Tag: Thinking

The Three Essential Properties of the Engineering Mind-Set

Engineers use a unique mode of thinking based on seeing everything as a system. They see structures that aren’t apparent to the layperson, they know how to design under constraints, and they understand trade-offs. Adopting an engineering mindset can help you in any field.

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In his book Applied Minds: How Engineers Think, Guru Madhavan explores the mental tools of engineers that allow engineering feats. His framework is built around a flexible intellectual tool kit called modular systems thinking.

The core of the engineering mind-set is what I call modular systems thinking. It’s not a singular talent, but a melange of techniques and principles. Systems-level thinking is more than just being systematic; rather, it’s about the understanding that in the ebb and flow of life, nothing is stationary and everything is linked. The relationships among the modules of a system give rise to a whole that cannot be understood by analyzing its constituent parts.

Thinking in Systems

Thinking in systems means that you can deconstruct (breaking down a larger system into its modules) and reconstruct (putting it back together).

The focus is on identifying the strong and weak links—how the modules work, don’t work, or could potentially work—and applying this knowledge to engineer useful outcomes.

There is no engineering method, so modular systems thinking varies with contexts.

Engineering Dubai’s Burj Khalifa is different from coding the Microsoft Office Suite. Whether used to conduct wind tunnel tests on World Cup soccer balls or to create a missile capable of hitting another missile midflight, engineering works in various ways. Even within a specific industry, techniques can differ. Engineering an artifact like a turbofan engine is different from assembling a megasystem like an aircraft, and by extension, a system of systems, such as the air traffic network.

The Three Essential Properties of the Engineering Mind-Set

1. The ability to see a structure where there’s nothing apparent.

From haikus to high-rise buildings, our world relies on structures. Just as a talented composer “hears” a sound before it’s put down on a score, a good engineer is able to visualize—and produce—structures through a combination of rules, models, and instincts. The engineering mind gravitates to the piece of the iceberg underneath the water rather than its surface. It’s not only about what one sees; it’s also about the unseen.

A structured systems-level thinking process would consider how the elements of the system are linked in logic, in time, in sequence, and in function—and under what conditions they work and don’t work. A historian might apply this sort of structural logic decades after something has occurred, but an engineer needs to do this preemptively, whether with the finest details or top-level abstractions. This is one of the main reasons why engineers build models: so that they can have structured conversations based in reality. Critically, envisioning a structure involves having the wisdom to know when a structure is valuable, and when it isn’t.

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Consider, for example, the following catechism by George Heilmeier—a former director of the U.S. Defense Advanced Research Projects Agency (DARPA), who also engineered the liquid crystal displays (LCDs) that are part of modern-day visual technologies. His approach to innovation is to employ a checklist-like template suitable for a project with well-defined goals and customers.

  • What are you trying to do? Articulate your objectives using absolutely no jargon.
  • How is it done today, and what are the limits of current practice?
  • What’s new in your approach and why do you think it will be successful?
  • Who cares? If you’re successful, what difference will it make?
  • What are the risks and the payoffs?
  • How much will it cost? How long will it take?
  • What are the midterm and final “exams” to check for success?

This type of structure “helps ask the right questions in a logical way.”

2. Adeptness at designing under constraints

The real world is full of constraints that make or break potential.

Given the innately practical nature of engineering, the pressures on it are far greater compared to other professions. Constraints—whether natural or human-made—don’t permit engineers to wait until all phenomena are fully understood and explained. Engineers are expected to produce the best possible results under the given conditions. Even if there are no constraints, good engineers know how to apply constraints to help achieve their goals. Time constraints on engineers fuel creativity and resourcefulness. Financial constraints and the blatant physical constraints hinging on the laws of nature are also common, coupled with an unpredictable constraint—namely, human behavior.

“Imagine if each new version of the Macintosh Operating System, or of Windows, was in fact a completely new operating system that began from scratch. It would bring personal computing to a halt,” Olivier de Week and his fellow researchers at the Massachusetts Institute of Technology point out. Engineers often augment their software products, incrementally addressing customer preferences and business necessities— which are nothing but constraints. “Changes that look easy at first frequently necessitate other changes, which in turn cause more change. . . . You have to find a way to keep the old thing going while creating something new.” The pressures are endless.

3. Understanding Trade-offs

The ability to hold alternative ideas in your head and make considered judgments.

Engineers make design priorities and allocate resources by ferreting out the weak goals among stronger ones. For an airplane design, a typical trade-off could be to balance the demands of cost, weight, wingspan, and lavatory dimensions within the constraints of the given performance specifications. This type of selection pressure even trickles down to the question of whether passengers like the airplane they’re flying in. If constraints are like tightrope walking, then trade-offs are inescapable tugs-of-war among what’s available, what’s possible, what’s desirable, and what the limits are.

Applied Minds: How Engineers Think will help you borrow strategies from engineering and apply them to your most pressing problems.

David Foster Wallace on The Moral Clarity of the Immature

David Foster Wallace, who brought us gems such as This is Water and insights into ambition and perfectionism, was the guest editor of the 2007 edition of Best American Essays.

His introduction explores why pre-formed positions are so appealing and how the role of having people decide for us has no clear alternative.

Commenting on how essays and other pre-packaged models of thinking help us deal with information and stimuli overload, Wallace writes:

Part of our emergency is that it’s so tempting to do this sort of thing now, to retreat to narrow arrogance, pre-formed positions, rigid filters, the “moral clarity” of the immature.

The alternative is dealing with massive, high-entropy amounts of info and ambiguity and conflict and flux; it’s continually discovering new areas of personal ignorance and delusion. In sum, to really try to be informed and literate today is to feel stupid nearly all the time and to need help.

That’s about as clearly as I can put it … That last one’s of especial value, I think. As exquisite verbal art, yes, but also as a model for what free, informed adulthood might look like in the context of Total Noise: not just the intelligence to discern one’s own error or stupidity, but the humility to address it, absorb it, and move on and out therefrom, bravely, toward the next revealed error.

This is probably the sincerest, most biased account of “best” your decider can give: these pieces are models — not templates, but models — of ways I wish I could think and live in what seems to me this world.

And commenting on the role of Google and curators alike as deciders for us Wallace writes:

I suspect that part of why ‘bias’ is so loaded and dicey a word just now — and why it’s so much-invoked and potent in cultural disputes — is that we are starting to become more aware of just how much subcontracting and outsourcing and submitting to other Deciders we’re all now forced to do, which is threatening (the inchoate awareness is) to our sense of ourselves as intelligent free agents. And yet there is no clear alternative to this outsourcing and submission. It may possibly be that acuity and taste in choosing which Deciders one submits to is now the real measure of informed adulthood. Since I was raised with more traditional, Enlightenment-era criteria, this possibility strikes me as consumerist and scary … to which the counterargument would be, again, that the alternatives are literally abysmal.

Still Curious? Check out the best book on the art of writing.

Elon Musk: A Framework for Thinking

In this brief video, Elon Musk, who previously brought us how to build knowledge and 12 book recommendations, talks about a framework for thinking.

I do think there is a good framework for thinking. It is physics – you know the sort of first principles reasoning … What I mean by that is boil things down to their fundamental truths and reason up from there as opposed to reasoning by analogy.

Though most of our life we get through it by reasoning through analogy, which essentially means copying what other people do with slight variations. And you have to do that, otherwise mentally you wouldn’t be able to get through the day. But when you want to do something new you have to apply the physics approach. Physics has really figured out how to discover new things that are counter-intuitive, like quantum mechanics … so I think that’s an important thing to do. And then also really pay attention to negative feedback and solicit it, particularly from friends. This may sound like simple advice but hardly anyone does that and it’s incredibly helpful.

Ray Dalio: Open-Mindedness And The Power of Not Knowing

Ray Dalio, founder of the investment firm Bridgewater Associates (and guest on The Knowledge Project), offers a prime example of what a learning organization looks like in the best book I’ve ever read on learning, Learn or Die: Using Science to Build a Leading-Edge Learning Organization.

He comes to us again with this bit of unconventional wisdom.

First, the context …

To make money in the markets, you have to think independently and be humble. You have to be an independent thinker because you can’t make money agreeing with the consensus view, which is already embedded in the price. Yet whenever you’re betting against the consensus there’s a significant probability you’re going to be wrong, so you have to be humble.

Early in my career I learned this lesson the hard way — through some very painful bad bets. The biggest of these mistakes occurred in 1981–’82, when I became convinced that the U.S. economy was about to fall into a depression. My research had led me to believe that, with the Federal Reserve’s tight money policy and lots of debt outstanding, there would be a global wave of debt defaults, and if the Fed tried to handle it by printing money, inflation would accelerate. I was so certain that a depression was coming that I proclaimed it in newspaper columns, on TV, even in testimony to Congress. When Mexico defaulted on its debt in August 1982, I was sure I was right. Boy, was I wrong. What I’d considered improbable was exactly what happened: Fed chairman Paul Volcker’s move to lower interest rates and make money and credit available helped jump-start a bull market in stocks and the U.S. economy’s greatest ever noninflationary growth period

What’s important isn’t that he was wrong, it’s what the experience taught him and how he implemented those lessons at Bridgewater.

This episode taught me the importance of always fearing being wrong, no matter how confident I am that I’m right. As a result, I began seeking out the smartest people I could find who disagreed with me so that I could understand their reasoning. Only after I fully grasped their points of view could I decide to reject or accept them. By doing this again and again over the years, not only have I increased my chances of being right, but I have also learned a huge amount.

There’s an art to this process of seeking out thoughtful disagreement. People who are successful at it realize that there is always some probability they might be wrong and that it’s worth the effort to consider what others are saying — not simply the others’ conclusions, but the reasoning behind them — to be assured that they aren’t making a mistake themselves. They approach disagreement with curiosity, not antagonism, and are what I call “open-minded and assertive at the same time.” This means that they possess the ability to calmly take in what other people are thinking rather than block it out, and to clearly lay out the reasons why they haven’t reached the same conclusion. They are able to listen carefully and objectively to the reasoning behind differing opinions.

When most people hear me describe this approach, they typically say, “No problem, I’m open-minded!” But what they really mean is that they’re open to being wrong. True open-mindedness is an entirely different mind-set. It is a process of being intensely worried about being wrong and asking questions instead of defending a position. It demands that you get over your ego-driven desire to have whatever answer you happen to have in your head be right. Instead, you need to actively question all of your opinions and seek out the reasoning behind alternative points of view.

Still curious? Check out my lengthy interview with Ed Hess.

Developing a Mental Framework for Effective Thinking

Becoming a better thinker means understanding the way you think and developing a way of approaching problems that allows you to see things from multiple lenses. These lenses, or mental models, are built on the foundations of physics, biology, math, psychology, as well as history and economics. The more lenses you have, the more you can see. The more you can see the more you can understand. The more you understand reality the more you will know what to do.

These tools also allow you to better understand when to follow and when to reject conventional wisdom. Ideally, you want to go through them checklist-style — just run right through them — asking what applies.

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John Snow was a doctor based in London during the acute cholera outbreak of the summer of 1854. He represents a powerful example of the impact a lollapalooza effect can have. A lollapalooza is when several ideas combine to produce an unusually powerful result. Snow developed systems to ease the pain of surgery with ether and chloroform.

In the book The Ghost Map, author Steven Johnson explains:

Snow was a truly consilient thinker, in the sense of the term as it was originally formulated by the Cambridge philosopher William Whewell in the 1840s (and recently popularized by Harvard biologist E. O. Wilson). “The Consilience of Inductions,” Whewell wrote, “takes place when an Induction, obtained from one class of facts, coincides with an Induction obtained from another different class. This Consilience is a test of the truth of the Theory in which it occurs.” Snow’s work was constantly building bridges between different disciplines, some which barely existed as functional sciences in his day, using data on one scale of investigation to make predictions about behavior on other scales. In studying ether and chloroform, he had moved from the molecular properties of the gas itself, to its circulation of those properties throughout the body’s overall system, to the psychological effects produced by these biological changes. He even ventured beyond the natural world into the design of technology that would best reflect our understanding of the anesthetics. Snow was not interested in individual, isolated phenomena; he was interested in chains and networks in the movement from scale to scale. His mind tripped happily from molecules to cells to brains to machines, and it was precisely that consilient study that helped Snow uncover so much about this nascent field in such a shockingly short amount of time.

Suspending belief in the common theory at the time on how diseases were spread, Snow ended up rejecting miasma theory, which said the disease was spread via “bad air.” He did this through science. He conducted interviews with residents and traced the majority of cases back to a single water source. His willingness to challenge conventional thinking, along with approaching the problem through multiple lenses, resulted in finding the deadly source and changes in municipal water systems from that day forward.

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Elements of the mental framework for Thinking

Charlie Munger is a strong advocate of a mental framework. In Damn Right: Behind the Scenes with Berkshire Hathaway Billionaire Charlie Munger, he offered five-simple notions that help solve complex problems.

In The Focused Few: Taking a Multidisciplinary Approach to Focus Investing, Richard Rockwood explores the concepts from many disciplines. Adding them together can yield a useful mental checklist.

Element 1: Invert

In The Focused Few, Rockwood writes:

Inverting, or thinking problems through backward, is a great way to understand information. Charlie Munger provides the best illustration I have ever seen of this type of thinking.

During a speech he offered an example of how a situation could be examined using the inversion process. He discussed the development process of Coca-Cola from the perspective of a person creating a soda company from scratch and examining the key issues that would need to be resolved to make it a reality.

He listed some of the issues the entrepreneur would need to address:

  • What kind of properties should the new drink strive for, and what are those it should avoid? One property the drink should not have is an aftertaste. Consumers should be able to consume large quantities over a period of time and not be deterred by an unpleasant aftertaste.
  • The soda should be developed in such a manner that it can be shipped in large quantities at minimal costs. This makes it easier to develop an efficient, large-scale distribution system.
  • Keeping the soda formulation a secret will help alleviate competition and create a certain aura of mystique around the product.
  • The company also can deter competition by expanding the business as quickly as possible. For example, the distribution system could be expanded until it reaches a critical mass that competitors would find hard to duplicate without massive capital expenditures.

(Read more about inversion)

Element 2: First-and second-level thinking

In The Focused Few, Rockwood writes:

Let’s examine the decision-making process by breaking it down into two components. The first component, first-level thinking, generally occurs when you make decisions quickly based on a simple theme or common sense. For example, a person may decide to invest in a company simply because its products are trendy. Making decisions based on first-level reasoning has significant problems, however. Common sense “is wonderful at making sense of the world, but not necessarily at understanding it.”

The danger is that you may think you understand a particular situation when in fact you have only developed a likely story.

Second-level thinkers, in contrast, approach decisions differently. What kinds of questions should a second-level thinker ask?

In his book, The Most Important Thing: Uncommon Sense for the Thoughtful Investor, Howard Marks provides a useful list of questions to ask.

  1. What is the range of likely future outcomes?
  2. Which outcome do I think will occur?
  3. What is the probability that I’m right?
  4. What is the prevailing consensus?
  5. How does my expectation differ from the consensus?
  6. How does the current price for the asset comport with the consensus view of the future— and with mine?
  7. Is the consensus psychology that is incorporated into the price too bullish or bearish?
  8. What will happen to the asset’s price if the consensus turns out to be right, and what if I’m right?

(Read more about second-level thinking)

Element 3: Use decision trees

decision trees

In The Focused Few, Rockwood writes:

Decision trees are excellent tools for helping you decide on a course of action. They enable you to lay out several possible scenarios, investigate their possible outcomes, and create a balanced picture of the risks and rewards associated with each.

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Let’s examine the decision-tree process in greater detail. First, identify the decision and the outcome alternatives available at each point. After you lay out each course of action, determine which option has the greatest value to you. Start by assigning a cash value to each possible outcome (i.e., what the expected value would be if that particular outcome were to occur). Next, look at each break, or point of uncertainty, in the tree and estimate the probability of each outcome occurring. If you use percentages, the combined total must equal 100% at each break point. If you use fractions, these must add up to 1.

After these two steps have been taken (i.e., the values of the outcomes have been entered and the probabilities have been estimated), it is time to begin calculating the expected values of the various branches in the decision tree.

Element 4: The multidisciplinary approach

When trying to resolve a difficult situation or determining exactly why a product has been, and may continue to be, successful, it helps to think about the problem by creating a checklist that incorporates the vital components of other disciplines.

(read more about multidisciplinary thinking)

The Focused Few is a tune up for your mind.

 

Remember Not to Trust Your Memory

Memories are the stories that we tell ourselves about the past. Sometimes they adjust and leave things out.

In an interesting passage in Think: Why You Should Question Everything, Guy P. Harrison talks about the fallibility of memory.

Did you know that you can’t trust even your most precious memories?

They may come to you in great detail and feel 100 percent accurate, but it doesn’t matter. They easily could be partial or total lies that your brain is telling you. Really, the personal past that your brain is supposed to be keeping safe for you is not what you think it is. Your memories are pieces and batches of information that your brain cobbles together and serves up to you, not to present the past as accurately as possible, but to provide you with information that you will likely find to be useful in the present. Functional value, not accuracy, is the priority. Your brain is like some power-crazed CIA desk jockey who feeds you memories on a need-to-know basis only. Daniel Schacter, a Harvard memory researcher, says that when the brain remembers, it does so in a way that is similar to how an archaeologist reconstructs a past scene relying on an artifact here, an artifact there. The end result might be informative and useful, but don’t expect it to be perfect. This is important because those who don’t know anything about how memory works already have one foot in fantasyland. Most people believe that our memory operates in a way that is similar to a video camera. They think that the sights, sounds, and feelings of our experiences are recorded on something like a hard drive in their heads. Totally wrong. When you remember your past, you don’t get to watch an accurately recorded replay.

To describe to people how memory really works, Harrison puts it this way:

Imagine a very tiny old man sitting by a very tiny campfire somewhere inside your head. He’s wearing a worn and raggedy hat and has a long, scruffy, gray beard. He looks a lot like one of those old California gold prospectors from the 1800s. He can be grumpy and uncooperative at times, but he’s the keeper of your memories and you are stuck with him. When you want or need to remember something from your past, you have to go through the old codger. Let’s say you want to recall that time when you scored the winning goal in a middle-school soccer match. You have to tap the old coot on the shoulder and ask him to tell you about it. He usually responds with something. But he doesn’t read from a faithfully recorded transcript, doesn’t review a comprehensive photo archive to create an accurate timeline, and doesn’t double-check his facts before speaking. He definitely doesn’t play a video recording of the game for you. Typically, he just launches into a tale about your glorious goal that won the big game. He throws up some images for you, so it’s kind of like a lecture or slideshow. Nice and useful, perhaps, but definitely not reliable