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TED Talks, Dan Pink on the surprising science of motivation

Dan Pink on the surprising science of motivation

I need to make a confession at the outset here.

A little over 20 years ago I did something that I regret, something that I'm not particularly proud of, something that, in many ways, I wish no one would ever know, but here I feel kind of obliged to reveal. (Laughter) In the late 1980s, in a moment of youthful indiscretion, I went to law school. (Laughter)

Now, in America law is a professional degree: you get your university degree, then you go on to law school. And when I got to law school, I didn't do very well. To put it mildly, I didn't do very well. I, in fact, graduated in the part of my law school class that made the top 90 percent possible. (Laughter) Thank you. I never practiced law a day in my life; I pretty much wasn't allowed to. (Laughter)

But today, against my better judgment, against the advice of my own wife, I want to try to dust off some of those legal skills -- what's left of those legal skills. I don't want to tell you a story. I want to make a case. I want to make a hard-headed, evidence-based, dare I say lawyerly case, for rethinking how we run our businesses.

So, ladies and gentlemen of the jury, take a look at this. This is called the candle problem. Some of you might have seen this before. It's created in 1945 by a psychologist named Karl Duncker. Karl Duncker created this experiment that is used in a whole variety of experiments in behavioral science. And here's how it works. Suppose I'm the experimenter. I bring you into a room. I give you a candle, some thumbtacks and some matches. And I say to you, "Your job is to attach the candle to the wall so the wax doesn't drip onto the table." Now what would you do?

Now many people begin trying to thumbtack the candle to the wall. Doesn't work. Somebody, some people -- and I saw somebody kind of make the motion over here -- some people have a great idea where they light the match, melt the side of the candle, try to adhere it to the wall. It's an awesome idea. Doesn't work. And eventually, after five or 10 minutes, most people figure out the solution, which you can see here. The key is to overcome what's called functional fixedness. You look at that box and you see it only as a receptacle for the tacks. But it can also have this other function, as a platform for the candle. The candle problem.

Now I want to tell you about an experiment using the candle problem, done by a scientist named Sam Glucksberg, who is now at Princeton University in the U.S. This shows the power of incentives. Here's what he did. He gathered his participants. And he said, "I'm going to time you. How quickly you can solve this problem?" To one group he said, "I'm going to time you to establish norms, averages for how long it typically takes someone to solve this sort of problem. " To the second group he offered rewards. He said, "If you're in the top 25 percent of the fastest times, you get five dollars. If you're the fastest of everyone we're testing here today, you get 20 dollars." Now this is several years ago. Adjusted for inflation, it's a decent sum of money for a few minutes of work. It's a nice motivator.

Question: How much faster did this group solve the problem? Answer: It took them, on average, three and a half minutes longer. Three and a half minutes longer. Now this makes no sense right? I mean, I'm an American. I believe in free markets. That's not how it's supposed to work. Right? (Laughter) If you want people to perform better, you reward them. Right? Bonuses, commissions, their own reality show. Incentivize them. That's how business works. But that's not happening here. You've got an incentive designed to sharpen thinking and accelerate creativity, and it does just the opposite. It dulls thinking and blocks creativity.

And what's interesting about this experiment is that it's not an aberration. This has been replicated over and over and over again, for nearly 40 years. These contingent motivators -- if you do this, then you get that -- work in some circumstances. But for a lot of tasks, they actually either don't work or, often, they do harm. This is one of the most robust findings in social science, and also one of the most ignored.

I spent the last couple of years looking at the science of human motivation, particularly the dynamics of extrinsic motivators and intrinsic motivators. And I'm telling you, it's not even close. If you look at the science, there is a mismatch between what science knows and what business does. And what's alarming here is that our business operating system -- think of the set of assumptions and protocols beneath our businesses, how we motivate people, how we apply our human resources -- it's built entirely around these extrinsic motivators, around carrots and sticks. That's actually fine for many kinds of 20th century tasks. But for 21st century tasks, that mechanistic, reward-and-punishment approach doesn't work, often doesn't work, and often does harm. Let me show you what I mean.

So Glucksberg did another experiment similar to this where he presented the problem in a slightly different way, like this up here. Okay? Attach the candle to the wall so the wax doesn't drip onto the table. Same deal. You: we're timing for norms. You: we're incentivizing. What happened this time? This time, the incentivized group kicked the other group's butt. Why? Because when the tacks are out of the box, it's pretty easy isn't it? (Laughter)

If-then rewards work really well for those sorts of tasks, where there is a simple set of rules and a clear destination to go to. Rewards, by their very nature, narrow our focus, concentrate the mind; that's why they work in so many cases. And so, for tasks like this, a narrow focus, where you just see the goal right there, zoom straight ahead to it, they work really well. But for the real candle problem, you don't want to be looking like this. The solution is not over here. The solution is on the periphery. You want to be looking around. That reward actually narrows our focus and restricts our possibility.

Let me tell you why this is so important. In western Europe, in many parts of Asia, in North America, in Australia, white-collar workers are doing less of this kind of work, and more of this kind of work. That routine, rule-based, left-brain work -- certain kinds of accounting, certain kinds of financial analysis, certain kinds of computer programming -- has become fairly easy to outsource, fairly easy to automate. Software can do it faster. Low-cost providers around the world can do it cheaper. So what really matters are the more right-brained creative, conceptual kinds of abilities.

Think about your own work. Think about your own work. Are the problems that you face, or even the problems we've been talking about here, are those kinds of problems -- do they have a clear set of rules, and a single solution? No. The rules are mystifying. The solution, if it exists at all, is surprising and not obvious. Everybody in this room is dealing with their own version of the candle problem. And for candle problems of any kind, in any field, those if-then rewards, the things around which we've built so many of our businesses, don't work.

Now, I mean it makes me crazy. And this is not -- here's the thing. This is not a feeling. Okay? I'm a lawyer; I don't believe in feelings. This is not a philosophy. I'm an American; I don't believe in philosophy. (Laughter) This is a fact -- or, as we say in my hometown of Washington, D.C., a true fact. (Laughter) (Applause) Let me give you an example of what I mean. Let me marshal the evidence here, because I'm not telling you a story, I'm making a case.

Ladies and gentlemen of the jury, some evidence: Dan Ariely, one of the great economists of our time, he and three colleagues, did a study of some MIT students. They gave these MIT students a bunch of games, games that involved creativity, and motor skills, and concentration. And the offered them, for performance, three levels of rewards: small reward, medium reward, large reward. Okay? If you do really well you get the large reward, on down. What happened? As long as the task involved only mechanical skill bonuses worked as they would be expected: the higher the pay, the better the performance. Okay? But one the task called for even rudimentary cognitive skill, a larger reward led to poorer performance.

Then they said, "Okay let's see if there's any cultural bias here. Lets go to Madurai, India and test this." Standard of living is lower. In Madurai, a reward that is modest in North American standards, is more meaningful there. Same deal. A bunch of games, three levels of rewards. What happens? People offered the medium level of rewards did no better than people offered the small rewards. But this time, people offered the highest rewards, they did the worst of all. In eight of the nine tasks we examined across three experiments, higher incentives led to worse performance.

Is this some kind of touchy-feely socialist conspiracy going on here? No. These are economists from MIT, from Carnegie Mellon, from the University of Chicago. And do you know who sponsored this research? The Federal Reserve Bank of the United States. That's the American experience.

Let's go across the pond to the London School of Economics -- LSE, London School of Economics, alma mater of 11 Nobel Laureates in economics. Training ground for great economic thinkers like George Soros, and Friedrich Hayek, and Mick Jagger. (Laughter) Last month, just last month, economists at LSE looked at 51 studies of pay-for-performance plans, inside of companies. Here's what the economists there said: "We find that financial incentives can result in a negative impact on overall performance. " There is a mismatch between what science knows and what business does. And what worries me, as we stand here in the rubble of the economic collapse, is that too many organizations are making their decisions, their policies about talent and people, based on assumptions that are outdated, unexamined, and rooted more in folklore than in science. And if we really want to get out of this economic mess, and if we really want high performance on those definitional tasks of the 21st century, the solution is not to do more of the wrong things, to entice people with a sweeter carrot, or threaten them with a sharper stick. We need a whole new approach.

And the good news about all of this is that the scientists who've been studying motivation have given us this new approach. It's an approach built much more around intrinsic motivation. Around the desire to do things because they matter, because we like it, because they're interesting, because they are part of something important. And to my mind, that new operating system for our businesses revolves around three elements: autonomy, mastery and purpose. Autonomy: the urge to direct our own lives. Mastery: the desire to get better and better at something that matters. Purpose: the yearning to do what we do in the service of something larger than ourselves. These are the building blocks of an entirely new operating system for our businesses.

I want to talk today only about autonomy. In the 20th century, we came up with this idea of management. Management did not emanate from nature. Management is like -- it's not a tree, it's a television set. Okay? Somebody invented it. And it doesn't mean it's going to work forever. Management is great. Traditional notions of management are great if you want compliance. But if you want engagement, self-direction works better.

Let me give you some examples of some kind of radical notions of self-direction. What this means -- you don't see a lot of it, but you see the first stirrings of something really interesting going on, because what it means is paying people adequately and fairly, absolutely -- getting the issue of money off the table, and then giving people lots of autonomy. Let me give you some examples.

How many of you have heard of the company Atlassian? It looks like less than half. (Laughter) Atlassian is an Australian software company. And they do something incredibly cool. A few times a year they tell their engineers, "Go for the next 24 hours and work on anything you want, as long as it's not part of your regular job. Work on anything you want." So that engineers use this time to come up with a cool patch for code, come up with an elegant hack. Then they present all of the stuff that they've developed to their teammates, to the rest of the company, in this wild and wooly all-hands meeting at the end of the day. And then, being Australians, everybody has a beer.

They call them FedEx Days. Why? Because you have to deliver something overnight. It's pretty. It's not bad. It's a huge trademark violation, but it's pretty clever. (Laughter) That one day of intense autonomy has produced a whole array of software fixes that might never have existed.

And it's worked so well that Atlassian has taken it to the next level with 20 Percent Time -- done, famously, at Google -- where engineers can work, spend 20 percent of their time working on anything they want. They have autonomy over their time, their task, their team, their technique. Okay? Radical amounts of autonomy. And at Google, as many of you know, about half of the new products in a typical year are birthed during that 20 Percent Time: things like Gmail, Orkut, Google News.

Let me give you an even more radical example of it: something called the Results Only Work Environment, the ROWE, created by two American consultants, in place in place at about a dozen companies around North America. In a ROWE people don't have schedules. They show up when they want. They don't have to be in the office at a certain time, or any time. They just have to get their work done. How they do it, when they do it, where they do it, is totally up to them. Meetings in these kinds of environments are optional.

What happens? Almost across the board, productivity goes up, worker engagement goes up, worker satisfaction goes up, turnover goes down. Autonomy, mastery and purpose, These are the building blocks of a new way of doing things. Now some of you might look at this and say, "Hmm, that sounds nice, but it's Utopian." And I say, "Nope. I have proof. " The mid-1990s, Microsoft started an encyclopedia called Encarta. They had deployed all the right incentives, all the right incentives. They paid professionals to write and edit thousands of articles. Well-compensated managers oversaw the whole thing to make sure it came in on budget and on time. A few years later another encyclopedia got started. Different model, right? Do it for fun. No one gets paid a cent, or a Euro or a Yen. Do it because you like to do it.

Now if you had, just 10 years ago, if you had gone to an economist, anywhere, and said, "Hey, I've got these two different models for creating an encyclopedia. If they went head to head, who would win?" 10 years ago you could not have found a single sober economist anywhere on planet Earth who would have predicted the Wikipedia model.

This is the titanic battle between these two approaches. This is the Ali-Frazier of motivation. Right? This is the Thrilla' in Manila. Alright? Intrinsic motivators versus extrinsic motivators. Autonomy, mastery and purpose, versus carrot and sticks. And who wins? Intrinsic motivation, autonomy, mastery and purpose, in a knockout. Let me wrap up.

There is a mismatch between what science knows and what business does. And here is what science knows. One: Those 20th century rewards, those motivators we think are a natural part of business, do work, but only in a surprisingly narrow band of circumstances. Two: Those if-then rewards often destroy creativity. Three: The secret to high performance isn't rewards and punishments, but that unseen intrinsic drive -- the drive to do things for their own sake. The drive to do things cause they matter.

And here's the best part. Here's the best part. We already know this. The science confirms what we know in our hearts. So, if we repair this mismatch between what science knows and what business does, if we bring our motivation, notions of motivation into the 21st century, if we get past this lazy, dangerous, ideology of carrots and sticks, we can strengthen our businesses, we can solve a lot of those candle problems, and maybe, maybe, maybe we can change the world. I rest my case. (Applause)

Dan Pink on the surprising science of motivation Dan Pink habla de la sorprendente ciencia de la motivación Dan Pink sulla sorprendente scienza della motivazione ダン・ピンクが語るモチベーションの驚くべき科学 Dan Pink sobre a surpreendente ciência da motivação Дэн Пинк об удивительной науке мотивации

I need to make a confession at the outset here. Je dois faire une confession au début ici. ここで最初に告白する必要があります。 Na początku muszę się spowiadać. Мне нужно сделать признание в самом начале здесь.

A little over 20 years ago I did something that I regret, something that I’m not particularly proud of, something that, in many ways, I wish no one would ever know, but here I feel kind of obliged to reveal. 20年ちょっと前、私は後悔していること、特に誇りに思っていないこと、多くの点で誰にも知られたくないことをしましたが、ここでは明らかにする義務があると感じています。 Nieco ponad 20 lat temu zrobiłem coś, czego żałuję, coś, z czego nie jestem szczególnie dumny, coś, co na wiele sposobów chciałbym, żeby nikt nigdy nie wiedział, ale tutaj czuję się zobowiązany do ujawnienia. Há pouco mais de 20 anos, fiz algo de que me arrependo, algo de que não me orgulho particularmente, algo que, de muitas maneiras, desejo que ninguém jamais saiba, mas aqui me sinto um pouco obrigado a revelar. Чуть более 20 лет назад я сделал что-то, о чем сожалею, чем-то, чем я не особо горжусь, чем-то, что, во многих отношениях, я бы хотел, чтобы никто никогда не узнал, но здесь я чувствую себя обязанным раскрыть это. (Laughter) In the late 1980s, in a moment of youthful indiscretion, I went to law school. (笑)1980年代後半、思慮のない若々しい瞬間に、ロースクールに通いました。 (Śmiech) Pod koniec lat 80., w chwili młodzieńczej niedyskrecji, poszedłem do szkoły prawniczej. (Risos) No final dos anos 80, em um momento de indiscrição juvenil, fui para a faculdade de direito. (Смех). В конце 1980-х, в момент юношеской неосторожности, я пошел в юридическую школу. (Laughter)

Now, in America law is a professional degree: you get your university degree, then you go on to law school. 現在、アメリカでは法律は専門の学位です。大学の学位を取得してから、法科大学院に進みます。 Agora, na América, o direito é um diploma profissional: você obtém seu diploma universitário e depois estuda direito. Теперь в Америке юриспруденция - это профессиональная степень: вы получаете университетское образование, а затем поступаете в юридическую школу. And when I got to law school, I didn’t do very well. そして、私がロースクールに入学したとき、私はあまりうまくいかなかった。 A kiedy dostałem się do szkoły prawniczej, nie radziłem sobie zbyt dobrze. И когда я поступил в юридическую школу, я не очень хорошо учился. To put it mildly, I didn’t do very well. Mówiąc łagodnie, nie zrobiłem zbyt dobrze. Para dizer o mínimo, não me saí muito bem. Мягко говоря, я не очень хорошо. I, in fact, graduated in the part of my law school class that made the top 90 percent possible. En fait, j'ai obtenu mon diplôme dans la partie de ma classe de droit qui a rendu possible le sommet des 90%. 実際、私はロースクールのクラスで卒業し、トップ90%を達成しました。 W rzeczywistości ukończyłem szkołę prawniczą, która umożliwiła uzyskanie 90% najlepszych. Na verdade, eu me formei na parte da minha turma da faculdade de direito que tornou os 90% melhores possíveis. На самом деле, я закончил ту часть своего юридического факультета, которая показала 90% лучших результатов. (Laughter) Thank you. I never practiced law a day in my life; I pretty much wasn’t allowed to. Je n'ai jamais pratiqué le droit un jour de ma vie; Je n'ai pratiquement pas été autorisé à le faire. 私は人生で毎日法律を実践したことはありません。私はほとんど許可されませんでした。 Nigdy w życiu nie praktykowałem prawa; Prawie nie wolno mi było. Eu nunca pratiquei direito por dia na minha vida; Eu praticamente não tinha permissão. Я никогда не занимался юридической практикой ни разу в жизни; Мне почти не разрешили. (Laughter)

But today, against my better judgment, against the advice of my own wife, I want to try to dust off some of those legal skills -- what’s left of those legal skills. Mais aujourd’hui, contre mon meilleur jugement, contre le conseil de ma propre femme, je veux essayer d’éponger certaines de ces compétences juridiques - ce qui reste de ces compétences juridiques. しかし、今日、私のより良い判断に逆らって、自分の妻の助言に逆らって、私はそれらの法的スキルのいくつかを払いのけようと試みたい-それらの法的スキルの残りのもの。 Ale dziś, wbrew mojej lepszej ocenie, wbrew radom mojej żony, chcę spróbować odkurzyć niektóre z tych umiejętności prawnych - co pozostało z tych umiejętności prawnych. Hoje, porém, contra meu melhor julgamento, contra o conselho de minha própria esposa, quero tentar remover algumas dessas habilidades legais - o que resta dessas habilidades legais. Но сегодня, вопреки моему лучшему суждению, вопреки советам моей собственной жены, я хочу попытаться стереть некоторые из этих юридических навыков - то, что осталось от этих юридических навыков. I don’t want to tell you a story. 話をしたくないです。 Я не хочу рассказывать тебе историю. I want to make a case. Je veux faire une affaire. 事件を起こしたい。 Chcę zrobić sprawę. Я хочу сделать случай. I want to make a hard-headed, evidence-based, dare I say lawyerly case, for rethinking how we run our businesses. Je veux faire un cas dur, fondé sur des preuves, oser un avocat, pour repenser la façon dont nous gérons nos entreprises. 私たちがビジネスをどのように運営しているかを再考するために、根拠のある、証拠に基づいた、あえて弁護士のケースを作りたいと思います。 Chcę stworzyć twardą, opartą na dowodach, ośmielę się powiedzieć, że sprawę prawniczą, za przemyślenie, w jaki sposób prowadzimy naszą działalność. Quero fazer uma ousada, baseada em evidências, ouso dizer um caso de advogado, por repensar a forma como administramos nossos negócios. Я хочу сделать твердое, основанное на фактах, осмелюсь сказать, адвокатское дело, для переосмысления того, как мы ведем наш бизнес.

So, ladies and gentlemen of the jury, take a look at this. 陪審の皆さん、これを見てください。 Panie i panowie jury, spójrzcie na to. Então, senhoras e senhores do júri, dê uma olhada nisso. Итак, дамы и господа присяжные, посмотрите на это. This is called the candle problem. C'est ce qu'on appelle le problème de la bougie. これはろうそくの問題と呼ばれます。 Nazywa się to problemem świecy. Isso é chamado de problema da vela. Some of you might have seen this before. あなた方の何人かは以前これを見たかもしれません。 Alguns de vocês já devem ter visto isso antes. Некоторые из вас, возможно, видели это раньше. It’s created in 1945 by a psychologist named Karl Duncker. 1945年に心理学者カールダンカーによって作成されました。 Он создан в 1945 году психологом по имени Карл Дункер. Karl Duncker created this experiment that is used in a whole variety of experiments in behavioral science. Karl Duncker created this experiment that is used in a whole variety of experiments in behavioral science. カールダンカーは、行動科学のさまざまな実験で使用されるこの実験を作成しました。 Karl Duncker criou esse experimento que é usado em toda uma variedade de experimentos em ciência do comportamento. Карл Дункер создал этот эксперимент, который используется в целом ряде экспериментов в поведенческой науке. And here’s how it works. そして、これがどのように機能するかです。 E aqui está como isso funciona. Suppose I’m the experimenter. 私が実験者だとしましょう。 Załóżmy, że jestem eksperymentatorem. I bring you into a room. 部屋に連れてきます。 I give you a candle, some thumbtacks and some matches. キャンドル、画鋲、マッチを差し上げます。 Eu lhe dou uma vela, algumas tachinhas e alguns fósforos. Я даю вам свечу, несколько канцелярских кнопок и несколько спичек. And I say to you, "Your job is to attach the candle to the wall so the wax doesn’t drip onto the table." そして私はあなたに言います、「あなたの仕事はろうそくを壁に取り付けて、ワックスがテーブルの上に垂れないようにすることです。」 E eu lhe digo: "Seu trabalho é prender a vela na parede para que a cera não pingue sobre a mesa". И я говорю вам: «Ваша задача - прикрепить свечу к стене, чтобы воск не капал на стол». Now what would you do? 今、あなたは何をしますか? Теперь, что бы вы сделали?

Now many people begin trying to thumbtack the candle to the wall. 今、多くの人々がろうそくを壁に画鋲で留めようとし始めます。 Agora, muitas pessoas começam a tentar prender a vela na parede. Сейчас многие люди начинают пытаться прижать свечу к стене. Doesn’t work. 動作しません。 Somebody, some people -- and I saw somebody kind of make the motion over here -- some people have a great idea where they light the match, melt the side of the candle, try to adhere it to the wall. 誰か、何人かの人々-そして私は誰かがここで動きを作っているのを見ました-一部の人々はマッチを照らし、キャンドルの側面を溶かし、それを壁に接着しようとする素晴らしいアイデアを持っています Alguém, algumas pessoas - e eu vi alguém meio que fazendo o movimento por aqui - algumas pessoas têm uma ótima idéia de onde acendem o fósforo, derretem o lado da vela, tentam aderir à parede. Кто-то, кто-то - и я видел, как кто-то тут делает движение - у некоторых людей есть отличная идея, где они зажгут спичку, растопят сторону свечи, попытаются приклеить ее к стене. It’s an awesome idea. C'est une idée géniale. それは素晴らしいアイデアです。 Doesn’t work. 動作しません。 And eventually, after five or 10 minutes, most people figure out the solution, which you can see here. Et finalement, après cinq ou dix minutes, la plupart des gens trouvent la solution que vous pouvez voir ici. そして、最終的には、5分または10分後に、ほとんどの人が解決策を見つけます。 И в конце концов, через пять или 10 минут большинство людей находят решение, которое вы можете увидеть здесь. The key is to overcome what’s called functional fixedness. La clé est de surmonter ce que l’on appelle la fixité fonctionnelle. 重要なのは、いわゆる機能的な固定性を克服することです。 A chave é superar o que é chamado de fixação funcional. Ключ должен преодолеть то, что называется функциональной неподвижностью. You look at that box and you see it only as a receptacle for the tacks. あなたはその箱を見ると、鋲の入れ物としてしか見えません。 Вы смотрите на эту коробку, и вы видите ее только как приемник для гвоздей. But it can also have this other function, as a platform for the candle. しかし、キャンドルのプラットフォームとして、この他の機能を持つこともできます。 Но он также может иметь эту другую функцию, как платформу для свечи. The candle problem. ろうそくの問題。

Now I want to tell you about an experiment using the candle problem, done by a scientist named Sam Glucksberg, who is now at Princeton University in the U.S. さて、キャンドルの問題を使った実験についてお話ししたいと思います。これは、現在米国のプリンストン大学にいるSam Glucksbergという科学者によって行われました。 Теперь я хочу рассказать вам об эксперименте с использованием проблемы со свечами, проведенном ученым по имени Сэм Глуксберг, который сейчас работает в Принстонском университете в США. This shows the power of incentives. これはインセンティブの力を示しています。 Это показывает силу стимулов. Here’s what he did. これが彼のしたことです。 He gathered his participants. 彼は参加者を集めた。 Zebrał swoich uczestników. Ele reuniu seus participantes. Он собрал своих участников. And he said, "I’m going to time you. そして彼は言った、「私はあなたに時間を計るつもりです。 A on powiedział: „Idę na czas. How quickly you can solve this problem?" この問題をどれだけ早く解決できますか?」 To one group he said, "I’m going to time you to establish norms, averages for how long it typically takes someone to solve this sort of problem. " À un groupe, il a dit: "Je vais vous donner le temps d'établir des normes, des moyennes sur combien de temps il faut généralement quelqu'un pour résoudre ce genre de problème." あるグループに対して、「このような問題を解決するために誰かが通常かかる時間の平均である、標準を確立するために時間をかけるつもりです。」 Para um grupo, ele disse: "Vou lhe dar tempo para estabelecer normas, médias de quanto tempo normalmente leva alguém para resolver esse tipo de problema". Одной группе он сказал: «Я собираюсь определить время, в среднем, сколько времени обычно требуется кому-то для решения такого рода проблем». To the second group he offered rewards. 2番目のグループに彼は報酬を提供しました。 He said, "If you’re in the top 25 percent of the fastest times, you get five dollars. 「最速の25%以内にいる場合、5ドルを獲得します。 Ele disse: "Se você está entre os 25% mais rápidos, obtém cinco dólares. If you’re the fastest of everyone we’re testing here today, you get 20 dollars." 私たちが今日ここでテストしているすべての人の中で最速なら、20ドルを獲得できます。」 Se você é o mais rápido de todos que testamos aqui hoje, ganha 20 dólares ". Если вы самый быстрый из всех, кого мы сегодня тестируем, вы получите 20 долларов ». Now this is several years ago. これは数年前です。 Agora isso é há vários anos. Теперь это несколько лет назад. Adjusted for inflation, it’s a decent sum of money for a few minutes of work. インフレ調整済みで、数分間の作業でまともな金額です。 Po uwzględnieniu inflacji jest to przyzwoita suma pieniędzy na kilka minut pracy. Ajustado pela inflação, é uma quantia decente em dinheiro por alguns minutos de trabalho. С учетом инфляции это приличная сумма денег за несколько минут работы. It’s a nice motivator. それは素晴らしい動機です。

Question: How much faster did this group solve the problem? 質問:このグループはどれだけ速く問題を解決しましたか? Pergunta: Com que rapidez esse grupo resolveu o problema? Вопрос: Насколько быстрее эта группа решила проблему? Answer: It took them, on average, three and a half minutes longer. 回答:平均して、3分半以上かかりました。 Odpowiedź: Zajęło im to średnio trzy i pół minuty dłużej. Resposta: Levaram, em média, três minutos e meio a mais. Ответ: На это у них ушло в среднем три с половиной минуты. Three and a half minutes longer. 3分半長くなります。 Três minutos e meio a mais. Now this makes no sense right? これは意味がありませんか? I mean, I’m an American. つまり、私はアメリカ人です。 I believe in free markets. 私は自由市場を信じています。 That’s not how it’s supposed to work. それはそれが機能するはずの方法ではありません。 Não é assim que deve funcionar. Это не так, как это должно работать. Right? (Laughter) If you want people to perform better, you reward them. (笑い)人々にもっと良いパフォーマンスをしてもらいたいなら、報酬を与えます。 (Смех). Если вы хотите, чтобы люди работали лучше, вы поощряете их. Right? Bonuses, commissions, their own reality show. Des bonus, des commissions, leur propre émission de télé réalité. ボーナス、コミッション、彼ら自身の現実ショー。 Bônus, comissões, seu próprio reality show. Incentivize them. Les inciter. それらを奨励します。 That’s how business works. それがビジネスの仕組みです。 But that’s not happening here. しかし、それはここでは起こっていません。 You’ve got an incentive designed to sharpen thinking and accelerate creativity, and it does just the opposite. Vous avez un incitatif conçu pour aiguiser la pensée et accélérer la créativité, et cela fait exactement le contraire. あなたは思考を研ぎ澄まし、創造性を加速するように設計されたインセンティブを持っています、そしてそれはちょうど反対をします。 Você tem um incentivo projetado para aprimorar o pensamento e acelerar a criatividade, e faz exatamente o oposto. У вас есть стимул, предназначенный для обострения мышления и ускорения творчества, а это как раз наоборот. It dulls thinking and blocks creativity. Cela perturbe la pensée et bloque la créativité. それは思考を鈍らせ、創造性を妨げます。 Isso embota o pensamento e bloqueia a criatividade. Это притупляет мышление и блокирует творчество.

And what’s interesting about this experiment is that it’s not an aberration. Et ce qui est intéressant dans cette expérience, c'est que ce n'est pas une aberration. そして、この実験の興味深い点は、それが異常ではないということです。 E o interessante desse experimento é que não é uma aberração. This has been replicated over and over and over again, for nearly 40 years. これは、40年近くにわたって何度も何度も繰り返されてきました。 Isso foi replicado repetidamente, por quase 40 anos. These contingent motivators -- if you do this, then you get that -- work in some circumstances. Ces motivations contingentes - si vous faites cela, alors vous obtenez cela - fonctionnent dans certaines circonstances. これらの偶発的な動機-これを行うと、それを得る-いくつかの状況で動作します。 But for a lot of tasks, they actually either don’t work or, often, they do harm. しかし、多くのタスクでは、実際には機能しないか、または害を及ぼすことがよくあります。 Mas, para muitas tarefas, elas na verdade não funcionam ou, frequentemente, causam danos. This is one of the most robust findings in social science, and also one of the most ignored. C’est l’une des découvertes les plus solides en sciences sociales, mais aussi l’une des plus ignorées. これは社会科学で最も強力な発見の1つであり、最も無視されているものの1つでもあります。 Это одна из самых убедительных находок в социальной науке, а также одна из самых игнорируемых.

I spent the last couple of years looking at the science of human motivation, particularly the dynamics of extrinsic motivators and intrinsic motivators. 私はここ2、3年を人間の動機付けの科学、特に外因性の動機と内発的な動機のダイナミクスを調査することに費やしました。 And I’m telling you, it’s not even close. Et je vous le dis, ce n'est même pas proche. そして、私はあなたに言っています、それは近くさえありません。 E estou lhe dizendo, não é nem perto. If you look at the science, there is a mismatch between what science knows and what business does. 科学を見ると、科学が知っていることとビジネスが何をしているのかが一致していません。 Se você olhar para a ciência, há uma incompatibilidade entre o que a ciência sabe e o que os negócios fazem. And what’s alarming here is that our business operating system -- think of the set of assumptions and protocols beneath our businesses, how we motivate people, how we apply our human resources -- it’s built entirely around these extrinsic motivators, around carrots and sticks. Et ce qui est alarmant ici, c’est que notre système d’exploitation - pensez à l’ensemble des hypothèses et des protocoles qui sous-tendent nos activités, à la façon dont nous motivons les employés, à la façon dont nous appliquons nos ressources humaines - s’est entièrement construit autour de ces facteurs de motivation extrinsèques, autour des carottes et des bâtons. そしてここで憂慮すべきことは、私たちのビジネスオペレーティングシステムが、ビジネスの下にある一連の仮定とプロトコル、人をやる気にさせる方法、人的資源をどのように活用するかを考えると、完全にこれらの外因性の動機、ニンジンとスティックの周りに構築されているということです。 E o que é alarmante aqui é que nosso sistema operacional de negócios - pense no conjunto de suposições e protocolos sob nossos negócios, como motivamos as pessoas, como aplicamos nossos recursos humanos - ele é construído inteiramente em torno desses motivadores extrínsecos, em torno de cenouras e paus. И что вызывает здесь тревогу, так это то, что наша операционная система для бизнеса - представьте себе набор допущений и протоколов, лежащих в основе нашего бизнеса, то, как мы мотивируем людей, как мы применяем наши человеческие ресурсы, - она полностью построена на этих внешних мотиваторах, вокруг кнута и пряников. That’s actually fine for many kinds of 20th century tasks. C'est en fait bien pour de nombreux types de tâches du 20ème siècle. 実際には、20世紀のさまざまな種類のタスクには問題ありません。 Isso é bom para muitos tipos de tarefas do século XX. But for 21st century tasks, that mechanistic, reward-and-punishment approach doesn’t work, often doesn’t work, and often does harm. Mais pour les tâches du XXIe siècle, cette approche mécaniste, récompense et punition ne fonctionne pas, ne fonctionne souvent pas et nuit souvent. しかし、21世紀のタスクの場合、その機械的で報酬と罰のアプローチは機能せず、機能しないことが多く、害を及ぼすことがよくあります。 Mas para as tarefas do século XXI, essa abordagem mecanicista de recompensa e punição não funciona, geralmente não funciona e muitas vezes prejudica. Let me show you what I mean. 私の言っていることをお見せしましょう。

So Glucksberg did another experiment similar to this where he presented the problem in a slightly different way, like this up here. したがって、グリュックスベルクはこれと同様の別の実験を行い、ここでこのように、少し異なる方法で問題を提示しました。 Então Glucksberg fez outro experimento semelhante a este, onde ele apresentou o problema de uma maneira um pouco diferente, como esta aqui em cima. Okay? Attach the candle to the wall so the wax doesn’t drip onto the table. ろうそくを壁に取り付けて、ワックスがテーブルの上に垂れないようにします。 Prenda a vela na parede para que a cera não pingue sobre a mesa. Same deal. 同じ取引。 O mesmo negócio. You: we’re timing for norms. あなた:私たちは規範のタイミングです。 Você: estamos no tempo de normas. You: we’re incentivizing. Vous: nous incitons. あなた:私たちはインセンティブを与えています。 What happened this time? 今回はどうしたの? This time, the incentivized group kicked the other group’s butt. Cette fois, le groupe motivé a donné un coup de pied au cul de l'autre groupe. 今回は、奨励されたグループが他のグループのお尻を蹴り飛ばしました。 Desta vez, o grupo incentivado chutou a bunda do outro grupo. На этот раз мотивированная группа пнула задницу другой группы. Why? Because when the tacks are out of the box, it’s pretty easy isn’t it? タックが箱から出したら、それはかなり簡単ですね。 Porque quando as tachinhas estão prontas para uso, é bem fácil, não é? (Laughter)

If-then rewards work really well for those sorts of tasks, where there is a simple set of rules and a clear destination to go to. Les récompenses if-then fonctionnent vraiment bien pour ce type de tâches, où il existe un ensemble de règles simples et une destination claire à atteindre. if-then報酬は、単純な一連のルールと明確な目的地があるこのような種類のタスクに非常に適しています。 As recompensas If-then funcionam muito bem para esses tipos de tarefas, nas quais há um conjunto simples de regras e um destino claro a ser seguido. Rewards, by their very nature, narrow our focus, concentrate the mind; that’s why they work in so many cases. Les récompenses, de par leur nature même, limitent notre attention, concentrent l’esprit; c'est pourquoi ils travaillent dans de nombreux cas. 報酬は、その性質上、焦点を絞って心を集中させます。これが、多くの場合に機能する理由です。 As recompensas, por sua própria natureza, restringem nosso foco, concentram a mente; é por isso que eles trabalham em muitos casos. And so, for tasks like this, a narrow focus, where you just see the goal right there, zoom straight ahead to it, they work really well. Et donc, pour des tâches comme celle-ci, une mise au point étroite, où vous voyez simplement l'objectif, zoomez dessus, ils fonctionnent vraiment bien. したがって、このようなタスクの場合、目標をその場で確認し、まっすぐ前にズームするという狭い焦点で、非常にうまく機能します。 E assim, para tarefas como essa, um foco estreito, onde você apenas vê a meta ali, aproxima-se dela com zoom, elas funcionam muito bem. But for the real candle problem, you don’t want to be looking like this. しかし、実際のろうそくの問題では、このようになりたくはありません。 The solution is not over here. 解決策はここではありません。 A solução não está aqui. The solution is on the periphery. 解決策は周辺にあります。 You want to be looking around. Vous voulez regarder autour de vous. That reward actually narrows our focus and restricts our possibility. Cette récompense réduit réellement notre attention et restreint notre possibilité.

Let me tell you why this is so important. In western Europe, in many parts of Asia, in North America, in Australia, white-collar workers are doing less of this kind of work, and more of this kind of work. Na Europa Ocidental, em muitas partes da Ásia, na América do Norte, na Austrália, os trabalhadores de colarinho branco estão realizando menos esse tipo de trabalho e mais esse tipo de trabalho. That routine, rule-based, left-brain work -- certain kinds of accounting, certain kinds of financial analysis, certain kinds of computer programming -- has become fairly easy to outsource, fairly easy to automate. Ce travail de routine, basé sur des règles et basé sur le cerveau gauche - certains types de comptabilité, certains types d'analyse financière, certains types de programmation informatique - est devenu assez facile à sous-traiter et à automatiser. Esse trabalho rotineiro, baseado em regras e no lado esquerdo do cérebro - certos tipos de contabilidade, certos tipos de análise financeira, certos tipos de programação de computadores - tornou-se bastante fácil de terceirizar, bastante fácil de automatizar. Software can do it faster. Le logiciel peut le faire plus rapidement. O software pode fazer isso mais rápido. Low-cost providers around the world can do it cheaper. Les fournisseurs à bas coûts du monde entier peuvent le faire moins cher. Fornecedores de baixo custo em todo o mundo podem fazer isso mais barato. So what really matters are the more right-brained creative, conceptual kinds of abilities. Donc, ce qui compte vraiment, ce sont les types de capacités créatives et conceptuelles plus cérébrales.

Think about your own work. Think about your own work. Are the problems that you face, or even the problems we’ve been talking about here, are those kinds of problems -- do they have a clear set of rules, and a single solution? No. The rules are mystifying. Les règles sont mystifiantes. As regras são misteriosas. The solution, if it exists at all, is surprising and not obvious. A solução, se é que existe, é surpreendente e não óbvia. Everybody in this room is dealing with their own version of the candle problem. Todos nesta sala estão lidando com sua própria versão do problema da vela. And for candle problems of any kind, in any field, those if-then rewards, the things around which we’ve built so many of our businesses, don’t work. Et pour les problèmes de bougies de toutes sortes, dans tous les domaines, les récompenses «si», les éléments autour desquels nous avons construit tant d’entreprises ne fonctionnent pas. E para problemas de velas de qualquer tipo, em qualquer campo, essas recompensas se-então, as coisas em torno das quais construímos tantos de nossos negócios, não funcionam.

Now, I mean it makes me crazy. And this is not -- here’s the thing. Et ce n'est pas - voici la chose. E isso não é - aqui está a coisa. This is not a feeling. Ce n'est pas un sentiment. Okay? I’m a lawyer; I don’t believe in feelings. This is not a philosophy. I’m an American; I don’t believe in philosophy. (Laughter) This is a fact -- or, as we say in my hometown of Washington, D.C., a true fact. (Risos) Isso é um fato - ou, como dizemos em minha cidade natal, Washington, DC, um fato verdadeiro. (Laughter) (Applause) Let me give you an example of what I mean. (Risos) (Aplausos) Deixe-me dar um exemplo do que quero dizer. Let me marshal the evidence here, because I’m not telling you a story, I’m making a case. Permettez-moi de rassembler les éléments de preuve, car je ne vous raconte pas une histoire, je plaide en ma faveur. Deixe-me reunir as evidências aqui, porque não estou contando uma história, estou fazendo um caso.

Ladies and gentlemen of the jury, some evidence: Dan Ariely, one of the great economists of our time, he and three colleagues, did a study of some MIT students. Senhoras e senhores do júri, algumas evidências: Dan Ariely, um dos grandes economistas de nossa época, ele e três colegas, estudou alguns estudantes do MIT. They gave these MIT students a bunch of games, games that involved creativity, and motor skills, and concentration. Eles deram a esses alunos do MIT vários jogos, jogos que envolviam criatividade, habilidades motoras e concentração. And the offered them, for performance, three levels of rewards: small reward, medium reward, large reward. E eles ofereceram, por desempenho, três níveis de recompensa: recompensa pequena, recompensa média, recompensa grande. Okay? If you do really well you get the large reward, on down. Se você se sair muito bem, receberá uma grande recompensa. What happened? As long as the task involved only mechanical skill bonuses worked as they would be expected: the higher the pay, the better the performance. Tant que la tâche ne comporte que des bonus de compétence mécanique, ils fonctionnent comme prévu: plus le salaire est élevé, meilleure est la performance. Enquanto a tarefa envolvia apenas bônus de habilidade mecânica funcionavam como seria de esperar: quanto maior o salário, melhor o desempenho. Okay? But one the task called for even rudimentary cognitive skill, a larger reward led to poorer performance. Mais une tâche nécessitait des compétences cognitives même rudimentaires: une récompense plus importante conduisait à une performance plus médiocre. Porém, uma tarefa que exigia habilidades cognitivas ainda rudimentares, uma recompensa maior levou a um desempenho inferior. Но если задача требовала даже элементарных когнитивных навыков, большее вознаграждение приводило к снижению производительности.

Then they said, "Okay let’s see if there’s any cultural bias here. Então eles disseram: "Ok, vamos ver se existe algum viés cultural aqui. Lets go to Madurai, India and test this." Standard of living is lower. In Madurai, a reward that is modest in North American standards, is more meaningful there. Em Madurai, uma recompensa modesta nos padrões norte-americanos é mais significativa lá. Same deal. O mesmo negócio. A bunch of games, three levels of rewards. What happens? People offered the medium level of rewards did no better than people offered the small rewards. But this time, people offered the highest rewards, they did the worst of all. Mas desta vez, as pessoas ofereceram as maiores recompensas, fizeram o pior de tudo. In eight of the nine tasks we examined across three experiments, higher incentives led to worse performance. Em oito das nove tarefas que examinamos em três experimentos, incentivos mais altos levaram a um desempenho pior.

Is this some kind of touchy-feely socialist conspiracy going on here? Est-ce une sorte de complot socialiste délicat qui se passe ici? Isso é algum tipo de conspiração socialista sensível aqui? No. These are economists from MIT, from Carnegie Mellon, from the University of Chicago. Esses são economistas do MIT, da Carnegie Mellon, da Universidade de Chicago. And do you know who sponsored this research? E você sabe quem patrocinou esta pesquisa? The Federal Reserve Bank of the United States. O Federal Reserve Bank dos Estados Unidos. That’s the American experience.

Let’s go across the pond to the London School of Economics -- LSE, London School of Economics, alma mater of 11 Nobel Laureates in economics. Vamos atravessar a lagoa para a London School of Economics - LSE, London School of Economics, alma mater de 11 ganhadores do Nobel de economia. Training ground for great economic thinkers like George Soros, and Friedrich Hayek, and Mick Jagger. (Laughter) Last month, just last month, economists at LSE looked at 51 studies of pay-for-performance plans, inside of companies. Here’s what the economists there said: "We find that financial incentives can result in a negative impact on overall performance. " Aqui está o que os economistas disseram: "Achamos que os incentivos financeiros podem resultar em um impacto negativo no desempenho geral". There is a mismatch between what science knows and what business does. Há uma incompatibilidade entre o que a ciência sabe e o que os negócios fazem. And what worries me, as we stand here in the rubble of the economic collapse, is that too many organizations are making their decisions, their policies about talent and people, based on assumptions that are outdated, unexamined, and rooted more in folklore than in science. Et ce qui me préoccupe, alors que nous nous trouvons dans les décombres de la crise économique, c’est que trop d’organisations prennent leurs décisions, leurs politiques en matière de talent et de personnel, sur la base d’hypothèses obsolètes, non examinées et plus enracinées dans le folklore. science. E o que me preocupa, como estamos aqui nos escombros do colapso econômico, é que muitas organizações estão tomando suas decisões, suas políticas sobre talentos e pessoas, baseadas em suposições desatualizadas, não examinadas e enraizadas mais no folclore do que em Ciência. И что меня беспокоит, когда мы стоим здесь на обломках экономического коллапса, так это то, что слишком многие организации принимают свои решения, свою политику в отношении талантов и людей, основываясь на устаревших, неизученных и основанных больше на фольклоре, чем на допущениях. наука. And if we really want to get out of this economic mess, and if we really want high performance on those definitional tasks of the 21st century, the solution is not to do more of the wrong things, to entice people with a sweeter carrot, or threaten them with a sharper stick. Et si nous voulons vraiment sortir de ce pétrin économique et si nous voulons vraiment de hautes performances dans les tâches de définition du XXIe siècle, la solution consiste à ne pas faire plus de mauvaises choses, à séduire les gens avec une carotte plus sucrée, ou les menacer avec un bâton plus tranchant. E se realmente queremos sair dessa bagunça econômica e se realmente queremos alto desempenho nessas tarefas de definição do século XXI, a solução não é fazer mais coisas erradas, atrair pessoas com uma cenoura mais doce ou ameaçá-los com uma vara mais afiada. We need a whole new approach.

And the good news about all of this is that the scientists who’ve been studying motivation have given us this new approach. It’s an approach built much more around intrinsic motivation. É uma abordagem construída muito mais em torno da motivação intrínseca. Around the desire to do things because they matter, because we like it, because they’re interesting, because they are part of something important. Autour du désir de faire des choses parce qu'elles comptent, parce que nous aimons cela, parce qu'elles sont intéressantes, parce qu'elles font partie de quelque chose d'important. Em torno do desejo de fazer as coisas porque elas importam, porque gostamos, porque são interessantes, porque fazem parte de algo importante. And to my mind, that new operating system for our businesses revolves around three elements: autonomy, mastery and purpose. Et à mon sens, ce nouveau système d'exploitation pour nos entreprises s'articule autour de trois éléments: autonomie, maîtrise et finalité. E, a meu ver, esse novo sistema operacional para nossos negócios gira em torno de três elementos: autonomia, domínio e propósito. Autonomy: the urge to direct our own lives. Autonomie: l'envie de diriger nos propres vies. Autonomia: o desejo de dirigir nossas próprias vidas. Mastery: the desire to get better and better at something that matters. Purpose: the yearning to do what we do in the service of something larger than ourselves. But: le désir de faire ce que nous faisons au service de quelque chose de plus grand que nous-mêmes. Objetivo: o desejo de fazer o que fazemos a serviço de algo maior que nós mesmos. These are the building blocks of an entirely new operating system for our businesses.

I want to talk today only about autonomy. In the 20th century, we came up with this idea of management. Au 20ème siècle, nous avons eu cette idée de gestion. Management did not emanate from nature. La direction n'a pas émané de la nature. Management is like -- it’s not a tree, it’s a television set. A administração é como - não é uma árvore, é um aparelho de televisão. Okay? Somebody invented it. And it doesn’t mean it’s going to work forever. Management is great. Traditional notions of management are great if you want compliance. Les notions traditionnelles de gestion sont excellentes si vous voulez la conformité. Noções tradicionais de gerenciamento são ótimas se você deseja conformidade. Традиционные понятия управления хороши, если вы хотите соблюдения. But if you want engagement, self-direction works better. Mais si vous voulez un engagement, l'auto-direction marche mieux.

Let me give you some examples of some kind of radical notions of self-direction. What this means -- you don’t see a lot of it, but you see the first stirrings of something really interesting going on, because what it means is paying people adequately and fairly, absolutely -- getting the issue of money off the table, and then giving people lots of autonomy. Ce que cela signifie - vous n'en voyez pas beaucoup, mais vous voyez les premières émotions d'un événement vraiment intéressant, parce que cela signifie que les gens sont payés correctement et équitablement, absolument - en éliminant la question de l'argent , puis en donnant aux gens beaucoup d’autonomie. Let me give you some examples.

How many of you have heard of the company Atlassian? Quantos de vocês já ouviram falar da empresa Atlassian? It looks like less than half. Parece menos da metade. (Laughter) Atlassian is an Australian software company. And they do something incredibly cool. A few times a year they tell their engineers, "Go for the next 24 hours and work on anything you want, as long as it’s not part of your regular job. Work on anything you want." So that engineers use this time to come up with a cool patch for code, come up with an elegant hack. Pour que les ingénieurs utilisent ce moment pour créer un correctif code pour le code, créez un hack élégant. Para que os engenheiros usem esse tempo para criar um patch legal de código, criar um hack elegante. Then they present all of the stuff that they’ve developed to their teammates, to the rest of the company, in this wild and wooly all-hands meeting at the end of the day. Ils présentent ensuite tous les éléments qu’ils ont développés à leurs coéquipiers, au reste de la société, lors de cette réunion sauvage et laineuse à la fin de la journée. Em seguida, eles apresentam todas as coisas que eles desenvolveram para seus colegas de equipe, para o resto da empresa, nesta reunião selvagem e cheia de mãos no final do dia. Затем они представляют все то, что они разработали, своим товарищам по команде, остальной части компании, на этой дикой и шерстяной встрече в конце дня. And then, being Australians, everybody has a beer. E então, sendo australianos, todo mundo toma uma cerveja.

They call them FedEx Days. Why? Because you have to deliver something overnight. Parce que vous devez livrer quelque chose du jour au lendemain. Porque você tem que entregar algo da noite para o dia. It’s pretty. É bonito. It’s not bad. It’s a huge trademark violation, but it’s pretty clever. C'est une violation de marque énorme, mais c'est assez intelligent. (Laughter) That one day of intense autonomy has produced a whole array of software fixes that might never have existed. (Rire) Cette journée d'autonomie intense a produit toute une série de correctifs logiciels qui n'auraient peut-être jamais existé. (Risos) Que um dia de intensa autonomia produziu toda uma série de correções de software que talvez nunca existissem.

And it’s worked so well that Atlassian has taken it to the next level with 20 Percent Time -- done, famously, at Google -- where engineers can work, spend 20 percent of their time working on anything they want. They have autonomy over their time, their task, their team, their technique. Okay? Radical amounts of autonomy. And at Google, as many of you know, about half of the new products in a typical year are birthed during that 20 Percent Time: things like Gmail, Orkut, Google News.

Let me give you an even more radical example of it: something called the Results Only Work Environment, the ROWE, created by two American consultants, in place in place at about a dozen companies around North America. Deixe-me dar um exemplo ainda mais radical: algo chamado Results Only Work Environment, o ROWE, criado por dois consultores americanos, em vigor em cerca de uma dúzia de empresas na América do Norte. In a ROWE people don’t have schedules. Em uma ROWE, as pessoas não têm horários. They show up when they want. Eles aparecem quando querem. They don’t have to be in the office at a certain time, or any time. They just have to get their work done. Eles só precisam fazer o trabalho. How they do it, when they do it, where they do it, is totally up to them. Como eles fazem, quando fazem, onde fazem, depende totalmente deles. Meetings in these kinds of environments are optional.

What happens? Almost across the board, productivity goes up, worker engagement goes up, worker satisfaction goes up, turnover goes down. Presque partout, la productivité augmente, l'engagement des travailleurs augmente, la satisfaction des employés augmente, le roulement diminue. Autonomy, mastery and purpose, These are the building blocks of a new way of doing things. Autonomie, maîtrise et finalité, Ce sont les fondements d’une nouvelle façon de faire les choses. Autonomia, domínio e propósito, esses são os alicerces de uma nova maneira de fazer as coisas. Now some of you might look at this and say, "Hmm, that sounds nice, but it’s Utopian." Agora, alguns de vocês podem olhar para isso e dizer: "Hmm, isso soa bem, mas é utópico". And I say, "Nope. I have proof. " Eu tenho provas. " The mid-1990s, Microsoft started an encyclopedia called Encarta. They had deployed all the right incentives, all the right incentives. They paid professionals to write and edit thousands of articles. Well-compensated managers oversaw the whole thing to make sure it came in on budget and on time. Des gestionnaires bien rémunérés ont supervisé l’ensemble du processus pour s’assurer qu’il respectait le budget et les délais impartis. A few years later another encyclopedia got started. Different model, right? Do it for fun. Faça isso por diversão. No one gets paid a cent, or a Euro or a Yen. Personne ne reçoit un centime, un euro ou un yen. Do it because you like to do it.

Now if you had, just 10 years ago, if you had gone to an economist, anywhere, and said, "Hey, I’ve got these two different models for creating an encyclopedia. If they went head to head, who would win?" S'ils se disputaient, qui gagnerait? " Se eles se enfrentassem, quem venceria? " 10 years ago you could not have found a single sober economist anywhere on planet Earth who would have predicted the Wikipedia model. Há dez anos, você não poderia encontrar um único economista sóbrio em qualquer lugar do planeta Terra que previsse o modelo da Wikipedia.

This is the titanic battle between these two approaches. This is the Ali-Frazier of motivation. Este é o Ali-Frazier da motivação. Right? This is the Thrilla' in Manila. Alright? Intrinsic motivators versus extrinsic motivators. Autonomy, mastery and purpose, versus carrot and sticks. And who wins? Intrinsic motivation, autonomy, mastery and purpose, in a knockout. Let me wrap up.

There is a mismatch between what science knows and what business does. And here is what science knows. One: Those 20th century rewards, those motivators we think are a natural part of business, do work, but only in a surprisingly narrow band of circumstances. Um: as recompensas do século XX, os motivadores que pensamos serem uma parte natural dos negócios, funcionam, mas apenas em uma faixa surpreendentemente estreita de circunstâncias. Two: Those if-then rewards often destroy creativity. Dois: Essas recompensas se-então frequentemente destroem a criatividade. Three: The secret to high performance isn’t rewards and punishments, but that unseen intrinsic drive -- the drive to do things for their own sake. Terceiro: o segredo do alto desempenho não são recompensas e punições, mas esse impulso intrínseco invisível - o desejo de fazer as coisas por eles mesmos. The drive to do things cause they matter. O desejo de fazer as coisas é importante.

And here’s the best part. Here’s the best part. We already know this. The science confirms what we know in our hearts. So, if we repair this mismatch between what science knows and what business does, if we bring our motivation, notions of motivation into the 21st century, if we get past this lazy, dangerous, ideology of carrots and sticks, we can strengthen our businesses, we can solve a lot of those candle problems, and maybe, maybe, maybe we can change the world. Portanto, se repararmos essa incompatibilidade entre o que a ciência sabe e o que os negócios fazem, se levarmos nossa motivação, noções de motivação para o século XXI, se superarmos essa ideologia preguiçosa e perigosa de cenouras e paus, podemos fortalecer nossos negócios , podemos resolver muitos desses problemas de vela e talvez, talvez, talvez possamos mudar o mundo. I rest my case. Je repose mon cas. Eu descanso meu caso. (Applause)