1
00:00:13,300 --> 00:00:15,757
I need to make a confession
at the outset here.

2
00:00:15,840 --> 00:00:20,590
A little over 20 years ago,
I did something that I regret,

3
00:00:21,670 --> 00:00:24,340
something that I'm not
particularly proud of.

4
00:00:25,040 --> 00:00:28,357
Something that, in many ways,
I wish no one would ever know,

5
00:00:28,440 --> 00:00:31,637
but here I feel kind of obliged to reveal.

6
00:00:31,720 --> 00:00:32,740
(Laughter)

7
00:00:34,000 --> 00:00:40,907
In the late 1980s, in a moment of youthful
indiscretion, I went to law school.

8
00:00:40,990 --> 00:00:42,930
(Laughter)

9
00:00:45,670 --> 00:00:48,047
In America, law is a professional degree:

10
00:00:48,130 --> 00:00:50,777
after your university degree,
you go on to law school.

11
00:00:50,860 --> 00:00:52,300
When I got to law school,

12
00:00:53,130 --> 00:00:54,430
I didn't do very well.

13
00:00:55,740 --> 00:00:57,607
To put it mildly, I didn't do very well.

14
00:00:57,690 --> 00:01:00,637
I, in fact, graduated in the
part of my law school class

15
00:01:00,720 --> 00:01:04,077
that made the top 90% possible.

16
00:01:04,160 --> 00:01:06,380
(Laughter)

17
00:01:08,160 --> 00:01:09,210
Thank you.

18
00:01:10,980 --> 00:01:16,487
I never practiced law a day in my life;
I pretty much wasn't allowed to.

19
00:01:16,570 --> 00:01:18,170
(Laughter)

20
00:01:19,310 --> 00:01:25,077
But today, against my better judgment,
against the advice of my own wife,

21
00:01:25,160 --> 00:01:29,077
I want to try to dust off
some of those legal skills --

22
00:01:29,160 --> 00:01:31,457
what's left of those legal skills.

23
00:01:31,540 --> 00:01:33,290
I don't want to tell you a story.

24
00:01:34,160 --> 00:01:40,077
I want to make a case. I want
to make a hard-headed, evidence-based,

25
00:01:40,160 --> 00:01:46,110
dare I say lawyerly case,
for rethinking how we run our businesses.

26
00:01:47,950 --> 00:01:51,347
So, ladies and gentlemen
of the jury, take a look at this.

27
00:01:51,430 --> 00:01:53,677
This is called the candle problem.

28
00:01:53,760 --> 00:01:59,077
Some of you might know it. It's created in
1945 by a psychologist named Karl Duncker.

29
00:01:59,160 --> 00:02:01,077
He created this experiment

30
00:02:01,160 --> 00:02:04,227
that is used in many other
experiments in behavioral science.

31
00:02:04,310 --> 00:02:07,077
And here's how it works.
Suppose I'm the experimenter.

32
00:02:07,160 --> 00:02:12,967
I bring you into a room. I give you a
candle, some thumbtacks and some matches.

33
00:02:13,050 --> 00:02:17,077
And I say to you, "Your job
is to attach the candle to the wall

34
00:02:17,160 --> 00:02:20,227
so the wax doesn't drip onto the table."

35
00:02:20,310 --> 00:02:21,787
Now what would you do?

36
00:02:21,870 --> 00:02:25,407
Many people begin trying
to thumbtack the candle to the wall.

37
00:02:25,490 --> 00:02:31,517
Doesn't work. I saw somebody kind
of make the motion over here --

38
00:02:31,600 --> 00:02:34,647
some people have a great idea
where they light the match,

39
00:02:34,730 --> 00:02:37,607
melt the side of the candle,
try to adhere it to the wall.

40
00:02:37,690 --> 00:02:39,780
It's an awesome idea. Doesn't work.

41
00:02:40,830 --> 00:02:45,077
And eventually, after five or ten minutes,
most people figure out the solution,

42
00:02:45,160 --> 00:02:46,847
which you can see here.

43
00:02:46,930 --> 00:02:50,657
The key is to overcome what's
called functional fixedness.

44
00:02:50,740 --> 00:02:54,647
You look at that box and you see it
only as a receptacle for the tacks.

45
00:02:54,730 --> 00:02:58,967
But it can also have this other function,
as a platform for the candle.

46
00:02:59,050 --> 00:03:00,077
The candle problem.

47
00:03:00,160 --> 00:03:04,077
I want to tell you about
an experiment using the candle problem,

48
00:03:04,160 --> 00:03:08,697
done by a scientist named Sam Glucksberg,
who is now at Princeton University, US,

49
00:03:08,780 --> 00:03:12,077
This shows the power of incentives.

50
00:03:12,160 --> 00:03:14,077
He gathered his participants and said:

51
00:03:14,160 --> 00:03:17,927
"I'm going to time you,
how quickly you can solve this problem."

52
00:03:18,010 --> 00:03:22,077
To one group he said, "I'm going
to time you to establish norms,

53
00:03:22,160 --> 00:03:26,637
averages for how long it typically takes
someone to solve this sort of problem."

54
00:03:26,720 --> 00:03:29,077
To the second group he offered rewards.

55
00:03:29,160 --> 00:03:34,920
He said, "If you're in the top 25% of
the fastest times, you get five dollars.

56
00:03:35,870 --> 00:03:41,077
If you're the fastest of everyone we're
testing here today, you get 20 dollars."

57
00:03:41,160 --> 00:03:43,987
Now this is several years ago,
adjusted for inflation,

58
00:03:44,070 --> 00:03:46,557
it's a decent sum of money
for a few minutes of work.

59
00:03:46,640 --> 00:03:52,640
It's a nice motivator. Question: How much
faster did this group solve the problem?

60
00:03:53,540 --> 00:04:00,387
Answer: It took them, on average,
three and a half minutes longer.

61
00:04:00,470 --> 00:04:03,477
3.5 min longer.
This makes no sense, right?

62
00:04:03,560 --> 00:04:06,607
I mean, I'm an American.
I believe in free markets.

63
00:04:06,690 --> 00:04:09,077
That's not how it's
supposed to work, right?

64
00:04:09,160 --> 00:04:14,227
(Laughter) If you want people to perform
better, you reward them. Right?

65
00:04:14,310 --> 00:04:17,077
Bonuses, commissions,
their own reality show.

66
00:04:17,160 --> 00:04:19,180
Incentivize them.

67
00:04:20,020 --> 00:04:23,387
That's how business works.
But that's not happening here.

68
00:04:23,470 --> 00:04:25,077
You've got an incentive designed

69
00:04:25,160 --> 00:04:31,077
to sharpen thinking and accelerate
creativity, and it does just the opposite.

70
00:04:31,160 --> 00:04:34,077
It dulls thinking and blocks creativity.

71
00:04:34,160 --> 00:04:37,627
What's interesting about this experiment
is that it's not an aberration.

72
00:04:37,710 --> 00:04:43,777
This has been replicated over
and over again for nearly 40 years.

73
00:04:43,860 --> 00:04:48,477
These contingent motivators -- if
you do this, then you get that --

74
00:04:48,560 --> 00:04:53,917
work in some circumstances. But for a lot
of tasks, they actually either don't work

75
00:04:54,000 --> 00:04:55,890
or, often, they do harm.

76
00:04:56,850 --> 00:05:01,740
This is one of the most robust
findings in social science,

77
00:05:02,940 --> 00:05:05,237
and also one of the most ignored.

78
00:05:05,320 --> 00:05:08,947
I spent the last couple of years looking
at the science of human motivation,

79
00:05:09,030 --> 00:05:13,077
particularly the dynamics of extrinsic
motivators and intrinsic motivators.

80
00:05:13,160 --> 00:05:15,517
And I'm telling you, it's not even close.

81
00:05:15,600 --> 00:05:19,747
If you look at the science, there
is a mismatch between what science knows

82
00:05:19,830 --> 00:05:21,187
and what business does.

83
00:05:21,270 --> 00:05:24,457
What's alarming here is that
our business operating system --

84
00:05:24,540 --> 00:05:27,787
think of the set of assumptions
and protocols beneath our businesses,

85
00:05:27,870 --> 00:05:31,580
how we motivate people,
how we apply our human resources--

86
00:05:32,630 --> 00:05:37,397
it's built entirely around these extrinsic
motivators, around carrots and sticks.

87
00:05:37,480 --> 00:05:41,607
That's actually fine for many
kinds of 20th century tasks.

88
00:05:41,690 --> 00:05:43,747
But for 21st century tasks,

89
00:05:43,830 --> 00:05:50,497
that mechanistic, reward-and-punishment
approach doesn't work, often doesn't work,

90
00:05:50,580 --> 00:05:52,897
and often does harm. Let me show you.

91
00:05:52,980 --> 00:05:55,997
Glucksberg did another similar experiment,

92
00:05:56,080 --> 00:05:59,740
he presented the problem in a slightly
different way, like this up here.

93
00:06:00,660 --> 00:06:03,877
Attach the candle to the wall so
the wax doesn't drip onto the table.

94
00:06:03,960 --> 00:06:06,377
Same deal. You: we're timing for norms.

95
00:06:06,460 --> 00:06:10,380
You: we're incentivizing.
What happened this time?

96
00:06:11,360 --> 00:06:17,507
This time, the incentivized group
kicked the other group's butt.

97
00:06:17,590 --> 00:06:18,600
Why?

98
00:06:19,410 --> 00:06:23,580
Because when the tacks are out
of the box, it's pretty easy isn't it?

99
00:06:25,420 --> 00:06:27,807
(Laughter)

100
00:06:27,890 --> 00:06:32,817
If-then rewards work really
well for those sorts of tasks,

101
00:06:32,900 --> 00:06:37,077
where there is a simple set of rules
and a clear destination to go to.

102
00:06:37,160 --> 00:06:41,077
Rewards, by their very nature,
narrow our focus, concentrate the mind;

103
00:06:41,160 --> 00:06:43,437
that's why they work in so many cases.

104
00:06:43,520 --> 00:06:48,917
So, for tasks like this, a narrow focus,
where you just see the goal right there,

105
00:06:49,000 --> 00:06:51,977
zoom straight ahead to it,
they work really well.

106
00:06:52,060 --> 00:06:56,737
But for the real candle problem,
you don't want to be looking like this.

107
00:06:56,820 --> 00:06:59,887
The solution is on the periphery.
You want to be looking around.

108
00:06:59,970 --> 00:07:04,077
That reward actually narrows our focus
and restricts our possibility.

109
00:07:04,160 --> 00:07:06,210
Let me tell you why this is so important.

110
00:07:07,340 --> 00:07:11,487
In western Europe, in many parts of Asia,

111
00:07:11,570 --> 00:07:14,287
in North America, in Australia,

112
00:07:14,370 --> 00:07:17,877
white-collar workers are doing
less of this kind of work,

113
00:07:17,960 --> 00:07:20,340
and more of this kind of work.

114
00:07:22,020 --> 00:07:24,937
That routine, rule-based,
left-brain work --

115
00:07:25,020 --> 00:07:29,397
certain kinds of accounting, financial
analysis, computer programming --

116
00:07:29,480 --> 00:07:33,667
has become fairly easy to outsource,
fairly easy to automate.

117
00:07:33,750 --> 00:07:38,217
Software can do it faster.
Low-cost providers can do it cheaper.

118
00:07:38,300 --> 00:07:41,207
So what really matters

119
00:07:41,290 --> 00:07:45,867
are the more right-brained creative,
conceptual kinds of abilities.

120
00:07:45,950 --> 00:07:50,100
Think about your own work.
Think about your own work.

121
00:07:51,030 --> 00:07:52,557
Are the problems that you face,

122
00:07:52,640 --> 00:07:55,077
or even the problems we've
been talking about here,

123
00:07:55,160 --> 00:07:59,597
do they have a clear set of rules,
and a single solution?

124
00:07:59,680 --> 00:08:04,347
No. The rules are mystifying.
The solution, if it exists at all,

125
00:08:04,430 --> 00:08:07,077
is surprising and not obvious.

126
00:08:07,160 --> 00:08:14,077
Everybody in this room is dealing with
their own version of the candle problem.

127
00:08:14,160 --> 00:08:18,927
And for candle problems
of any kind, in any field,

128
00:08:19,010 --> 00:08:21,947
those if-then rewards,

129
00:08:22,030 --> 00:08:28,067
the things around which we've built
so many of our businesses, don't work!

130
00:08:28,150 --> 00:08:32,517
It makes me crazy. And here's the thing.

131
00:08:32,600 --> 00:08:34,650
This is not a feeling.

132
00:08:35,860 --> 00:08:38,887
Okay? I'm a lawyer;
I don't believe in feelings.

133
00:08:38,970 --> 00:08:44,847
This is not a philosophy. I'm an American;
I don't believe in philosophy.

134
00:08:44,930 --> 00:08:46,610
(Laughter)

135
00:08:47,520 --> 00:08:52,907
This is a fact -- or, as we say
in my hometown of Washington, D.C.,

136
00:08:52,990 --> 00:08:56,987
a true fact. (Laughter)

137
00:08:57,070 --> 00:09:02,467
(Applause) Let me give you an example.

138
00:09:02,550 --> 00:09:04,077
Let me marshal the evidence here.

139
00:09:04,160 --> 00:09:06,217
I'm not telling a story,
I'm making a case.

140
00:09:06,300 --> 00:09:08,507
Ladies and gentlemen
of the jury, some evidence:

141
00:09:08,590 --> 00:09:11,907
Dan Ariely, one of the great
economists of our time,

142
00:09:11,990 --> 00:09:15,407
he and three colleagues did
a study of some MIT students.

143
00:09:15,490 --> 00:09:20,077
They gave these MIT students a bunch
of games, games that involved creativity,

144
00:09:20,160 --> 00:09:22,377
and motor skills, and concentration.

145
00:09:22,460 --> 00:09:26,527
And the offered them, for performance,
three levels of rewards:

146
00:09:26,610 --> 00:09:30,797
small reward, medium reward, large reward.

147
00:09:30,880 --> 00:09:34,957
If you do really well you
get the large reward, on down.

148
00:09:35,040 --> 00:09:39,077
What happened? As long as the task
involved only mechanical skill

149
00:09:39,160 --> 00:09:41,077
bonuses worked as they would be expected:

150
00:09:41,160 --> 00:09:44,797
the higher the pay,
the better the performance.

151
00:09:44,880 --> 00:09:51,077
Okay? But once the task called
for even rudimentary cognitive skill,

152
00:09:51,160 --> 00:09:57,177
a larger reward led to poorer performance.

153
00:09:57,260 --> 00:10:00,507
Then they said, "Let's see if
there's any cultural bias here.

154
00:10:00,590 --> 00:10:02,487
Let's go to Madurai, India and test it."

155
00:10:02,570 --> 00:10:04,077
Standard of living is lower.

156
00:10:04,160 --> 00:10:07,577
In Madurai, a reward that is modest
in North American standards,

157
00:10:07,660 --> 00:10:09,000
is more meaningful there.

158
00:10:09,860 --> 00:10:13,197
Same deal. A bunch of games,
three levels of rewards.

159
00:10:13,280 --> 00:10:14,370
What happens?

160
00:10:15,300 --> 00:10:18,247
People offered the medium level of rewards

161
00:10:18,330 --> 00:10:20,847
did no better than people
offered the small rewards.

162
00:10:20,930 --> 00:10:26,930
But this time, people offered the highest
rewards, they did the worst of all.

163
00:10:28,980 --> 00:10:32,287
In eight of the nine tasks we
examined across three experiments,

164
00:10:32,370 --> 00:10:35,840
higher incentives led
to worse performance.

165
00:10:37,630 --> 00:10:43,547
Is this some kind of touchy-feely
socialist conspiracy going on here?

166
00:10:43,630 --> 00:10:46,347
No, these are economists from MIT,

167
00:10:46,430 --> 00:10:49,077
from Carnegie Mellon,
from the University of Chicago.

168
00:10:49,160 --> 00:10:51,717
Do you know who sponsored this research?

169
00:10:51,800 --> 00:10:55,867
The Federal Reserve Bank
of the United States.

170
00:10:55,950 --> 00:10:57,707
That's the American experience.

171
00:10:57,790 --> 00:11:00,507
Let's go across the pond
to the London School of Economics,

172
00:11:00,590 --> 00:11:03,077
LSE, London School of Economics,

173
00:11:03,160 --> 00:11:06,547
alma mater of eleven Nobel
Laureates in economics.

174
00:11:06,630 --> 00:11:09,077
Training ground for great
economic thinkers

175
00:11:09,160 --> 00:11:13,387
like George Soros,
and Friedrich Hayek, and Mick Jagger.

176
00:11:13,470 --> 00:11:18,027
(Laughter) Last month, just last month,

177
00:11:18,110 --> 00:11:21,077
economists at LSE looked at 51 studies

178
00:11:21,160 --> 00:11:24,077
of pay-for-performance plans,
inside of companies.

179
00:11:24,160 --> 00:11:27,377
Here's what they said:
"We find that financial incentives

180
00:11:27,460 --> 00:11:31,510
can result in a negative
impact on overall performance."

181
00:11:32,940 --> 00:11:38,077
There is a mismatch between what
science knows and what business does.

182
00:11:38,160 --> 00:11:43,077
And what worries me, as we stand here
in the rubble of the economic collapse,

183
00:11:43,160 --> 00:11:47,077
is that too many organizations
are making their decisions,

184
00:11:47,160 --> 00:11:53,627
their policies about talent and people,
based on assumptions that are outdated,

185
00:11:53,710 --> 00:11:57,680
unexamined, and rooted more
in folklore than in science.

186
00:11:58,560 --> 00:12:01,077
And if we really want to get
out of this economic mess,

187
00:12:01,160 --> 00:12:03,197
if we really want high performance

188
00:12:03,280 --> 00:12:05,667
on those definitional
tasks of the 21st century,

189
00:12:05,750 --> 00:12:11,627
the solution is not to do
more of the wrong things,

190
00:12:11,710 --> 00:12:16,397
to entice people with a sweeter carrot,
or threaten them with a sharper stick.

191
00:12:16,480 --> 00:12:20,077
We need a whole new approach.
The good news is that the scientists

192
00:12:20,160 --> 00:12:23,287
who've been studying motivation
have given us this new approach.

193
00:12:23,370 --> 00:12:26,407
It's built much more
around intrinsic motivation.

194
00:12:26,490 --> 00:12:28,887
Around the desire to do
things because they matter,

195
00:12:28,970 --> 00:12:32,477
because we like it, they're interesting,
or part of something important.

196
00:12:32,560 --> 00:12:36,077
And to my mind, that new
operating system for our businesses

197
00:12:36,160 --> 00:12:41,077
revolves around three elements:
autonomy, mastery and purpose.

198
00:12:41,160 --> 00:12:44,077
Autonomy: the urge
to direct our own lives.

199
00:12:44,160 --> 00:12:48,347
Mastery: the desire to get better
and better at something that matters.

200
00:12:48,430 --> 00:12:51,077
Purpose: the yearning to do what we do

201
00:12:51,160 --> 00:12:54,297
in the service of something
larger than ourselves.

202
00:12:54,380 --> 00:12:57,617
These are the building blocks
of an entirely new operating system

203
00:12:57,700 --> 00:13:01,720
for our businesses.
I want to talk today only about autonomy.

204
00:13:03,160 --> 00:13:06,077
In the 20th century, we came
up with this idea of management.

205
00:13:06,160 --> 00:13:08,397
Management did not emanate from nature.

206
00:13:08,480 --> 00:13:12,077
Management is not a tree,
it's a television set.

207
00:13:12,160 --> 00:13:16,347
Somebody invented it. It doesn't
mean it's going to work forever.

208
00:13:16,430 --> 00:13:20,457
Management is great. Traditional
notions of management are great

209
00:13:20,540 --> 00:13:25,287
if you want compliance. But if you want
engagement, self-direction works better.

210
00:13:25,370 --> 00:13:29,347
Some examples of some kind
of radical notions of self-direction.

211
00:13:29,430 --> 00:13:32,307
You don't see a lot of it,

212
00:13:32,390 --> 00:13:35,807
but you see the first stirrings
of something really interesting going on,

213
00:13:35,890 --> 00:13:39,477
what it means is paying people
adequately and fairly, absolutely --

214
00:13:39,560 --> 00:13:43,787
getting the issue of money off the table,
and then giving people lots of autonomy.

215
00:13:43,870 --> 00:13:48,110
Some examples. How many of you
have heard of the company Atlassian?

216
00:13:49,630 --> 00:13:52,507
It looks like less than half. (Laughter)

217
00:13:52,590 --> 00:13:57,077
Atlassian is an Australian
software company.

218
00:13:57,160 --> 00:13:59,067
And they do something incredibly cool.

219
00:13:59,150 --> 00:14:01,837
A few times a year they
tell their engineers,

220
00:14:01,920 --> 00:14:05,867
"Go for the next 24 hours
and work on anything you want,

221
00:14:05,950 --> 00:14:08,007
as long as it's not
part of your regular job.

222
00:14:08,090 --> 00:14:09,417
Work on anything you want."

223
00:14:09,500 --> 00:14:13,207
Engineers use this time to come
up with a cool patch for code,

224
00:14:13,290 --> 00:14:14,667
come up with an elegant hack.

225
00:14:14,750 --> 00:14:17,657
Then they present all of the
stuff that they've developed

226
00:14:17,740 --> 00:14:20,407
to their teammates,
to the rest of the company,

227
00:14:20,490 --> 00:14:24,377
in this wild and woolly all-hands
meeting at the end of the day.

228
00:14:24,460 --> 00:14:26,597
Being Australians, everybody has a beer.

229
00:14:26,680 --> 00:14:28,700
They call them FedEx Days.

230
00:14:29,610 --> 00:14:30,640
Why?

231
00:14:31,670 --> 00:14:34,070
Because you have to deliver
something overnight.

232
00:14:34,980 --> 00:14:36,487
It's pretty; not bad.

233
00:14:36,570 --> 00:14:39,177
It's a huge trademark violation,
but it's pretty clever.

234
00:14:39,260 --> 00:14:42,237
(Laughter) That one
day of intense autonomy

235
00:14:42,320 --> 00:14:46,077
has produced a whole array of software
fixes that might never have existed.

236
00:14:46,160 --> 00:14:49,167
It's worked so well that Atlassian
has taken it to the next level

237
00:14:49,250 --> 00:14:52,447
with 20% time -- done,
famously, at Google --

238
00:14:52,530 --> 00:14:56,497
where engineers can spend 20% of their
time working on anything they want.

239
00:14:56,580 --> 00:15:00,427
They have autonomy over their time,
their task, their team, their technique.

240
00:15:00,510 --> 00:15:06,357
Radical amounts of autonomy.
And at Google, as many of you know,

241
00:15:06,440 --> 00:15:08,707
about half of the new
products in a typical year

242
00:15:08,790 --> 00:15:14,077
are birthed during that 20% time:
things like Gmail, Orkut, Google News.

243
00:15:14,160 --> 00:15:17,017
Let me give you an even
more radical example of it:

244
00:15:17,100 --> 00:15:20,917
something called the Results
Only Work Environment (the ROWE),

245
00:15:21,000 --> 00:15:23,007
created by two American consultants,

246
00:15:23,090 --> 00:15:25,707
in place at a dozen companies
around North America.

247
00:15:25,790 --> 00:15:28,400
In a ROWE people don't have schedules.

248
00:15:29,730 --> 00:15:31,317
They show up when they want.

249
00:15:31,400 --> 00:15:35,397
They don't have to be in the office
at a certain time, or any time.

250
00:15:35,480 --> 00:15:37,367
They just have to get their work done.

251
00:15:37,450 --> 00:15:41,610
How they do it, when they do it,
where they do it, is totally up to them.

252
00:15:42,640 --> 00:15:45,980
Meetings in these kinds
of environments are optional.

253
00:15:47,040 --> 00:15:50,177
What happens? Almost across the board,

254
00:15:50,260 --> 00:15:53,407
productivity goes up,
worker engagement goes up,

255
00:15:53,490 --> 00:15:57,077
worker satisfaction goes up,
turnover goes down.

256
00:15:57,160 --> 00:15:59,077
Autonomy, mastery and purpose,

257
00:15:59,160 --> 00:16:01,717
the building blocks of a
new way of doing things.

258
00:16:01,800 --> 00:16:06,620
Some of you might look at this and say,
"Hmm, that sounds nice, but it's Utopian."

259
00:16:07,520 --> 00:16:09,000
And I say, "Nope.

260
00:16:10,520 --> 00:16:16,077
I have proof." The mid-1990s, Microsoft
started an encyclopedia called Encarta.

261
00:16:16,160 --> 00:16:19,417
They had deployed all
the right incentives,

262
00:16:19,500 --> 00:16:23,287
They paid professionals to write
and edit thousands of articles.

263
00:16:23,370 --> 00:16:25,907
Well-compensated managers
oversaw the whole thing

264
00:16:25,990 --> 00:16:28,290
to make sure it came
in on budget and on time.

265
00:16:30,160 --> 00:16:32,607
A few years later, another
encyclopedia got started.

266
00:16:32,690 --> 00:16:34,090
Different model, right?

267
00:16:35,510 --> 00:16:39,760
Do it for fun. No one gets
paid a cent, or a euro or a yen.

268
00:16:41,260 --> 00:16:43,117
Do it because you like to do it.

269
00:16:43,200 --> 00:16:47,347
Just 10 years ago, if you had
gone to an economist, anywhere,

270
00:16:47,430 --> 00:16:50,947
"Hey, I've got these two different
models for creating an encyclopedia.

271
00:16:51,030 --> 00:16:53,897
If they went head to head, who would win?"

272
00:16:53,980 --> 00:16:57,487
10 years ago you could not have
found a single sober economist

273
00:16:57,570 --> 00:17:02,627
anywhere on planet Earth who would
have predicted the Wikipedia model.

274
00:17:02,710 --> 00:17:05,347
This is the titanic battle
between these two approaches.

275
00:17:05,430 --> 00:17:08,437
This is the Ali-Frazier
of motivation, right?

276
00:17:08,520 --> 00:17:10,297
This is the Thrilla in Manila.

277
00:17:10,380 --> 00:17:13,497
Intrinsic motivators
versus extrinsic motivators.

278
00:17:13,580 --> 00:17:17,657
Autonomy, mastery and purpose,
versus carrot and sticks, and who wins?

279
00:17:17,740 --> 00:17:21,217
Intrinsic motivation, autonomy,
mastery and purpose, in a knockout.

280
00:17:21,300 --> 00:17:22,300
Let me wrap up.

281
00:17:24,680 --> 00:17:27,927
There is a mismatch between what
science knows and what business does.

282
00:17:28,010 --> 00:17:31,247
Here is what science knows.
One: Those 20th century rewards,

283
00:17:31,330 --> 00:17:34,247
those motivators we think are
a natural part of business,

284
00:17:34,330 --> 00:17:37,977
do work, but only in a surprisingly
narrow band of circumstances.

285
00:17:38,060 --> 00:17:42,787
Two: Those if-then rewards
often destroy creativity.

286
00:17:42,870 --> 00:17:46,617
Three: The secret to high performance
isn't rewards and punishments,

287
00:17:46,700 --> 00:17:51,077
but that unseen intrinsic drive--
the drive to do things for their own sake.

288
00:17:51,160 --> 00:17:53,077
The drive to do things cause they matter.

289
00:17:53,160 --> 00:17:56,317
And here's the best part.
We already know this.

290
00:17:56,400 --> 00:17:58,897
The science confirms what
we know in our hearts.

291
00:17:58,980 --> 00:18:03,747
So, if we repair this mismatch
between science and business,

292
00:18:03,830 --> 00:18:08,457
if we bring our motivation, notions
of motivation into the 21st century,

293
00:18:08,540 --> 00:18:14,547
if we get past this lazy, dangerous,
ideology of carrots and sticks,

294
00:18:14,630 --> 00:18:19,907
we can strengthen our businesses, we
can solve a lot of those candle problems,

295
00:18:19,990 --> 00:18:22,720
and maybe, maybe --

296
00:18:24,160 --> 00:18:27,187
we can change the world. I rest my case.

297
00:18:27,270 --> 00:18:30,270
(Applause)