Tag: Systems

Descriptions Aren’t Prescriptions

When we look at a representation of reality, we can choose to either see it as descriptive, meaning it tells us what the world is currently like, or as prescriptive, meaning it tells us how the world should be. Descriptions teach us, but they also give us room to innovate. Prescriptions can get us stuck. One place this tension shows up is in language.

In one chapter of The Utopia of Rules: On Technology, Stupidity, and the Secret Joys of Bureaucracy, David Graeber describes his experience of learning Malagasy, the national language of Madagascar. While the language’s writing system came about in the fifteenth century, it wasn’t until the early nineteenth century that missionaries documented the rules of Malagasy grammar for the purpose of translating scripture.

Of course, the “rules” of Malagasy the missionaries recorded weren’t rules at all. They were reflections of how people spoke at that point in time, as far as outside observers could tell. Languages don’t usually come into existence when someone invents the rules for them. Instead, languages evolve and change over time as speakers make modifications or respond to new needs.

However, those early nineteenth-century records remained in place as the supposed “official” version of Malagasy. Children learned the old form of grammar in school, even as they spoke a somewhat different version of the language at home. For Graeber, learning to speak the version of Malagasy people actually understood in conversation was a challenge. Native speakers he hired would instruct him on the nineteenth-century grammatical principles, then turn and speak to each other in a whole other fashion.

When asked why they couldn’t teach him the version of the language they spoke, Graeber’s Malagasy teachers responded that they were just using slang. Asked why no one seemed to speak the official version, they said people were too lazy. Graeber writes, “Clearly the problem was that the entire population had failed to memorize their lessons properly. But what they were actually denying was the legitimacy of collective creativity, the free play of the system. ” While the official rules stayed the same over the decades, the language itself kept evolving. People assumed the fault of not speaking “proper” Malagasy lay with them, not with the outdated dictionary and grammar. They confused a description for a prescription. He writes:

It never seems to occur to anyone—until you point it out—that had the missionaries came and written their books two hundred years later, current usages would be considered the correct ones, and anyone speaking as they had two hundred years ago would themselves be assumed to be in error.

Graeber sees the same phenomenon playing out in other languages for which grammars and dictionaries only came into existence a century or two ago. Often, such languages were mostly spoken and, like Malagasy, no one made formal records until the need arose for people from elsewhere to make translations. Instead of treating those records as descriptive and outdated, those teaching the language treat them as prescriptive—despite knowing they’re not practical for everyday use.

***

Why don’t people talk “proper”?

So why can’t people just speak a language per the official rules? If someone has gone to all the effort of identifying and recording the rules and people received instruction on them in school, why not follow them? Why keep changing things up?

If languages didn’t evolve, it would make life a lot easier for historians looking at texts from the past. It would also simplify matters for people learning the language, for those coming from different areas, and even for speakers across generations. Yet all languages change all the time.

Graeber suggests the reason for this is because people like to play. We find it dull to speak according to the official rules of our language. We seek out novelty in our everyday lives and do whatever it takes to avoid boredom. Even if each person only plays a little bit once in a while, the results compound. Graeber explains that “this playing around will have cumulative effects.”

Languages still need conventions so people can understand each other. The higher the similarity between the versions of a language different people speak, the more they can communicate. At the same time, they cannot remain rigid. Trying to follow an unyielding set of strict rules will inevitably curtail the usefulness of a language and prevent it from developing in interesting and necessary ways. Languages need a balance: enough guidance to help everyone understand each other and provide an entry point for learners, and enough flexibility to keep updating the rules as actual usage changes.

As a result, languages call into question our idea of freedom: “It’s worth thinking about language for a moment, because one thing it reveals, probably better than any other example, is that there is a basic paradox in our very idea of freedom. On the one hand, rules are by their nature constraining. Speech codes, rules of etiquette, and grammatical rules, all have the effect of limiting what we can and cannot say. ” On the other hand, no rules whatsoever mean no one can understand each other.

Languages need frameworks, but no amount of grammar classes or official dictionaries will prevent people from playing and having fun with their speech.

***

The dictionary is not the language

“The map is not the territory” means that any representation of reality has to be a simplification that may contain errors, become outdated, or reflect biases. Maps remove details that aren’t necessary for their intended use. Representations of complex systems may show expected behavior or ideal behavior. For example, the London Underground map doesn’t reflect the distances between stations because this information isn’t important to most commuters. If a map represented its territory without reducing anything, it would be identical to the territory and therefore would be useless. In fact, the simplest maps can be the most useful because they’re the easiest to understand and remember.

Sometimes maps are descriptive, and sometimes they’re prescriptive; often they’re a bit of both. We run into problems when we confuse one type for another and try to navigate an idealized territory or make the real territory fit an idealized image.

A language’s grammar and dictionary are a sort of map. They take a complex system—a language spoken by what could be tens of millions of people—and aim to represent it with something which is, by comparison, simple. The official rules are not the language itself, but they provide guidance for navigating it. Much like a map of a city needs periodic updates as parts are torn down, built up, renamed, destroyed, added, and so on, the official rules need updating as the language changes. Trying to learn Malagasy using grammar rules written two hundred years ago is like trying to navigate Antananarivo using a street map made two hundred years ago.

A map of a complex system, like a language, is meant to help us find our way by giving us a sense of how things looked at one point in time—it’s usually descriptive. It doesn’t necessarily tell us how that system should look, and we may run into problems if we try to make it conform to the map, ignoring the system’s own adaptive properties. Even if the cartographer never intended this, we can end up treating a map as a prescription. We try to make reality conform to the map. This is what occurs with languages. Graeber calls this the “grammar-book effect”:

People do not invent languages by writing grammars, they write grammars—at least, the first grammars to be written for any given language—by observing the tacit, largely unconscious rules that people seem to be employing when they speak. Yet once a book exists, and especially once it is employed in schoolrooms, people feel that the rules are not just descriptions of how people do talk, but prescriptions for how they should talk.

As we’ve seen, one reason the map is not the territory with language is because people feel compelled to play and experiment. When we encounter representations of systems involving people, we should keep in mind that while we may need rules for the sake of working together and understanding each other, we’re always pushing up against and reshaping those rules. We find it boring to follow a rigid prescription.

For instance, imagine some of the documents you might receive upon starting a role at a new company. Process documents showing step by step how to do the main tasks you’ll be expected to perform. But when the person you’re replacing shows you how to do those same tasks, you notice they don’t follow the listed steps at all. When you ask why, they explain that the process documents were written before they started actually carrying out those tasks, meaning they discovered more efficient ways afterward.

Why keep the process documents, then? Because for someone filling in or starting out, it might make sense to follow them. It’s the most defensible option. Once you truly know the territory and won’t change something without considering why it was there in the first place, you can play with the rules. Those documents might be useful as a description, but they’re unlikely to remain a prescription for long.

The same is true for laws. Sometimes aspects of them are just descriptive of how things are at one point in time, but we end up having to keep following them to the letter because they haven’t been updated. A law might have been written at a time when documents needed sending by letter, meaning certain delays for shipping. Now they can be sent by email. If the law hasn’t been updated, those delay allowances turn from descriptions into prescriptions. Or a law might reflect what people were permitted to do at the time, but now we assume people should have the right to do that thing even if we have new evidence it’s not the best idea. We are less likely to change laws if we persist in viewing them as prescriptive.

***

Conclusion

Descriptions of reality are practical for helping us navigate it, while also giving us room to change things. Prescriptions are helpful for giving us ways of understanding each other and providing enough structure for shared conventions, but they can also become outdated or end up limiting flexibility. When you encounter a representation of something, it’s useful to consider which parts are descriptive and which parts are prescriptive. Remember that both prescriptions and descriptions can and should change over time.

***

The FS team were saddened to hear of David Graeber’s passing, shortly after we completed this article. We hope his books will continue to inspire and educate new readers for many years to come.

Why Life Can’t Be Simpler

We’d all like life to be simpler. But we also don’t want to sacrifice our options and capabilities. Tesler’s law of the conservation of complexity, a rule from design, explains why we can’t have both. Here’s how the law can help us create better products and services by rethinking simplicity.

“Why can’t life be simple?”

We’ve all likely asked ourselves that at least once. After all, life is complicated. Every day, we face processes that seem almost infinitely recursive. Each step requires the completion of a different task to make it possible, which in itself requires another task. We confront tools requiring us to memorize reams of knowledge and develop additional skills just to use them. Endeavors that seem like they should be simple, like getting utilities connected in a new home or figuring out the controls for a fridge, end up having numerous perplexing steps.

When we wish for things to be simpler, we usually mean we want products and services to have fewer steps, fewer controls, fewer options, less to learn. But at the same time, we still want all of the same features and capabilities. These two categories of desires are often at odds with each other and distort how we understand the complex.

***

Conceptual Models

In Living with Complexity, Donald A. Norman explains that complexity is all in the mind. Our perception of a product or service as simple or complex has its basis in the conceptual model we have of it. Norman writes that “A conceptual model is the underlying belief structure held by a person about how something works . . . Conceptual models are extremely important tools for organizing and understanding otherwise complex things.”

For example, on many computers, you can drag and drop a file into a folder. Both the file and the folder often have icons that represent their real-world namesakes. For the user, this process is simple; it provides a clear conceptual model. When people first started using graphical interfaces, real-world terms and icons made it easier to translate what they were doing. But the process only seems simple because of this effective conceptual model. It doesn’t represent what happens on the computer, where files and folders don’t exist. Computers store data wherever is convenient and may split files across multiple locations.

When we want something to be simpler, what we truly need is a better conceptual model of it. Once we know how to use them, complex tools end up making our lives simpler because they provide the precise functionality we want. A computer file is a great conceptual model because it hijacked something people already understood: physical files and folders. It would have been much harder for them to develop a whole new conceptual model reflecting how computers actually store files. What’s important to note is that giving users this simple conceptual model didn’t change how things work behind the scenes.

Removing functionality doesn’t make something simpler, because it removes options. Simple tools have a limited ability to simplify processes. Trying to do something complex with a simple tool is more complex than doing the same thing with a more complex tool.

A useful analogy here is the hand tools used by craftspeople, such as a silversmith’s planishing hammer (a tool used to shape and smooth the surface of metal). Norman highlights that these tools seem simple to the untrained eye. But using them requires great skill and practice. A craftsperson needs to know how to select them from the whole constellation of specialized tools they possess.

In itself, a planishing hammer might seem far, far simpler than, say, a digital photo editing program. Look again, Norman says. We have to compare the photo editing tool with the silversmith’s whole workbench. Both take a lot of time and practice to master. Both consist of many tools that are individually simple. Learning how and when to use them is the complex part.

Norman writes, “Whether something is complicated is in the mind of the beholder. ” Looking at a workbench of tools or a digital photo editing program, a novice sees complexity. A professional sees a range of different tools, each of which is simple to use. They know when to use each to make a process easier. Having fewer options would make their life more complex, not simpler, because they wouldn’t be able to break what they need to do down into individually simple steps. A professional’s experience-honed conceptual model helps them navigate a wide range of tools.

***

The conservation of complexity

To do difficult things in the simplest way, we need a lot of options.

Complexity is necessary because it gives us the functionality we need. A useful framework for understanding this is Tesler’s law of the conservation of complexity, which states:

The total complexity of a system is a constant. If you make a user’s interaction with a system simpler, the complexity behind the scenes increases.

The law originates from Lawrence Tesler (1945–2020), a computer scientist specializing in human-computer interactions who worked at Xerox, Apple, Amazon, and Yahoo! Tesler was influential in the development of early graphical interfaces, and he was the co-creator of the copy-and-paste functionality.

Complexity is like energy. It cannot be created or destroyed, only moved somewhere else. When a product or service becomes simpler for users, engineers and designers have to work harder. Norman writes, “With technology, simplifications at the level of usage invariably result in added complexity of the underlying mechanism. ” For example, the files and folders conceptual model for computer interfaces doesn’t change how files are stored, but by putting in extra work to translate the process into something recognizable, designers make navigating them easier for users.

Whether something looks simple or is simple to use says little about its overall complexity. “What is simple on the surface can be incredibly complex inside: what is simple inside can result in an incredibly complex surface. So from whose point of view do we measure complexity? ”

***

Out of control

Every piece of functionality requires a control—something that makes something happen. The more complex something is, the more controls it needs—whether they are visible to the user or not. Controls may be directly accessible to a user, as with the home button on an iPhone, or they may be behind the scenes, as with an automated thermostat.

From a user’s standpoint, the simplest products and services are those that are fully automated and do not require any intervention (unless something goes wrong.)

As long as you pay your bills, the water supply to your house is probably fully automated. When you turn on a tap, you don’t need to have requested there to be water in the pipes first. The companies that manage the water supply handle the complexity.

Or, if you stay in an expensive hotel, you might find your room is always as you want it, with your minifridge fully stocked with your favorites and any toiletries you forgot provided. The staff work behind the scenes to make this happen, without you needing to make requests.

On the other end of the spectrum, we have products and services that require users to control every last step.

A professional photographer is likely to use a camera that needs them to manually set every last setting, from white balance to shutter speed. This means the camera itself doesn’t need automation, but the user needs to operate controls for everything, giving them full control over the results. An amateur photographer might use a camera that automatically chooses these settings so all they need to do is point and shoot. In this case, the complexity transfers to the camera’s inner workings.

In the restaurants inside IKEA stores, customers typically perform tasks such as filling up drinks and clearing away dishes themselves. This means less complexity for staff and much lower prices compared to restaurants where staff do these things.

***

Lessons from the conservation of complexity

The first lesson from Tesler’s law of the conservation of complexity is that how simple something looks is not a reflection of how simple it is to use. Removing controls can mean users need to learn complex sequences to use the same features—similar to how languages with fewer sounds have longer words. One way to conceptualize the movement of complexity is through the notion of trade-offs. If complexity is constant, then there are trade-offs depending on where that complexity is moved.

A very basic example of complexity trade-offs can be found in the history of arithmetic. For centuries, many counting systems all over the world employed tools using stones or beads like a tabula (the Romans) or soroban (the Japanese) to facilitate adding and subtracting numbers. They were easy to use, but not easily portable. Then the Hindu-Arabic system came along (the one we use today) and by virtue of employing columns, and thus not requiring any moving parts, offered a much more portable counting system. However, the portability came with a cost.

Paul Lockhart explains in Arithmetic, “With the Hindu-Arabic system the writing and calculating are inextricably linked. Instead of moving stones or sliding beads, our manipulations become transmutations of the symbols themselves. That means we need to know things. We need to know that one more than 2 is 3, for instance. In other words, the price we pay [for portability] is massive amounts of memorization.” Thus, there is a trade-off. The simpler arithmetic system requires more complexity in terms of the memorization required of the users. We all went through the difficult process of learning mathematical symbols early in life. Although they might seem simple to us now, that’s just because we’re so accustomed to them.

Although perceived simplicity may have greater appeal at first, users are soon frustrated if it means greater operational complexity. Norman writes:

Perceived simplicity is not at all the same as simplicity of usage: operational simplicity. Perceived simplicity decreases with the number of visible controls and displays. Increase the number of visible alternatives and the perceived simplicity drops. The problem is that operational simplicity can be drastically improved by adding more controls and displays. The very things that make something easier to learn and to use can also make it be perceived as more difficult.

Even if it receives a negative reaction before usage, operational simplicity is the more important goal. For example, in a company, having a clearly stated directly responsible person for each project might seem more complex than letting a project be a team effort that falls to whoever is best suited to each part. But in practice, this adds complexity when someone tries to move forward with it or needs to know who should hear feedback about problems.

A second lesson is that things don’t always need to be incredibly simple for users. People have an intuitive sense that complexity has to go somewhere. When using a product or service is too simple, users can feel suspicious or like they’ve been robbed of control. They know that a lot more is going on behind the scenes, they just don’t know what it is. Sometimes we need to preserve a minimum level of complexity so that users feel like an actual participant. According to legend, cake mixes require the addition of a fresh egg because early users found that dried ones felt a bit too lazy and low effort.

An example of desirable minimum complexity is help with homework. For many parents, helping their children with their homework often feels like unnecessary complexity. It is usually subjects and facts they haven’t thought about in years, and they find themselves having to relearn them in order to help their kids. It would be far simpler if the teachers could cover everything in class to a degree that each child needed no additional practice. However, the complexity created by involving parents in the homework process helps make parents more aware of what their children are learning. In addition, they often get insight into areas of both struggle and interest, can identify ways to better connect with their children, and learn where they may want to teach them some broader life skills.

When we seek to make things simpler for other people, we should recognize that there be a point of diminishing negative returns wherein further simplification leads to a worse experience. Simplicity is not an end in itself—other things like speed, usability, and time-saving are. We shouldn’t simplify things from the user standpoint for the sake of it.

If changes don’t make something better for users, we’re just creating unnecessary behind-the-scenes complexity. People want to feel in control, especially when it comes to something important. We want to learn a bit about what’s happening, and an overly simple process teaches us nothing.

A third lesson is that products and services are only as good as what happens when they break. Handling a problem with something that has lots of controls on the user side may be easier for the user. They’re used to being involved in it. If something has been fully automated up until the point where it breaks, users don’t know how to react. The change is jarring, and they may freeze or overreact. Seeing as fully automated things fade into the background, this may be their most salient and memorable interaction with a product or service. If handling a problem is difficult for the user—for example, if there’s a lack of rapid support or instructions available or it’s hard to ascertain what went wrong in the first place—they may come away with a negative overall impression, even if everything worked fine for years beforehand.

A big challenge in the development of self-driving cars is that a driver needs to be able to take over if the car encounters a problem. But if someone hasn’t had to operate the car manually for a while, they may panic or forget what to do. So it’s a good idea to limit how long the car drives itself for. The same is purportedly true for airplane pilots. If the plane does too much of the work, the pilot won’t cope well in an emergency.

A fourth lesson is the importance of thinking about how the level of control you give your customers or users influences your workload. For a graphic designer, asking a client to detail exactly how they want their logo to look makes their work simpler. But it might be hard work for the client, who might not know what they want or may make poor choices. A more experienced designer might ask a client for much less information and instead put the effort into understanding their overall brand and deducing their needs from subtle clues, then figuring out the details themselves. The more autonomy a manager gives their team, the lower their workload, and vice versa.

If we accept that complexity is a constant, we need to always be mindful of who is bearing the burden of that complexity.

 

Unlikely Optimism: The Conjunctive Events Bias

When certain events need to take place to achieve a desired outcome, we’re overly optimistic that those events will happen. Here’s why we should temper those expectations.

***

Why are we so optimistic in our estimation of the cost and schedule of a project? Why are we so surprised when something inevitably goes wrong? If we want to get better at executing our plans successfully, we need to be aware of how the conjunctive events bias can throw us way off track.

We often overestimate the likelihood of conjunctive events—occurrences that must happen in conjunction with one another. The probability of a series of conjunctive events happening is lower than the probability of any individual event. This is often very hard for us to wrap our heads around. But if we don’t try, we risk seriously underestimating the time, money, and effort required to achieve our goals.

The Most Famous Bank Teller

In Thinking, Fast and Slow, Daniel Kahneman gives a now-classic example of the conjunctive events bias. Students at several major universities received a description of a woman. They were told that Linda is 31, single, intelligent, a philosophy major, and concerned with social justice. Students were then asked to estimate which of the following statements is most likely true:

  • Linda is a bank teller.
  • Linda is a bank teller and is active in the feminist movement.

The majority of students (85% to 95%) chose the latter statement, seeing the conjunctive events (that she is both a bank teller and a feminist activist) as more probable. Two events together seemed more likely that one event. It’s perfectly possible that Linda is a feminist bank teller. It’s just not more probable for her to be a feminist bank teller than it is for her to be a bank teller. After all, the first statement does not exclude the possibility of her being a feminist; it just does not mention it.

The logic underlying the Linda example can be summed up as follows: The extension rule in probability theory states that if B is a subset of A, B cannot be more probable than A. Likewise, the probability of A and B cannot be higher than the probability of A or B. Broader categories are always more probable than their subsets. It’s more likely a randomly selected person is a parent than it is that they are a father. It’s more likely someone has a pet than they have a cat. It’s more likely someone likes coffee than they like cappuccinos. And so on.

It’s not that we always think conjunctive events are more likely. If the second option in the Linda Problem was ‘Linda is a bank teller and likes to ski’, maybe we’d all pick just the bank teller option because we don’t have any information that makes either a good choice. The point here, is that given what we know about Linda, we think it’s likely she’s a feminist. Therefore, we are willing to add almost anything to the Linda package if it appears with ‘feminist’. This willingness to create a narrative with pieces that clearly don’t fit is the real danger of the conjunctive events bias.

“Plans are useless, but planning is indispensable.” 

— Dwight D. Eisenhower

Why the best laid plans often fail

The conjunctive events bias makes us underestimate the effort required to accomplish complex plans. Most plans don’t work out. Things almost always take longer than expected. There are always delays due to dependencies. As Max Bazerman and Don Moore explain in Judgment in Managerial Decision Making, “The overestimation of conjunctive events offers a powerful explanation for the problems that typically occur with projects that require multistage planning. Individuals, businesses, and governments frequently fall victim to the conjunctive events bias in terms of timing and budgets. Home remodeling, new product ventures, and public works projects seldom finish on time.”

Plans don’t work because completing a sequence of tasks requires a great deal of cooperation from multiple events. As a system becomes increasingly complex, the chance of failure increases. A plan can be thought of as a system. Thus, a change in one component will very likely have impacts on the functionality of other parts of the system. The more components you have, the more chances that something will go wrong in one of them, causing delays, setbacks, and fails in the rest of the system. Even if the chance of an individual component failing is slight, a large number of them will increase the probability of failure.

Imagine you’re building a house. Things start off well. The existing structure comes down on schedule. Construction continues and the framing goes up, and you are excited to see the progress. The contractor reassures you that all trades and materials are lined up and ready to go. What is more likely:

  • The building permits get delayed
  • The building permits get delayed and the electrical goes in on schedule

You know a bit about the electrical schedule. You know nothing about the permits. But you bucket them in optimistically, erroneously linking one with the other. So you don’t worry about the building permits and never imagine that their delay will impact the electrical. When the permits do get delayed you have to pay the electrician for the week he can’t work, and then have to wait for him to finish another job before he can resume yours.

Thus, the more steps involved in a plan, the greater the chance of failure, as we associate probabilities to events that aren’t at all related. That is especially true as more people get involved, bringing their individual biases and misconceptions of chance.

In Seeking Wisdom: From Darwin to Munger, Peter Bevelin writes:

A project is composed of a series of steps where all must be achieved for success. Each individual step has some probability of failure. We often underestimate the large number of things that may happen in the future or all opportunities for failure that may cause a project to go wrong. Humans make mistakes, equipment fails, technologies don’t work as planned, unrealistic expectations, biases including sunk cost-syndrome, inexperience, wrong incentives, changing requirements, random events, ignoring early warning signals are reasons for delays, cost overruns, and mistakes. Often we focus too much on the specific base project case and ignore what normally happens in similar situations (base rate frequency of outcomes—personal and others). Why should some project be any different from the long-term record of similar ones? George Bernard Shaw said: “We learn from history that man can never learn anything from history.”

The more independent steps that are involved in achieving a scenario, the more opportunities for failure and the less likely it is that the scenario will happen. We often underestimate the number of steps, people, and decisions involved.

We can’t pretend that knowing about conjunctive events bias will automatically stop us from having it. When, however, we are doing planning where a successful outcome is of importance to us, it’s useful to run through our assumptions with this bias in mind. Sometimes, assigning frequencies instead of probabilities can also show us where our assumptions might be leading us astray. In the housing example above, asking what is the frequency of having building permits delayed in every hundred houses, versus the frequency of having permits delayed and electrical going in on time for the same hundred demonstrates more easily the higher frequency of option one.

It also extremely useful to keep a decision journal for our major decisions, so that we can more realistic in our estimates on the time and resources we need for future plans. The more realistic we are, the higher our chances of accomplishing what we set out to do.

The conjunctive events bias teaches us to be more pessimistic about plans and to consider the worst-case scenario, not just the best. We may assume things will always run smoothly but disruption is the rule rather than the exception.

Habits vs. Goals: A Look at the Benefits of a Systematic Approach to Life

Nothing will change your future trajectory like your habits. We all have goals, big or small, things we want to achieve within a certain time frame. Some people want to make a million dollars by the time they turn 30. Some people want to lose 20 pounds before summer. Some people want to write a book in the next six months. When we begin to chase an intangible or vague concept (success, wealth, health, happiness), making a tangible goal is often the first step.

Habits are algorithms operating in the background that power our lives. Good habits help us reach our goals more effectively and efficiently. Bad ones makes things harder or prevent success entirely. Habits powerfully influence our automatic behavior.

“First forget inspiration.
Habit is more dependable.
Habit will sustain you whether you’re inspired or not.
Habit is persistence in practice.”

— Octavia Butler

The difference between habits and goals is not semantic. Each requires different forms of action. For example:

  • We want to learn a new language. We could decide we want to be fluent in six months (goal), or we could commit to 30 minutes of practice each day (habit).
  • We want to read more books. We could set the goal to read 50 books by the end of the year, or we could decide to always carry a book with us (habit).
  • We want to spend more time with our families. We could plan to spend seven hours a week with them (goal), or we could choose to eat dinner with them each night (habit).

The Problems With Goals

When we want to change an aspect of our lives, setting a goal is often the logical first step. Despite being touted by many a self-help guru, this approach has some problematic facets.

Goals have an endpoint. This is why many people revert to their previous state after achieving a certain goal. People run marathons, then stop exercising altogether afterward. Or they make a certain amount of money, then fall into debt soon after. Others reach a goal weight, only to spoil their progress by overeating to celebrate.

Goals rely on factors which we do not always have control over. It’s an unavoidable fact that reaching a goal is not always possible, regardless of effort. An injury might derail a fitness goal. An unexpected expense might sabotage a financial goal. A family tragedy might impede a creative-output goal. When we set a goal, we are attempting to transform what is usually a heuristic process into an algorithmic one.

Goals rely on willpower and self-discipline. As Charles Duhigg wrote in The Power of Habit:

Willpower isn’t just a skill. It’s a muscle, like the muscles in your arms or legs, and it gets tired as it works harder, so there’s less power left over for other things.

Keeping a goal in mind and using it to direct our actions requires constant willpower. During times when other parts of our lives deplete our supply of willpower, it can be easy to forget our goals. For example, the goal of saving money requires self-discipline each time we make a purchase. Meanwhile, the habit of putting $50 in a savings account every week requires little effort. Habits, not goals, make otherwise difficult things easy.

Goals can make us complacent or reckless. Studies have shown that people’s brains can confuse goal setting with achievement. This effect is more pronounced when people inform others of their goals. Furthermore, unrealistic goals can lead to dangerous or unethical behavior.

“Habit is the intersection of knowledge (what to do), skill (how to do), and desire (want to do).”

— Stephen Covey

The Benefits of Habits

Once formed, habits operate automatically. Habits take otherwise difficult tasks—like saving money—and make them easy.

The purpose of a well-crafted set of habits is to ensure that we reach our goals with incremental steps. The benefits of a systematic approach to achievement include the following:

Habits can mean we overshoot our goals. Let’s say a person’s goal is to write a novel. They decide to write 200 words a day, so it should take 250 days. Writing 200 words takes little effort, and even on the busiest, most stressful days, the person gets it done. However, on some days, that small step leads to their writing 1000 or more words. As a result, they finish the book in much less time. Yet setting “write a book in four months” as a goal would have been intimidating.

Habits are easy to complete. As Duhigg wrote,

Habits are powerful, but delicate. They can emerge outside our consciousness or can be deliberately designed. They often occur without our permission but can be reshaped by fiddling with their parts. They shape our lives far more than we realize—they are so strong, in fact, that they cause our brains to cling to them at the exclusion of all else, including common sense.”

Once we develop a habit, our brains actually change to make the behavior easier to complete. After about 30 days of practice, enacting a habit becomes easier than not doing so.

Habits are for life. Our lives are structured around habits, many of them barely noticeable. According to Duhigg’s research, habits make up 40% of our waking hours. These often minuscule actions add up to make us who we are. William James (a man who knew the problems caused by bad habits) summarized their importance as such:

All our life, so far as it has definite form, is but a mass of habits — practical, emotional, and intellectual — systematically organized for our weal or woe, and bearing us irresistibly toward our destiny, whatever the latter may be.

Once a habit becomes ingrained, it can last for life (unless broken for some reason).

Habits can compound. Stephen Covey paraphrased Gandhi when he explained:

Sow a thought, reap an action; sow an action, reap a habit; sow a habit, reap a character; sow a character, reap a destiny.

In other words, building a single habit can have a wider impact on our lives. Duhigg calls these keystone habits. These are behaviors that cause people to change related areas of their lives. For example, people who start exercising daily may end up eating better and drinking less. Likewise, those who quit a bad habit may end up replacing it with a positive alternative. (Naval and I talked about habit replacement a lot on this podcast episode.)

Habits can be as small as necessary. A common piece of advice for those seeking to build a habit is to start small. Stanford psychologist BJ Fogg recommends “tiny habits,” such as flossing one tooth. Once these become ingrained, the degree of complexity can be increased. If you want to read more, you can start with 25 pages a day. After this becomes part of your routine, you can increase the page count to reach your goal.

“First we make our habits, then our habits make us.”

— Charles C. Nobel

Why a Systematic Approach Works

By switching our focus from achieving specific goals to creating positive long-term habits, we can make continuous improvement a way of life. This is evident from the documented habits of many successful people.

Warren Buffett reads all day to build the knowledge necessary for his investments.

Stephen King writes 1000 words a day, 365 days a year (a habit he describes as “a sort of creative sleep”). Athlete Eliud Kipchoge makes notes after each training session to establish areas which can be improved. These habits, repeated hundreds of times over years, are not incidental. With consistency, the benefits of these non-negotiable actions compound and lead to extraordinary achievements.

While goals rely on extrinsic motivation, habits are automatic. They literally rewire our brains.

When seeking to attain something in our lives, we would do well to invest our time in forming positive habits, rather than concentrating on a specific goal.

For further reading on this topic, look at Drive: The Surprising Secret of What Motivates Us, How to Fail at Almost Everything and Still Win Big, and The Power of Habit.

Under One Roof: What Can we Learn from the Mayo Clinic?

The Mayo Clinic is one of the top-rated hospitals in the US and enjoys remarkable success. In this post, we consider the reasons for the Mayo Clinic’s success and what we can learn from it to apply to our own organizations.

***

The biologist Lewis Thomas, who we’ve written about before, has a wonderful thought on creating great organizations.

For Thomas, creating great science was not about command-and-control. It was about Getting the Air Right.

It cannot be prearranged in any precise way; the minds cannot be lined up in tidy rows and given directions from printed sheets. You cannot get it done by instructing each mind to make this or that piece, for central committees to fit with the pieces made by the other instructed minds. It does not work this way.

What it needs is for the air to be made right. If you want a bee to make honey, you do not issue protocols on solar navigation or carbohydrate chemistry, you put him together with other bees (and you’d better do this quickly, for solitary bees do not stay alive) and you do what you can to arrange the general environment around the hive. If the air is right, the science will come in its own season, like pure honey.

One organization which clearly “gets the air right” is the much lauded Mayo Clinic in Rochester, Minnesota.

The organization has 4,500 physicians and over $10 billion in revenue from three main campuses, and it is regularly rated among the top hospital systems in the United States in a wide variety of specialities, and yet was founded back in the late 20th century by William Worrall Mayo. Its main campus is in Rochester, Minnesota; not exactly a hub of bustling activity, yet its patients are willing to fly or drive hundreds of miles to receive care. (So-called “destination medicine.”)

How does an organization sustain that kind of momentum for more than 150 years, in an industry that’s changed as much as medicine? What can the rest of us learn from that?

It’s a prime example of where culture eats strategy. Even Warren Buffett admires the system:

A medical partnership led by your area’s premier brain surgeon may enjoy outsized and growing earnings, but that tells little about its future. The partnership’s moat will go when the surgeon goes. You can count, though, on the moat of the Mayo Clinic to endure, even though you can’t name its CEO.

Pulling the Same Oar

The Mayo Clinic is an integrated, multi-specialty organization — they’re known for doing almost every type of medicine at a world class level. And the point of having lots of specialities integrated under one roof is teamwork: Everyone is pulling the same oar. Integrating all specialities under one umbrella and giving them a common set of incentives focuses Mayo’s work on the needs of the patient, not the hospital or the doctor.

This extreme focus on patient needs and teamwork creates a unique environment that is not present in most healthcare systems, where one’s various care-takers often don’t know each other, fail to communicate, and even have trouble accessing past medical records. (Mayo is able to have one united electronic patient record system because of its deep integration.)

Importantly, they don’t just say they focus on integrated care, they do it. Everything is aligned in that direction. For example, as with Apple Retail stores (also known for extreme customer focus), there are no bonuses or incentive payments for physicians — only salaries.

An interesting book called Management Lessons from the Mayo Clinic (recommended by the great Sanjay Bakshi) details some of Mayo’s interesting culture:

The clinic ardently searches for team players in its hiring and then facilitates their collaboration through substantial investment in communications technology and facilities design. Further encouraging collaboration is an all-salary compensation system with no incentive payments based on the number of patients seen or procedures performed. A Mayo physician has no economic reason to hold onto patients rather than referring them to colleagues better suited to meet their needs. Nor does taking the time to assist a colleague result in lost personal income.

[…]

The most amazing thing of all about the Mayo clinic is the fact that hundreds of members of the most highly individualistic profession in the world could be induced to live and work together in a small town on the edge of nowhere and like it.

The Clinic was carefully constructed by self-selection over time: It’s a culture that attracts teamwork focused physicians and then executes on that promise.

One of the internists in the book is quoting as saying working at Mayo is like “working in an organism; you are not a single cell when you are out there practicing. As a generalists, I have access to the best minds on any topic, any disease or problem I come up with and they’re one phone call away.”

In that sense, part of the Mayo’s moat is simply a feedback loop of momentum: Give a group of high performers an amazing atmosphere in which to do their work, and eventually they will simply be attracted by each other. This can go on a long time.

Under One Roof

The other part of Mayo’s success — besides correct incentives, a correct system, and a feedback loop — is simply scale and critical mass. Mayo is like a Ford in its early days: They can do everything under one roof, with all of the specialities and sub-specialities covered. That allows them to deliver a very different experience, accelerating the patient care cycle due to extreme efficiency relative to a “fractured” system.

Craig Smoldt, chair of the department of facilities and support services in Rochester, makes the point that Mayo clinic can offer efficient care–the cornerstone of destination medicine–because it functions as one integrated organization. He notes the fact that everyone works under one roof, so to speak, and is on the payroll of the same organization, makes a huge difference. The critical mass of what we have here is another factor. Few healthcare organizations in the country have as many specialities and sub-specialities working together in one organization.” So Mayo Clinic patients come to one of three locations, and virtually all of their diagnoses and treatment can be delivered by that single organization in a short time.

Contrast that to the way care is delivered elsewhere, the fractured system that represents Mayo’s competitors. This is another factor in Mayo’s success — they’re up against a pretty uncompetitive lot:

Most U.S. healthcare is not delivered in organizations with a comparable degree of integrated operations. Rather than receiving care under one roof, a single patient’s doctors commonly work in offices scattered around a city. Clinical laboratories and imaging facilities may be either in the local hospital or at different locations. As a report by the Institute of Medicine and the National Academy of Engineering notes, “The increase in specialization in medicine has reinforced the cottage-industry structure of U.S. healthcare, helping to create a delivery system characterized by disconnected silos of function and specialization.

How does this normally work out in practice, at places that don’t work like Mayo? We’re probably all familiar with the process. The Institute of Medicine report referenced above continues:

“Suppose the patient has four medical problems. That means she would likely have at least five different doctors.” For instance, this patient could have (1) a primary care doctor providing regular examinations and treatments for general health, (2) an orthopedist who treats a severely arthritic knee, (3) a cardiologist who is monitoring the aortic valve in her heart that may need replacement soon, (4) a psychiatrist who is helping her manage depression, and (5) and endocrinologist who is helping her adjust her diabetes medications. Dr. Cortese then notes,”With the possible exception of the primary care physician, most of these doctors probably do not know that the patient is seeing the others. And even if they do know, it is highly unlikely they know the impressions and recommendations the other doctors have recorded in the medical record, or exactly what medications and dosages are prescribed.” If the patient is hospitalized, it is probably that only the admitting physician and the primary care physician will have that knowledge.

Coordinating all of these doctors takes time and energy on the part of the patient. Repeat, follow-up visits are done days later; often test results, MRI results, or x-ray results are not determined quickly or communicated effectively to the other parts of the chain.

Mayo solves that by doing everything efficiently and under one roof. The patient or his/her family doesn’t have to push to get efficient service. Take the case of a woman with fibrocystic breast disease who had recently found a lump. Her experience at Mayo took a few hours; the same experience in the past had taken multiple days elsewhere, and initiative on her end to speed things up.

As a patient in the breast clinic, she began with an internist/breast specialists who took the medical history and performed an exam. The mammogram followed in the nearby breast imaging center. The breast ultrasound, ordered to evaluate a specific area on the breast, was done immediately after the mammogram.

The breast radiologist who performed the ultrasound had all the medical history and impressions of the other doctors available in the electronic medical record (EMR). The ultrasound confirmed that the lump was a simple cyst, not a cancer. The radiologist shared this information with the patient and offered her an aspiration of the cyst that would draw off fluid if the cyst was painful. But comforted with the diagnosis of the simple cyst and with the fact that it was not painful, the veteran patient declined the aspiration. Within an hour of completing the breast imaging, the radiologist communicated to the breast specialist a “verbal report” of the imaging findings. The patient returned to the internist/breast specialist who then had a wrap-up visit with the patient and recommended follow-up care. This patient’s care at Mayo was completed in three and one-half hours–before lunch.

So what are some lessons we can pull together from studying Mayo?

The book offers a bunch, but one in particular seemed broadly useful, from a chapter describing Mayo’s “systems” approach to consistently improving the speed and level of care. (Industrial engineers are put to work fixing broken systems inside Mayo.)

Mayo wins by solving the totality of the customer’s problem, not part of it. This is the essence of an integrated system. While this wouldn’t work for all types of businesses; it’s probably a useful way for most “service” companies to think.

Why is this lesson particularly important? Because it leads to all the others. Innovation in patient care, efficiency in service delivery, continuous adoption of new technology, “Getting the Air Right” to attract and retain the best possible physicians, and creating a feedback loop are products of the “high level” thought process below: Solve the whole problem.

Lesson 1: Solve the customer’s total problem. Mayo Clinic is a “systems seller” competing with a connected, coordinated service. systems sellers market coordinated solutions to the totality of their customers’ problems; they offer whole solutions instead of partial solutions. In system selling, the marketer puts together all the services needed by customers to do it themselves. The Clinic uses systems thinking to execute systems selling that pleasantly surprises patients (and families) and exceeds their expectations.

The scheduling and service production systems at Mayo Clinic have created a differentiated product–destination medicine–that few competitors can approach. So even if patients feel that the doctors and hospitals at home are fine, they still place a high value on a service system that can deliver a product in days rather than weeks or months.

[…]

Patients not only require competent care but also coordinated and efficient care. Mayo excels in both areas. In a small Midwestern town, it created a medical city offering “systems solutions” that encourage favorable word of mouth and sustained brand strength, and then it exported the model to new campuses in Arizona and Florida.

At Some Point, You Have to Eat The Broccoli

It’s a wonderful idea to try to find a set of systems and principles that “work better” for big swaths of your life. Better habits, better mental tendencies, better methods of inquiry, and so on. We’re strong advocates of this approach, believing that good thinking and good decision making can be learned the same as a good golf swing can: Through practice and instruction.

So, read the below with this caveat in mind: Constant learning and self-improvement can and must be done for great life results.

Now, with that out of the way.

Progress Requires Effort

The problem with the search for self-improvement methods, including the kind of multidisciplinary thinking we espouse, is that many, perhaps most of them, are a snare and a delusion for most people. And there’s a simple reason why: They won’t actually do it.

Think about it. Isn’t that the most common result? That you don’t do it? For example, we heard from many people after we wrote a piece late last year on Reading 25 Pages a Day, a little practice that we think would benefit almost anyone in creating a very desirable reading habit.

What we suspect, though, is that even of the subset of people who felt so strongly about the idea that they contacted us, only a minority of them followed through and maintained to the habit to this day, ten months later.

The Failure to Implement Habits

Why is that? A huge part of it is Homeostasis: The basic self-regulating feedback loops that keep us repeating the same habits over and over. Predictable forces that keep us from changing ourselves, just as some forces keep us from changing organizations. (Or any self-regulating system.)

The failure to follow new systems and habits (mental or physical) follows this basic formula:

  1. A system is proposed which makes the adherent think that they can live life a healthy life “without eating any broccoli.” (Whether intended by the author or not.) You see this over and over: Money-making schemes, exercise-habit formation routines, 4-hour workweek promises, new cultural principles for businesses, and so on. Promises that lead people to think “healthy eating with no broccoli,” so to speak. An easy fix.
  2. Potential adherent to the “broccoli-free” system buys into the paradigm, and starts giving it a try.
  3. Potential adherent realizes very quickly that either (A) The broccoli must, indeed, be eaten, or (B) The system does not work.

Do the Work

Now, with regards to the 25-pages a day “system” we outlined, we were careful not to make a “no broccoli” promise: All we said was that reading 25 pages per day was a habit that almost anyone could form and that it would lead them far. But you still have to do all the reading. You have to actually do the thing. That’s the part where everyone falls away.

We suspect that some people thought it would be easy to read 25 pages per day. That the pages would essentially “read themselves,” or that the time to do so would spontaneously free up, just because they starting wanting it. This is never, ever the case. At some point, to be healthy, you do need to suck it up and eat some broccoli! And for many days in a row. Or, more to the point: The “failure point” with any new system; any method of improvement; any proposed solution to a life problem or an organization problem, is when the homeostatic regulation kicks in, when we realize some part of it will be hard, new, or unnatural.

Even a really well-designed system can only cut up the broccoli into little pieces and sneak it into your mac-and-cheese. A popular example would be a fitness system whereby you do one pushup a day, then two pushups on the second day, then three the third day, and so on. It makes the habit digestible at first, as you get used to it. This is plenty smart.

But eventually, if you’re going to hang on to that habit, you’ll have to do a whole lot of pushups every day! You can’t just go back to plain mac-and-cheese, no broccoli. When the newness of the “one day at a time” system wears off, you’ll be left with a heaping portion of broccoli. Will you continue eating it?

There is no free lunch. When you’re evaluating a proposed improvement to your life or to your organization, you must figure out when and where the broccoli will get eaten, and understand that you will have to sacrifice something (even if it’s just comfort) to get what you want. And if anyone ever promises you “no broccoli,” it’s a sham.

The willingness to pay the price is what separates people into two groups. On one hand, you have the people who want to want something and won’t do anything hard to get it. These people are passive — life is always happening to them … stuff is never perfect … there is always something getting in the way. Soon enough they’ll trade today’s want for a new one, momentarily distracting themselves from their lack of progress. But nothing will ever change for these people. They’ll never put in the work needed to make progress because they’re not willing to pay the price or they’re scared of failing. On the other hand, the second group is willing to do the work. They don’t make excuses. They don’t wait for perfection. They put their head down and get better every day. While they sometimes come up short, they get up and try again.

Which group do you think is more likely to succeed? Which group do you think is happier? Which group do you want to be a part of?

Remember that anything really worth doing is probably hard work, and will absolutely require you to do things you don’t currently do, which will feel uncomfortable for a while. This is a “hard truth” we must all face. If it was easy, everyone would already be doing it. 

***

Let’s take the example of learning how to give better feedback. What could be a more useful skill? But actually doing so, actually following through with the idea, is not at all easy. You have to overcome your natural impulse to criticize. You have to get over your natural ego. You have to be very careful to watch your words, trying to decipher what will be heard when you deliver feedback. All of these are hard things to do, all of them unnatural. All will require some re-doubling to accomplish.

Thus, most people won’t actually do it. This an Iron Rule of life: Biological systems tend towards what is comfortable. (Yes, human beings are “biological systems”.)

But this Iron Rule is a problem and an opportunity wrapped together. As the saying goes, “If you do what everyone else does, you’ll get what everyone else gets.” If you can recognize that all things worth doing are hard at first, and that there is always some broccoli to be eaten, you are part of the way toward true advantageous differentiation. The rest is self-discipline.

We “go back” on our habits when they aren’t truly formed yet. We think we’re there, but we’re really not — we’ve just been fooled by our sensory apparatus.

And the real and comforting truth is that you might really start liking, and even get used to eating, broccoli. Eating potato chips and candy will eventually feel like the uncomfortable and unnatural thing.

And that’s when you know you’ve really got a great new discipline: Going back would feel like cutting off your hands.

12