitive toolbox of mental models to apply. This becomes your own personal “latticework of theory,” to use Charlie Munger’s term.

You might be surprised by just how many of these mental models you already know about, or even use frequently. As you look over the following list, take note of which models “click” with you—these are the ones that deserve your attention and are likely to be useful to you in the future.

Here are 6 mental models that you can use to deepen your understanding of practically any subject:

  1. Occam’s razor. Among competing and equally plausible explanations for a phenomenon, simplicity should be given preference; that is, the explanation requiring the least number of assumptions. When you hear the sound of galloping hooves, first assume horses, not zebras.
  2. The map-territory relation. A representation of reality is not necessarily reality itself. Complex systems require abstract representation in order to simplify them sufficiently to be understood. We use maps, pictures, sketches, and measurements to represent something, but those representations are always potentially fallible. There is an imperfect relationship between reality and the models we use to represent and understand reality. This mental model suggests two questions: Is what I am looking at the map or the territory? And, is the map an accurate representation of the territory?
  3. Bell curves or normal distribution. You’ve probably heard of bell curves and standard deviations. For many things in life, there is a normal distribution of outcomes that can be represented as a bell curve. Find the average, then expect an equal distribution on either side of that average. Height and IQ are two normally distributed attributes. The average IQ might be 100, but 2% will have scores above 130 and 2% will have scores below 70. This mental model triggers the question: Is what I am looking at the average or the exception? 
  4. Feedback loops. Many systems have one or more feedback mechanisms that can impact strategic decisionmaking. Some systems are very simple: A causes B. In complex systems, there are many steps like A causes B, B causes C, and C causes D, ultimately leading to the outcome H. In these cases the feedback mechanisms is so that B is confirmed back to A and C is confirmed back to B, ensuring sustained quality along the way.For example, you move into an office which, unknown to you, has a remotely controlled thermostat. It feels chilly so you bring in a portable electric heater. No matter how warm you set the heater, the room stays cool because the thermostat is a hidden feedback mechanism. The warmer you set the heater, the cooler the ventilation becomes in order to maintain the thermostatic setting. In order to accurately change complex systems, you have to know what all the feedback mechanisms are. 
  5. Zero-sum or non-zero-sum. Some systems are zero-sum and others are non-zero-sum, and it is vital to know the difference. Zero-sum systems have winners and losers. Sports games, spelling bees, and chess are all examples where there is a winner and a loser. Non-zero-sum systems are far more desirable because everyone can emerge better off than they were before—everyone can be a winner. Voluntary markets are an example of a non-zero-sum systems where everyone participates and finishes better off than if they had not participated. Zero-sum systems rest on the question: How do I win? Non-zero-sum systems rest on the question: How can we win? 
  6. Correlation is not causation. This mental model is one of the most fundamental laws in statistics. When one thing happens and then a second thing happens, you can’t rely on the fact that there was a causal relationship between the two. Many things are correlated that are not causally related. For example, data will show a correlation between the age of Miss America and the number of people who die by hot steam; clearly, there is no cause-and-effect relationship between these two things. Our pattern-seeking brains fall prey to natural confirmation bias all the time, making unrelated correlations one of the most common decisionmaking mistakes. This mental model suggests the question: Am I confident that I know the real causal relationships?

Remember, these are only 6 of many possible mental models. They are listed here as a useful set of perspectives that can help you understand complex situations or get up to speed on a new topic. Using them and discovering your own can quickly deepen your understanding of the world around you.