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)