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

譯者: Regina Chu 審譯者: Marssi Draw

Recently, the leadership team of an American supermarket chain

最近，美國某連鎖超市的領導團隊

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

決定要讓他們的企業更有效率。

So they embraced their digital transformation with zeal.

所以他們火熱擁抱數位化轉型。

Out went the teams supervising meat, veg, bakery,

團隊出去監看肉品、 蔬果及麵包部門，

and in came an algorithmic task allocator.

回來的時候想出了一套 任務分配演算法。

Now, instead of people working together,

現在，員工不再一同工作，

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

而是每個員工自己去打卡， 拿分配的任務，做完，

came back for more.

然後再去領更多的任務。

This was scientific management on steroids,

這是科學管理大補丸，

standardizing and allocating work.

標準化及分配每個工作。

It was super efficient.

超有效率。

Well, not quite,

才怪。

because the task allocator didn't know

因為任務分配法不知道

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

什麼時候顧客會打破一盒蛋，

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

不能預測什麼時候哪來的小鬼 會打翻陳列的商品，

or when the local high school decided

或什麼時候當地某高中會突然決定

that everybody needed to bring in coconuts the next day.

學生隔天通通要帶椰子去學校。

(Laughter)

（笑聲）

Efficiency works really well

效率要在你能準確預估

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

你到底需要什麼的時候才會有用。

But when the anomalous or unexpected comes along --

如果有任何異常 或無預警的情況發生──

kids, customers, coconuts --

小孩、顧客、椰子──

well, then efficiency is no longer your friend.

那效率就不再是你的朋友。

This has become a really crucial issue,

這件事已經變成非常重要的問題，

this ability to deal with the unexpected,

就是處理意外的能力，

because the unexpected is becoming the norm.

因為意外變得愈來愈正常。

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

這就是為什麼專家及預測人員

很不願意預測四百天後的情況。

more than 400 days out.

Why?

為什麼？

Because over the last 20 or 30 years,

因為在過去二三十年，

much of the world has gone from being complicated

世界上的大部分地區從複雜

to being complex --

轉變到複合式的複雜。

which means that yes, there are patterns,

也就是說是的，的確有模式存在，

but they don't repeat themselves regularly.

但是這些模式並不經常重複。

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

也就是說非常小的變化 就會造成不成比例的衝擊，

And it means that expertise won't always suffice,

這也代表著專業知識 不見得永遠夠用，

because the system just keeps changing too fast.

因為系統總是變化太快。

So what that means

這就意味著

is that there's a huge amount in the world

這個世界有很大一片地方，

that kind of defies forecasting now.

現在可以說不符合預測。

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

這就是為什麼英國央行會說， 是，的確會有下一波的崩盤，

but we don't know why or when.

但是我們不知道為什麼 或什麼時候發生。

We know that climate change is real,

我們知道氣候變遷是真的，

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

但是我們無法預測 森林大火會在哪裡發生，

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

我們也不知道哪個工廠會淹水。

It's why companies are blindsided

這也就是為什麼 製造公司會完全看不到

when plastic straws and bags and bottled water

塑膠吸管、塑膠袋和瓶裝水

go from staples to rejects overnight,

會在一夕之間從生活必需品 變成人人喊打，

and baffled when a change in social mores

也不懂什麼時候社會民德改變，

turns stars into pariahs and colleagues into outcasts:

讓巨星隕落成賤民，同僚被放逐；

ineradicable uncertainty.

根深蒂固的不確定性。

In an environment that defies so much forecasting,

在一個經常無可預測的環境內，

efficiency won't just not help us,

效率不但不能幫助我們，

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

還特別會破壞並磨掉 我們適應及反應的能力。

So if efficiency is no longer our guiding principle,

如果效率不再是我們的 最高指導原則，

how should we address the future?

那我們未來要怎麼做呢？

What kind of thinking is really going to help us?

什麼樣的思維才能真正幫助我們？

What sort of talents must we be sure to defend?

什麼樣的人才是我們一定要保住的？

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

我想，過去我們 只著重「及時」管理，

now we have to start thinking about just in case,

現在我們必須開始思考「萬一」，

preparing for events that are generally certain

準備應付還算有把握，

but specifically remain ambiguous.

但某些項目仍不能完全掌控的情況。

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

流行病預防聯盟 CEPI 就是這方面的例子。

We know there will be more epidemics in future,

我們知道未來會有更多流行病，

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

但是我們不知道何時、 何地或何種會發生。

So we can't plan.

所以我們不能事先計畫。

But we can prepare.

但是我們可以事先準備。

So CEPI's developing multiple vaccines for multiple diseases,

所以流行病預防聯盟 為多種疾病開發出多種疫苗，

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

因為他們知道他們無法預測 哪種疫苗會有效，

or which diseases will break out.

或哪種疾病會爆發，

So some of those vaccines will never be used.

所以某些開發出的疫苗 就會永遠用不到。

That's inefficient.

這很沒效率。

But it's robust,

卻很萬全，

because it provides more options,

因為這提供了更多選擇，

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

也意味著我們不需要依賴 單一技術解決方案。

Epidemic responsiveness also depends hugely

流行病應變很大程度也取決於

on people who know and trust each other.

相互了解和信任的人。

But those relationships take time to develop,

但是這種關係需要時間來培養，

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

流行病爆發時，時間永遠不夠用。

So CEPI is developing relationships, friendships, alliances now

所以流行病預防聯盟 現在就培養關係、友誼、結盟，

knowing that some of those may never be used.

即使知道這些關係 可能永遠都用不上。

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

這很沒效率，也可以說是浪費時間，

but it's robust.

但這很萬全。

You can see robust thinking in financial services, too.

萬全的想法在金融服務業也看的到。

In the past, banks used to hold much less capital

過去，銀行的資本要求

than they're required to today,

比現在少很多，

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

因為持有那麼少的資金 雖然效率超高，

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

卻讓銀行一開始就非常脆弱。

Now, holding more capital looks and is inefficient.

現在，資本要求變高乍看 ──也的確──很沒效率，

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

但是很萬全，

因為這樣能保護金融系統免受驚嚇。

Countries that are really serious about climate change

極為看重氣候變遷的國家

know that they have to adopt multiple solutions,

知道他們必須多管齊下，

multiple forms of renewable energy,

採用多種可再生能源，

not just one.

而非只有一種。

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

進展好的國家已經實行了很多年，

changing their water and food supply and healthcare systems,

改變他們的水源 及食物來源及健保系統，

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

因為他們意識到就算他們預測到了，

that information may very well come too late.

到那個時候資訊 也可能已經來得太晚。

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

同樣的方法也可以用在貿易戰上， 許多國家都這樣做。

Instead of depending on a single huge trading partner,

與其倚靠一個超強貿易夥伴，

they try to be everybody's friends,

還不如試著跟大家都交朋友，

because they know they can't predict

因為他們知道他們不能預測

which markets might suddenly become unstable.

哪個市場可能會突然崩盤。

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

這很花時間也很花金錢， 要協商各式交易，

but it's robust

但這很萬全，

because it makes their whole economy better defended against shocks.

因為這讓他們的整個經濟 更能防禦衝擊。

It's particularly a strategy adopted by small countries

這種策略特別受小國青睞，

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

因為他們知道他們的市場 永遠不能做主，

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

所以最好擁有非常多朋友。

But if you're stuck in one of these organizations

但是如果你待的組織，

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

還卡在效率這樣的迷思裡，

how do you start to change it?

你要怎麼開始做出改變？

Try some experiments.

嘗試一些實驗。

In the Netherlands,

在荷蘭，

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

以前居家護理師的調配 還用很像超市的做法：

standardized and prescribed work

標準化及指定化的工作——

to the minute:

以分鐘計：

nine minutes on Monday, seven minutes on Wednesday,

星期一做九分鐘，星期三做七分鐘，

eight minutes on Friday.

星期五做八分鐘。

The nurses hated it.

護理師恨死了！

So one of them, Jos de Blok,

所以護理師勃洛克

proposed an experiment.

就提出一個實驗。

Since every patient is different,

既然每個病人的情況都不一樣，

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

我們根本無從得知他們到底要什麼，

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

那我們為什麼不讓護士自己判斷呢？

Sound reckless?

聽起來有欠考慮喔？

(Laughter)

（笑聲）

(Applause)

（掌聲）

In his experiment, Jos found the patients got better

勃洛克在他的實驗中發現

病人只要原本一半的時間就好轉，

in half the time,

and costs fell by 30 percent.

花費下降了 30% 。

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

我問勃洛克他的實驗裡 哪個部分最讓他驚訝，

he just kind of laughed and he said,

他只笑了一下說：

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

「嗯，我真的不知道這麼簡單

to find such a huge improvement,

就能有這麼大的改進，

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

因為這不是你坐在書桌前 或盯著電腦螢幕

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

就能知道或預測的。」

So now this form of nursing has proliferated across the Netherlands

所以現在這樣的照護系統

已經通行荷蘭及全世界。

and around the world.

But in every new country it still starts with experiments,

但是在每個新國家 都還是要以實驗開始，

because each place is slightly and unpredictably different.

因為每個地方都不太一樣， 這種不同也很難預測。

Of course, not all experiments work.

當然，不是每個實驗都會成功。

Jos tried a similar approach to the fire service

勃洛克把類似的方法用在消防隊上，

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

發現沒有用，

因為消防隊實在非常集中派工。

Failed experiments look inefficient,

失敗的實驗看起來很沒效率，

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

但這經常是你能找出實際情況

how the real world works.

如何運作的唯一的方法。

So now he's trying teachers.

所以現在他去試試看老師這行。

Experiments like that require creativity

像這樣的實驗需要創造力

and not a little bravery.

和不只一點點的勇氣。

In England --

在英格蘭，

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

我本來要說英國，但是在英格蘭，

(Laughter)

（笑聲）

(Applause)

（掌聲）

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

在英格蘭，稱霸的橄欖球隊， 或說稱霸的橄欖球隊之一，

is Saracens.

就是薩拉森人隊。

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

球隊經理及教練意識到 他們所做的體格訓練

and the data-driven conditioning that they do

及數據導向的體能訓練

has become generic;

都變成通用的，

really, all the teams do exactly the same thing.

真的，所有的隊伍 都在做一模一樣的事。

So they risked an experiment.

所以他們放手一搏做了個實驗。

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

他們把整個隊伍調開， 即使在賽季中，

on ski trips

也跑去滑雪，

and to look at social projects in Chicago.

去芝加哥當義工。

This was expensive,

這很貴，

it was time-consuming,

這很花時間，

and it could be a little risky

而且還有點小風險，

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

你想，把整隊的橄欖球員 拉去滑雪欸？

(Laughter)

（笑聲）

But what they found was that the players came back

但是他們發現球員回去時，

with renewed bonds of loyalty and solidarity.

他們彼此之間的忠誠度 及團結度都更新了。

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

現在他們在球場上 面對極大的壓力時，

they manifest what the manager calls "poise" --

他們表現出經理說的「沉穩」——

an unflinching, unwavering dedication

一種堅定不移的彼此奉獻。

to each other.

Their opponents are in awe of this,

他們的敵隊都對此敬畏無比，

but still too in thrall to efficiency to try it.

但還是被效率束縛而不敢嘗試。

At a London tech company, Verve,

在倫敦有家科技公司叫 Verve，

the CEO measures just about everything that moves,

只要是會動的東西， 他們的執行長都要算一算，

but she couldn't find anything that made any difference

但是她找不出任何東西

to the company's productivity.

對公司的生產力有影響。

So she devised an experiment that she calls "Love Week":

所以她設計了一個實驗， 她稱為「愛情週」：

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

整整一週的時間， 每個員工都要尋找真正高明、

helpful, imaginative things

有幫助、有想像力的東西，

that a counterpart does,

是他們的對手做的，

call it out and celebrate it.

找出來並慶祝一下。

It takes a huge amount of time and effort;

這要花很多時間和努力，

lots of people would call it distracting.

很多人會說這是分心。

But it really energizes the business

但是這確實為企業注入了活力，

and makes the whole company more productive.

使整個公司更有生產力。

Preparedness, coalition-building,

準備、結盟、

imagination, experiments,

想像、實驗、

bravery --

勇氣——

in an unpredictable age,

在無法預測的時代，

these are tremendous sources of resilience and strength.

這些都是韌性與力量的重大來源。

They aren't efficient,

這些都沒有效率，

but they give us limitless capacity

但是會給我們無限的能力

for adaptation, variation and invention.

來適應、變化及創新。

And the less we know about the future,

我們對未來所知愈少，

the more we're going to need these tremendous sources

就愈需要這些巨大的來源，

of human, messy, unpredictable skills.

給我們人性化、亂七八糟、 不可預測的能力。

But in our growing dependence on technology,

但是在我們對科技 愈來愈依賴的過程中，

we're asset-stripping those skills.

我們正以資產剝離的手法 剝奪這些能力。

Every time we use technology

每次我們用科技

to nudge us through a decision or a choice

推動自己做決定或做選擇，

or to interpret how somebody's feeling

或詮釋別人的情感，

or to guide us through a conversation,

或引導我們對話，

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

我們就是把本來可以 自己做的東西外包給機器，

and it's an expensive trade-off.

而這是非常昂貴的交易。

The more we let machines think for us,

我們愈讓機器幫我們思考，

the less we can think for ourselves.

我們自己就愈不會思考。

The more --

醫師——

(Applause)

（掌聲）

The more time doctors spend staring at digital medical records,

醫師盯著數位病例的時間愈多，

the less time they spend looking at their patients.

他們花在看病人的時間就愈少，

The more we use parenting apps,

我們愈常使用育兒應用程式，

the less we know our kids.

就愈不了解自己的兒女。

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

我們花愈多時間

與自己預測並設計好 會喜歡的人相處，

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

就愈不會與異己之人建立關係。

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

我們需要的同情心愈來愈少， 我們的同情心就會愈來愈少。

What all of these technologies attempt to do

這些科技企圖要做的，

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

是把可預測現實的標準化模式

onto a world that is infinitely surprising.

硬塞到一個瞬息萬變的世界來用。

What gets left out?

這遺漏了什麼？

Anything that can't be measured --

無法測量的事物，

which is just about everything that counts.

這幾乎包含了所有事物。

(Applause)

（掌聲）

Our growing dependence on technology

我們愈來愈依賴科技，

risks us becoming less skilled,

風險就是讓我們愈來愈沒有能力，

more vulnerable

更無法應對

to the deep and growing complexity

深不可測、日益複雜的

of the real world.

真實世界。

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

在我思索著我們知道

一定會面對的極端壓力與混亂時，

that we know we will have to confront,

I went and I talked to a number of chief executives

我去找了幾位執行長談談，

whose own businesses had gone through existential crises,

他們的公司都經歷過生存危機，

when they teetered on the brink of collapse.

瀕臨倒閉的窘境。

These were frank, gut-wrenching conversations.

這些都是坦率、令人心碎的對談。

Many men wept just remembering.

許多男士想起來就掉淚。

So I asked them:

我問他們：

"What kept you going through this?"

「什麼讓你熬過去？」

And they all had exactly the same answer.

他們的回答都一模一樣。

"It wasn't data or technology," they said.

「不是數據或科技，」他們說。

"It was my friends and my colleagues

「是我的朋友及同事讓我繼續走下去。」

who kept me going."

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

有一位還補充說： 「這跟零工經濟大相逕庭。」

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

然後我去跟一群 年輕的後起新秀對談，

and I asked them,

我問他們：

"Who are your friends at work?"

「誰是你在職場上的朋友？」

And they just looked blank.

他們都兩眼空空的瞪著我。

"There's no time."

「沒有時間。」

"They're too busy."

「他們太忙了。」

"It's not efficient."

「這沒有效率。」

Who, I wondered, is going to give them

我心想，誰會給他們

imagination and stamina and bravery

想像力、耐力和勇敢，

when the storms come?

在風暴來臨之時？

Anyone who tries to tell you that they know the future

任何試圖告訴你他們知道未來的人，

is just trying to own it,

只是想佔有它，

a spurious kind of manifest destiny.

一種虛假的昭昭天命。

The harder, deeper truth is

更艱難更深沉的事實是，

that the future is uncharted,

未來是未知的，

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

我們無法把它標到地圖上， 直到我們到達為止。

But that's OK,

但這沒關係，

because we have so much imagination --

因為我們有這麼多的想像力——

if we use it.

如果我們運用想像力。

We have deep talents of inventiveness and exploration --

我們有深不可測的創新及探索才能——

if we apply them.

如果我們應用這些才能。

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

我們有足夠的勇氣 去發明我們從未見過的事物。

Lose those skills,

失去這些才能，

and we are adrift.

我們只能隨波逐流。

But hone and develop them,

但是磨練及開發這些才能，

we can make any future we choose.

我們可以創造我們選擇的未來。

Thank you.

謝謝各位。

(Applause)

（掌聲）