The books claims that in a world filled with an abundance of information and not enough time to deliberate, coming up with simple rules helps future decision making by providing a good balance of consistency and flexibility. In other words,
simple rules allow people to act without having to stop and rethink every decision. In group settings, shared rules help orient and synchronize people in new situations. They also let people efficiently rely on the wisdom of and avoid mistakes of their peers.
Authors start with a few stories and examples of the complexity of the modern world.
Complexity arises whenever a system—technical, social, or natural—has multiple interdependent parts.
Consider how central bankers responded to increased complexity in the global banking system. In 1988 bankers from around the world met in Basel, Switzerland, to agree on international banking regulations, and published a 30-page agreement (known as Basel I). Sixteen years later, the Basel II accord was an order of magnitude larger, at 347 pages, and Basel III was twice as long as its predecessor. When it comes to the sheer volume of regulations generated, the U.S. Congress makes the central bankers look like amateurs. 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.
The exponential growth in legislation reminds me of libertarian critique of government regulation — for every new regulation, special interest groups arise demanding exceptions. This quickly results in taxes, tax exemptions, tax exemption exceptions ad infinitum, a spiraling resource waste on bureaucracy at the cost of actual value.
The policies governing U.S. income taxes totaled 3.8 million words as of 2010. […] Such an exhaustive tome should leave nothing to chance. And yet, when forty-five tax professionals were given identical data to calculate one fictional family’s tax bill, they came up with forty-five different estimates of the couple’s tax liability, ranging from $36,322 to $94,438. The tax code is so confusing, even IRS experts give the wrong advice one time out of three.
Regulation that no single person can understand eventually ends becoming a weapon. It’s inevitable that people make unlawful steps sooner or later, and with a noose hanging around everyone’s neck, it’s a matter of just picking who to prosecute.
People often attempt to address complex problems with complex solutions. For example, governments tend to manage complexity by trying to anticipate every possible scenario that might arise, and then promulgate regulations to cover every case.
Complicated solutions to all complex problems are exactly what the authors try to avoid, claiming that simple heuristics outperform more complex ones in practice. Take company strategy, for example:
Don and his colleague Rebecca Homkes conducted a survey of managers in over 250 companies around the world. When asked to list their company’s top priorities for the next few years, only half of the managers could name even their company’s single most important objective.
Corporate strategy is better relayed to employees through simple rules they can apply easily than through obtuse manuals too time consuming to consult. Using simple rules need not necessarily result in simplistic behavior. A colony of ants, following very basic coordination rules, end up with quite advanced behavior of obstacle avoidance and resource gathering.
Essence of Simple Rules
Michael Pollan distilled his nutritional insights into three simple rules: “Eat food. Not too much. Mostly plants.” By “food” Pollan means real food—vegetables, fruits, nuts, whole grains, and meat and fish—rather than what he calls “edible food-like substances” found in the processed-food aisles of the grocery store.
Pollan’s principles follow the four traits of simple rules:
First, they are limited to a handful.
Capping the number of rules makes them easy to remember and maintains a focus on what matters most.
Second, simple rules are tailored to the person or organization using them.
Third, simple rules apply to a well-defined activity or decision, such as prioritizing injured soldiers for medical care.
Finally, simple rules give concrete guidance without being overly prescriptive.
Limiting the number of rules plays to the Pareto principle (or power law distribution), which states that the majority of effects emerge from a minority of causes. An extraneous long tail would have diminishing returns. A handful of rules, preferably from 3 to 5, also fit well in the 4±2 items our memories are said to handle at once. The more rules there are, the more ways they have to interact or contradict each other. Being able to think about them together may highlight inconsistencies that with longer lists could remain hidden.
In contrast to Pollan’s eating rules above, rules for a college football team should be different from rules for the average dieter, highlighting how simple rules should be specific to a particular group or type of person.
[…] Turley’s rules for his players are “Eat breakfast,” “Stay hydrated,” and “Eat as much as you want of anything that you can pick, pluck, or kill.” These rules make a lot of sense for very large and very active college-football players, who have a tendency to stay up late and get up late, exercise voraciously, and easily work off the calories.
Aside from being tailored to specific people, rules should also be unique to particular activities. If they cover too broad situations and contexts, they become platitudes or clichés.
Consistency vs Flexibility
A hammer is just the thing for nails, but useless when it comes to sawing a plank. The same is true of simple rules: to be effective, they must fit the task at hand. Simple rules work best when flexibility matters more than consistency.
Simple rules aren’t always the best way to approach decision making. Environments that require a rote activity or where lives are on the line, checklists form a better guide. While airline maintenance and medical procedures benefit more from precise checklists, medical triage, where time is priority, is better served by heuristics.
There’s a risk of overfitting with any model of the world and rules derived from it. An overfitted model is one that followed historical data and its errors too precisely, missing the underlying trend and assuming the future will look exactly like the past. It can’t handle additional historical data without fail, let alone predict the future in any accuracy. Overfitting shows up in laws and regulations that were relevant for a short period and later become useless or worse, dangerous.
In very complex systems, like the stock market or the economy as a whole, where causal relations are poorly understood and shift over time, the risks of overfitting past data are particularly acute. Statisticians have found that complicated models consistently fail to outperform simple ones in forecasting economic trends, and the accuracy of their predictions has not improved over time. When it comes to modeling complex systems, sophisticated does not always equal effective.
Simple rules avoid overfitting by not being too specific.
Counter-intuitive 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. This is especially true in situations when the links between cause and effect are poorly understood, when important variables are highly correlated, when a few factors matter most, and when a gap exists between knowing what to do and actually doing it. Simple rules do not trump complicated models every time, but they do so more often than you might think.
Given the possibility, it seems people voluntarily end up considering peripheral details at the expense of more important ones:
One study, for example, asked college students to consider several factors (such as the required reading, syllabus, prerequisites, and past students’ ratings) and weigh their relative importance before deciding which courses to take. A control group was given the same information and simply asked to choose their courses. The students who gave less thought to the variables tended to focus on a single variable—past students’ ratings—in making their decisions. In contrast, their classmates who considered more variables actually made worse decisions (as measured by their ultimate satisfaction with the courses they took). By ruminating on unimportant details, the students failed to give the most important variables the weight they deserved. Simple rules minimize the risk of overweighing peripheral considerations by focusing on the criteria most crucial for making good decisions.
Simple rules, being relatively easy to remember and follow, are also more likely be used than more comprehensive guidelines, as highlighted by another study:
They participated in a study to learn basic accounting to run their businesses better. Each entrepreneur was randomly assigned to one of three experimental groups. The first group studied accounting the way it is taught in most universities, as a complicated body of knowledge to be mastered. A second group studied accounting as simple rules like “Keep personal and business money in different drawers” and “Only transfer money from one drawer to the other with a written IOU.” The third group received no accounting instruction. The entrepreneurs who learned the simple rules of accounting were more likely to translate their knowledge into action. They improved their bookkeeping and cash management and also increased sales by 25 percent. In contrast, the entrepreneurs who were exposed to accounting as a complicated body of knowledge were no better off than those who were not taught any accounting at all.
Simplicity plays an even bigger role when people are tired or stressed:
One study of dieting, for example, compared perseverance and weight loss on a simple diet plan versus a complicated one. While the dieters who stuck with the program lost weight on both plans, people were more likely to adhere to the simple diet and abandon the complicated one. When asked why they quit, the lapsed dieters cited complexity as the single most important reason for giving up.
Authors describe three rule types that are often used in decision making.
- Boundary rules help choose among mutually exclusive options.
- Prioritizing rules help choose where to direct resources.
- Stopping rules help choose when to reverse a decision or cancel an action.
Boundary rules, like when to go forward with a deal, help narrow down and choose between mutually exclusive options. Limited not only to professionals, boundary rules are used even by burglars:
But most real-life burglars rely on only a few simple rules to decide if a house is unoccupied, and hence a good candidate for breaking and entering.
The burglars significantly outperformed chance in identifying occupied houses, and two-thirds of the time they used a single rule to pick their target: “Avoid houses with a vehicle parked outside.” This simple rule is unlikely to dazzle fans of heist films like Ocean’s Eleven, but it works. The presence of a vehicle was indeed the single most reliable predictor of occupancy in the homes that the researchers photographed.
When it comes to quick decision making, nothing beats having a heuristic in place to quickly disqualify options. They turn out to be handy even in psychological evaluations, identifying depressed patients 97% of the time if they answer yes to all four questions:
A recently developed diagnostic tool for depression relies on four simple rules, expressed as questions that can be asked in under a minute: Have you cried more than usual within the last week? Have you been disappointed in yourself or hated yourself within the last week? Have you felt discouraged about the future within the last week? Have you felt that you failed in your life within the last week
With boundary rules help pick options to qualify, prioritizing rules help distribute finite resources among alternatives. They help resolve bottlenecks, where the amount of opportunities exceed resources, by helping focus on what can have the greatest impact.
In decision theory circles, the best known stopping problem is the secretary problem. Suppose you need to hire the best secretary out of all the candidates. You also get a single interview with every candidate and have to decide then and there whether to hire or move to the next. Who do you select, or in other words, when you stop searching and settle down? If you pick a candidate too quickly, you’re likely to miss out on later better candidates. If you hesitate for too long, you might pass on the best candidate of the group and have no choice but to settle on a worse candidate.
Whenever alternatives present themselves sequentially (as opposed to appearing all at once), the question of when to stop searching and make a choice arises.
Another manifestation of the stopping problem is mate selection:
Biologists have observed several different rules that insects use to decide when to end their search and settle on a mate. These rules include “Choose a mate who meets your quality threshold,” which is known as the fixed-threshold strategy. In contrast, the female crickets that lower the bar if they do not run across enough high-quality males adhere to what is known as the variable-threshold strategy. […] Another simple rule for ending a mate search is to visit a fixed number of potential mates and then return to the highest-quality mate within that sample. And anyone who has stayed until last call at a singles bar will recognize the “fixed threshold with last chance option” rule, where the seeker maintains his or her threshold until a set time, and then mates with the next potential partner regardless of quality.
Sometimes it’s not about stopping search, but instead stopping an ongoing engagement, be it financial or professional.
A well-documented tendency among human decision makers, known as the status quo bias, leads individuals to hold ’em when they should fold ’em across a range of decisions.
Stopping rules can help investors by providing some guidance on when to sell their assets. And, if there was ever a good time to know when to sell a stock, it was right before the Great Depression.
Out of the rubble of the 1929 crash, one banker rose up stronger than ever. Gerald Loeb, the son of a French wine merchant, sniffed out the crash of 1929 before it happened and helped his clients avoid heavy stock market losses.
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.
Being able to walk away is especially vital in situations where people have a tendency to double down:
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).
With decision rules covering what to do, process rules cover how to do something. Here, too, three are brought out:
- How-to rules cover basic task execution.
- Coordination rules cover and handle multiple people working towards one goal.
- Timing rules cover schedules and deadlines.
How-to rules address the basics of getting things done without prescribing every detail of what to do.
Being adaptable makes simple how-to rules fit novel situations far better than precise checklists. How-to rules also provide direction when approaching creative tasks.
By constraining infinite possibilities, 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.
This was the musical strategy of White Stripes:
“The whole point of the White Stripes,” according to founder and frontman Jack White, “is the liberation of limiting yourself.” Their breakout album, 2001’s White Blood Cells, which is featured on many lists of the decade’s best albums, follows five simple rules: (1) no blues; (2) no guitar solos; (3) no slide guitar; (4) no covers; and (5) no bass. These rules constrained the band to a box—but it was their box, and staying in that box helped enable their rapid-fire creativity. “I’m disgusted by artists or songwriters who pretend there are no rules,” Jack White said in a New York Times interview. “There’s 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.”
As with decision rules, authors suggest there’s a balance between having no rules and having too many:
The firms that eschewed rules altogether were soon overcome by complexity, dissipating their scarce time, attention, and cash in the pursuit of any opportunity that passed their way. But the firms that followed many rules were too slow and stodgy. The environment of these technology-based companies was far too complex for a structured solution, enumerated in a fat rule book, to ever make sense.
Flight of birds is an example of coordination rules, where a simple algorithm guides each bird results in complex group behavior. Coordination rules describe behavior in relation to others, even if those others are distant in time or space.
Groups can achieve objectives that are out of reach for a single individual. Predators, for example, can hunt prey many times their size if they manage to coordinate their attack. Even insects.
A solitary locust is nothing special. But as a swarm, locusts constitute a pestilence of, well, biblical proportions. Even today, locusts threaten the sustenance of one in every ten people on earth. A swarm can contain millions of locusts, blacken the sky over several kilometers, and travel the length of a continent, devastating crops and livestock along the way. Yet most of the time locusts live a solitary existence, avoiding contact with one another, and only occasionally mobilize into a hellish army.
Improvisation is an activity that benefits from coordination.
The best-known rule is to build on whatever is said or done just beforehand by saying, “Yes, and . . .” Another rule is “Don’t tell jokes,” because they often stifle an emerging storyline by imposing an artificial punch line onto an organic situation. The rule to make others look good underscores the importance of helping other players shine. In improv, prima donnas just make everyone, including themselves, look second-rate. Instead, you help yourself by helping the group.
Some situations require rules to coordinate across time and distance:
To foster battlefield coordination, Napoleon is reputed to have issued a standing order to “march toward the sound of gunfire,” a simple rule that enabled his officers to coordinate their activities without knowing exactly what was happening. Generals and soldiers could locally adapt to the facts on the ground, such as deteriorating weather, a gap in enemy defenses, or unexpectedly intense resistance, which were impossible to anticipate. But the rule also helped ensure that the fighting force would arrive where it was most needed and would have the most impact.
Where how-to and coordination rules dictate what and who should do something, timing rules help decide when to act. One problem that benefits from timing rules is insomnia, whose sufferers may be able to alleviate their symptoms by following these four simple rules for when to sleep:
“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.
“Avoid going to bed until you feel sleepy,” even if this means hitting the hay later than you would ideally like.
“Do not stay in bed if you are not sleeping,”
“Reduce the time spent in bed.”
Following these rules keeps troubled sleepers from spending ten or twelve hours in bed in order to snag a few hours of sleep—a common pattern in older adults. In the short run, these rules may lead to people feeling tired or sleep deprived as they adjust. But over the long term, patients who follow these rules usually enjoy a deeper, more restful sleep that comes on more quickly.
Timing rules can be split into two:
- Event pacing, where an external event triggers an action, like going to bed only when tired.
- Time pacing, where the trigger lies in the time of day or deadline, such as a daily alarm clock.
Out of all rule types you might use, timing rules may often surface last —
knowledge about time requires experiencing enough events over a sufficiently long period to recognize sequences of action or particular rhythms that make sense to use.
Dragonflies follow a few timing rules to guide their migration:
The scientists also discovered that a few timing rules explained when the insects fly and when they stay put. One rule is to fly only when the nighttime temperature falls for two consecutive nights. Falling nocturnal temperatures are highly correlated with frigid northern winds that carry the green darners south and remind the dragonflies to get going. While some wind is ideal, extreme gusts are dangerous regardless of which way the wind is blowing. So the second timing rule is to stay put on windy days—that is, when the wind blows more than fifteen miles per hour. Together, these timing rules specify the events that trigger when green darners start flying.
Source of Rules
The book enumerates a few sources of inspiration for coming up with simple rules:
- Evolution, where natural selection or culture picks the best and worse rules for us.
- Personal experience, where you rely on your own career.
- Others’ experience, where you rely on others’ mistakes.
- Scientific experience, where you rely on the scientific method more than personal anecdotes.
It’s not always people that need to come up with simple rules to get tasks done. Butterflies have a particularly important problem they need to solve, and that’s where to meet:
Butterflies have a lot of space to cover, and very little time to do it. If butterflies were the size of humans, their population density would be one-tenth that of Alaska. Butterflies live, on average, just one month, so time is of the essence. The butterflies need to find each other, and quickly. From an evolutionary perspective, the stakes are high, since romantics who fail to mate cannot pass their genes on to the next generation.
After 50 millions years of speed dating and missed appointments, they converged on a few simples rules of their own:
First, “Fly uphill most of the time.” Second, “Fly toward the highest slope in sight” (within the butterfly’s range of vision of about 165 feet). Third, “Pause to check out local peaks, even if they are not the highest, but leave if you do not get lucky right away.” Fourth, “Periodically make a random movement” to avoid getting trapped on a summit that is the highest peak in the nearby vicinity, but not the highest overall.
Some rules evolve not through natural selection, but in human communities through changes in culture.
Joke stealing is the cardinal sin in standup comedy today, but it was not always so. For much of the twentieth century, stealing jokes was no big deal. In the vaudeville era, performers would repeat other comedians’ material verbatim without attributing the source. Later comedians, such as Milton Berle and Bob Hope, drew on vast stores of generic jokes. Expert delivery and timing, rather than originality, mattered most.
For example, comedians often formulate material collaboratively. In this instance, the rule gives ownership of the joke to the person who came up with the premise, rather than the punch line. This rule arose through discussions among comedians and spread. When two performers come up with similar jokes, the rule is that the first person to perform the joke on television owns it, giving authorship to the comedian who can prove he or she told the joke first. Another ownership issue, what to do when one comic sells a joke to another, or writes the joke as the comic’s employee, is resolved by the rule that the person who paid for a joke owns it, and the originator cannot publicly identify herself as the joke’s writer.
While rules that have evolved through evolution often end up elegant and simple, being ingrained, they don’t lend themselves to easy adaption if circumstances change. That’s when people should turn to more concious rule making.
As rules are intended to be context and person specific, getting inspiration from personal experience is a good way to create relevant simple rules. Personal rules are also more likely to be adhered to.
The second best source is personal experience of people around you:
The experience of others can be as valuable as one’s own experience in shaping people’s simple rules. Advice from experienced people about how to parent, play poker, or manage people, for example, whether given directly or conveyed through a book or magazine article, can prove useful in formulating one’s own approach. Personal observation is another effective way to learn what works for others. We also use analogies, finding similarities between our own experience and others’, which can streamline the process of devising our rules.
They have a few suggestions on eliciting rules:
When talking with 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. A few tactics can help surface tacit rules. First, you can 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. People typically find it easier to describe their rules in the context of concrete examples rather than in abstract terms.
“Others” don’t even have to be humans. The book describes the designing of the Tokyo commuter-rail system for which its designers drew inspiration from biology. To figure out ways to best link up Tokyo with its 36 nearby towns, they turned to many-headed slime mold. By placing food to stand in for cities and lights, which the mold avoids, to stand in for mountains, lakes and other inaccessible places, they could investigate the methods evolution has come up with for network design.
From their observations, the team codified the how-to and stopping rules for the slime’s expansion, which included: (1) begin by searching randomly in many directions for food; (2) when you find food, thicken the tube; and (3) when you don’t find food, shrink the tube.
Mold isn’t the only useful biological source of inspiration. Social insects, like termites and bees, have long used simple rules from which interesting behavior arises.
They have enough collective intelligence to accomplish complex tasks like finding nests or migrating long distances, but since each animal has little brainpower and few physical skills, their actions can often be captured by simple rules.
More methodological approaches to experience, with quantifiable data, gets us to deriving rules from scientific evidence.
Scientific evidence, however, is not inherently simple. The resulting knowledge is often full of qualifications and contingencies that hold under some circumstances, but not others. One way to develop simple rules is to review a body of scientific research, sort through to determine the most consistent findings across studies, and distill these findings into a few simple rules.
A distillation of scientific results to simple rules also benefits less scientifically minded people:
It prevents scientists and laypeople from speaking past one another. Marine ecologists, like all scientists, prefer to acknowledge the limits of their findings and qualify their recommendations. But to the layperson unfamiliar with scientific discourse, these uncertain statements sound like so much waffling. By focusing on the most consistent findings, scientists can be more comfortable advocating them, without qualification, as practical advice. Nonscientists receive what they want—clear guidance on action.
A general strategy the authors suggested for coming up with simple rules followed three steps:
Figure out what will move the needles.
Choose a bottleneck.
Craft the rules.
In a group setting, they warned against appeal to authority.
Developing rules from the top down is a big mistake. 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. It is much better to involve a team, typically ranging in size from four to eight members, and use a structured process to harness members’ diverse insights and points of view. When drafting the dream team to develop simple rules, it is critical to include some of the people who will be using them on a day-to-day basis.
What do you do when people around you can’t come to an agreement? You turn to negotiation.
[…] negotiating simple rules works particularly well when it is cumbersome or impossible to resolve conflicts by escalating them to a higher authority. James Buchanan, a Nobel Prize–winning economist, argued that when there are competing interests, it is critical for stakeholders to negotiate decision rules before haggling over specific decisions.
People that participated in the rule making process are far more likely to accept the consequences of using the rules, even if that means they experience loss.
Having users make the rules confers several advantages. First, they are closest to the facts on the ground and best positioned to codify experience into usable rules. Because they will make decisions based on the rules, they can strike the right balance between guidance and discretion, avoiding rules that are overly vague or restrictive. Users can also phrase the rules in language that resonates for them, rather than relying on business jargon. By actively participating in the process, users are more likely to buy into the final rules and therefore apply them in practice. Firsthand knowledge also makes it easier to explain the rules, and their underlying rationale, to colleagues who did not participate in the process.
After coming up with your own set of rules, it’s important to test them both against historical data to see if they actually match the examples they were derived from and against future opportunities.
Although the systematic process laid out in the last two chapters can be a big help, initial rules are often automatic, obvious, and generally weak. Over time, three things happen. First, their content shifts from superficial and convenient rules to strategic and abstract ones that prove more effective over a broader range of activities and decisions. Second, the different types of rules are learned in a specific sequential order. Boundary and how-to rules usually come first, while the other rule types follow and are harder to learn. Third, the rules go through simplification cycling in which their number grows, and then shrinks and becomes constant. Over time, the rules may continue to shift as circumstances change, but the best rule users keep the number small.
Authors also briefly touch on a general learning strategies:
The first, specialized practice, mirrors the old saying “Practice makes perfect,” and repeats the same activity. The second, unrelated experience exploits what is known as massed practice, in which individuals take periodic breaks to do something completely different from what they are trying to learn. This strategy provides time to consolidate knowledge before moving on. The third strategy is related experience, which is what Shannon did by coaching different sports and Raghu did by practicing different kinds of poker playing.
Based on an experiment that put the three strategies above against each other, it turned out the best strategy was the third.
So while very specialized practice might seem better for improving because it focuses time and energy on one task, it lacks the informative contrasts that enrich understanding. While unrelated activities may offer a helpful break, they are not germane to what is being learned. Instead, people improve most rapidly with varied but related experiences.
With all the benefits of simple rules, why aren’t they more used?
The first obstacle is the effort required to develop simple rules. Like most worthwhile endeavors, it takes time and energy to get them right. The process of developing simple rules requires ruthless prioritization—honing in on the essential and decluttering the peripheral.
As briefly touched on at the beginning, people form the second obstacle to simplicity:
The costs of complex solutions are distributed across many people while the benefits of complexity tend to be concentrated in the hands of a few. These beneficiaries have, as a consequence, strong incentives to resist simplification. Much of the complexity of the U.S. tax code, for example, exists because special-interest groups secure tax breaks, including write-offs for owning a racehorse or building a race track, that benefit a small number of individuals.
After creating a labyrinth of rules, regulators and politicians often walk through the revolving door to join the companies they formerly supervised. In the private sector they can guide their new employers through the maze of regulations they themselves helped build. And the revolving door between government and business is likely to spin faster as regulatory complexity increases. A recent study found that the number of former regulators hired by financial service firms increased by 55 percent between 2001 and 2013.
Finally, its complexity itself.
The third obstacle to simplicity is what we call the “myth of requisite complexity,” the mistaken belief that complex problems demand complicated solutions. There are, naturally, situations when complicated solutions are appropriate—recall the detailed checklists used by pilots and surgeons. But detailed rules and regulations aren’t the only possible way to deal with complexity. The U.S. Congress responded to the 2008 financial crisis by drafting tens of thousands of pages of detailed regulations covering financial service organizations.
Whether detailed regulation wins over simple rules is an unfortunately seldom investigated empirical question. The few that exist so far, seem to point against more rules:
Consider the results of a recent study that analyzed legal systems around the world. The authors compared how well the judicial systems in 109 countries resolved two of the most common legal disputes—evicting a tenant who stops paying rent and chasing down payment on a bounced check. Their study revealed enormous variation across countries in terms of the number of rules limiting a judge’s discretion, with more rule-laden systems taking an order of magnitude longer to mete out justice. In the United States, a landlord could evict a delinquent tenant in under two months, a process that took eighteen months in Austria. The authors measured justice along several dimensions, including whether citizens considered their legal systems impartial, free from corruption, affordable, and consistent. The number of rules was negatively correlated with all measures of justice. Any way the authors cut the data, the result was the same—more rules, less justice.
Sometimes forgoing rules gives a firm a competitive advantage.
After studying their human resources policies, executives at Netflix determined that 97 percent of their employees were trustworthy. Nearly all of the company’s time writing, monitoring, and enforcing detailed personnel policies was directed at the remaining 3 percent. Rather than continue to produce binders of detailed regulations, Netflix executives concentrated on not hiring people who would cause problems, and removing them quickly when hiring mistakes were made. This change allowed the company to replace thick manuals with simple rules. The company’s policy for expenses, travel, gifts, and conducting personal business at work, for example, was reduced to four rules: (1) expense what you would not otherwise spend, (2) travel as if it were your own money, (3) disclose nontrivial gifts from vendors, and (4) do personal stuff at work when it is inefficient not to.
Authors included a chapter on the online dating experience of Harry, a recent architecture graduate, to illustrate the process of creating his own rules. It’s difficult enough to be noticed and be attractive online, but doing it aside a busy career highlights the value of a systematic approach. After an initial frustration with the slow progress and poor dates, he went over every aspect of the process, identifying bottlenecks in his own online image to the way he messaged people.
While he first considered his profile and its picture to be in need of refreshing, the one-off task meant it wouldn’t be a good candidate for simple rules. Further analysis led him to filtering potential mates and contacting them — two activities that he’d be doing a lot and where he could improve the most. He had found, for example, that only 1 in 6 women responded to his introductions. Out of women that had responded, half led to the exchange of phone numbers, and ⅔ of those to a date. Dates were fifty-fifty, leading to a total of one out of 36 matches being an enjoyable date.
Based on his earlier messages he come up with the first rule:
Send feelers before essays. Sending short messages to establish interest, then following up with gradually longer ones, was a better course of action.
Second, he looked at dates:
Harry noted a common pattern to these dates. It seemed like a good idea when they agreed to go out, but on the way to the restaurant he realized he was not particularly excited about dinner. These dates were often pleasant enough, but they represented a significant opportunity cost, in Harry’s view, because his work schedule meant he could only go out a few nights a week at most. This observation based on experience led to Harry’s second rule: “Only pursue her if you would like to see her tonight.” By making theoretical opportunities immediate, this rule helped Harry avoid approaching potential dates where they had little in common.
Then, at his selection process:
Another source of disappointing dates occurred when someone posted pictures and then didn’t look anything like their photos when they arrived. Harry was not overly hung up on physical appearance, but he was bothered by the attempt at deception. He turned to his friend Will, who had been dating online for a while, for advice. Will explained that he had encountered the same problem early in his online dating career, but eventually learned a few tactics to detect misleading photographs. Will’s tips centered around photographic variety: if there was none, especially if all the pictures were taken from the same angle, it raised a red flag. Will also cautioned against “beautiful outliers,” which occurred when one picture was much more fetching than others. Harry added a third rule to “avoid photographic red flags”
Harry also looked into testing his initial messages based on the results of OkCupid’s article on “Exactly What To Say In A First Message” and ended up with a simple “Ask her how it’s going”.
There was also a story of a mechanical engineer coming up with his own rules on how to be a better communicator, reading among others “The Charisma Myth: How Anyone Can Master the Art and Science of Personal Magnetism” by Olivia Fox Cabane, and came up with the following personal rules:
Imagine the person you are talking to is the sympathetic star in a film you are watching.
Carry yourself like a king — calm, comfortable, and without excessive nodding, “uh-huh”-ing, and fidgeting.
Make and maintain soft eye contact, which means relaxing your eyes and face when you look at someone. By maintaining soft eye contact, Daniel learned, he could focus on what the other person was saying and build a stronger connection as they spoke.
Both authors have given talks about the book. Out of the two below, I recommend Donald Sull’s.