The human skills we need in an unpredictable world Margaret Heffernan

Recently, the leadership team
of an American supermarket chain

decided that their business
needed to get a lot more efficient.

So they embraced their digital
transformation with zeal.

Out went the teams
supervising meat, veg, bakery,

and in came an algorithmic task allocator.

Now, instead of people working together,

each employee went, clocked in,
got assigned a task, did it,

came back for more.

This was scientific
management on steroids,

standardizing and allocating work.

It was super efficient.

Well, not quite,

because the task allocator didn’t know

when a customer was going
to drop a box of eggs,

couldn’t predict when some crazy kid
was going to knock over a display,

or when the local high school decided

that everybody needed
to bring in coconuts the next day.

(Laughter)

Efficiency works really well

when you can predict
exactly what you’re going to need.

But when the anomalous
or unexpected comes along –

kids, customers, coconuts –

well, then efficiency
is no longer your friend.

This has become a really crucial issue,

this ability to deal with the unexpected,

because the unexpected
is becoming the norm.

It’s why experts and forecasters
are reluctant to predict anything

more than 400 days out.

Why?

Because over the last 20 or 30 years,

much of the world has gone
from being complicated

to being complex –

which means that yes, there are patterns,

but they don’t repeat
themselves regularly.

It means that very small changes
can make a disproportionate impact.

And it means that expertise
won’t always suffice,

because the system
just keeps changing too fast.

So what that means

is that there’s a huge amount in the world

that kind of defies forecasting now.

It’s why the Bank of England will say
yes, there will be another crash,

but we don’t know why or when.

We know that climate change is real,

but we can’t predict
where forest fires will break out,

and we don’t know which factories
are going to flood.

It’s why companies are blindsided

when plastic straws
and bags and bottled water

go from staples to rejects overnight,

and baffled when a change in social mores

turns stars into pariahs
and colleagues into outcasts:

ineradicable uncertainty.

In an environment that defies
so much forecasting,

efficiency won’t just not help us,

it specifically undermines and erodes
our capacity to adapt and respond.

So if efficiency is no longer
our guiding principle,

how should we address the future?

What kind of thinking
is really going to help us?

What sort of talents
must we be sure to defend?

I think that, where in the past we used to
think a lot about just in time management,

now we have to start thinking
about just in case,

preparing for events
that are generally certain

but specifically remain ambiguous.

One example of this is the Coalition
for Epidemic Preparedness, CEPI.

We know there will be
more epidemics in future,

but we don’t know where or when or what.

So we can’t plan.

But we can prepare.

So CEPI’s developing multiple vaccines
for multiple diseases,

knowing that they can’t predict
which vaccines are going to work

or which diseases will break out.

So some of those vaccines
will never be used.

That’s inefficient.

But it’s robust,

because it provides more options,

and it means that we don’t depend
on a single technological solution.

Epidemic responsiveness
also depends hugely

on people who know and trust each other.

But those relationships
take time to develop,

time that is always in short supply
when an epidemic breaks out.

So CEPI is developing relationships,
friendships, alliances now

knowing that some of those
may never be used.

That’s inefficient,
a waste of time, perhaps,

but it’s robust.

You can see robust thinking
in financial services, too.

In the past, banks used to hold
much less capital

than they’re required to today,

because holding so little capital,
being too efficient with it,

is what made the banks
so fragile in the first place.

Now, holding more capital
looks and is inefficient.

But it’s robust, because it protects
the financial system against surprises.

Countries that are really serious
about climate change

know that they have to adopt
multiple solutions,

multiple forms of renewable energy,

not just one.

The countries that are most advanced
have been working for years now,

changing their water and food supply
and healthcare systems,

because they recognize that by the time
they have certain prediction,

that information may very well
come too late.

You can take the same approach
to trade wars, and many countries do.

Instead of depending on a single
huge trading partner,

they try to be everybody’s friends,

because they know they can’t predict

which markets might
suddenly become unstable.

It’s time-consuming and expensive,
negotiating all these deals,

but it’s robust

because it makes their whole economy
better defended against shocks.

It’s particularly a strategy
adopted by small countries

that know they’ll never have
the market muscle to call the shots,

so it’s just better to have
too many friends.

But if you’re stuck
in one of these organizations

that’s still kind of captured
by the efficiency myth,

how do you start to change it?

Try some experiments.

In the Netherlands,

home care nursing used to be run
pretty much like the supermarket:

standardized and prescribed work

to the minute:

nine minutes on Monday,
seven minutes on Wednesday,

eight minutes on Friday.

The nurses hated it.

So one of them, Jos de Blok,

proposed an experiment.

Since every patient is different,

and we don’t quite know
exactly what they’ll need,

why don’t we just leave it
to the nurses to decide?

Sound reckless?

(Laughter)

(Applause)

In his experiment, Jos found
the patients got better

in half the time,

and costs fell by 30 percent.

When I asked Jos what had surprised him
about his experiment,

he just kind of laughed and he said,

“Well, I had no idea it could be so easy

to find such a huge improvement,

because this isn’t the kind of thing
you can know or predict

sitting at a desk
or staring at a computer screen.”

So now this form of nursing
has proliferated across the Netherlands

and around the world.

But in every new country
it still starts with experiments,

because each place is slightly
and unpredictably different.

Of course, not all experiments work.

Jos tried a similar approach
to the fire service

and found it didn’t work because
the service is just too centralized.

Failed experiments look inefficient,

but they’re often the only way
you can figure out

how the real world works.

So now he’s trying teachers.

Experiments like that require creativity

and not a little bravery.

In England –

I was about to say in the UK,
but in England –

(Laughter)

(Applause)

In England, the leading rugby team,
or one of the leading rugby teams,

is Saracens.

The manager and the coach there realized
that all the physical training they do

and the data-driven
conditioning that they do

has become generic;

really, all the teams
do exactly the same thing.

So they risked an experiment.

They took the whole team away,
even in match season,

on ski trips

and to look at social projects in Chicago.

This was expensive,

it was time-consuming,

and it could be a little risky

putting a whole bunch of rugby players
on a ski slope, right?

(Laughter)

But what they found was that
the players came back

with renewed bonds
of loyalty and solidarity.

And now when they’re on the pitch
under incredible pressure,

they manifest what the manager
calls “poise” –

an unflinching, unwavering dedication

to each other.

Their opponents are in awe of this,

but still too in thrall
to efficiency to try it.

At a London tech company, Verve,

the CEO measures just about
everything that moves,

but she couldn’t find anything
that made any difference

to the company’s productivity.

So she devised an experiment
that she calls “Love Week”:

a whole week where each employee
has to look for really clever,

helpful, imaginative things

that a counterpart does,

call it out and celebrate it.

It takes a huge amount of time and effort;

lots of people would call it distracting.

But it really energizes the business

and makes the whole company
more productive.

Preparedness, coalition-building,

imagination, experiments,

bravery –

in an unpredictable age,

these are tremendous sources
of resilience and strength.

They aren’t efficient,

but they give us limitless capacity

for adaptation, variation and invention.

And the less we know about the future,

the more we’re going to need
these tremendous sources

of human, messy, unpredictable skills.

But in our growing
dependence on technology,

we’re asset-stripping those skills.

Every time we use technology

to nudge us through a decision or a choice

or to interpret how somebody’s feeling

or to guide us through a conversation,

we outsource to a machine
what we could, can do ourselves,

and it’s an expensive trade-off.

The more we let machines think for us,

the less we can think for ourselves.

The more –

(Applause)

The more time doctors spend
staring at digital medical records,

the less time they spend
looking at their patients.

The more we use parenting apps,

the less we know our kids.

The more time we spend with people that
we’re predicted and programmed to like,

the less we can connect with people
who are different from ourselves.

And the less compassion we need,
the less compassion we have.

What all of these
technologies attempt to do

is to force-fit a standardized model
of a predictable reality

onto a world that is
infinitely surprising.

What gets left out?

Anything that can’t be measured –

which is just about
everything that counts.

(Applause)

Our growing dependence on technology

risks us becoming less skilled,

more vulnerable

to the deep and growing complexity

of the real world.

Now, as I was thinking about
the extremes of stress and turbulence

that we know we will have to confront,

I went and I talked to
a number of chief executives

whose own businesses had gone
through existential crises,

when they teetered
on the brink of collapse.

These were frank,
gut-wrenching conversations.

Many men wept just remembering.

So I asked them:

“What kept you going through this?”

And they all had exactly the same answer.

“It wasn’t data or technology,” they said.

“It was my friends and my colleagues

who kept me going.”

One added, “It was pretty much
the opposite of the gig economy.”

But then I went and I talked to a group
of young, rising executives,

and I asked them,

“Who are your friends at work?”

And they just looked blank.

“There’s no time.”

“They’re too busy.”

“It’s not efficient.”

Who, I wondered, is going to give them

imagination and stamina and bravery

when the storms come?

Anyone who tries to tell you
that they know the future

is just trying to own it,

a spurious kind of manifest destiny.

The harder, deeper truth is

that the future is uncharted,

that we can’t map it till we get there.

But that’s OK,

because we have so much imagination –

if we use it.

We have deep talents
of inventiveness and exploration –

if we apply them.

We are brave enough to invent things
we’ve never seen before.

Lose those skills,

and we are adrift.

But hone and develop them,

we can make any future we choose.

Thank you.

(Applause)

最近,
一家美国连锁超市的领导团队

决定他们的业务需要提高效率。

因此,他们热情地接受了数字化
转型。

监督肉类、蔬菜、面包店的团队出去了

,进来了一个算法任务分配器。

现在,不是人们一起工作,而是

每个员工都去上班、打卡、
分配任务、完成任务、

回来完成任务。

这是科学
管理类固醇,

规范和分配工作。

这是超级有效的。

嗯,不完全是,

因为任务分配器不知道

顾客什么时候
会掉一盒鸡蛋,

无法预测某个疯子什么
时候会打翻显示器,

或者当地高中什么时候决定

让每个人都
第二天需要带来椰子。

(笑声)

当你能
准确预测你将需要什么时,效率会非常好。

但是当异常
或意外出现时——

孩子、顾客、椰子——

好吧,那么效率
就不再是你的朋友了。

这已经成为一个非常关键的问题,

这种处理意外的能力,

因为意外
正在成为常态。

这就是为什么专家和预测
者不愿意预测

超过 400 天的任何事情。

为什么?

因为在过去的 20 或 30 年里,

世界上的大部分地区已经
从复杂

变为复杂——

这意味着是的,存在模式,

但它们不会
定期重复。

这意味着非常小的变化
会产生不成比例的影响。

这意味着专业
知识并不总是足够的,

因为
系统总是变化得太快。

所以这意味着

世界上有大量的

东西现在无法预测。

这就是为什么英格兰银行会说
是的,会有另一场崩盘,

但我们不知道为什么或何时。

我们知道气候变化是真实存在的,

但我们无法预测
森林大火会在哪里爆发

,我们也不知道哪些
工厂会被淹。

这就是为什么

当塑料吸管
、塑料袋和瓶装水

在一夜之间从主食变成拒绝品时,公司会措手不及,当

社会习俗的变化

将明星变成贱民
,将同事变成弃儿时,公司会感到困惑:

无法根除的不确定性。

在一个无法预测的环境中

效率不仅不会帮助我们,

它还会特别破坏和侵蚀
我们的适应和响应能力。

那么,如果效率不再是
我们的指导原则,

我们应该如何应对未来呢?

什么样的
想法真正能帮助我们?

我们必须确保保护什么样的人才?

我认为,过去我们经常
考虑时间管理,

现在我们必须开始
考虑以防万一

,为通常确定

但具体仍然模棱两可的事件做准备。

这方面的一个例子
是流行病防范联盟,CEPI。

我们知道
未来会有更多的流行病,

但我们不知道在哪里、何时或什么。

所以我们不能计划。

但我们可以做好准备。

因此,CEPI 正在开发
针对多种疾病的多种疫苗,

因为他们知道他们无法预测
哪些疫苗会起作用

或哪些疾病会爆发。

因此,其中一些疫苗
将永远不会被使用。

那是低效的。

但它很强大,

因为它提供了更多选择

,这意味着我们不依赖
于单一的技术解决方案。

流行病应对能力
也很大程度上

取决于彼此了解和信任的人。

但这些关系
需要时间来发展,

当流行病爆发时,时间总是供不应求。

因此,CEPI 正在发展关系、
友谊和联盟,现在

知道其中一些
可能永远不会被使用。

这可能效率低下
,浪费时间,

但它很强大。

您也可以
在金融服务中看到稳健的思维。

过去,银行持有
的资本

比现在所需的要少得多,

因为持有如此少的资本
,使用它的效率太高

,首先使银行
如此脆弱。

现在,持有更多的资本
看起来效率很低。

但它很强大,因为它可以
保护金融系统免受意外。

真正认真
对待气候变化的国家

知道,他们必须采用
多种解决方案,

多种形式的可再生能源,

而不仅仅是一种。

最先进的国家
多年来一直在努力

改变他们的水和食品供应
以及医疗保健系统,

因为他们认识到,当
他们做出一定的预测时,

这些信息很可能
来得太晚了。

您可以对贸易战采取相同的方法
,许多国家都这样做。

他们不依赖于一个
巨大的贸易伙伴,

而是试图成为每个人的朋友,

因为他们知道他们无法预测

哪些市场可能会
突然变得不稳定。 谈判所有这些交易

既费时又昂贵,

但它很强大,

因为它可以让他们的整个经济
更好地抵御冲击。

这尤其是
小国采用的一种策略

,他们知道自己永远
没有市场力量来做主,

所以最好有
太多朋友。

但是,如果您被困
在其中一个

仍然被效率神话所吸引的组织中,

您将如何开始改变它?

尝试一些实验。

在荷兰,

家庭护理过去的运作方式
非常像超市:

标准化和规定的

工作时间:

周一 9 分钟,
周三 7 分钟,

周五 8 分钟。

护士们讨厌它。

所以其中一个,乔斯·德布洛克,

提出了一个实验。

既然每个病人都是不同的,

而且我们不太
清楚他们需要什么,

为什么不让
护士来决定呢?

听起来鲁莽?

(笑声)

(掌声)

在他的实验中,乔斯
发现病人

在一半的时间内好转

,成本下降了 30%。

当我问乔斯他的实验有什么让他吃惊的时候

,他只是笑了笑说:

“嗯,我不知道

发现这么大的改进会这么容易,

因为这不是你想要的那种东西。
可以知道或预测

坐在办公桌前
或盯着电脑屏幕。”

所以现在这种形式的护理
已经在荷兰

和世界各地激增。

但在每个新国家,
它仍然从实验开始,

因为每个地方都略有
不同,而且出乎意料。

当然,并不是所有的实验都能奏效。

Jos 对消防服务尝试了类似的方法
,但

发现它不起作用,因为
该服务过于集中。

失败的实验看起来效率低下,

但它们通常是

弄清楚现实世界如何运作的唯一方法。

所以现在他正在尝试老师。

像这样的实验需要创造力,

而不是一点勇气。

在英格兰——

我正要说在英国,
但在英格兰——

(笑声)

(掌声)

在英格兰,领先的橄榄球队,
或领先的橄榄球队之一,

是撒拉逊人。

那里的经理和教练
意识到,他们所做的所有体能训练

和他们所做的数据驱动的训练

已经变得通用;

真的,所有的团队
都做同样的事情。

所以他们冒险进行实验。

他们把整个球队都带走了,
即使是在比赛赛季

、滑雪旅行

和芝加哥的社会项目中。

这很昂贵,

很耗时,

而且

把一大群橄榄球运动员
放在滑雪场上可能有点冒险,对吧?

(笑声)

但他们发现
,球员们

带着新
的忠诚和团结的纽带回来了。

而现在,当他们在球场上
承受着巨大的压力时,

他们表现出了主教练
所说的“平衡”——

一种坚定不移、坚定不移的

对彼此的奉献精神。

他们的对手对此感到敬畏,

但仍然过于
追求效率而无法尝试。

在伦敦的一家科技公司 Verve

,CEO 几乎测量
所有移动的东西,

但她找不到任何对公司生产力有任何影响的东西

因此,她设计了
一个她称之为“爱周”的实验:

在这一周里,每个员工
都必须寻找对方所做的真正聪明、

乐于助人、富有想象力的事情

,大声说出并庆祝。

这需要大量的时间和精力;

很多人会称之为分散注意力。

但它确实为业务注入了活力

,并使整个公司
更有效率。

准备、联盟建设、

想象力、实验、

勇敢——

在一个不可预测的时代,

这些都是
韧性和力量的巨大来源。

它们效率不高,

但它们给了我们无限

的适应、变化和发明的能力。

我们对未来的了解越少,

我们就越需要
这些巨大

的人力资源,杂乱无章的,不可预测的技能。

但在我们
对技术日益依赖的情况下,

我们正在剥夺这些技能的资产。

每次我们使用技术

来推动我们做出决定或选择,

或者解释某人的感受

或引导我们进行对话时,

我们都会将
我们能做的、自己能做的事情外包给机器

,这是一个代价高昂的权衡取舍。

我们让机器为我们思考的次数越多

,我们为自己思考的次数就越少。

越多——

(掌声)

医生
花在数字医疗记录

上的时间越多,
他们看病人的时间就越少。

我们使用育儿应用程序越多,

我们对孩子的了解就越少。

我们花在
预测和编程喜欢

的人身上的时间越多,我们与
与自己不同的人的联系就越少。

我们需要
的同情心越少,我们的同情心就越少。

所有这些
技术试图做的

是将可预测现实的标准化模型强制拟合

到一个
无限令人惊讶的世界上。

什么被遗漏了?

任何无法衡量的东西——

这几乎就是
所有重要的东西。

(掌声)

我们对技术的日益依赖有

可能使我们变得不熟练,

更容易

受到现实世界的深刻和日益复杂

的影响。

现在,当我在思考

我们知道我们将不得不面对的极端压力和动荡时,

我去和
一些

自己的企业经历了
生存危机的首席执行官进行了交谈,

当时他们
在崩溃的边缘摇摇欲坠 .

这些是坦率的、
令人痛心的对话。

许多男人一想起就哭了。

所以我问他们:

“是什么让你经历了这一切?”

他们都有完全相同的答案。

“这不是数据或技术,”他们说。

“是我的朋友和

同事让我继续前进。”

一位补充说,“这
与零工经济几乎相反。”

但后来我去和
一群年轻的、正在崛起的高管交谈

,我问他们,

“你的工作朋友是谁?”

他们只是看起来一片空白。

“没有时间了。”

“他们太忙了。”

“效率不高。”

我想知道,当暴风雨来临时,谁会给他们

想象力、耐力和勇气

任何试图告诉
你他们知道未来的人

都只是想拥有它,这

是一种虚假的昭昭天命。

更难、更深刻的事实是

,未来是未知的

,我们无法绘制它直到我们到达那里。

但这没关系,

因为我们有太多的想象力——

如果我们使用它的话。

我们拥有深厚
的创造力和探索才能——

如果我们运用它们的话。

我们有足够的勇气去发明
我们以前从未见过的东西。

失去这些技能

,我们就会漂泊。

但是磨练和发展它们,

我们可以创造我们选择的任何未来。

谢谢你。

(掌声)