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Information Without Context

Information without context is falsely empowering and incredibly dangerous.

As an adult, have you ever picked up a child’s shape-sorter and tried to put the square item through the round hole? Of course not. Adults know better — or at least we’re supposed to. Yet we often take square solutions and cram them into round problems.

Consider, for example, a project that falls behind schedule. A project manager is apt to adopt whatever solution worked the last time a project was falling behind schedule. If more people were added last time and that produced a successful outcome why not do it again? Our tendency to stick with what has worked in the past, regardless of why it worked, creates a powerful illusion that we are solving the problem or doing the right thing.

When posed a difficult question by an informed reporter, politicians often answer something related but simpler. The politician treats what should be a complex topic as something black and white and portrays the topic as simpler than it really is (reductive bias). In the corporate world we do the same thing when we take something that worked previously (or somewhere else) and blindly apply it to the next problem without giving due consideration to why it worked.

Maybe we’re just becoming an intellectually lazy society constantly looking for then next soundbite from “experts” on how to do something better.  We like the easy solution.

In Think Twice, Michael Mauboussin writes: “Consultants, researchers, and practitioners often observe some success, seek common attributes among them and proclaim that those attributes can lead others to succeed. This simply does not work.”

Our brains may be adult, yet we demonstrate a very childlike level of consideration. Decision makers often fail to ask key questions, such as: What’s different about this project? Under which circumstances is adding more people likely to work? and, Am I doing this because someone else is doing it?

Adopting best practices has become the reason to do something in and of itself.  It is, after all, hard to challenge logic of best practices. But what do best practices mean? Whom are they best for? What makes them successful? Can we replicate them in our company? Culture? Circumstance? Do we have the necessary skills? What are the side effects? What are the incentives? … More often than not, we embrace a solution without understanding under which conditions it succeeds or fails.

I think there are some parallels between business decision making and medicine. In Medicine our understanding of the particulars can never be complete: misdiagnosing a patient is common so doctors look at each patient as a new mystery.

A doctor, applying the same thoughtlessness spewed by management consultants might, reasonably, determine that all people with a fever have a cold. However, we know people are more complex than this simple correlation. Medical practitioners know the difference between correlation and cause. A fever by itself tells the doctor something but not everything. It could indicate a cold and it could be something more serious. Doctors, like good decision makers, check the context and seek out information that might disprove their diagnosis.

Free Radicals: Don’t Follow your Passion, Cultivate it

“Luck is what happens when preparation meets opportunity.”
— Seneca

***

We’ve entered a new phase of self-invention.

Thanks in large part to technology and the pace of the modern world, finding your way through the labyrinth is more difficult than ever.

Maximize Your Potential: Grow Your Expertise, Take Bold Risks & Build an Incredible Career, edited by Behance’s 99U editor-in-chief Jocelyn Glei, and featuring contributions from over twenty of today’s creative minds, explores the timeless skills—generating opportunities, building relationships, and taking risks—that can help you navigate today’s changing landscape.

In the foreword to the book, Behance founder Scott Belsky, author Making Ideas Happen, explains the concept of free radicals.

Chalk it up to new technology, social media, or the once out-of-reach business tools now at your fingertips. The fact is, we’re empowered to work on our own terms and do more with less. As a result, we expect more from those that employ us and we expect more from ourselves. When we get the resources and opportunities we deserve, we create the future.

Here’s a name for us: Free Radicals.

Free Radicals want to take their careers into their own hands and put the world to work for them. Free Radicals are resilient, self-reliant, and extremely potent. You’ll find them working solo, in small teams, or within large companies. As the world changes, Free Radicals have re-imagined “work” as we know it. No doubt, we have lofty expectations:

We do work that is, first and foremost, intrinsically rewarding. But, we don’t create solely for ourselves, we want to make a real and lasting impact in the world around us.

We thrive on flexibility and are most productive when we feel fully engaged. We demand freedom, whether we work within companies or on our own, to run experiments, participate in multiple projects at once, and move our ideas forward.

We make stuff often, and therefore, we fail often. Ultimately, we strive for little failures that help us course-correct along the way, and we view every failure as a learning opportunity, part of our experiential education.

We have little tolerance for the friction of bureaucracy, old-boy networks, and antiquated business practices. As often as possible, we question “standard operating procedure” and assert ourselves. But even when we can’t, we don’t surrender to the friction of the status quo. Instead, we find clever ways (and hacks) around it.

We expect to be fully utilized and constantly optimized, regardless of whether we’re working in a start-up or a large organization. When our contributions and learning plateau, we leave. But when we’re leveraging a large company’s resources to make an impact in something we care about, we are thrilled! We want to always be doing our best work and making the greatest impact we can.

We believe that “networking” is sharing. People listen to (and follow) us because of our discernment and curatorial instinct. As we share our creations as well as what fascinates us, we authentically build a community of supporters who give us feedback, encouragement, and lead us to new opportunities. For this reason and more, we often (though, not always) opt for transparency over privacy.

We believe in meritocracy and the power of online networks and peer communities to advance our ability to do what we love, and do well by doing it. We view competition as a positive motivator rather than a threat, because we want the best idea—and the best execution—to triumph.

We make a great living doing what we love. We consider ourselves to be both artisans and businesses. In many cases, we are our own accounting department, Madison Avenue marketing agency, business development manager, negotiator, and salesperson. We spend the necessary energy to invest in ourselves as businesses—leveraging the best tools and knowledge (most of which are free and online) to run ourselves as a modern-day enterprise.

One of the best insights in the book revolves around cultivating passion. We’re told from a very young age to follow our passion. Cal Newport, the author of How to Become a Straight-A Student: The Unconventional Strategies Real College Students Use to Score High While Studying Less, points out the flaw in this wisdom.

This pattern is common in the lives of people who end up loving their work. As described in Lesson 1, careers become compelling once they feature the general traits you seek. These traits, however, are rare and valuable—no one will hand you a lot of autonomy or impact just because you really want it, for example. Basic economics tells us that if you want something rare and valuable, you need to offer something rare and valuable in return—and in the working world, what you have to offer are your skills. This is why the systematic development of skill almost always precedes passion.

In other words, Newport argues that what you do for a living matters less than you think.

“[T]he right question is not “What job am I passionate about doing?” but instead, “What way of working and living will nurture my passion.”

Stepping back, he writes:

The goal of feeling passionate about your work is sound. But following your passion—choosing a career path solely because you are already passionate about the nature of the work—is a poor strategy for accomplishing this goal. It assumes that you have a pre-existing passion to follow that matches up to a viable career, and that matching your work to a strong interest is sufficient to build long-term career satisfaction. Both of these assumptions are flawed.

Newport argues a more sophisticated strategy for finding passion means “we should begin by developing rare and valuable skills.” Once we’ve done that, we can use these skills to navigate our career towards the general lifestyle that resonates with us.

In a section on reprogramming your daily habits, Scott Young speaks to how automatic many of our decisions become and how routines drive our lives.

If you think hard about it, you’ll notice just how many “automatic” decisions you make each day. But these habits aren’t always as trivial as what you eat for breakfast. Your health, your productivity, and the growth of your career are all shaped by the things you do each day — most by habit, not by choice.

Even the choices you do make consciously are heavily influenced by automatic patterns. Researchers have found that our conscious mind is better understood as an explainer of our actions, not the cause of them. Instead of triggering the action itself, our consciousness tries to explain why we took the action after the fact, with varying degrees of success. This means that even the choices we do appear to make intentionally are at least somewhat influenced by unconscious patterns.

Given this, what you do every day is best seen as an iceberg, with a small fraction of conscious decision sitting atop a much larger foundation of habits and behaviors.

Maximize Your Potential: Grow Your Expertise, Take Bold Risks & Build an Incredible Career explores how creating opportunities, building expertise, cultivating relationships, and taking risks can propel you forward. With contributions from Tony Schwartz to Ben Casnocha, you’ll be left thinking about the next opportunity and how to get there. (Best served with a side of its prequel: Manage Your Day-to-Day.)

Becoming Wise: An Inquiry Into the Art of Living

“I am a person who listens for a living. I listen for wisdom, and beauty, and for voices not shouting to be heard.”

***

Krista Tippett, the host of the compelling podcast On Being, is an incredible conversationalist. From poets and physicists to neuroscientists — her show offers conversations that traverse time and disciplines. At the heart of her inquiry lies space to explore what it means to live a meaningful life.

In Becoming Wise: An Inquiry into the Mystery and Art of Living, Tippett, who listens for a living, offers an illuminating slice of these conversations. As a illuminating guide, her reflections walk us through the work of a lifetime exploring love, compassion, and forgiveness.

The book is organized around virtue and “gentle shifts of mind and habit.” She explores five raw materials for living a meaningful life:

Words — The language we use to tell stories to ourselves and others;
Body — “The body is where every virtue lives or dies”;
Love — More than something we fall into or out of, love is “the only aspiration big enough for the immensity of the human community.”;
Faith — “Literal reality is not all there is.”;
Hope — Hope has nothing to do with optimism or wishing, rather it reflects reality and reveres truth. Hope is a habit.

Tippet resurfaces questions many have explored before us. “What does it mean to be human? What matters in life? What matters in death? How to be of service to each other and the world?”

Each person explores these questions at one point or another in the context of our age and ourselves. The questions are not independent. Who we are to each other is a reflection of what it means to be human.

Wisdom leavens intelligence, and ennobles consciousness, and advances evolution itself.

Life is where we explore the mystery of ourselves and others. Here Tippett offers a voice to “those raw, essential, heartbreaking and life-giving places in us, so that we may know them more consciously, live what they teach us, and mine their wisdom for our life together.”

In the introduction Tippett refuses the false duality and headlines that drive so much of our divide.

[M]any features of national public life are also better suited to adolescence than to adulthood. We don’t do things adults learn to do, like calm ourselves, and become less narcissistic. Much of politics and media sends us in the opposite, infantilizing direction. We reduce great questions of meaning and morality to “issues” and simplify them to two sides, allowing pundits and partisans to frame them in irreconcilable extremes. But most of us don’t see the world this way, and it’s not the way the world actually works. I’m not sure there’s such a thing as the cultural “center,” or that it’s very interesting if it exists. But left of center and right of center, in the expansive middle and heart of our life together, most of us have some questions left alongside our answers, some curiosity alongside our convictions.

Imagination and nuance and the spaces between headlines is where we live. The book is an exploration of these spaces.

I have yet to meet a wise person who doesn’t know how to find some joy even in the midst of what is hard, and to smile and laugh easily, including at oneself. A sense of humor is high on my list of virtues, in interplay with humility and compassion and a capacity to change when that is the right thing to do. It’s one of those virtues that softens us for all the others.

She also offers a sobering reminder of our capacity to control.

We are never really running the show, never really in control, and nothing will go quite as we imagined it. Our highest ambitions will be off, but so will our worst prognostications.

No section of the book is more compelling than exploring words — “I take it as an elemental truth of life,” she writes, “that words matter.”

This is so plain that we can ignore it a thousand times a day. The words we use shape how we understand ourselves, how we interpret the world, how we treat others. From Genesis to the aboriginal songlines of Australia, human beings have forever perceived that naming brings the essence of things into being. The ancient rabbis understood books, texts, the very letters of certain words as living, breathing entities. Words make worlds.

On our affinity for tolerance she challenges us:

We chose too small a word in the decade of my birth— tolerance— to make the world we want to live in now. We opened to the racial difference that had been there all along, separate but equal, and to a new infusion of religions, ethnicities, and values. But tolerance doesn’t welcome. It allows, endures, indulges. In the medical lexicon, it is about the limits of thriving in an unfavorable environment. Tolerance was a baby step to make pluralism possible, and pluralism, like every ism, holds an illusion of control. It doesn’t ask us to care for the stranger. It doesn’t even invite us to know each other, to be curious, to be open to be moved or surprised by each other.

Words are containers.

The connection between words and meanings resembles the symbiosis between religion and spirituality. Words are crafted by human beings, wielded by human beings. They take on all of our flaws and frailties. They diminish or embolden the truths they arose to carry. We drop and break them sometimes. We renew them, again and again.

In one illuminating conversation, Tippett talks with one of her favorite thinkers about the failure of “official language and discourse” the poet Elizabeth Alexander, who read at the first Obama inauguration.

Alexander offers:

Here’s what we crave. We crave truth tellers. We crave real truth. There is so much baloney all the time. You know, the performance of political speech, of speeches you see on the news, doesn’t it often feel to you like there should be a thought bubble over it that says, “what I really would say if I could say it is . . .”

And how we are drawn to words that shimmer.

I learn so much every day from being a mother. My sons are 11 and 12, and you see the way children know when they’re being bamboozled. And they also are drawn towards language that shimmers, individual words with power. They will stop you and ask you to repeat a shimmering word if they’re hearing it for the first time. You can see it in their faces.

Words are the backbones to stories — the ones we tell others and the ones we tell ourselves.

The art of conversation I’m describing here is related, but it is something subtly and directionally different— sharing our stories in the service of probing together who we are and who we want to be. To me, every great story opens into an equally galvanizing exchange we can have together: So what? How does this change the way you see and live? How might it inform the way I see and live? I believe we can push ourselves further, and use words more powerfully and tell and make the story of our time anew.

“The world,” says physician Rachel Naomi Remen in an interview with Tippett, “is made up stories; it is not made of up facts.”

And yet we tell ourselves facts to piece together stories. Stories are how we make sense of life. Remen continues:

Well, the facts are the bones of the story, if you want to think of it that way. I mean, the facts are, for example, that I have had Crohn’s disease for 52 years. I’ve had eight major surgeries. But that doesn’t tell you about my journey and what’s happened to me because of that, and what it means to live with an illness like this and discover the power of being a human being. And whenever there’s a crisis, like 9/ 11, do you notice how the whole of the United States turned towards the stories? Where I was, what happened, what happened in those buildings, what happened to the people who were connected to the people in those buildings. Because that is the only way we can make sense out of life, through the stories. The facts are a certain number of people died there. The stories are about the greatness of being a human being and the vulnerability of being a human being.

[…]

There’s a powerful saying that sometimes we need a story more than food in order to live. They tell us about who we are, what is possible for us, what we might call upon. They also remind us we’re not alone with whatever faces us.

Becoming Wise is for those of us who want to explore the great questions of life with imagination and courage, realizing that much of life is lived in nuance that changes with who we are and, importantly, where we are standing.

Smarter, Not Harder: How to Succeed at Work

We each have 96 energy blocks each day to spend however we’d like. Using this energy blocking system will ensure you’re spending each block wisely to make the most progress on your most important goals.

Warren Buffett “ruled out paying attention to almost anything but business—art, literature, science, travel, architecture—so that he could focus on his passion,” wrote Alice Schroder in her book The Snowball. This isn’t unique to Warren Buffett. Almost all of the successful people I know follow a similar approach to focusing their efforts.

The key to better outcomes is not working harder. Most of us already work long hours. We take work home, we’re always on, we tackle anything we’re asked to do, and we do it to the best of our ability. It doesn’t seem to matter how many things we check off our to-do lists or how many hours we work, though; our performance doesn’t seem to improve. Better outcomes come from applying your energy in a particular direction.

While we like to think of exceptionally successful people as being more talented than we are, the more I looked around, the more I discovered that was rarely the case. One of the reasons we think that talent is the explanation is that it gives us a pass. We’re not as talented as those super-successful people are, so of course we don’t have the same results they have. The problem with this explanation is that it’s wrong. Talent matters, of course, but not as much as you think.

The most successful people I know have one thing in common: they are masters at eliminating the unnecessary from their lives. The French writer Antoine de Saint-Exupéry hit on the same idea, writing in his memoir, “Perfection is finally attained not when there is no longer anything to add, but when there is no longer anything to take away.” This principle, it turns out, is the key to success.

Incredibly successful people focus their time on just a few priorities and obsess over doing things right. This is simple but not easy.

Here’s one method to help you choose what to focus on and how to use your time (it’s a mix of time blocking and a variation of Warren Buffet’s two-list system):

Step 1: Change how you think about your day. Think of your day as having 96 blocks of energy, with each block being a 15-minute chunk of time (four blocks per hour × 24 hours = 96). A week has 672 blocks, and a year has 34,944.

Not all of those blocks are direct productivity blocks — they can’t be unless we’re androids. Given that we’re human, we need to allocate some blocks to activities that humans require for good health, like sleeping. Sleeping for eight hours uses 32 blocks of your 96-block day. Let’s say that another 32 blocks go toward family, friends, commuting, and general life stuff. That leaves 32 blocks for you to apply your energy toward keeping your job and doing something amazing.

Think you can get more done by sleeping less? Think again. Sleep has a way of affecting your other blocks. If you get enough sleep, the other 64 blocks are amplified. If you don’t get enough, their efficacy is reduced. Almost every successful person I know makes sleep a priority. Some go as far as getting ChiliPads to regulate their bed’s temperature and going to bed at exactly the same time every night; others use the same wind-down routine every night. Almost all of them go to bed early (or least before 12), and wake up early to get a start on the day.

Step 2: Write a list of all the goals you have. When I did this, I stopped at 100 and I could have kept going. I would venture to guess that if you sat alone for half an hour, you’d come up with just as many. Writing them down not only frees up your mind from keeping track of them but also gives you a visual representation of just how many things you want to do.

Step 3: Circle your top three goals. Take your time; there’s no need to rush. It’s hard to narrow them down, which is why so few of us think about these things consciously.

Step 4: Eliminate everything else. This is where things get interesting. When it comes to the 32 blocks of work time you have to allocate, everything that’s not on your top-three list should be dropped. You can pick up the “everything-else” list after you’ve achieved a goal, but until then it’s what Warren Buffet calls your “avoid-at-all-costs” list.

The Power of Focus

Let’s look at an example. Say we’re working on 10 projects. We have priorities that we try to focus on, but we also give the other projects a decent effort. Let’s say we allocate our 32 blocks of energy to our 10 projects as follows:

1. 10
2. 5
3. 5
4. 3
5. 2
6. 2
7. 2
8. 1
9. 1
10. 1

Not bad, eh? But if we do the above exercise, it will look more like this:

1. 16
2. 8
3. 8

Focus directs your energy toward your goals. The more focused you are, the more energy goes toward what you’re working on.

Eliminating things that you care about is hard. You have to make tradeoffs. If you can’t make those tradeoffs, you’re not going to get far. The cost of not being focused is high.

The direction you’re going in is important to the extent that you’re applying energy to it. If you’re focusing your energy on 10 goals, you’re not focused, and instead of having a few completed projects, you have numerous unfinished projects. Like Sisyphus, you’re constantly getting halfway up the mountain but never reaching the top. I can’t think of a bigger waste of time.

It’s not about working harder to get better results. You have only so much energy to apply. Pick what matters. Eliminate the rest.

FS Members can discuss this article on the Learning Community Forum.

The Secret Ingredient for Success: The Brutal Discipline Necessary for Self-Assessment

Camille Sweeney and Josh Gosfield, authors of The Art of Doing: How Superachievers Do What They Do and How They Do It So Well, came out with an op-ed in the New York Times.

The interesting argument, one that is echoed by Charles Darwin, is that the to success is a brutal self-assessment.

“Discipline is the attitude that helps us discern right from wrong … Discipline is what makes us responsible toward ourselves [and] toward the society in which we live.”

— Massimo Vignelli

What happens to organizations and people when they find obstacles in their paths?

Professor Argyris called the most common response single loop learning — an insular mental process in which we consider possible external or technical reasons for obstacles.

LESS common but vastly more effective is the cognitive approach that Professor Argyris called double-loop learning. In this mode we — like Mr. Chang — question every aspect of our approach, including our methodology, biases and deeply held assumptions. This more psychologically nuanced self-examination requires that we honestly challenge our beliefs and summon the courage to act on that information, which may lead to fresh ways of thinking about our lives and our goals.

In interviews we did with high achievers… we expected to hear that talent, persistence, dedication and luck played crucial roles in their success. Surprisingly, however, self-awareness played an equally strong role.

The successful people we spoke with — in business, entertainment, sports and the arts — all had similar responses when faced with obstacles: they subjected themselves to fairly merciless self-examination that prompted reinvention of their goals and the methods by which they endeavoured to achieve them.

In part, an accurate self-assessment allows for the feedback necessary to grow. It’s the evidence you need to move forward. It doesn’t matter if it comes from nobodies or somebodies, a coach or anyone else, which is precisely the point of being open to what others have to say if you are really interested in improving your own skills.

The discipline of self-assessment is only the start. It produces knowledge that allows us to understand the edge of our competency, which is the key to learning. What you do with that knowledge matters and there is a difference between the good and the great.

Average performers believe their errors are caused by things they don’t controla fixed mindset if there ever was one. Top performers, however, as Geoff Colvin writes in is book, Talent is Overrated, “believe they are responsible for their errors.”

Note that this is not just a difference of personality or attitude. Recall that the best performers have set highly specific, technique-based goals and strategies for themselves; they have though through exactly how they intend to achieve what they want. So when something doesn’t work, they can relate the failure to specific elements of their performance that may have misfired. (more)

It’s precisely the combination of a brutal self-assessment and a growth mindset that tilts that increases the odds we become better. And these skills come down to discipline.

As Anna Deavere Smith wrote in Letters to a Young Artist: Straight-up Advice on Making a Life in the Arts for Actors, Performers, Writers, and Artists of Every Kind,

Discipline — both mental and physical — is crucial.

 

Habit Stacking: 17 Small Productivity Habits

“The goal of a mini-habit is to be consistent. In fact, consistency is much more important than what you accomplish with this daily habit.”

The Mini-Habit

The idea behind mini habits is that you can get to a larger habit if you start small, create simple goals, and aim for consistency.

In his book Mini Habits: Small Habits, Bigger Results, Stephen Guise gives the example of “The One Pushup Challenge.”

He was doing what a lot of us do. Feeling guilty about not working out, he tried to fit years’ worth of exercise into the first workout which created an all or nothing attitude (not to mention a focus on goals and not process.) Well, one day he decided to do the opposite. He did only one pushup.

This allowed him to check the box that he did his activity. Only he didn’t stop at one, he did 14 more. Then he did one pull-up and guess what? He didn’t stop at one. His workout went on like this and when he was done it was a pretty decent effort. It started with one pushup.

In Habit Stacking: 97 Small Life Changes That Take Five Minutes or Less, author S. J. Scott writes:

The core idea behind the mini-habits concept is that you can build a major habit by thinking small enough to get started. Most people don’t need motivation to do one pushup, so it’s easy to get started. And once you get going, you’ll find it’s easy to keep at it.

Habit-Stacking

The purpose of habit-stacking is to create simple and repeatable routines (managed by a checklist). The goal is to get this out of the cognitive load, “because all you have to remember to do is follow the checklist,” and not each individual habit. You do this by doing the same set of actions in the same order and way each day. Checklists, do more than simply tell you what you need to do next, they help you deal with complexity and increase productivity.

“Linking habits together is a way of getting more done in less time, resulting in a positive change in your life. As you perform the stacked actions every day, they become part of your daily routine.”

 

According to Scott there are 8 Elements of a habit-stacking routine.

  1. Each habit takes less than five minutes to complete.
  2. It’s a complete habit.
  3. It improves your life.
  4. It’s simple to complete.
  5. The entire routine takes less than 30 minutes.
  6. It follows a logical process.
  7. It follows a checklist.
  8. It fits your life.

17 Small Productivity Habits

All of these habits are from Scott’s Habit Stacking: 97 Small Life Changes That Take Five Minutes or Less.

I don’t agree with all of them; Most of these seem like common sense.

Scott argues that if you add them to a routine, “you’ll see a dramatic improvement in both the quantity and the quality of your efforts.” I think a lot of that improvement will be from simply bringing awareness to how you spend your time and what you’re doing.

#1 Drink a Large Glass of Water

Even mild dehydration can cause headaches and fatigue, affect your concentration, impair short-term memory and impede mental function. If you want to be at your most productive , it’s important for your brain to be firing on all cylinders. Therefore, you should make sure you are sufficiently hydrated before starting work.

#2. Schedule Your Day and Prioritize Your Tasks

Without at least a basic schedule, it’s frighteningly easy to get to the end of the day and realize you’ve achieved nothing of importance. At the very least, you should make a list of the tasks you want to accomplish during the day and decide where your priorities lie.

If you’re lost on how to make this change or what it looks like, let Peter Bregman explain.

#3. Focus on Your Three Most Important Tasks

Another way to plan out your day is to focus on your Most Important Tasks (MITs). With a daily schedule, it’s easy to try to do too much. Then, when you get to the end of the day and haven’t completed everything, you feel like a failure . Picking your MITs each day gives you something to focus on so you don’t waste your day on tasks of low importance. If you manage to complete your MITs, you’ll feel productive— even if you do nothing else on your list.

#4. Turn Tasks into Manageable Steps

For each task on your schedule, consider how it can be broken down into smaller steps.

#5. Create Accountability by Telling Others

If your tasks don’t have accountability built into them (like a client deadline), creating accountability by letting others know your intentions is a great way to discipline yourself into staying on task. You won’t want to embarrass yourself by admitting you didn’t get any work done, so you’re much more likely to achieve your goals if you make them public.

#6. Reward Yourself for Task Completion

To keep your energy up and motivation high, alternate your work tasks with small treats. These treats not only act as a break to replenish depleted levels of concentration, but also work like a carrot on a stick— you’ll work faster and with more enthusiasm when you have something to look forward to at the end of it.

#7. Remove Distractions Before Working

Rather than struggling against your brain’s natural inclination to procrastinate, save yourself a lot of time and hassle by simply closing your email tab and banning social media during work time.

#8. Clear Your Desktop

Clear all paperwork off your desk except what you will need that day. Put everything else into physical folders, file boxes and drawers— out of sight, out of mind.

#9. Play Music or White Noise to Improve Focus

Low-level background noise helps muffle any distracting sounds that could interrupt your work and has been shown to improve creativity and focus for many people.

#10. Do the Hardest (or Most Unappealing) Task First

Look at your list of MITs (Most Important Tasks) and underline the one that you know you’d put off indefinitely if you had the chance. Get started on this task before you have a chance to think about it. Don’t work on your other tasks until it’s finished.

#11. Commit to a Very Small Goal

Look at your hardest task and plan a small, easy first step to completing it that will take only a few minutes. Pick a simple metric that you know (without a doubt) you can complete.

#12. Work in Small Blocks of Time

The Pomodoro technique is probably the most well-known version of this technique. It involves working for twenty-five minutes and then taking a five-minute break.

#13. Track Time for Different Activities

Most people overestimate the amount of time they spend doing actual work and spend a surprisingly large amount of time doing mindless tasks. By tracking your time, you become more aware of how you’re spending it, and you can start to spot patterns in your schedule that are reducing your productivity.

#14. Use the Two-Minute Rule

If a task will take you two minutes or less to do, deal with it immediately and move on.

Keep in mind that this type of framework is how the urgent trumps the meaningful.

#15. Capture Every Idea
Our minds tend to wander. Despite our intentions, they drift off from the task at hand. Rather than a drawback, this is one of the fascinating ways that we gain insights. Pull out a notepad and write them down. You can come back to them later and, who knows, it just might be a great idea or the solution to a problem you’ve been working on.

#16. Write a Done List

Most people are familiar with to-do lists, but these lists can easily make you feel overwhelmed and demotivated if you try to plan too much. A done list has the opposite effect. By writing down everything you achieve each day, you’ll feel motivated to continue.

#17. Review Your Goals

Everybody has goals. Whether they are big or small, we all have things that we want to accomplish. Sadly, the daily hustle and bustle of life can make us get off track. You need to review your goals so that you can create plans to reach those goals, put your day in perspective and know what’s important to accomplish.

Habit Stacking: 97 Small Life Changes That Take Five Minutes or Less goes on to offer small habits in six other areas: relationships, finances, organization, mental well-being, physical fitness, and leisure.

Do Algorithms Beat Us at Complex Decision Making?

Decision-making algorithms are undoubtedly controversial. If a decision is being made that will have a major influence on your life, most people would prefer a human make it. But what if algorithms really can make better decisions?

***

Algorithms are all the rage these days. AI researchers are taking more and more ground from humans in areas like rules-based games, visual recognition, and medical diagnosis. However, the idea that algorithms make better predictive decisions than humans in many fields is a very old one.

In 1954, the psychologist Paul Meehl published a controversial book with a boring sounding name: Clinical vs. Statistical Prediction: A Theoretical Analysis and a Review of the Evidence.

The controversy? After reviewing the data, Meehl claimed that mechanical, data-driven algorithms could better predict human behavior than trained clinical psychologists — and with much simpler criteria. He was right.

The passing of time has not been friendly to humans in this game: Studies continue to show that the algorithms do a better job than experts in a range of fields. In Daniel Kahneman’s Thinking Fast and Slow, he details a selection of fields which have demonstrated inferior human judgment compared to algorithms:

The range of predicted outcomes has expanded to cover medical variables such as the longevity of cancer patients, the length of hospital stays, the diagnosis of cardiac disease, and the susceptibility of babies to sudden infant death syndrome; economic measures such as the prospects of success for new businesses, the evaluation of credit risks by banks, and the future career satisfaction of workers; questions of interest to government agencies, including assessments of the suitability of foster parents, the odds of recidivism among juvenile offenders, and the likelihood of other forms of violent behavior; and miscellaneous outcomes such as the evaluation of scientific presentations, the winners of football games, and the future prices of Bordeaux wine.

The connection between them? Says Kahneman: “Each of these domains entails a significant degree of uncertainty and unpredictability.” He called them “low-validity environments”, and in those environments, simple algorithms matched or outplayed humans and their “complex” decision making criteria, essentially every time.

***

A typical case is described in Michael Lewis’ book on the relationship between Daniel Kahneman and Amos Tversky, The Undoing Project. He writes of work done at the Oregon Research Institute on radiologists and their x-ray diagnoses:

The Oregon researchers began by creating, as a starting point, a very simple algorithm, in which the likelihood that an ulcer was malignant depended on the seven factors doctors had mentioned, equally weighted. The researchers then asked the doctors to judge the probability of cancer in ninety-six different individual stomach ulcers, on a seven-point scale from “definitely malignant” to “definitely benign.” Without telling the doctors what they were up to, they showed them each ulcer twice, mixing up the duplicates randomly in the pile so the doctors wouldn’t notice they were being asked to diagnose the exact same ulcer they had already diagnosed. […] The researchers’ goal was to see if they could create an algorithm that would mimic the decision making of doctors.

This simple first attempt, [Lewis] Goldberg assumed, was just a starting point. The algorithm would need to become more complex; it would require more advanced mathematics. It would need to account for the subtleties of the doctors’ thinking about the cues. For instance, if an ulcer was particularly big, it might lead them to reconsider the meaning of the other six cues.

But then UCLA sent back the analyzed data, and the story became unsettling. (Goldberg described the results as “generally terrifying”.) In the first place, the simple model that the researchers had created as their starting point for understanding how doctors rendered their diagnoses proved to be extremely good at predicting the doctors’ diagnoses. The doctors might want to believe that their thought processes were subtle and complicated, but a simple model captured these perfectly well. That did not mean that their thinking was necessarily simple, only that it could be captured by a simple model.

More surprisingly, the doctors’ diagnoses were all over the map: The experts didn’t agree with each other. Even more surprisingly, when presented with duplicates of the same ulcer, every doctor had contradicted himself and rendered more than one diagnosis: These doctors apparently could not even agree with themselves.

[…]

If you wanted to know whether you had cancer or not, you were better off using the algorithm that the researchers had created than you were asking the radiologist to study the X-ray. The simple algorithm had outperformed not merely the group of doctors; it had outperformed even the single best doctor.

The fact that doctors (and psychiatrists, and wine experts, and so forth) cannot even agree with themselves is a problem called decision making “noise”: Given the same set of data twice, we make two different decisions. Noise. Internal contradiction.

Algorithms win, at least partly, because they don’t do this: The same inputs generate the same outputs every single time. They don’t get distracted, they don’t get bored, they don’t get mad, they don’t get annoyed. Basically, they don’t have off days. And they don’t fall prey to the litany of biases that humans do, like the representativeness heuristic.

The algorithm doesn’t even have to be a complex one. As demonstrated above with radiology, simple rules work just as well as complex ones. Kahneman himself addresses this in Thinking, Fast and Slow when discussing Robyn Dawes’s research on the superiority of simple algorithms using a few equally-weighted predictive variables:

The surprising success of equal-weighting schemes has an important practical implication: it is possible to develop useful algorithms without prior statistical research. Simple equally weight formulas based on existing statistics or on common sense are often very good predictors of significant outcomes. In a memorable example, Dawes showed that marital stability is well predicted by a formula: Frequency of lovemaking minus frequency of quarrels.

You don’t want your result to be a negative number.

The important conclusion from this research is that an algorithm that is constructed on the back of an envelope is often good enough to compete with an optimally weighted formula, and certainly good enough to outdo expert judgment. This logic can be applied in many domains, ranging from the selection of stocks by portfolio managers to the choices of medical treatments by doctors or patients.

Stock selection, certainly a “low validity environment”, is an excellent example of the phenomenon.

As John Bogle pointed out to the world in the 1970’s, a point which has only strengthened with time, the vast majority of human stock-pickers cannot outperform a simple S&P 500 index fund, an investment fund that operates on strict algorithmic rules about which companies to buy and sell and in what quantities. The rules of the index aren’t complex, and many people have tried to improve on them with less success than might be imagined.

***

Another interesting area where this holds is interviewing and hiring, a notoriously difficult “low-validity” environment. Even elite firms often don’t do it that well, as has been well documented.

Fortunately, if we take heed of the advice of the psychologists, operating in a low-validity environment has rules that can work very well. In Thinking Fast and Slow, Kahneman recommends fixing your hiring process by doing the following (or some close variant), in order to replicate the success of the algorithms:

Suppose you need to hire a sales representative for your firm. If you are serious about hiring the best possible person for the job, this is what you should do. First, select a few traits that are prerequisites for success in this position (technical proficiency, engaging personality, reliability, and so on). Don’t overdo it — six dimensions is a good number. The traits you choose should be as independent as possible from each other, and you should feel that you can assess them reliably by asking a few factual questions. Next, make a list of questions for each trait and think about how you will score it, say on a 1-5 scale. You should have an idea of what you will call “very weak” or “very strong.”

These preparations should take you half an hour or so, a small investment that can make a significant difference in the quality of the people you hire. To avoid halo effects, you must collect the information one at a time, scoring each before you move on to the next one. Do not skip around. To evaluate each candidate, add up the six scores. […] Firmly resolve that you will hire the candidate whose final score is the highest, even if there is another one whom you like better–try to resit your wish to invent broken legs to change the ranking. A vast amount of research offers a promise: you are much more likely to find the best candidate if you use this procedure than if you do what people normally do in such situations, which is to go into the interview unprepared and to make choices by an overall intuitive judgment such as “I looked into his eyes and liked what I saw.”

In the battle of man vs algorithm, unfortunately, man often loses. The promise of Artificial Intelligence is just that. So if we’re going to be smart humans, we must learn to be humble in situations where our intuitive judgment simply is not as good as a set of simple rules.

Thinking About Thinking

I wrote a response on quora recently to the question ‘how do I become a better thinker’ that generated a lot of attention and feedback so I thought I’d build on that a little and post it here too.

Thinking is not IQ. When people talk about thinking they make the mistake of thinking that people with high IQs think better. That’s not what I’m talking about. I hate to break it to you but unless you’re trying to get into Mensa, IQ tests don’t matter as much as we think they do. After a certain point, that’s not the type of knowledge or brainpower that makes you better at life, happier, or more successful. It’s a measure sure, but a relatively useless one.

If you want to outsmart people who are smarter than you, temperament and life-long learning are more important than IQ.

Two of the guiding principles that I follow on my path towards seeking wisdom are: (1) Go to bed smarter than when you woke up; and (2) I’m not smart enough to figure everything out myself, so I want to ‘master the best of what other people have already figured out.’

Acquiring wisdom is hard. Learning how to think is hard. It means sifting through information, filtering the bunk, and connecting it to a framework that you can use. A lot of people want to get their opinions from someone else. I know this because whenever anyone blurts out an opinion and I ask why, I get some hastily re-phrased sound-byte that doesn’t contextualize the problem, identify the forces at play, demonstrate differences or similarities with previous situations, consider base rates, or … anything else that would demonstrate some level of thinking. (One of my favorite questions to probe thinking is to ask what information would cause someone to change their mind. Immediately stop listening and leave if they say ‘I can’t think of anything.’)

Thinking is hard work. I get it. You don’t have time to think but that doesn’t mean you get a pass from me. I want to think for myself, thank you.

***

So one effective thing you can do if you want to think better is to become better at probing other people’s thinking. Ask questions. Simple ones are better. “Why” is the best. If you ask that three or four times you get to a place where you’re going to understand more and you’ll be able to tell who really knows what they are talking about. Shortcuts in thinking are easy, and this is how you tease them out. Not to make the other person look bad – don’t do this maliciously – but to avoid mistakes, air assumptions, and discuss conclusions.

Another thing you can do is to slow down. Make sure you give yourself time to think. I know, it’s a fast-paced internet world where we get some cultural machoism points for answering on the spot but unless it has to be decided at that very moment, simply say “let me think about that for a bit and get back to you.” The world will not end while you think about it.

You should also probe yourself. Try and understand if you’re talking about something you really know something about or if you’re just regurgitating some talking head you heard on the news last night. Your life will become instantly better and your mind clearer if you simply stop the latter. You’re only fooling yourself and if you don’t understand the limits of what you know, you’re going to get in trouble.

Learning How To Think

Learning how to think really means continuously learning.

How can we do that?

First we need a framework to put things on so we can remember, integrate, and make them available for use.

A Latticework of Mental Models, if you will.

Acquiring knowledge may seem like a daunting task. There is so much to know and time is precious. Luckily, we don’t have to master everything. To get the biggest bang for the buck we can study the big ideas from physics, biology, psychology, philosophy, literature, and sociology.

Our aim is not to remember facts and try to repeat them when asked. We’re going to try and hang these ideas on a latticework of mental models. Doing this puts them in a useable form and enables us to make better decisions.

A mental model is simply a representation of an external reality inside your head. Mental models are concerned with understanding knowledge about the world.

Decisions are more likely to be correct when ideas from multiple disciplines all point towards the same conclusion.

It’s like the old saying, “To the man with only a hammer, every problem looks like a nail.” Let’s make every attempt not to be the man with only a hammer.

Charlie Munger further elaborates:

And the models have to come from multiple disciplines because all the wisdom of the world is not to be found in one little academic department. That’s why poetry professors, by and large, are so unwise in a worldly sense. They don’t have enough models in their heads. So you’ve got to have models across a fair array of disciplines.

You may say, “My God, this is already getting way too tough.” But, fortunately, it isn’t that tough because 80 or 90 important models will carry about 90% of the freight in making you a worldly wise person. And, of those, only a mere handful really carry very heavy freight.

These models generally fall into two categories: (1) ones that help us simulate time (and predict the future) and better understand how the world works (e.g. understanding a useful idea from like autocatalysis), and (2) ones that help us better understand how our mental processes lead us astray (e.g., availability bias).

When our mental models line up with reality they help us avoid problems. However, they also cause problems when they don’t line up with reality as we think something that isn’t true. So Beware.

In Peter Bevelin’s masterful book Seeking Wisdom, he highlights Munger talking about autocatalysis:

If you get a certain kind of process going in chemistry, it speeds up on its own. So you get this marvellous boost in what you’re trying to do that runs on and on. Now, the laws of physics are such that it doesn’t run on forever. But it runs on for a goodly while. So you get a huge boost. You accomplish A – and, all of a sudden, you’re getting A + B + C for awhile.

But knowing is not enough. You need to know how to apply this to other problems outside of the domain in which you learned it.

Munger continues:

Disney is an amazing example of autocatalysis … They had those movies in the can. They owned the copyright. And just as Coke could prosper when refrigeration came, when the videocassette was invented, Disney didn’t have to invent anything or do anything except take the thing out of the can and stick it on the cassette.

What models do we need?

I keep a running list that I’m filling in over time, but really how we store and sort these are individual preferences. The framework is not a one-stop-shop, it’s how it fits into your brain.

How can we acquire these models?

There are several ways to acquire the models, the first and probably best source is reading. Even Warren Buffett says reading is one of the best ways to get wiser.

But sadly if your goal is wisdom acquisition, you can’t just pick up a book and read it. You need to Learn How To Read A Book all over again. Most people look at my reading habits (What I’m Reading) and think that I speed read. I don’t. I think that’s a bunch of hot air. If you think you can pick up a book on a subject you’re unfamiliar with and in 30 minutes become an expert … well, good luck to you. Please go back to getting your opinions from twitter.

Focus on the big, simple ideas.

Focus on deeply understanding the simple ideas (see Five Elements of Effective Thinking). These simple ideas, not the cutting-edge ones are the ones you want to hang on your latticework. The latticework is important because it makes the knowledge useable – you not only recall but you internalize.

But the world is always changing … what should we learn first?

One of the biggest mistakes I see people making is to try and learn the cutting-edge research first. The way we prioritize learning has huge implications beyond the day-to-day. When we chase the latest thing, we’re really jumping into an arms race (see: The Red Queen Effect). We have to spend more and more of our time and energy to stay in the same place.

Despite our intentions, learning in this way fails to take advantage of cumulative knowledge. We’re not adding, we’re only maintaining.

If we are to prioritize learning, we should focus on ideas that change slowly – these tend to be the ones from the hard sciences. (see Adding Mental Models to Your Toolbox)

The models that come from hard science and engineering are the most reliable models on this Earth. And engineering quality control – at least the guts of it that matters to you and me and people who are not professional engineers – is very much based on the elementary mathematics of Fermat and Pascal: It costs so much and you get so much less likelihood of it breaking if you spend this much… And, of course, the engineering idea of a backup system is a very powerful idea. The engineering idea of breakpoints – that’s a very powerful model, too. The notion of a critical mass – that comes out of physics – is a very powerful model.

To help further prioritize learning

From : What Should I Read?

Knowledge has a half-life. The most useful knowledge is a broad-based multidisciplinary education of the basics. These ideas are ones that have lasted, and thus will last, for a long time. And by last, I mean mathematical expectation; I know what will happen in general but not each individual case.

Integrating Knowledge

(Source: Adding Mental Models to Your Toolbox)

Our world is mutli-dimensional and our problems are complicated. Most problems cannot be solved using one model alone. The more models we have the better able we are to rationally solve problems. But if we don’t have the models we become the proverbial man with a hammer.

To the man with a hammer everything looks like a nail. If you only have one model you will fit whatever problem you face to the model you have. If you have more than one model, however, you can look at the problem from a variety of perspectives and increase the odds you come to a better solution.

No one discipline has all the answers, only by looking at them all can we come to grow worldly wisdom.

Charles Munger illustrates the importance of this:

Suppose you want to be good at declarer play in contract bridge. Well, you know the contract – you know what you have to achieve. And you can count up the sure winners you have by laying down your high cards and your invincible trumps.

But if you’re a trick or two short, how are you going to get the other needed tricks? Well, there are only six or so different, standard methods: You’ve got long-suit establishment. You’ve got finesses. You’ve got throw-in plays.

You’ve got cross-ruffs. You’ve got squeezes. And you’ve got various ways of misleading the defense into making errors. So it’s a very limited number of models. But if you only know one or two of those models, then you’re going to be a horse’s patoot in declarer play…

If you don’t have the full repertoire, I guarantee you that you’ll over-utilize the limited repertoire you have – including use of models that are inappropriate just because they’re available to you in the limited stock you have in mind.

As for how we can use different ideas, Munger again shows the way …

Have a full kit of tools … go through them in your mind checklist-style. … [Y]ou can never make any explanation that can be made in a more fundamental way in any other way than the most fundamental way.

When you combine things you get lollapalooza effects — the integration of more than one effect to create a non-linear response.

A two-step process for making effective decisions

There is no point in being wiser unless you use it for good. You know, as Aunt May put it to Peter Parker, “with great power comes great responsibility.”

(Source: A Two-step Process for Making Effective Decisions)

Personally, I’ve gotten so that I now use a kind of two-track analysis. First, what are the factors that really govern the interests involved, rationally considered? And second, what are the subconscious influences where the brain at a subconscious level is automatically doing these things-which by and large are useful, but which often misfunction.

One approach is rationality-the way you’d work out a bridge problem: by evaluating the real interests, the real probabilities and so forth. And the other is to evaluate the psychological factors that cause subconscious conclusions-many of which are wrong.

This is the path, the rest is up to you.

Why Early Decisions Have the Greatest Impact and Why Growing too Much is a Bad Thing

I never went to Engineering school. My undergrad is Computer Science. Despite that I’ve always wanted to learn more about Engineering.

John Kuprenas and Matthew Frederick have put together a book, 101 Things I Learned in Engineering School, which contains some of the big ideas.

In the author’s note, Kuprenas writes:

(This book) introduces engineering largely through its context, by emphasizing the common sense behind some of its fundamental concepts, the themes intertwined among its many specialities, and the simple abstract principles that can be derived from real-world circumstances. It presents, I believe, some clear glimpses of the forest as well as the trees within it.

Here are three (of the many) things I noted in the book.

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#8 An object receives a force, experiences stress, and exhibits strain.

force-stress-strain

Force, stress, and strain are used somewhat interchangeably in the lay world and may even be used with less than ideal rigor by engineers. However, they have different meanings.

A force, sometimes called “load,” exists external to and acts upon a body, causing it to change speed, direction, or shape. Examples of forces include water pressure on a submarine hull, snow loads on a bridge, and wind loads on the sides of a skyscraper.

Stress is the “Experience” of a body—its internal resistance to an external force acting on it. Stress is force divided by unit area, and is expressed in units such as pounds per square inch.

Strain is a product of stress. It is the measurable percentage of deformation or change in an object such as a change in length.

#48 Early decisions have the greatest impact.

Early Decisions Have Greater Impact

Decisions made just days or weeks into a project—assumptions of end-user needs, commitments to a schedule, the size and shape of a building footprint, and so on—have the most significant impact on design, feasibility, and cost. As decisions are made later and later in the design process, their influence decreases. Minor cost savings sometimes can be realized through value engineering in the later stages of design, but the biggest cost factors are embedded at the outset in a project’s DNA.

Everyone seems to understand this point on the surface and yet few people consider the implications. I know a lot of people who make their career on cleaning up their own mess. That is, they make a poor initial decision and then work extra hours while running around with stress and panic as they clean up their own mess. In the worst organizations these people are promoted for doing an exceptional job.

Proper management of early decisions produces more free time and lower stress.

#75 A successful system won’t necessarily work at a different scale.

Systems Scale

An imaginary team of engineers sought to build a “super-horse” that would be twice as tall as a normal horse. When they created it, they discovered it to be a troubled, inefficient beast. Not only was it two times the height of a normal horse, it was twice as wide and twice as long, resulting in an overall mass eight times greater than normal. But the cross sectional area of its veins and arteries was only four times that of a normal horse calling for its heart to work twice as hard. The surface area of its feed was four times that of a normal horse, but each foot had to support twice the weight per unit of surface area compared to a normal horse. Ultimately, the sickly animal had to be put down.

This becomes interesting when you think of the ideal size for things and how we, as well intentioned humans, often make things worse. This has a name. It’s called iatrogenics.

Let us briefly put an organizational lens on this. Inside organizations resources are scarce. Generally the more people you have under you the more influence and authority you have inside the organization. Unless there is a proper culture and incentive system in place, your incentive is to grow and not shrink. In fact, in all the meetings I’ve ever been in with senior management, I can’t recall anyone who ran a division saying I have too many resources. It’s a derivative of Parkinson’s Law — only work isn’t expanding to fill the time available. Instead, work is expanding to fill the number of people.

Contrast that with Berkshire Hathaway, run by Warren Buffett. In a 2010 letter to shareholders he wrote:

Our flexibility in respect to capital allocation has accounted for much of our progress to date. We have been able to take money we earn from, say, See’s Candies or Business Wire (two of our best-run businesses, but also two offering limited reinvestment opportunities) and use it as part of the stake we needed to buy BNSF.

In the 2014 letter he wrote:

To date, See’s has earned $1.9 billion pre-tax, with its growth having required added investment of only $40 million. See’s has thus been able to distribute huge sums that have helped Berkshire buy other businesses that, in turn, have themselves produced large distributable profits. (Envision rabbits breeding.) Additionally, through watching See’s in action, I gained a business education about the value of powerful brands that opened my eyes to many other profitable investments.

There is an optimal size to See’s. Had they retained that $1.9 billion in earnings they distributed to Berkshire, the CEO and management team might have a claim to bigger pay checks, they’d be managing ~$2 billion in assets instead of $40 million, but the result would have been very sub-optimal.

Our pursuit of growth beyond a certain point often ensures that one of the biggest forces in the world, time, is working against us. “What is missing,” writes Jeff Stibel in BreakPoint, “is that the unit of measure for progress isn’t size, it’s time.”

***

Other books in the series:
101 Things I Learned in Culinary School
101 Things I Learned in Business School
101 Things I Learned in Law School
101 Things I Learned in Film School

Former Canadian Prime Minister Mackenzie King on The Law of Competing Standards

I came across that passage while reading “Industry and Humanity,” by former Canadian Prime Minister Mackenzie King. We’ll add this to our previous knowledge on Gresham’s Law.

In the reign of Queen Elizabeth, an official named Gresham observed that where different metals were in circulation as coinage and some were better than others of the same nominal value, the coins made of the inferior metal tended to drive the better out of circulation. The better coins were either hoarded or melted down and sold as bullion, were used in the fine arts, or were absorbed in the foreign exchanges. In other words, what Gresham discovered was that cheaper money tends to drive out dearer; that when people begin to discriminate between two coinages, they will invariably pay out the inferior and hoard the better, thus removing the better from circulation. This phenomenon once generally observed came to be described as a “Law,” and was identified with Gresham’ s name, since it was Gresham who was first successful in drawing public attention to it. Amongst money-changers, Gresham’ s Law of the precious metals is better known than the Ten Commandments.

Something analogous to Gresham’s Law will be found to obtain in the case of competing standards in Industry. Assuming there is indifference in the matter of choice between competing commodities or services, but that in the case of such commodities or services the labor standards involved vary, the inferior standard, if brought in this manner into competition with a higher standard, will drive it out, or drag the higher down to its level. This is effected by the opportunity of under-selling which comes, where in such cases human well-being is sacrificed to material ends. The superior standard, not being recognized or demanded, is unable to hold its own, and in time disappears. This Law is just as real and relentless in its operation in Industry as Gresham’s Law of the precious metals is with respect to money and the mechanism of exchange. Indeed, a more accurate exposition would describe both as manifestations of one and the same law, which I propose to call the Law of Competing Standards. I see no reason why economists should not recognize the existence of such a law, and incorporate it immediately in economic science as being quite as significant as the Law of Supply and Demand, the Law of Diminishing Returns, or any other Law accorded a place in its nomenclature.

The Law of Competing Standards is doubtless a part of the general Law of Competition, under which the cheaper of two commodities gains in competition a preference over the dearer. What Gresham discovered was an important sequence of the Law of Competition as applied to coinage; namely, the disappearance, in the course of time, of the superior metals. Observance of a like sequence in the case of standards in Industry is highly desirable. As respects labor standards, I believe that recognition of the operation of the Law of Competing Standards over ever-widening areas would do more than aught else to clear up the most baffling problems with which Industry is confronted, and to point the way to a solution of many situations which hitherto have seemed incapable of solution.