0:00:00.731,0:00:04.337
Recently, the leadership team[br]of an American supermarket chain

0:00:04.361,0:00:07.817
decided that their business[br]needed to get a lot more efficient.

0:00:07.841,0:00:11.696
So they embraced their digital[br]transformation with zeal.

0:00:12.174,0:00:16.122
Out went the teams[br]supervising meat, veg, bakery,

0:00:16.146,0:00:20.302
and in came an algorithmic task allocator.

0:00:20.914,0:00:23.017
Now, instead of people working together,

0:00:23.041,0:00:27.282
each employee went, clocked in,[br]got assigned a task, did it,

0:00:27.306,0:00:28.884
came back for more.

0:00:29.429,0:00:33.156
This was scientific[br]management on steroids,

0:00:33.180,0:00:35.262
standardizing and allocating work.

0:00:35.580,0:00:37.670
It was super efficient.

0:00:38.750,0:00:40.116
Well, not quite,

0:00:41.351,0:00:43.677
because the task allocator didn't know

0:00:43.701,0:00:46.623
when a customer was going[br]to drop a box of eggs,

0:00:46.647,0:00:50.496
couldn't predict when some crazy kid[br]was going to knock over a display,

0:00:50.520,0:00:52.436
or when the local high school decided

0:00:52.460,0:00:55.095
that everybody needed[br]to bring in coconuts the next day.

0:00:55.119,0:00:56.119
(Laughter)

0:00:56.143,0:00:58.280
Efficiency works really well

0:00:58.304,0:01:01.343
when you can predict[br]exactly what you're going to need.

0:01:01.815,0:01:05.091
But when the anomalous[br]or unexpected comes along --

0:01:05.115,0:01:07.447
kids, customers, coconuts --

0:01:07.471,0:01:10.344
well, then efficiency[br]is no longer your friend.

0:01:12.074,0:01:14.191
This has become a really crucial issue,

0:01:14.215,0:01:16.833
this ability to deal with the unexpected,

0:01:17.771,0:01:21.228
because the unexpected[br]is becoming the norm.

0:01:21.660,0:01:25.737
It's why experts and forecasters[br]are reluctant to predict anything

0:01:25.761,0:01:28.333
more than 400 days out.

0:01:29.054,0:01:30.500
Why?

0:01:30.524,0:01:32.448
Because over the last 20 or 30 years,

0:01:32.472,0:01:36.282
much of the world has gone[br]from being complicated

0:01:36.306,0:01:37.602
to being complex --

0:01:38.431,0:01:40.714
which means that yes, there are patterns,

0:01:40.738,0:01:43.034
but they don't repeat[br]themselves regularly.

0:01:43.440,0:01:47.728
It means that very small changes[br]can make a disproportionate impact.

0:01:48.244,0:01:50.910
And it means that expertise[br]won't always suffice,

0:01:50.934,0:01:54.568
because the system[br]just keeps changing too fast.

0:01:56.192,0:01:58.824
So what that means

0:01:58.848,0:02:01.735
is that there's a huge amount in the world

0:02:01.759,0:02:04.749
that kind of defies forecasting now.

0:02:04.773,0:02:08.603
It's why the Bank of England will say[br]yes, there will be another crash,

0:02:08.627,0:02:11.057
but we don't know why or when.

0:02:11.807,0:02:14.423
We know that climate change is real,

0:02:14.447,0:02:17.523
but we can't predict[br]where forest fires will break out,

0:02:17.547,0:02:20.797
and we don't know which factories[br]are going to flood.

0:02:21.313,0:02:24.004
It's why companies are blindsided

0:02:24.028,0:02:28.897
when plastic straws[br]and bags and bottled water

0:02:28.921,0:02:32.226
go from staples to rejects overnight,

0:02:33.488,0:02:37.060
and baffled when a change in social morays

0:02:37.084,0:02:41.624
turns stars into pariahs[br]and colleagues into outcasts:

0:02:43.155,0:02:46.209
ineradicable uncertainty.

0:02:47.319,0:02:51.655
In an environment that defies[br]so much forecasting,

0:02:51.679,0:02:54.883
efficiency won't just not help us,

0:02:54.907,0:03:01.861
it specifically undermines and erodes[br]our capacity to adapt and respond.

0:03:04.055,0:03:07.196
So if efficiency is no longer[br]our guiding principle,

0:03:07.220,0:03:08.968
how should we address the future?

0:03:08.992,0:03:11.444
What kind of thinking[br]is really going to help us?

0:03:11.468,0:03:16.615
What sort of talents[br]must we be sure to defend?

0:03:17.601,0:03:22.486
I think that, where in the past we used to[br]think a lot about just in time management,

0:03:22.510,0:03:26.394
now we have to start thinking[br]about just in case,

0:03:26.418,0:03:29.815
preparing for events[br]that are generally certain

0:03:29.839,0:03:32.382
but specifically remain ambiguous.

0:03:33.110,0:03:38.308
One example of this is the Coalition[br]for Epidemic Preparedness, CEPI.

0:03:38.332,0:03:42.428
We know there will be[br]more epidemics in future,

0:03:42.452,0:03:46.338
but we don't know where or when or what.

0:03:46.362,0:03:48.303
So we can't plan.

0:03:48.942,0:03:50.593
But we can prepare.

0:03:51.257,0:03:57.025
So CEPI's developing multiple vaccines[br]for multiple diseases,

0:03:57.866,0:04:01.413
knowing that they can't predict[br]which vaccines are going to work

0:04:01.437,0:04:03.457
or which diseases will break out.

0:04:03.481,0:04:06.454
So some of those vaccines[br]will never be used.

0:04:06.478,0:04:07.950
That's inefficient.

0:04:08.794,0:04:10.705
But it's robust,

0:04:10.729,0:04:12.664
because it provides more options,

0:04:12.688,0:04:17.698
and it means that we don't depend[br]on a single technological solution.

0:04:18.566,0:04:21.934
Epidemic responsiveness[br]also depends hugely

0:04:21.958,0:04:24.875
on people who know and trust each other.

0:04:24.899,0:04:27.686
But those relationships[br]take time to develop,

0:04:27.710,0:04:31.935
time that is always in short supply[br]when an epidemic breaks out.

0:04:31.959,0:04:37.047
So CEPI is developing relationships,[br]friendships, alliances now

0:04:38.197,0:04:41.393
knowing that some of those[br]may never be used.

0:04:41.949,0:04:45.102
That's inefficient,[br]a waste of time, perhaps,

0:04:45.126,0:04:46.420
but it's robust.

0:04:47.161,0:04:50.966
You can see robust thinking[br]in financial services, too.

0:04:50.990,0:04:54.744
In the past, banks used to hold[br]much less capital

0:04:54.768,0:04:56.991
than they're required to today,

0:04:57.015,0:05:00.756
because holding so little capital,[br]being too efficient with it,

0:05:00.780,0:05:03.930
is what made the banks[br]so fragile in the first place.

0:05:04.581,0:05:10.070
Now, holding more capital[br]looks and is inefficient.

0:05:10.094,0:05:16.147
But it's robust, because it protects[br]the financial system against surprises.

0:05:17.078,0:05:20.072
Countries that are really serious[br]about climate change

0:05:20.096,0:05:23.650
know that they have to adopt[br]multiple solutions,

0:05:23.674,0:05:26.702
multiple forms of renewable energy,

0:05:26.726,0:05:28.055
not just one.

0:05:28.079,0:05:32.939
The countries that are most advanced[br]have been working for years now,

0:05:32.963,0:05:36.629
changing their water and food supply[br]and healthcare systems,

0:05:36.653,0:05:41.265
because they recognize that by the time[br]they have certain prediction,

0:05:41.289,0:05:44.600
that information may very well[br]come too late.

0:05:45.458,0:05:49.914
You can take the same approach[br]to trade wars, and many countries do.

0:05:49.938,0:05:53.761
Instead of depending on a single[br]huge trading partner,

0:05:53.785,0:05:55.889
they try to be everybody's friends,

0:05:55.913,0:05:58.251
because they know they can't predict

0:05:58.275,0:06:02.029
which markets might[br]suddenly become unstable.

0:06:02.053,0:06:06.290
It's time-consuming and expensive,[br]negotiating all these deals,

0:06:06.314,0:06:07.472
but it's robust

0:06:07.496,0:06:12.907
because it makes their whole economy[br]better defended against shocks.

0:06:12.931,0:06:16.610
It's particularly a strategy[br]adopted by small countries

0:06:16.634,0:06:20.720
that know they'll never have[br]the market muscle to call the shots,

0:06:20.744,0:06:23.898
so it's just better to have[br]too many friends.

0:06:25.922,0:06:28.329
But if you're stuck[br]in one of these organizations

0:06:28.353,0:06:33.248
that's still kind of captured[br]by the efficiency myth,

0:06:33.272,0:06:35.034
how do you start to change it?

0:06:36.011,0:06:37.567
Try some experiments.

0:06:38.421,0:06:39.787
In the Netherlands,

0:06:39.811,0:06:44.525
home care nursing used to be run[br]pretty much like the supermarket:

0:06:44.549,0:06:47.327
standardized and prescribed work

0:06:47.351,0:06:49.119
to the minute:

0:06:49.143,0:06:52.799
nine minutes on Monday,[br]seven minutes on Wednesday,

0:06:52.823,0:06:54.537
eight minutes on Friday.

0:06:54.561,0:06:56.943
The nurses hated it.

0:06:56.967,0:06:59.339
So one of them, Jos de Blok,

0:06:59.363,0:07:00.944
proposed an experiment.

0:07:01.564,0:07:03.196
Since every patient is different,

0:07:03.220,0:07:05.634
and we don't quite know[br]exactly what they'll need,

0:07:05.658,0:07:08.345
why don't we just leave it[br]to the nurses to decide?

0:07:09.267,0:07:10.637
Sound reckless?

0:07:10.661,0:07:12.056
(Laughter)

0:07:12.080,0:07:14.200
(Applause)

0:07:14.224,0:07:18.358
In his experiment, Jos found[br]the patients got better

0:07:18.382,0:07:20.911
in half the time,

0:07:20.935,0:07:24.614
and costs fell by 30 percent.

0:07:25.920,0:07:30.132
When I asked Jos what had surprised him[br]about his experiment,

0:07:30.156,0:07:31.949
he just kind of laughed and he said,

0:07:31.973,0:07:35.165
"Well, I had no idea it could be so easy

0:07:35.189,0:07:37.779
to find such a huge improvement,

0:07:37.803,0:07:41.426
because this isn't the kind of thing[br]you can know or predict

0:07:41.450,0:07:44.280
sitting at a desk[br]or staring at a computer screen."

0:07:44.734,0:07:48.508
So now this form of nursing[br]has proliferated across the Netherlands

0:07:48.532,0:07:50.266
and around the world.

0:07:50.290,0:07:53.510
But in every new country[br]it still starts with experiments,

0:07:53.534,0:07:58.392
because each place is slightly[br]and unpredictably different.

0:07:59.246,0:08:03.196
Of course, not all experiments work.

0:08:03.220,0:08:06.276
Jos tried a similar approach[br]to the fire service

0:08:06.300,0:08:09.837
and found it didn't work because[br]the service is just too centralized.

0:08:09.861,0:08:12.424
Failed experiments look inefficient,

0:08:12.448,0:08:15.631
but they're often the only way[br]you can figure out

0:08:15.655,0:08:17.929
how the real world works.

0:08:18.280,0:08:21.313
So now he's trying teachers.

0:08:22.746,0:08:26.493
Experiments like that require creativity

0:08:26.517,0:08:28.824
and not a little bravery.

0:08:29.613,0:08:31.176
In England --

0:08:31.978,0:08:34.883
I was about to say in the UK,[br]but in England --

0:08:34.907,0:08:36.649
(Laughter)

0:08:36.673,0:08:40.987
(Applause)

0:08:41.363,0:08:45.449
In England, the leading rugby team,[br]or one of the leading rugby teams,

0:08:45.473,0:08:46.833
is Saracens.

0:08:47.299,0:08:52.364
The manager and the coach there realized[br]that all the physical training they do

0:08:52.388,0:08:55.102
and the data-driven[br]conditioning that they do

0:08:55.126,0:08:56.280
has become generic;

0:08:56.304,0:08:59.094
really, all the teams[br]do exactly the same thing.

0:08:59.683,0:09:02.015
So they risked an experiment.

0:09:02.039,0:09:06.284
They took the whole team away,[br]even in match season,

0:09:06.308,0:09:07.723
on ski trips

0:09:07.747,0:09:11.041
and to look at social projects in Chicago.

0:09:11.065,0:09:12.591
This was expensive,

0:09:12.615,0:09:14.567
it was time-consuming,

0:09:14.591,0:09:16.272
and it could be a little risky

0:09:16.296,0:09:20.070
putting a whole bunch of rugby players[br]on a ski slope, right?

0:09:20.094,0:09:21.141
(Laughter)

0:09:21.165,0:09:24.509
But what they found was that[br]the players came back

0:09:24.533,0:09:29.799
with renewed bonds[br]of loyalty and solidarity.

0:09:29.823,0:09:33.232
And now when they're on the pitch[br]under incredible pressure,

0:09:33.256,0:09:37.682
they manifest what the manager[br]calls "poise" --

0:09:38.515,0:09:42.674
an unflinching, unwavering dedication

0:09:42.698,0:09:44.173
to each other.

0:09:44.824,0:09:48.577
Their opponents are in awe of this,

0:09:48.601,0:09:52.753
but still too in thrall[br]to efficiency to try it.

0:09:53.783,0:09:55.815
At a London tech company, Verve,

0:09:55.839,0:09:59.182
the CEO measures just about[br]everything that moves,

0:09:59.206,0:10:02.230
but she couldn't find anything[br]that made any difference

0:10:02.254,0:10:04.381
to the company's productivity.

0:10:04.405,0:10:08.160
So she devised an experiment[br]that she calls "Love Week":

0:10:08.184,0:10:12.721
a whole week where each employee[br]has to look for really clever,

0:10:12.745,0:10:15.024
helpful, imaginative things

0:10:15.048,0:10:16.848
that a counterpart does,

0:10:16.872,0:10:19.336
call it out and celebrate it.

0:10:19.360,0:10:21.477
It takes a huge amount of time and effort;

0:10:21.501,0:10:24.538
lots of people would call it distracting.

0:10:24.562,0:10:26.794
But it really energizes the business

0:10:26.818,0:10:30.456
and makes the whole company[br]more productive.

0:10:32.048,0:10:35.354
Preparedness, coalition-building,

0:10:35.378,0:10:38.960
imagination, experiments,

0:10:38.984,0:10:40.151
bravery --

0:10:41.028,0:10:42.625
in an unpredictable age,

0:10:42.649,0:10:48.317
these are tremendous sources[br]of resilience and strength.

0:10:48.673,0:10:51.241
They aren't efficient,

0:10:52.278,0:10:54.947
but they give us limitless capacity

0:10:54.971,0:10:59.466
for adaptation, variation and invention.

0:11:00.284,0:11:02.706
And the less we know about the future,

0:11:02.730,0:11:08.132
the more we're going to need[br]these tremendous sources

0:11:08.156,0:11:13.777
of human, messy, unpredictable skills.

0:11:15.336,0:11:19.396
But in our growing[br]dependence on technology,

0:11:20.318,0:11:23.668
we're asset-stripping those skills.

0:11:24.642,0:11:28.207
Every time we use technology

0:11:28.231,0:11:32.423
to nudge us through a decision or a choice

0:11:32.447,0:11:34.761
or to interpret how somebody's feeling

0:11:34.785,0:11:36.962
or to guide us through a conversation,

0:11:36.986,0:11:42.100
we outsource to a machine[br]what we could, can do ourselves,

0:11:42.124,0:11:44.648
and it's an expensive trade-off.

0:11:45.847,0:11:48.749
The more we let machines think for us,

0:11:49.780,0:11:52.649
the less we can think for ourselves.

0:11:53.661,0:11:54.814
The more --

0:11:54.838,0:11:59.408
(Applause)

0:11:59.432,0:12:04.153
The more time doctors spend[br]staring at digital medical records,

0:12:04.177,0:12:07.563
the less time they spend[br]looking at their patients.

0:12:08.325,0:12:11.113
The more we use parenting apps,

0:12:11.137,0:12:13.294
the less we know our kids.

0:12:14.310,0:12:19.396
The more time we spend with people that[br]we're predicted and programmed to like,

0:12:19.420,0:12:23.130
the less we can connect with people[br]who are different from ourselves.

0:12:23.154,0:12:28.181
And the less compassion we need,[br]the less compassion we have.

0:12:29.825,0:12:33.359
What all of these[br]technologies attempt to do

0:12:33.383,0:12:40.180
is to force-fit a standardized model[br]of a predictable reality

0:12:40.204,0:12:43.572
onto a world that is[br]infinitely surprising.

0:12:44.926,0:12:46.278
What gets left out?

0:12:46.965,0:12:49.568
Anything that can't be measured --

0:12:50.451,0:12:52.810
which is just about[br]everything that counts.

0:12:53.810,0:13:00.775
(Applause)

0:13:02.854,0:13:06.941
Our growing dependence on technology

0:13:06.965,0:13:10.738
risks us becoming less skilled,

0:13:10.762,0:13:12.357
more vulnerable

0:13:12.381,0:13:15.332
to the deep and growing complexity

0:13:15.356,0:13:16.729
of the real world.

0:13:17.951,0:13:23.335
Now, as I was thinking about[br]the extremes of stress and turbulence

0:13:23.359,0:13:26.015
that we know we will have to confront,

0:13:27.412,0:13:30.364
I went and I talked to[br]a number of chief executives

0:13:30.388,0:13:34.556
whose own businesses had gone[br]through existential crises,

0:13:34.580,0:13:37.468
when they teetered[br]on the brink of collapse.

0:13:38.594,0:13:43.402
These were frank,[br]gut-wrenching conversations.

0:13:44.302,0:13:47.579
Many men wept just remembering.

0:13:48.214,0:13:49.728
So I asked them:

0:13:50.603,0:13:52.668
"What kept you going through this?"

0:13:53.328,0:13:55.982
And they all had exactly the same answer.

0:13:56.006,0:13:59.116
"It wasn't data or technology," they said.

0:13:59.926,0:14:03.311
"It was my friends and my colleagues

0:14:03.335,0:14:04.671
who kept me going."

0:14:05.173,0:14:10.488
One added, "It was pretty much[br]the opposite of the gig economy."

0:14:12.056,0:14:15.790
But then I went and I talked to a group[br]of young, rising executives,

0:14:15.814,0:14:17.621
and I asked them,

0:14:17.645,0:14:19.187
"Who are your friends at work?"

0:14:19.211,0:14:20.989
And they just looked blank.

0:14:21.765,0:14:23.615
"There's no time."

0:14:23.639,0:14:25.448
"They're too busy."

0:14:25.472,0:14:26.910
"It's not efficient."

0:14:27.906,0:14:31.478
Who, I wondered, is going to give them

0:14:31.502,0:14:36.041
imagination and stamina and bravery

0:14:36.065,0:14:37.581
when the storms come?

0:14:39.694,0:14:43.337
Anyone who tries to tell you[br]that they know the future

0:14:43.361,0:14:45.559
is just trying to own it,

0:14:45.583,0:14:48.891
a spurious kind of manifest destiny.

0:14:49.794,0:14:52.115
The harder, deeper truth is

0:14:53.126,0:14:55.535
that the future is uncharted,

0:14:55.559,0:14:57.803
that we can't map it till we get there.

0:14:58.734,0:15:00.797
But that's OK,

0:15:00.821,0:15:03.838
because we have so much imagination --

0:15:03.862,0:15:05.309
if we use it.

0:15:05.333,0:15:10.810
We have deep talents[br]of inventiveness and exploration --

0:15:10.834,0:15:12.611
if we apply them.

0:15:12.635,0:15:18.152
We are brave enough to invent things[br]we've never seen before.

0:15:19.175,0:15:20.790
Lose those skills,

0:15:21.810,0:15:23.532
and we are adrift.

0:15:24.384,0:15:27.109
But hone and develop them,

0:15:28.498,0:15:30.956
we can make any future we choose.

0:15:32.382,0:15:33.556
Thank you.

0:15:33.580,0:15:39.666
(Applause)