ABOUT THE SPEAKER
Margaret Heffernan - Management thinker
The former CEO of five businesses, Margaret Heffernan explores the all-too-human thought patterns -- like conflict avoidance and selective blindness -- that lead organizations and managers astray.

Why you should listen

How do organizations think? In her book Willful Blindness, Margaret Heffernan examines why businesses and the people who run them often ignore the obvious -- with consequences as dire as the global financial crisis and Fukushima Daiichi nuclear disaster.

Heffernan began her career in television production, building a track record at the BBC before going on to run the film and television producer trade association IPPA. In the US, Heffernan became a serial entrepreneur and CEO in the wild early days of web business. She now blogs for the Huffington Post and BNET.com. Her latest book, Beyond Measure, a TED Books original, explores the small steps companies can make that lead to big changes in their culture.

More profile about the speaker
Margaret Heffernan | Speaker | TED.com
TEDSummit 2019

Margaret Heffernan: The human skills we need in an unpredictable world

Filmed:
2,773,555 views

The more we rely on technology to make us efficient, the fewer skills we have to confront the unexpected, says writer and entrepreneur Margaret Heffernan. She shares why we need less tech and more messy human skills -- imagination, humility, bravery -- to solve problems in business, government and life in an unpredictable age. "We are brave enough to invent things we've never seen before," she says. "We can make any future we choose."
- Management thinker
The former CEO of five businesses, Margaret Heffernan explores the all-too-human thought patterns -- like conflict avoidance and selective blindness -- that lead organizations and managers astray. Full bio

Double-click the English transcript below to play the video.

00:12
Recently, the leadership team
of an American supermarket chain
0
731
3606
00:16
decided that their business
needed to get a lot more efficient.
1
4361
3456
00:19
So they embraced their digital
transformation with zeal.
2
7841
3855
00:24
Out went the teams
supervising meat, veg, bakery,
3
12174
3948
00:28
and in came an algorithmic task allocator.
4
16146
4156
00:32
Now, instead of people working together,
5
20914
2103
00:35
each employee went, clocked in,
got assigned a task, did it,
6
23041
4241
00:39
came back for more.
7
27306
1578
00:41
This was scientific
management on steroids,
8
29429
3727
00:45
standardizing and allocating work.
9
33180
2082
00:47
It was super efficient.
10
35580
2090
00:50
Well, not quite,
11
38750
1366
00:53
because the task allocator didn't know
12
41351
2326
00:55
when a customer was going
to drop a box of eggs,
13
43701
2922
00:58
couldn't predict when some crazy kid
was going to knock over a display,
14
46647
3849
01:02
or when the local high school decided
15
50520
1916
01:04
that everybody needed
to bring in coconuts the next day.
16
52460
2635
01:07
(Laughter)
17
55119
1000
01:08
Efficiency works really well
18
56143
2137
01:10
when you can predict
exactly what you're going to need.
19
58304
3039
01:13
But when the anomalous
or unexpected comes along --
20
61815
3276
01:17
kids, customers, coconuts --
21
65115
2332
01:19
well, then efficiency
is no longer your friend.
22
67471
2873
01:24
This has become a really crucial issue,
23
72074
2117
01:26
this ability to deal with the unexpected,
24
74215
2618
01:29
because the unexpected
is becoming the norm.
25
77771
3457
01:33
It's why experts and forecasters
are reluctant to predict anything
26
81660
4077
01:37
more than 400 days out.
27
85761
2572
01:41
Why?
28
89054
1446
01:42
Because over the last 20 or 30 years,
29
90524
1924
01:44
much of the world has gone
from being complicated
30
92472
3810
01:48
to being complex --
31
96306
1296
01:50
which means that yes, there are patterns,
32
98431
2283
01:52
but they don't repeat
themselves regularly.
33
100738
2296
01:55
It means that very small changes
can make a disproportionate impact.
34
103440
4288
02:00
And it means that expertise
won't always suffice,
35
108244
2666
02:02
because the system
just keeps changing too fast.
36
110934
3634
02:08
So what that means
37
116192
2632
02:10
is that there's a huge amount in the world
38
118848
2887
02:13
that kind of defies forecasting now.
39
121759
2990
02:16
It's why the Bank of England will say
yes, there will be another crash,
40
124773
3830
02:20
but we don't know why or when.
41
128627
2430
02:23
We know that climate change is real,
42
131807
2616
02:26
but we can't predict
where forest fires will break out,
43
134447
3076
02:29
and we don't know which factories
are going to flood.
44
137547
3250
02:33
It's why companies are blindsided
45
141313
2691
02:36
when plastic straws
and bags and bottled water
46
144028
4869
02:40
go from staples to rejects overnight,
47
148921
3305
02:45
and baffled when a change in social mores
48
153488
3572
02:49
turns stars into pariahs
and colleagues into outcasts:
49
157084
4540
02:55
ineradicable uncertainty.
50
163155
3054
02:59
In an environment that defies
so much forecasting,
51
167319
4336
03:03
efficiency won't just not help us,
52
171679
3204
03:06
it specifically undermines and erodes
our capacity to adapt and respond.
53
174907
6954
03:16
So if efficiency is no longer
our guiding principle,
54
184055
3141
03:19
how should we address the future?
55
187220
1748
03:20
What kind of thinking
is really going to help us?
56
188992
2452
03:23
What sort of talents
must we be sure to defend?
57
191468
5147
03:29
I think that, where in the past we used to
think a lot about just in time management,
58
197601
4885
03:34
now we have to start thinking
about just in case,
59
202510
3884
03:38
preparing for events
that are generally certain
60
206418
3397
03:41
but specifically remain ambiguous.
61
209839
2543
03:45
One example of this is the Coalition
for Epidemic Preparedness, CEPI.
62
213110
5198
03:50
We know there will be
more epidemics in future,
63
218332
4096
03:54
but we don't know where or when or what.
64
222452
3886
03:58
So we can't plan.
65
226362
1941
04:00
But we can prepare.
66
228942
1651
04:03
So CEPI's developing multiple vaccines
for multiple diseases,
67
231257
5768
04:09
knowing that they can't predict
which vaccines are going to work
68
237866
3547
04:13
or which diseases will break out.
69
241437
2020
04:15
So some of those vaccines
will never be used.
70
243481
2973
04:18
That's inefficient.
71
246478
1472
04:20
But it's robust,
72
248794
1911
04:22
because it provides more options,
73
250729
1935
04:24
and it means that we don't depend
on a single technological solution.
74
252688
5010
04:30
Epidemic responsiveness
also depends hugely
75
258566
3368
04:33
on people who know and trust each other.
76
261958
2917
04:36
But those relationships
take time to develop,
77
264899
2787
04:39
time that is always in short supply
when an epidemic breaks out.
78
267710
4225
04:43
So CEPI is developing relationships,
friendships, alliances now
79
271959
5088
04:50
knowing that some of those
may never be used.
80
278197
3196
04:53
That's inefficient,
a waste of time, perhaps,
81
281949
3153
04:57
but it's robust.
82
285126
1294
04:59
You can see robust thinking
in financial services, too.
83
287161
3805
05:02
In the past, banks used to hold
much less capital
84
290990
3754
05:06
than they're required to today,
85
294768
2223
05:09
because holding so little capital,
being too efficient with it,
86
297015
3741
05:12
is what made the banks
so fragile in the first place.
87
300780
3150
05:16
Now, holding more capital
looks and is inefficient.
88
304581
5489
05:22
But it's robust, because it protects
the financial system against surprises.
89
310094
6053
05:29
Countries that are really serious
about climate change
90
317078
2994
05:32
know that they have to adopt
multiple solutions,
91
320096
3554
05:35
multiple forms of renewable energy,
92
323674
3028
05:38
not just one.
93
326726
1329
05:40
The countries that are most advanced
have been working for years now,
94
328079
4860
05:44
changing their water and food supply
and healthcare systems,
95
332963
3666
05:48
because they recognize that by the time
they have certain prediction,
96
336653
4612
05:53
that information may very well
come too late.
97
341289
3311
05:57
You can take the same approach
to trade wars, and many countries do.
98
345458
4456
06:01
Instead of depending on a single
huge trading partner,
99
349938
3823
06:05
they try to be everybody's friends,
100
353785
2104
06:07
because they know they can't predict
101
355913
2338
06:10
which markets might
suddenly become unstable.
102
358275
3754
06:14
It's time-consuming and expensive,
negotiating all these deals,
103
362053
4237
06:18
but it's robust
104
366314
1158
06:19
because it makes their whole economy
better defended against shocks.
105
367496
5411
06:24
It's particularly a strategy
adopted by small countries
106
372931
3679
06:28
that know they'll never have
the market muscle to call the shots,
107
376634
4086
06:32
so it's just better to have
too many friends.
108
380744
3154
06:37
But if you're stuck
in one of these organizations
109
385922
2407
06:40
that's still kind of captured
by the efficiency myth,
110
388353
4895
06:45
how do you start to change it?
111
393272
1762
06:48
Try some experiments.
112
396011
1556
06:50
In the Netherlands,
113
398421
1366
06:51
home care nursing used to be run
pretty much like the supermarket:
114
399811
4714
06:56
standardized and prescribed work
115
404549
2778
06:59
to the minute:
116
407351
1768
07:01
nine minutes on Monday,
seven minutes on Wednesday,
117
409143
3656
07:04
eight minutes on Friday.
118
412823
1714
07:06
The nurses hated it.
119
414561
2382
07:08
So one of them, Jos de Blok,
120
416967
2372
07:11
proposed an experiment.
121
419363
1581
07:13
Since every patient is different,
122
421564
1632
07:15
and we don't quite know
exactly what they'll need,
123
423220
2414
07:17
why don't we just leave it
to the nurses to decide?
124
425658
2687
07:21
Sound reckless?
125
429267
1370
07:22
(Laughter)
126
430661
1395
07:24
(Applause)
127
432080
2120
07:26
In his experiment, Jos found
the patients got better
128
434224
4134
07:30
in half the time,
129
438382
2529
07:32
and costs fell by 30 percent.
130
440935
3679
07:37
When I asked Jos what had surprised him
about his experiment,
131
445920
4212
07:42
he just kind of laughed and he said,
132
450156
1793
07:43
"Well, I had no idea it could be so easy
133
451973
3192
07:47
to find such a huge improvement,
134
455189
2590
07:49
because this isn't the kind of thing
you can know or predict
135
457803
3623
07:53
sitting at a desk
or staring at a computer screen."
136
461450
2830
07:56
So now this form of nursing
has proliferated across the Netherlands
137
464734
3774
08:00
and around the world.
138
468532
1734
08:02
But in every new country
it still starts with experiments,
139
470290
3220
08:05
because each place is slightly
and unpredictably different.
140
473534
4858
08:11
Of course, not all experiments work.
141
479246
3950
08:15
Jos tried a similar approach
to the fire service
142
483220
3056
08:18
and found it didn't work because
the service is just too centralized.
143
486300
3537
08:21
Failed experiments look inefficient,
144
489861
2563
08:24
but they're often the only way
you can figure out
145
492448
3183
08:27
how the real world works.
146
495655
2274
08:30
So now he's trying teachers.
147
498280
3033
08:34
Experiments like that require creativity
148
502746
3747
08:38
and not a little bravery.
149
506517
2307
08:41
In England --
150
509613
1563
08:43
I was about to say in the UK,
but in England --
151
511978
2905
08:46
(Laughter)
152
514907
1742
08:48
(Applause)
153
516673
4314
08:53
In England, the leading rugby team,
or one of the leading rugby teams,
154
521363
4086
08:57
is Saracens.
155
525473
1360
08:59
The manager and the coach there realized
that all the physical training they do
156
527299
5065
09:04
and the data-driven
conditioning that they do
157
532388
2714
09:07
has become generic;
158
535126
1154
09:08
really, all the teams
do exactly the same thing.
159
536304
2790
09:11
So they risked an experiment.
160
539683
2332
09:14
They took the whole team away,
even in match season,
161
542039
4245
09:18
on ski trips
162
546308
1415
09:19
and to look at social projects in Chicago.
163
547747
3294
09:23
This was expensive,
164
551065
1526
09:24
it was time-consuming,
165
552615
1952
09:26
and it could be a little risky
166
554591
1681
09:28
putting a whole bunch of rugby players
on a ski slope, right?
167
556296
3774
09:32
(Laughter)
168
560094
1047
09:33
But what they found was that
the players came back
169
561165
3344
09:36
with renewed bonds
of loyalty and solidarity.
170
564533
5266
09:41
And now when they're on the pitch
under incredible pressure,
171
569823
3409
09:45
they manifest what the manager
calls "poise" --
172
573256
4426
09:50
an unflinching, unwavering dedication
173
578515
4159
09:54
to each other.
174
582698
1475
09:56
Their opponents are in awe of this,
175
584824
3753
10:00
but still too in thrall
to efficiency to try it.
176
588601
4152
10:05
At a London tech company, Verve,
177
593783
2032
10:07
the CEO measures just about
everything that moves,
178
595839
3343
10:11
but she couldn't find anything
that made any difference
179
599206
3024
10:14
to the company's productivity.
180
602254
2127
10:16
So she devised an experiment
that she calls "Love Week":
181
604405
3755
10:20
a whole week where each employee
has to look for really clever,
182
608184
4537
10:24
helpful, imaginative things
183
612745
2279
10:27
that a counterpart does,
184
615048
1800
10:28
call it out and celebrate it.
185
616872
2464
10:31
It takes a huge amount of time and effort;
186
619360
2117
10:33
lots of people would call it distracting.
187
621501
3037
10:36
But it really energizes the business
188
624562
2232
10:38
and makes the whole company
more productive.
189
626818
3638
10:44
Preparedness, coalition-building,
190
632048
3306
10:47
imagination, experiments,
191
635378
3582
10:50
bravery --
192
638984
1167
10:53
in an unpredictable age,
193
641028
1597
10:54
these are tremendous sources
of resilience and strength.
194
642649
5668
11:00
They aren't efficient,
195
648673
2568
11:04
but they give us limitless capacity
196
652278
2669
11:06
for adaptation, variation and invention.
197
654971
4495
11:12
And the less we know about the future,
198
660284
2422
11:14
the more we're going to need
these tremendous sources
199
662730
5402
11:20
of human, messy, unpredictable skills.
200
668156
5621
11:27
But in our growing
dependence on technology,
201
675336
4060
11:32
we're asset-stripping those skills.
202
680318
3350
11:36
Every time we use technology
203
684642
3565
11:40
to nudge us through a decision or a choice
204
688231
4192
11:44
or to interpret how somebody's feeling
205
692447
2314
11:46
or to guide us through a conversation,
206
694785
2177
11:48
we outsource to a machine
what we could, can do ourselves,
207
696986
5114
11:54
and it's an expensive trade-off.
208
702124
2524
11:57
The more we let machines think for us,
209
705847
2902
12:01
the less we can think for ourselves.
210
709780
2869
12:05
The more --
211
713661
1153
12:06
(Applause)
212
714838
4570
12:11
The more time doctors spend
staring at digital medical records,
213
719432
4721
12:16
the less time they spend
looking at their patients.
214
724177
3386
12:20
The more we use parenting apps,
215
728325
2788
12:23
the less we know our kids.
216
731137
2157
12:26
The more time we spend with people that
we're predicted and programmed to like,
217
734310
5086
12:31
the less we can connect with people
who are different from ourselves.
218
739420
3710
12:35
And the less compassion we need,
the less compassion we have.
219
743154
5027
12:41
What all of these
technologies attempt to do
220
749825
3534
12:45
is to force-fit a standardized model
of a predictable reality
221
753383
6797
12:52
onto a world that is
infinitely surprising.
222
760204
3368
12:56
What gets left out?
223
764926
1352
12:58
Anything that can't be measured --
224
766965
2603
13:02
which is just about
everything that counts.
225
770451
2359
13:05
(Applause)
226
773810
6965
13:14
Our growing dependence on technology
227
782854
4087
13:18
risks us becoming less skilled,
228
786965
3773
13:22
more vulnerable
229
790762
1595
13:24
to the deep and growing complexity
230
792381
2951
13:27
of the real world.
231
795356
1373
13:29
Now, as I was thinking about
the extremes of stress and turbulence
232
797951
5384
13:35
that we know we will have to confront,
233
803359
2656
13:39
I went and I talked to
a number of chief executives
234
807412
2952
13:42
whose own businesses had gone
through existential crises,
235
810388
4168
13:46
when they teetered
on the brink of collapse.
236
814580
2888
13:50
These were frank,
gut-wrenching conversations.
237
818594
4808
13:56
Many men wept just remembering.
238
824302
3277
14:00
So I asked them:
239
828214
1514
14:02
"What kept you going through this?"
240
830603
2065
14:05
And they all had exactly the same answer.
241
833328
2654
14:08
"It wasn't data or technology," they said.
242
836006
3110
14:11
"It was my friends and my colleagues
243
839926
3385
14:15
who kept me going."
244
843335
1336
14:17
One added, "It was pretty much
the opposite of the gig economy."
245
845173
5315
14:24
But then I went and I talked to a group
of young, rising executives,
246
852056
3734
14:27
and I asked them,
247
855814
1807
14:29
"Who are your friends at work?"
248
857645
1542
14:31
And they just looked blank.
249
859211
1778
14:33
"There's no time."
250
861765
1850
14:35
"They're too busy."
251
863639
1809
14:37
"It's not efficient."
252
865472
1438
14:39
Who, I wondered, is going to give them
253
867906
3572
14:43
imagination and stamina and bravery
254
871502
4539
14:48
when the storms come?
255
876065
1516
14:51
Anyone who tries to tell you
that they know the future
256
879694
3643
14:55
is just trying to own it,
257
883361
2198
14:57
a spurious kind of manifest destiny.
258
885583
3308
15:01
The harder, deeper truth is
259
889794
2321
15:05
that the future is uncharted,
260
893126
2409
15:07
that we can't map it till we get there.
261
895559
2244
15:10
But that's OK,
262
898734
2063
15:12
because we have so much imagination --
263
900821
3017
15:15
if we use it.
264
903862
1447
15:17
We have deep talents
of inventiveness and exploration --
265
905333
5477
15:22
if we apply them.
266
910834
1777
15:24
We are brave enough to invent things
we've never seen before.
267
912635
5517
15:31
Lose those skills,
268
919175
1615
15:33
and we are adrift.
269
921810
1722
15:36
But hone and develop them,
270
924384
2725
15:40
we can make any future we choose.
271
928498
2458
15:44
Thank you.
272
932382
1174
15:45
(Applause)
273
933580
6086

▲Back to top

ABOUT THE SPEAKER
Margaret Heffernan - Management thinker
The former CEO of five businesses, Margaret Heffernan explores the all-too-human thought patterns -- like conflict avoidance and selective blindness -- that lead organizations and managers astray.

Why you should listen

How do organizations think? In her book Willful Blindness, Margaret Heffernan examines why businesses and the people who run them often ignore the obvious -- with consequences as dire as the global financial crisis and Fukushima Daiichi nuclear disaster.

Heffernan began her career in television production, building a track record at the BBC before going on to run the film and television producer trade association IPPA. In the US, Heffernan became a serial entrepreneur and CEO in the wild early days of web business. She now blogs for the Huffington Post and BNET.com. Her latest book, Beyond Measure, a TED Books original, explores the small steps companies can make that lead to big changes in their culture.

More profile about the speaker
Margaret Heffernan | Speaker | TED.com