Smartcuts: The Breakthrough Power of Lateral Thinking

by Shane Snow

This waiting for luck to strike is the antithesis of lateral thinking.

a smartcut-savvy mentee approaches things a bit differently. She develops personal relationships with her mentors, asks their advice on other aspects of life, not just the formal challenge at hand. And she cares about her mentors’ lives too.

vulnerability. It’s the key, he says, to developing a deep and organic relationship that leads to journey-focused mentorship and not just a focus on practice.

open up about their fears, and that builds trust, which in turn accelerates learning. That trust opens us up to actually heeding the difficult advice we might otherwise ignore. “It drives you to do more,”

two people can study the same business model, watch the same video, or even take the same advice from a mentor, and one person might pick up critical details that the other misses.

someone with the ability to spot important details among noise a “first-class noticer.” This is a key difference between those who learn more quickly than others.

“A master is able to give you feedback on a much more nuanced level, [and] has very little patience with distraction.”

mentees in this chapter succeeded in the long run is that mentors who were invested in their success, who showed vulnerability and cared enough to tell them what they didn’t want to hear when they needed to hear it, forced them to examine success-crucial details more closely than they might have on their own.

Gandhi.

talisman the revered Indian leader once gave to his grandson Arun, which listed the seven “blunders” he believed led to violence: Wealth without work. Pleasure without conscience. Knowledge without character. Commerce without morality. Science without humanity. Religion without sacrifice. Politics without principle.

“It was not easy to spell. It’s a French word that we added a letter to.” But more important, he recognized, at the end of the day he’d “built something that nobody wanted.” After about six months, he shut the app down.

Oscar Wilde once said, “Experience is the name everyone gives to their mistakes.”

“If you’re not failing you are either very lucky, very good, or not pushing the boundaries enough,” Staats says.

turns out that after you adjust for statistical margin of error, an entrepreneur who’d failed in a previous venture was not likely to do better than someone who’d never run a business in her life. Expecting to be suddenly great at business after running one into the ground is akin to losing the first basketball game you ever played and expecting to win the next game because you lost the first one. According to the study, successful entrepreneurs, on the other hand, are 50 percent more likely to succeed in a second venture. The more you win, the more likely you are to win again.

So, failing in business doesn’t make us better or smarter. But succeeding makes us more likely to continue to succeed.

This, of course, poses a chicken-and-egg problem. How do we increase the chance of success if the best way to do so is to . . . already . . . succeed?

As our hearts beat, a small portion of the oxygen they process gets pushed through the coronary arteries, small tubes that supply O2 directly to the heart muscle itself. It’s a brilliant perpetual motion machine, like a battery that powers its own charger. But as we age, plaque builds up inside the coronary artery, making it harder and harder for enough blood to squeeze through. This leads to heart attacks and is caused by cheeseburgers.

what’s really interesting is what happened to the surgeons who saw their colleagues fail at the new CABG procedure. These showed significant increases in their own success rates with every failure that they saw another doctor experience. Further perplexing, however: seeing a colleague perform a successful surgery didn’t seem to translate to one’s own future success. It was indeed a paradox. Screwups got worse. When colleagues screwed up, observers got better. When a doctor succeeded, she did better on her subsequent surgeries. When her colleagues did well, it didn’t affect her.

colleagues called this attribution theory. The theory says that people explain their successes and failures “by attributing them to factors that will allow them to feel as good as possible about themselves.” Remember what the Startup Funeral founders said? “We ran out of money.” “People didn’t want it.” “The ‘gray hairs’ had no plan.” Look at what they did. They each attributed their companies’ failures to external factors. Things that made them feel better about themselves.

On the other hand, we tend to pin our successes on internal factors. Think back to the last competition you won. It was your hard work, your skill, your quick thinking in the heat of the moment that won the day. Right?

Since they have control over their own effort and actions, these attributions motivate them to exert effort in subsequent tasks so that they can continue improving and learning.” This made the successful doctors better and better.

However, when failure isn’t personal, we often do the opposite. When someone else fails, we blame his or her lack of effort or ability. When we see people succeed, we tend to attribute it to situational forces beyond their control, namely luck.

The research showed that experts—people who were masters at a trade—vastly preferred negative feedback to positive. It spurred the most improvement. That was because criticism is generally more actionable than compliments. “You did well” is less helpful in improving your bowling game than “You turned your wrist too much.” Crucially, experts tended to be able to turn off the part of their egos that took legitimate feedback personally when it came to their craft, and they were confident enough to parse helpful feedback from incorrect feedback. Meanwhile novices psyched themselves out. They needed encouragement and feared failure. The tough part about negative feedback is in separating ourselves from the perceived failure and turning our experiences into objective experiments. But when we do that, feedback becomes much more powerful.

Second City teaches its students to take such things in stride, to become scientists who see audience reaction as commentary on the joke, not the jokester. To turn off the part of their brains that says “I fail” when they get negative feedback. And then the school has students continuously parlay up to harder audiences and harsher feedback as they grow more comfortable. This forces them to both toughen up and push creative boundaries. With this process, The Second City transforms failure (something that implies finality) into simply feedback (something that can be used to improve). Hundreds of times a week.

THE SECOND CITY MANAGES to accomplish three things to accelerate its performers’ growth: (1) it gives them rapid feedback; (2) it depersonalizes the feedback; and (3) it lowers the stakes and pressure, so students take risks that force them to improve.

By embracing all these tiny failures, there is no actual failure.* In contrast, a typical acting class might spend an entire semester building up to a single performance. Students practice together in class, but they don’t know if the audience will like their show until the final day. And if the audience hates it, there’s nothing students can do. If you think about it, that’s how most businesses operate. When releasing a new product, a company will spend months, sometimes years, fine-tuning, building up to one critical moment: the launch. Then on launch day the product either is a success or a failure. People buy it and the company makes a profit, or they don’t and the product fails. The Second City, on the other hand, puts its students on stage in front of live crowds every week. The class I sat in on wasn’t just practicing for the big show in four weeks; they were practicing for the little live show they did every week, the one with a crowd that would give them feedback on their material-in-progress. That’s how in just eight weeks—half a typical college semester—a class can put together a full-length sketch comedy show and it will be extremely funny. They know, because they got the feedback early, and often.

“Speed is an essential part of our game,” Leonard explains. “The rapid feedback . . . it’s non-stop.”

With thin, postchemo blond hair and a permanent smile, Zach took his crutches to school, asked his best friend out, and started a band. A filmmaker made a short documentary about this happy-go-lucky teenager on death row, called My Last Days. It showed Zach living happily, hanging out with his family, and playing music. Everybody loved Zach. When you see the footage, you can’t help but like him. As you watch him laugh and love and sing, you catch yourself forgetting: this kid is about to die. Zach’s family tells the camera how knowing he would die has helped them realize what matters in life and to find true meaning. “It’s really simple, actually,” Zach says. “Just try and make people happy.”

Upworthy reposted the video with a new title: “We Lost This Kid 80 Years Too Early. I’m Glad He Went Out with a Bang,” and shared it with a small number of its subscribers, then waited to see who clicked. Meanwhile, Upworthy sent the same video with a handful of other headlines to different subscribers. For example, “I Cried Through This Entire Video. That’s OK Though, Because This Kid’s Life Was Wonderful” and “The Happiest Story about a Kid Dying of Cancer I’ve Ever Seen.” Upworthy watched the “feedback” pour in, monitoring both the percentage of people who clicked each headline and the number who shared it with their friends. It was a perfect, dispassionate science experiment, where the feedback could show Upworthy editors exactly which packaging would have the biggest impact—before they released it to the rest of the world. In moments, the results became clear: people clicked on the third headline 20 percent more often than the original. But that wasn’t the end of the test. Upworthy wrote alternate versions of the winning headline and sent it out to several other groups. It repeated the process a ruthless 18 times, for a total of 75 variations

This rapid feedback process didn’t just increase views to the video by the calculated 186 percent, they increased views by that percentage for every cycle of sharers. So when you shared the video with your friends, they were three times as likely to click and share it with their friends. And those people were three times as likely to click and share. And so on. Like The Second City, Upworthy turned its work into rapid, scientific experiments. It turned tiny failures into depersonalized feedback and created an environment where total failure was nearly impossible.

WHEN HEINEMEIER HANSSON WALKED onto the racing scene in his early 30s, he was a virtual unknown, both older and less experienced than almost anyone in the leagues.

That makes him one of the fastest risers in championship racing. Despite that, Heinemeier Hansson is far better known among computer programmers—where he goes by the moniker DHH—than car enthusiasts. Though most of his fellow racers don’t know it, he’s indirectly responsible for the development of Twitter. And Hulu and Airbnb. And a host of other transformative technologies for which he receives no royalties. His work has contributed to revolutions, and lowered the barrier for thousands of tech companies* to launch products. All because David Heinemeier Hansson hates to do work he doesn’t have to do.

THINK OF THE WAY a stretch of grass becomes a road. At first, the stretch is bumpy and difficult to drive over. A crew comes along and flattens the surface, making it easier to navigate. Then, someone pours gravel. Then tar. Then a layer of asphalt. A steamroller smooths it; someone paints lines. The final surface is something an automobile can traverse quickly. Gravel stabilizes, tar solidifies, asphalt reinforces, and now we don’t need to build our cars to drive over bumpy grass. And we can get from Philadelphia to Chicago in a single day. That’s what computer programming is like. Like a highway, computers are layers on layers of code that make them increasingly easy to use. Computer scientists call this abstraction.

In the same way that driving on pavement makes a road trip faster, and layers of code let you work on a computer faster, hackers like DHH find and build layers of abstraction in business and life that allow them to multiply their effort. I call these layers platforms.

“My whole thing was, if I can put in 5 percent of the effort of somebody getting an A, and I can get a C minus, that’s amazing,” he explains. “It’s certainly good enough, right? [Then] I can take the other 95 percent of the time and invest it in something I really care about.”

One day, a small American Web design agency called 37signals asked DHH to build a project management tool to help organize its work. Hoping to save some time on this new project, he decided to try a relatively new programming language called Ruby, developed by a guy in Japan who liked simplicity. DHH started coding in earnest. Despite several layers of abstraction, Ruby (and all other code languages) forces programmers to make countless unimportant decisions. What do you name your databases? How do you want to configure your server? Those little things added up. And many programs required repetitive coding of the same basic components every time. That didn’t jibe with DHH’s selective slacking habit. “I hate repeating myself.” (He almost spits on me when he says it.) But conventional coders considered such repetition a rite of passage, a barrier to entry for newbies who hadn’t paid their dues in programming. “A lot of programmers took pride in the Protestant work ethic, like it has to be hard otherwise it’s not right,” DHH says. He thought that was stupid. “I could do a lot of other interesting things with my life,” he decided. “So if programming has to be it, it has to be awesome.” So DHH built a layer on top of Ruby to automate all the repetitive tasks and arbitrary decisions he didn’t want taking up his time. (It didn’t really matter what he named his databases.) His new layer on top of programming’s pavement became a set of railroad tracks that made creating a Ruby appl...

Finland’s students consistently ranked at the top—or very near the top—each year on international mathematics, science, and reading tests. Finland had left the States—and pretty much everyone else—in the dust.

Finnish students entered school one year later than most others. They took fewer classes and spent less time in school per day. They had fewer tests and less homework. And they thought school was fun.

“I THINK IT’S A great mistake to force children to learn mathematics,” said renowned physicist Freeman Dyson,

“Obviously there are things that a citizen ought to know,” he continued. But, “[we’re using] the entirely wrong approach.” Dyson believes that American schools teach kids to, metaphorically, drive on bumpy grass instead of to pilot cars on highways. Memorization of facts and figures is the primary culprit. What we really need, he says, is to teach kids to use tools that do math for us. In other words, no more multiplication tables. Calculators at age six. Parents and teachers, prepare your pitchforks.

John mused, “Wouldn’t it be cool if there were an engineering toy to get girls into programming?” So she built an iPad app called Daisy the Dinosaur, where kids could begin to harness programming’s concepts without having to learn its underpinnings through a series of increasingly difficult puzzles—like Angry Birds and the other touchscreen games kids were used to. Then she created a programming language called Hopscotch for the iPad. It allows kids to generate their own games, apps, and animations using those same puzzle-solving techniques. In the Hopscotch language, with a couple of finger swipes, you can create an “If > Then” statement, a staple of programming logic. This might look like a cartoon squid, with a box underneath it that lets you drag commands like “Turn Right.” With another swipe, you can make the squid repeat everything you dragged into the box, creating a loop, making the squid turn in circles. This is what that MIT mathematician Seymour Papert calls constructionism, or learning by making and manipulating objects. It’s incredibly effective for concept mastery and recall, and it’s almost always aided by platforms. With Hopscotch, kids have re-created their favorite video games, built animated cartoons, and created programs that solve real-world problems. An eighth-grade class made math quizzes for their first-grade mentees, for example. One user made a spin-the-bottle app. Many of these kids don’t even know long division. But John says that’s OK. “You nee...

Studies show that students who use calculators have better attitudes toward math, and are more likely to pursue highly computational careers in science, technology, engineering, and mathematics (STEM) than those who don’t or can’t. This is certainly the case with games like John’s, too. Dyson says, and Papert confirms, that to get kids to become interested in an academic subject on their own, they have to play. Building with LEGOs, visiting museums, experimenting with tools. Says Dyson, “Mathematics ought to be entertainment.”

Moursund says that before high school, we devote roughly three-quarters of our math education to memorizing and practicing the use of rules. This leaves too little time, he believes, for higher-order thinking: applying math to solving problems, creating models, or enhancing our understanding of the world. “Calculators and computers can replace some of the memorizing,” he says. “Mathematics is

But this, Devlin adds, is the clincher: “Get the thinking right and the skills come largely for free.”

By learning the tool (calculator) first, we actually master the discipline (math) faster. This is the point that Dyson was making earlier. Hands-on learning and the use of tools, he says, helps us to want to learn, to get rapid feedback, and to actually grasp math better than memorizing facts from the bottom up.

while we may need deep expertise in our industries to become innovators, we actually need only higher-order thinking and the ability to use platforms to do everything else. In a pre–technology era, people with abstract knowledge were highly valued. But in the age of smartphones and Wikipedia, does it matter that you don’t know offhand the name of the second-largest city in Botswana? What’s important today is knowing how to use platforms to retrieve the information we need, whether it’s the capital of Botswana or the result of 124,502 divided by 8.* In an age of platforms, creative problem solving is more valuable than computational skill.

what all this research tells us is that platforms can help us master those basics faster than learning the basics from scratch. In

For example, today’s children should be taught to use Excel spreadsheets—and all their calculations—instead of times tables. Rather than teaching a mile wide in every subject, we ought to first teach kids to use platforms, then let them go deep in the areas that interest them.

In a typical US high school, many of the teachers fall into the category of broad but shallow experts themselves. The health teacher becomes the Spanish teacher, then temporarily the geography teacher. But, really, he’s the football coach. Bless his heart, but he’s basically building a road out of mud. And that’s where Finland’s education system found its platform advantage.

The secret of the Finland phenomenon, Wagner discovered, was a platform it built by elevating the education level of its teachers. Finland’s public school system was experiencing the same thing that made Harvard University’s curriculum and network the envy of the academic world: it hired only teachers with incredible qualifications and it had them mentor students closely. Thus, students who went to school at Harvard—or in Finland—started out a rung above their peers.