“The best way to understand something is to try to change it.” -Kurt Lewin (MIT academic)

I read this book my junior year and it was one of the positive impacts on my college career, because I instituted two simple rules. The first: brush teeth by 10:30pm. The second, eat breakfast when you wake up, whenever that is. Those seem rudimentary, but created enough of a routine to rein in a wild sleep schedule, which had been the bottleneck to my emotional baseline. I suddenly had energy throughout the day, wasn’t managing crazy highs and lows emotionally, and could start to enjoy the many perks of college life.

Why we favor complexity:

A search for the word complexity in books published since 1800 shows that the term was initially rare, rose gradually for 150 years, and then exploded just after the Second World War.

Many of the most critical scientific and social challenges of today—the aging of cells, or hunger in emerging markets—result from multiple variables that interact in numerous and often unpredictable ways.

People often attempt to address complex problems with complex solutions. Often, complex rules and regulations arise out of a distrust of human nature. If people cannot be trusted to do the right thing, detailed regulations are necessary to prevent malfeasance.

Some examples of (bad) complex solutions:

The Glass-Steagall Act, a law passed during the Great Depression, which guided U.S. banking regulation for seven decades, totaled 37 pages. Its successor, Dodd-Frank, is expected to weigh in at over 30,000 pages when all supporting legislation is complete. A study of personal income tax compliance in forty-five countries found that the complexity of the tax code was the single best predictor of whether citizens would dodge or pay their taxes.

When the first mp3 devices came out, they had up to 14 buttons, and twice as many functions. The most depressing part was not the product flaws themselves, but the customers’ willingness to accept complicated interfaces as inevitable. Users believed that MP3 players had to be complicated because they integrated so many moving parts—hardware, software, various file formats, music sources, and a dizzying array of accessories. Then came the iPod.

Why we are bad at making decisions:

We often assume that the best way to make a decision is by considering all the factors that might influence our choice and weighing their relative importance. Psychologists have found, however, that people tend to overweigh peripheral variables at the expense of critical ones when they try to take all factors into account.

For example, some entrepreneurs were taught simple rules for accounting (ex: keep personal money and business money in separate drawers), while others were exposed to accounting as a complicated body of knowledge. The latter group was no better off than entrepreneurs who were not taught any accounting at all. In a separate study, groups who received superficial details before being asked about policy recommendation were easily swayed by those details (we are bad at separating the crucial facts from other details - too many possible correlations).

A well-documented decision error occurs when people embark on a course of action, receive negative feedback, and then up the ante rather than stop. Escalating commitment to a failed course of action is a well-documented error, with over 150 studies of cases as diverse as NBA teams overplaying draft-pick busts, rogue traders doubling down on their money-losing investments, construction projects becoming money pits, and failing military campaigns where success is always described as just around the corner (the Vietnam War is often used as the poster child of escalating commitment to a failed course of action).

Why simple rules are better:

Meeting complexity with complexity can create more confusion than it resolves. Counterintuitive as it may sound, simple rules can outperform more analytically complicated and information-intensive approaches even when there is ample time and information to make a decision.

Simple rules work because they:

1. Confer the flexibility to pursue new opportunities while maintaining some consistency.
2. Favor efficient decision-making: when information is limited and time is short, simple rules make it fast and easy for people, organizations, and governments to make sound choices.
3. Allow the members of a community to synchronize their activities with one another on the fly.

They work well when:

1. Applied to a well-defined activity or decision, such as prioritizing injured soldiers for medical care. Rules that cover multiple activities or choices end up as vague platitudes, such as “Do your best” and “Focus on customers.”
2. When flexibility matters more than consistency (ex: deciding what to eat, disciplining your toddler)
3. Links between cause and effect are poorly understood but important variables are highly correlated
4. A Gap exists between knowing what to do and actually doing it
5. Trying to channel willpower, especially for activities that require short-term sacrifices for long-term gains (like exercising, saving money, dieting)

Making rules together:

The first instinct of many leaders in formulating simple rules is to go to their office, close the door, write down their ideas, and then emerge, like Moses coming down from the mountain, with their rules etched in stone. When leaders rely on their gut instincts, they overemphasize recent events, build in their personal biases, and ignore data that doesn’t fit with their preconceived notions.

The key to moving past the political impasse was shifting the debate from “Which programs should we run?” to “What simple rules should we use to decide which programs to run?”

Use a discussion to generate lots of possible rules (use Post-it notes), and start grouping similar ones. Afterwards, test the rules against historical data to see if the initial rules would have selected promising requests and screened out unattractive ones.

Move the needles:

Figure out what will move the needles. Choose a bottleneck. Craft the rules.

The field of strategy is based on a precise point of view of what a company’s ultimate objective should be—to create economic value over time and capture it as profits. Economic value is defined as the difference between what a customer is willing to pay for a product and the cost of all the inputs required to produce it.

Personal value could be a gap between what energizes you and what stresses you out.

Bottlenecks:

The best bottlenecks to focus on share three characteristics:

1. Have direct and significant impact on value creation.
2. Represent recurrent decisions (rather than one-off choices), so the rules can be tested, refined, and used many times.
3. Lend themselves to simple rules (recurrent activities, vs. one-off decisions)

Some more key questions to consider when selecting a bottleneck include: Do you frequently make this decision or participate in this activity? Does the number of options exceed your available time, money, energy, or attention? Does this activity or decision require willpower? Does this activity or decision require some flexibility? Can you measure results to test and refine your rules?

How to learn from other people’s rules:

Asking your role models: it’s important to recognize that their simple rules will most likely be implicit, so asking for a list of rules may not be the best approach. Instead, explain how you manage your identified bottleneck, and ask them what they do differently. It’s also productive to tease out extremes, by asking if there are things that they always do or never do when managing the target activity. Another way to explore your role model’s tacit rules is to ask them to walk you through a few recent decisions—what they did and why.

In general, it is better to get more comprehensive data for a shorter time period than relying on your imperfect recall of events for a longer period. If you rely too much on your memory alone, you are likely to overweigh vivid examples, ignore cases that don’t jibe with your assumptions, or simply forget details.

A few sample domains and associated rules:

Food Rules:

User logged food on an app for a week, and a review of the data showed them doing well most of the day, eating reasonable amounts of healthy foods through dinnertime. But post-dinner snacks were a problem, contributing as many calories as an extra lunch or breakfast every day on average. Rules for late-night snacking, for example, consisted of “Eat snacks from a small bowl, not the bag” (from Brian Wansink’s book), “Don’t stockpile snacks in the cupboard” (his wife), and “No dessert during the week” (his experience).

Renowned nutritionist summarized all his research in three simple rules: “Eat food. Not too much. Mostly plants.”

Football coach’s three rules for eating: (1) eat breakfast, (2) stay hydrated, and (3) eat as much as you want of anything that can be picked, plucked, or killed.

Sleep Rules:

“Get up at the same time every morning,” which turns out to be more crucial than a regular bedtime for establishing a restful sleep pattern. The second is “Avoid going to bed until you feel sleepy,” even if this means hitting the hay later than you would ideally like. The third rule is “Do not stay in bed if you are not sleeping,” and the final rule, which follows from the others, is “Reduce the time spent in bed.”

Mental Health Rules:

Susan decided to research drug-free ways to manage depression. She began tracking how she felt when she woke up every morning on a scale of 1 to 10, where anything below a 5 was a depressed state.

If her mood had dropped more than one point from the previous day (a large change for her), she would identify troubling events, record her negative thoughts, and challenge each of them systematically. Second, she noticed that the worst drops almost always occurred on a Monday. So, every Monday she went through a CBT exercise, even if she felt okay when she woke up.

Investing rules:

The secret weapon of Loeb’s investing strategy was a simple but powerful stopping rule: “If an investment loses 10 percent of its initial value, sell it.” This rule ensures that the investor does not stick with a loser over the long term. While it may be tempting to wait for a pet stock to regain its value, Loeb’s 10 percent rule recognizes that it is often best to cut your losses and move your money elsewhere. “It is a great mistake to think that what comes down must come back up,” he wrote. “The most important single thing I learned is that accepting losses promptly is the first key to success.”

Rothschild’s rule: “Buy when there is blood on the streets, even if that blood is your own.”

A private equity firm based in Moscow, for example, developed simple rules to screen the cascade of investment opportunities that appeared during Russia’s transition to capitalism in the 1990s. A potential investment should, according to the company’s rules, have revenues of $100 million to $500 million and compete in an industry in which the firm had previously invested. Another guideline identified target companies as those offering products the typical Russian family might purchase if they had an extra $100 to spend each month. A final rule was to work only with executives who knew criminals but weren’t criminals themselves, which acknowledged the ubiquity of illegal activity in Russia while providing clear directions to avoid involvement with the Russian mafia.

Jesuit Rules:

1. Carry out whatever task you were assigned
2. Favor education
3. No obligation to recite their daily prayers in unison

The Jesuits’ simple rules attracted spiritual entrepreneurs who relished the opportunity to seize the initiative and exercise creativity in pursuit of missionary opportunities.

Starling Swarm rules (using computer animation):

1. Avoid collisions
2. Head in the same direction as your nearest neighbors
3. Stay close to your nearest neighbors.

Behavioral biologists, who tested Reynolds’s rules in the wild, found that they could explain collective behavior in a wide range of settings, including how mosquitofish shoal, starlings flock, and pedestrians self-organize into orderly lines on busy streets.

Railway Rules (using slime):

1. Begin by searching randomly in many directions for food
2. When you find food, thicken the tube
3. When you don’t find food, shrink the tube.

The scientists used these rules to build a computer simulation to determine the optimal rail network. By experimenting with variables, such as the amount of food per city or the size of tubes, the scientists could try out various designs to find the optimal network—all without laying a single kilometer of track.

I, Robot Rules - Isaac Asimov (not in book):

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

Artistic Constraints:

Simple rules allow creativity to flourish, less from thinking outside the box and more from deciding how to draw the box in the first place.

Truly original artists work by imposing constraints on themselves, in terms of the subjects they paint, materials they use, and artists they draw upon for inspiration. Monet, for example, purposefully limited his subjects, repeatedly painting pictures, by the dozens, of subjects like grain stacks and water lilies. This self-imposed constraint allowed him to focus on exploring how light changes, and his exploration helped spark a transition in the art world from representation to impressionism.

Musical constraints: “Most artists have nothing guiding them in their creativity. We could’ve spent six months making our last album. We could have recorded 600 tracks. Instead, we went and made the whole album, 18 songs, in 10 days.” By restricting their creative process, how-to rules freed the White Stripes to follow a short, clear path to their favorite patch of creativity.

Google used open-plan offices that were sized like cramped grad-student cubicles. Saved money, but also heightened communication and creative exchanges and helped keep even Google’s millionaire employees in hungry, underdog-startup mode.

Notes that were of personal interest:

Warren Weaver:

Over his three decades at the Rockefeller Foundation, Weaver acted as a banker, talent scout, and kingmaker to support the nascent field of molecular biology, a term he himself coined. Weaver had an uncanny knack for picking future all-stars. Eighteen scientists won Nobel Prizes for research related to molecular biology in the middle of the century, and Weaver had funded all but three of them.

While at the Rockefeller Foundation, Weaver also handpicked and financed a team that spent two decades developing high-yield varieties of wheat that were impervious to disease. Their work helped Mexico feed itself within a generation. When India and Pakistan faced widespread famine in the early 1960s, they adopted the practices pioneered by the Rockefeller team, and doubled their wheat production in five years, saving hundreds of millions of people from starvation.

In his 1948 article, Weaver described science as progressing through successive eras, defined by the three types of problems—simple, uncertain, and complex—that they solved. Simple problems address a few variables that can be reduced to a deterministic formula. Isaac Newton’s laws of motion (force = mass x acceleration, for example) were powerful tools to solve simple problems, such as how a satellite orbits the Earth or what happens when two billiard balls collide. Simple problems occupied scientists for most of the seventeenth to nineteenth centuries, and their solutions yielded life-changing inventions ranging from the telephone to the diesel engine. By the late nineteenth century, scientists shifted their attention to problems of uncertainty, such as the motion of gas particles in a jar, which consisted of large numbers of objects. While scientists could not track the movement of every molecule, they could use probability theory and statistical analysis to predict how large numbers of particles behave in aggregate, paving the way for advances in thermodynamics, genetics, and information theory.

Moneyball:

Unlike baseball traditionalists, Alderson saw scoring runs as a process, not an outcome, and imagined baseball as a factory with a flow of players moving along the bases. This view led Alderson and later his protégé and replacement, Billy Beane, to the insight that most teams overvalue batting average (hits only) and miss the relevance of on-base percentage (walks plus hits) to keeping the runners moving. Like many insightful rules, this boundary rule of picking players with a high on-base percentage has subtle second- and third-order effects. Hitters with a high on-base percentage are highly disciplined (i.e., patient, with a good eye for strikes). This means they get more walks, and their reputation for discipline encourages pitchers to throw strikes, which are easier to hit. They tire out pitchers by making them throw more pitches overall, and disciplined hitting does not erode much with age.