Tag: Systems

Efficiency is the Enemy

There’s a good chance most of the problems in your life and work come down to insufficient slack. Here’s how slack works and why you need more of it.

Imagine if you, as a budding productivity enthusiast, one day gained access to a time machine and decided to take a trip back several decades to the office of one of your old-timey business heroes. Let’s call him Tony.

You disguise yourself as a janitor and figure a few days of observation should be enough to reveal the secret of that CEO’s incredible productivity and shrewd decision-making. You want to learn the habits and methods that enabled him to transform an entire industry for good.

Arriving at the (no doubt smoke-filled) office, you’re a little surprised to find it’s far from a hive of activity. In fact, the people you can see around seem to be doing next to nothing. Outside your hero’s office, his secretary lounges at her desk (and let’s face it, the genders wouldn’t have been the other way around.) Let’s call her Gloria. She doesn’t appear busy at all. You observe for half an hour as she reads, tidies her desk, and chats with other secretaries who pass by. They don’t seem busy either. Confused as to why Tony would squander money on idle staff, you stick around for a few more hours.

With a bit more observation, you realize your initial impression was entirely wrong. Gloria does indeed do nothing much of the time. But every so often, a request, instruction, or alert comes from Tony and she leaps into action. Within minutes, she answers the call, sends the letter, reschedules the appointment, or finds the right document. Any time he has a problem, she solves it right away. There’s no to-do list, no submitting a ticket, no waiting for a reply to an email for either Tony or Gloria.

As a result, Tony’s day goes smoothly and efficiently. Every minute of his time goes on the most important part of his work—making decisions—and not on dealing with trivial inconveniences like waiting in line at the post office.

All that time Gloria spends doing nothing isn’t wasted time. It’s slack: excess capacity allowing for responsiveness and flexibility. The slack time is important because it means she never has a backlog of tasks to complete. She can always deal with anything new straight away. Gloria’s job is to ensure Tony is as busy as he needs to be. It’s not to be as busy as possible.

If you ever find yourself stressed, overwhelmed, sinking into stasis despite wanting to change, or frustrated when you can’t respond to new opportunities, you need more slack in your life.

In Slack: Getting Past Burnout, Busywork, and the Myth of Total Efficiency, Tom DeMarco explains that most people and organizations fail to recognize the value of slack. Although the book is now around twenty years old, its primary message is timeless and worth revisiting.

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The enemy of efficiency

“You’re efficient when you do something with minimum waste. And you’re effective when you’re doing the right something.”

Many organizations are obsessed with efficiency. They want to be sure every resource is utilized to its fullest capacity and everyone is sprinting around every minute of the day doing something. They hire expert consultants to sniff out the faintest whiff of waste.

As individuals, many of us are also obsessed with the mirage of total efficiency. We schedule every minute of our day, pride ourselves on forgoing breaks, and berate ourselves for the slightest moment of distraction. We view sleep, sickness, and burnout as unwelcome weaknesses and idolize those who never seem to succumb to them. This view, however, fails to recognize that efficiency and effectiveness are not the same thing.

Total efficiency is a myth. Let’s return to Gloria and Tony. Imagine if Tony decided to assign her more work to ensure she spends a full eight hours a day busy. Would that be more efficient? Not really. Slack time enables her to respond to his requests right away, thus being effective at her job. If Gloria is already occupied, Tony will have to wait and whatever he’s doing will get held up. Both of them would be less effective as a result.

Any time we eliminate slack, we create a build-up of work. DeMarco writes, “As a practical matter, it is impossible to keep everyone in the organization 100 percent busy unless we allow for some buffering at each employee’s desk. That means there is an inbox where work stacks up.

Many of us have come to expect work to involve no slack time because of the negative way we perceive it. In a world of manic efficiency, slack often comes across as laziness or a lack of initiative. Without slack time, however, we know we won’t be able to get through new tasks straight away, and if someone insists we should, we have to drop whatever we were previously doing. One way or another, something gets delayed. The increase in busyness may well be futile:

“It’s possible to make an organization more efficient without making it better. That’s what happens when you drive out slack. It’s also possible to make an organization a little less efficient and improve it enormously. In order to do that, you need to reintroduce enough slack to allow the organization to breathe, reinvent itself, and make necessary change.”

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Defining slack

DeMarco defines slack as “the degree of freedom required to effect change. Slack is the natural enemy of efficiency and efficiency is the natural enemy of slack.” Elsewhere, he writes: “Slack represents operational capacity sacrificed in the interests of long-term health.”

To illustrate the concept, DeMarco asks the reader to imagine one of those puzzle games consisting of eight numbered tiles in a box, with one empty space so you can slide them around one at a time. The objective is to shuffle the tiles into numerical order. That empty space is the equivalent of slack. If you remove it, the game is technically more efficient, but “something else is lost. Without the open space, there is no further possibility of moving tiles at all. The layout is optimal as it is, but if time proves otherwise, there is no way to change it.

Having a little bit of wiggle room allows us to respond to changing circumstances, to experiment, and to do things that might not work.

Slack consists of excess resources. It might be time, money, people on a job, or even expectations. Slack is vital because it prevents us from getting locked into our current state, unable to respond or adapt because we just don’t have the capacity.

Not having slack is taxing. Scarcity weighs on our minds and uses up energy that could go toward doing the task at hand better. It amplifies the impact of failures and unintended consequences.

Too much slack is bad because resources get wasted and people get bored. But, on the whole, an absence of slack is a problem far more often than an excess of it. If you give yourself too much slack time when scheduling a project that goes smoother than expected, you probably won’t spend the spare time sitting like a lemon. Maybe you’ll recuperate from an earlier project that took more effort than anticipated. Maybe you’ll tinker with some on-hold projects. Maybe you’ll be able to review why this one went well and derive lessons for the future. And maybe slack time is just your reward for doing a good job already! You deserve breathing room.

Slack also allows us to handle the inevitable shocks and surprises of life. If every hour in our schedules is accounted for, we can’t slow down to recover from a minor cold, shift a bit of focus to learning a new skill for a while, or absorb a couple of hours of technical difficulties.

In general, you need more slack than you expect. Unless you have a lot of practice, your estimations of how long things will take or how difficult they are will almost always be on the low end. Most of us treat best-case scenarios as if they are the most likely scenarios and will inevitably come to pass, but they rarely do.

You also need to keep a vigilant eye on how fast you use up your slack so you can replenish it in time. For example, you might want to review your calendar once per week to check it still has white space each day and you haven’t allowed meetings to fill up your slack time. Think of the forms of slack that are more important to you, then check up on them regularly. If you find you’re running out of slack, take action.

Once in a while, you might need to forgo slack to reap the benefits of constraints. Lacking slack in the short term or in a particular area can force you to be more inventive. If you find yourself struggling to come up with a creative solution, try consciously reducing your slack. For example, give yourself five-minutes to brainstorm ideas or ask yourself what you might do if your budget were slashed by 90%.

Most of the time, though, it’s critical to guard your slack with care. It’s best to assume you’ll always tend toward using it up—or other people will try to steal it from you. Set clear boundaries in your work and keep an eye on tasks that might inflate.

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Slack and change

In the past, people and organizations could sometimes get by without much slack—at least for a while. Now, even as slack keeps becoming more and more vital for survival, we’re keener than ever to eliminate it in the name of efficiency. Survival requires constant change and reinvention, which “require a commodity that is absent in our time as it has never been before. That commodity—the catalytic ingredient of change—is slack.” DeMarco goes on to write:

“Slack is the time when reinvention happens. It is time when you are not 100 percent busy doing the operational business of your firm. Slack is the time when you are 0 percent busy. Slack at all levels is necessary to make the organization work effectively and to grow. It is the lubricant of change. Good companies excel in creative use of slack. And bad ones only obsess about removing it.”

Only when we are 0 percent busy can we step back and look at the bigger picture of what we’re doing. Slack allows us to think ahead. To consider whether we’re on the right trajectory. To contemplate unseen problems. To mull over information. To decide if we’re making the right trade-offs. To do things that aren’t scalable or that might not have a chance to prove profitable for a while. To walk away from bad deals.

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Slack and productivity

The irony is that we achieve far more in the long run when we have slack. We are more productive when we don’t try to be productive all the time.

DeMarco explains that the amount of work each person in an organization has is never static: “Things change on a day-to-day basis. This results in new unevenness of the tasks, with some people incurring additional work (their buffers build up), while others become less loaded, since someone ahead of them in the work chain is slower to generate their particular kind of work to pass along.” An absence of slack is unsustainable. Inevitably, we end up needing additional resources, which have to come from somewhere.

Being comfortable with sometimes being 0 percent busy means we think about whether we’re doing the right thing. This is in contrast to grabbing the first task we see so no one thinks we’re lazy. The expectation of “constant busyness means efficiency” creates pressure to always look occupied and keep a buffer of work on hand. If we see our buffer shrinking and we want to keep busy, the only possible solution is to work slower.

Trying to eliminate slack causes work to expand. There’s never any free time because we always fill it.

Amos Tversky said the secret to doing good research is to always be a little underemployed; you waste years by not being able to waste hours. Those wasted hours are necessary to figure out if you’re headed in the right direction.

“Jootsing”: The Key to Creativity

Creativity can seem like a mysterious process. But many of the most creative people understand that you can actually break it down into a simple formula, involving what researcher Douglas Hofstadter calls “jootsing.” Here’s how understanding systems can help us think more creatively.

“Art is limitation; the essence of every picture is the frame. If you draw a giraffe, you must draw him with a long neck. If in your bold creative way you hold yourself free to draw a giraffe with a short neck, you will really find that you are not free to draw a giraffe.” —G.K. Chesterton

We can break the creative process down into the following three steps:

  1. Gain a deep understanding of a particular system and its rules.
  2. Step outside of that system and look for something surprising that subverts its rules.
  3. Use what you find as the basis for making something new and creative.

It may not be simple to do, but it is reliable and repeatable.

In Intuition Pumps and Other Tools for Thinking, philosopher Daniel C. Dennett describes this process of understanding a system in order to step outside of it as “jootsing,” using a term coined by Douglas Hofstadter. “Jootsing” means “jumping out of the system.”

Dennett explains that jootsing is the method behind creativity in science, philosophy, and the arts: “Creativity, that ardently sought but only rarely found virtue, often is a heretofore unimagined violation of the rules of the system from which it springs.” The rules within a system could be things like the idea that a painting must have a frame, a haiku must only have seventeen syllables, or a depiction of landscape must have a blue sky. But galleries hang paintings without frames all the time. Haiku without seventeen syllables win international contests. And landscape paintings don’t need to contain a sky, let alone a blue one.

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Creativity, as Dennett describes it, is not about pure novelty. The concept of jootsing shows us that constraints and restrictions are essential for creativity.

Breaking rules you don’t know exist is not a statement. It’s a common refrain that much of modern art could be the work of a five-year-old. Yet while a five-year-old could produce a random combination of elements that looks similar to a famous work of modern art, it would not be creative in the same way because the child would not be jootsing. They wouldn’t have an understanding of the system they now sought to subvert.

Limitations are essential because they give us a starting point and a shape to work against.

While amateurs may attempt to start from scratch when trying to make something creative in a new area, professionals know they must first get in touch with the existing territory. Before even contemplating their own work, they take the time to master the conventional ways of doing things, to know what the standards are, and to become well-versed in the types of work considered exemplary. Doing so can take years or even the best part of a career. Dennett summarizes: “It helps to know the tradition if you want to subvert it. That’s why so few dabblers or novices succeed in coming up with anything truly creative.”

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Understanding a system first is necessary for creativity for two reasons. First, it provides something comprehensible to use as a starting point, and second, it makes it possible to come up with something more interesting or useful. If you try to start a creative effort from nothing, you’ll end up with mere chaos.

Dennett writes: “Sit down at a piano and try to come up with a good new melody and you soon discover how hard it is. All the keys are available, in any combination you choose, but until you can find something to lean on, some style or genre or pattern to lay down and exploit a bit, or allude to, before you twist it, you will come up with nothing but noise.

Creativity often begins with accidents that end up showing a new possibility or reveal that violating a particular rule isn’t as harmful as expected. Elsewhere in the book, Dennett suggests that any computer model intended to generate creativity must include mistakes and randomness, “junk lying around that your creative process can bump into, noises that your creative process can’t help overhearing.

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Most of us say we want to be creative—and we want the people we work with and for to be creative. The concept of jootsing reveals why we often end up preventing that from happening. Creativity is impossible without in some way going against rules that exist for a good reason.

Psychologists Jacob Getzels and Phillip Jackson studied creativity in the 1950s. Their findings were repeated across many studies and described what was termed as the Getzels-Jackson effect: “The vast majority—98 percent—of teachers say creating is so important that it should be taught daily, but when tested, they nearly always favor less creative children over more creative children.”

Kevin Ashton, in How to Fly a Horse, explains why. Teachers favor less creative children “because people who are more creative also tend to be more playful, unconventional, and unpredictable, and all of this makes them harder to control. No matter how much we say we value creation, deep down, most of us value control more. And so we fear change and favor familiarity. Rejecting is a reflex.” Ashton notes that the Getzels-Jackson effect is also present in the organizations we are a part of in adulthood. When the same tests are applied to decision-makers and authority figures in business, science, and government, the results are the same: they all say they value creation, but it turns out they don’t value creators.

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If you want people to be creative, you can’t complain or punish them when they question a system that is “typically so entrenched that it is as invisible as the air you breathe,” as Dennett says. You need to permit a lot of exploration, including ideas that don’t work out. Not everything outside of a system proves worth pursuing. And often the rules that are most beneficial to break are those that seem the most load-bearing, as if meddling with them will cause the whole system to collapse. It might—or it might make it much better.

You also need to permit the making of mistakes if you want to foster creativity, because that often ends up leading to new discoveries. Dennett writes, “The exploitation of accidents is the key to creativity, whether what is being made is a new genome, a new behavior, or a new melody.” Most accidents never end up being profitable or valuable in a measurable way. But they’re necessary because they’re part of the process of developing something new. Accidents fuel creativity.

In the book Loonshots, Safi Bahcall explores, among other ideas, how to nurture and develop those seemingly crazy ideas that turn out to be paradigm-shifting innovations. He gives many examples of now ubiquitous technologies that were initially laughed at, rejected, or buried. He notes that it’s not easy to immediately buy in to radical developments, and if we want to have environments where creating is possible, then we have to give creativity space and understanding. “It’s worth keeping in mind,” he says, “that revving the creative engine to fire at higher speeds . . . means more ideas and more experiments, which also means, inevitably, more failed experiments.

As individuals, if we want to be creative, we need to give ourselves space to play and experiment without a set agenda. Amos Tversky famously said that the secret to doing good work is being a little unemployed so you always have hours in the day to waste as you wish. During that wasted time, you’ll likely have your best, most creative ideas.

If your schedule is crammed with only room for what’s productive in an obvious way, you’ll have a hard time seeing outside of the existing system.

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.

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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.

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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.

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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.

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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.

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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.

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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? ”

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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.

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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.

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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. Maybe you want to make a million dollars by the time you turn 30. Or to lose 20 pounds before summer. Or to write a book in the next six months. When we begin to chase a 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:

Let’s say you want to read more books. You could set the goal to read 50 books by the end of the year, or you could create a habit and decide to always carry a book with you.

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The problems with goals

Let’s go over the problems with only having goals.

First off, 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. 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.

Habits avoid these pitfalls because they continue indefinitely.

Second, goals rely on factors that 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. And family issues might impede a creative-output goal.

When we set a goal, we’re attempting to transform what is usually a heuristic process into an algorithmic one. Habits are better algorithms, and therefore more reliable in terms of getting us to where we want to go.

The third problem with goals is keeping a goal in mind and using it to direct our actions requires a lot of thinking and effort to evaluate different options.

Presented with a new situation, we have to figure out the course of action best suited to achieving a goal. With habits, we already know what to do by default.

During times when other parts of our lives require additional attention, it can be easy to push off attaining our goals to another day. 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 less effort as a practical action.

Habits, not goals, make otherwise difficult things easy.

Finally, goals can make us complacent or reckless.

Sometimes our brains can confuse goal setting with achievement because setting the goal feels like an end in itself. This effect is more pronounced when people inform others of their goals. Furthermore, unrealistic goals can lead to dangerous or unethical behavior because we make compromises to meet our stated objective.

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

— Stephen Covey

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The benefits of habits

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

The purpose of a well-crafted set of habits is to ensure that we reach our goals with incremental steps.

As the saying goes, the way to eat an elephant is one bite at a time. The benefits of a systematic approach to life include:

Habits can mean we overshoot our goals.

Consider a person who has the goal to write a novel. They decide to write 500 words a day, so it should take 200 days. Writing 500 words generally doesn’t require an enormous amount of effort assuming interest in and knowledge of the topic, and even on the busiest, most stressful days, the person gets it done. However, on some days, that smaller step leads to their writing 1000 or more words. As a result, they finish the book in much less time.

On the contrary, setting “write a book in four months” as a goal would have been intimidating on final word count alone.

Habits are easy to complete.

As Charles Duhigg wrote in The Power of Habit,

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 for a simple action like drinking water first thing in the morning, enacting a habit becomes easier than not doing so. More complex habits take longer to form, but they can still become automatic.

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 and takes a lot of work to break.

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 alcohol. Basically, those who quit a bad habit may end up replacing it with a positive alternative. (Listen to Naval Ravikant riff on 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.  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. Once your small habits become ingrained, the degree of complexity can be increased.

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

— Charles C. Nobel

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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. Even if we backtrack sometimes, we’re pointed in the right direction.

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

Stephen King writes 1000 words a day, 365 days a year (a habit he describes as “a sort of creative sleep”). Olympic 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 non-negotiable actions compound and lead to extraordinary achievements.

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

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

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