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.
Hai pouco, o equipo de liderado dunha cadea de supermercados dos EEUU decidiu que había que mellorar a eficiencia da empresa. Así que se apuntaron entusiasmados á súa transformación dixital. Suprimiron os equipos de supervisión de carne, verduras e panadaría e introduciron un algoritmo para asignar tarefas. Ben, no canto de a xente, traballaren xunta cada empregado fichaba ao chegar, asignábaselle unha tarefa, realizábaa, e volvía por máis. Era xestión científica en grao sumo, á hora de estandarizar e asignar traballo. Era supereficiente.
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.
Ou non de todo, dado que o asignador de tarefas non sabía cando a un cliente lle ía caer unha caixa de ovos, non podía prever cando un neno revoltoso ía entornar un expositor, ou cando o instituto do barrio decidía que todo o mundo tiña que vir cun coco ao día seguinte.
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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.
A eficiencia vai moi ben cando podes prever con precisión que vas necesitar. Pero cando xorde o anómalo ou o inesperado --nenos, clientes, cocos-- ben, entón a eficiencia xa non está do teu lado.
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.
Isto volveuse unha cuestión esencial, esta capacidade para facer fronte aos imprevistos, porque os imprevistos están a converterse na norma. É o motivo polo que aos expertos e aos analistas lles custa facer predicións con máis de 400 días de antelación. Por que? Porque nos últimos 20 ou 30 anos, boa parte do mundo pasou de ser complicado a ser complexo -- é dicir, é verdade que hai certas pautas, pero non se repiten de xeito regular. O que significa que cambios moi pequenos poden ter un impacto desproporcionado. E significa que non sempre vai abondar coa experiencia, porque o sistema non deixa de mudar demasiado rápido.
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.
Así que o que todo iso significa é que hai una enorme cantidade de cousas que, digamos, se resisten ás predicións. É por iso que o Banco de Inglaterra di que, efectivamente, haberá outra crise pero non sabemos por que ou cando. Sabemos que o cambio climático é real, pero non podemos prever en que lugar se vai producir un incendio e non sabemos que fábricas van quedar asolagadas. Por iso ás empresas cólleas por sorpresa que, de repente, as pallas de plástico, as bolsas e as botellas de auga pasen de ser produtos básicos a ser algo que hai que evitar. E confúndeos que un cambio de costumes convirta estrelas en marxinados e colegas en proscritos: incerteza imsuprimible. Nun entorno que desafía de tal xeito as predicións, a eficiencia non só non nos vai servir; de feito socaba e debilita a nosa capacidade de adaptación e resposta.
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.
Entón, se a eficiencia xa non é o noso pricipio guía, como debemos afrontar o futuro? Que modo de pensar é o que nos vai axudar? Que clase de talentos debemos asegurarnos de defender? Penso que onde antes adoitabamos pensar moito en xestión "xusto a tempo", temos que comezar a pensar en "por se acaso". e prepararnos para acontecementos que son en xeral seguros pero permanecen ambiguos no específico.
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.
Un exemplo é a Coalición para a Preparación ante Epidemias, a CEPI. Sabemos que no futuro haberá máis epidemias, pero non sabemos onde, cando ou que. Así que non podemos planificar nada. Pero podemos prepararnos. A CEPI está a crear múltiples vacinas para múltiples doenzas, aínda que non poden predicir cales desas vacinas van funcionar ou que enfermidades van aparecer. Así que algunhas desas vacinas non se van usar nunca. É ineficiente. Pero é sólido, porque ofrece máis opcións, o que significa que non dependemos dunha única solución tecnolóxica. A capacidade de resposta ás epidemias tamén depende en gran medida de persoas que se coñecen e confían uns noutros. Pero desenvolvermos esas relacións leva tempo, e tempo é o que sempre escasea cando estala unha epidemia. Por iso a CEPI está a desenvolver relacións, amizades, alianzas, aínda que saben que algunhas delas poden non chegar a necesitarse. É pouco eficiente, se cadra unha perda de tempo, pero é sólido.
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.
Tamén podemos ver razoamento sólido nos servizos financeiros. No pasado, os bancos adoitaban dispor de moito menos capital do que se lles esixe hoxe, porque dispor de tan pouco capital, ser demasiado eficientes con el, era precisamente a causa da fraxilidade dos bancos. É certo que dispor de máis capital semella e, de feito, é ineficiente. Pero dá solidez, porque protexe o sistema financeiro das sorpresas.
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.
Os países que toman en serio o cambio climático saben que teñan que adoptar solucións múltiples, múltiples formas de enerxías renovables, e non unha soa. Os países máis avanzados levan anos traballando, cambiando o abastecemento de auga e alimentos e o sistema sanitario, porque recoñecen que no momento en que poidan predicir con certeza, se cadra esa información xa chega tarde.
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.
O mesmo enfoque é aplicable ás guerras comerciais, como saben moitos países. No canto de depender dun único socio comercial enorme, tratan de ser amigos de todos, dado que saben que non se pode predicir que mercados poden volverse inestables de súpeto. Negociar todos eses acordos require moito tempo e é caro, pero é sólido, porque proporciona unha defensa mellor de toda a economía fronte a sobresaltos. É sobre todo a estratexia que adoptan os países pequenos que saben que carecen de músculo para mandar no mercado, así que é simplemente mellor contar con demasiados amigos. Mais se estás atrapado nunha destas organizacións que seguen prisioneiras do mito da eficiencia, como comezas a cambiala? Intenta uns experimentos.
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?
Nos Países Baixos, a asistencia a domicilio xestionábase máis ou menos coma o supermercado: traballo estandarizado e prescrito minuto a minuto: nove minutos os luns, sete minutos os mércores, oito minutos os venres. Os enfermeiros odiábano. Así que un deles, Jos de Blok, propuxo un experimento. Dado que cada paciente é distinto, e non sabemos ben que vai necesitar, por que non deixamos que decidan os enfermeiros?
Sound reckless?
Soa irresponsable?
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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.
Neste experimento, Jos descubriu que os pacientes melloraban na metade de tempo, e os custos reducíronse un 30 por cento. Cando lle preguntei a Jos que o sorprendera do experimento díxome rindo: "Non tiña nin idea de que podía ser tan doado lograr melloras tan enormes, porque isto non é algo que se poida saber ou predicir sentado nunha mesa ou diante dun ordenador" Así que esta forma de asistencia espallouse polos Países Baixos e por todo o mundo. Pero cada vez que se instala nun país comeza con experimentos, porque en cada lugar hai pequenas diferencias imprevisibles.
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.
Por suposto, non todos os experimentos funcionan. Jos probou un enfoque similar co servizo de bombeiros e viu que non funcionaba porque o servizo está demasiado centralizado. Os experimentos errados semellan ineficientes, pero son a miúdo o único xeito que temos de descubrir como funciona o mundo real. Así que agora está probando cos mestres. Experimentos coma ese requeren creatividade e non pouca audacia.
In England -- I was about to say in the UK, but in England --
En Inglaterra -- case digo Reino Unido, pero é en Inglaterra --
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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?
En Inglaterra, o mellor equipo de rugby, ou un dos mellores, son os Saracens. O presidente e o entrenador decatáronse de que todo o seu adestramento físico e a preparación baseada en datos que poñen en práctica volvéronse xenéricos; de feito, tódolos equipos fan exactamento o mesmo. Así que se arriscaron a experimentar. Levaron a todo o equipo, mesmo en plena temporada, de viaxe a esquiar e a ver proxectos sociais en Chicago. Foi caro, levou moito tempo, e podía ser un tanto arriscado poñer un feixe de xogadores de rugby nunha pista de esquí, non si?
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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.
Pero o que descubriron foi que os xogadores voltaban con vínculos renovados de lealdade e solidariedade. E agora cando están no campo baixo unha presión incrible, manifestan o que o presidente chama "confianza" -- unha inquebrantable e firme dedicación mútua. Os seus rivais están abraiados, pero seguen demasiado atados á eficiencia como para intentar iso.
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.
En Verve, unha tecnolóxica londinense, a directora xeral mide practicamente todo o que se move, pero non logrou atopar nada que tivese impacto na produtividade da empresa. Así que deseñou un experimento que chama "A semana do cariño": durante toda unha semana cada empregado ten que buscar algo enxeñoso, práctico e imaxinativo que faga algún compañeiro, pregoalo e festexalo. Esixe moitísimo tempo e esforzo; moitos dirían que é unha distracción. Pero en realidade estimula a actividade e fai que toda a empresa sexa máis produtiva.
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.
Preparación, formación de coalicións, imaxinación, experimentos, coraxe -- nunha época imprevisible, esas son fontes extraordinarias de resiliencia e fortaleza. Son eficientes, pero apórtannos unha capacidade infinita para a adaptación, a variación e a invención. E canto menos saibamos sobre o futuro, máis imos necesitar destas fontes fabulosas de destrezas humanas, caóticas e imprevisibles.
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 --
Pero a nosa crecente dependencia da tecnoloxía lévanos a liquidar esas destrezas. Cada vez que nos servimos da tecnoloxía para animarnos a tomar unha decisión ou facer unha elección ou para interpretar os sentimentos dalguén ou para guiarnos nunha conversa, estamos subcontratando unha máquina para o que podemos facer nós mesmos, e é un intercambio que sae moi caro. Canto máis deixamos que as máquinas pensen por nós, menos podemos pensar por nós mesmos. Canto máis --
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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.
Canto máis tempo pasan os médicos mirando historiais dixitalizados, menos tempo pasan vendo pacientes. Canto máis usamos apps para pais e nais menos coñecemos aos nosos fillos. Canto máis tempo pasamos con persoas que está previsto e programado que nos gusten, menos capaces somos de conectar coas que son diferentes de nós. E canta menos compaixón necesitamos, menos compaixón temos
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.
O que tentan facer todas estas tecnoloxías é aplicar á forza un modelo estandarizado dunha realidade previsible a un mundo de infinitas sorpresas. Que é o que queda fóra? Calquera cousa que non se poida medir -- o que vén sendo practicamente todo o que importa.
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Our growing dependence on technology risks us becoming less skilled, more vulnerable to the deep and growing complexity of the real world.
A nosa crecente dependencia da tecnoloxía ponnos en risco de perder destrezas, de ser máis vulnerables diante da profunda e crecente complexidade do mundo real.
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?"
Cando estaba a pensar nos extremos de tensión e axitación aos que sabemos que nos imos ter que enfrontar, fun falar cunha serie de directivos cuxas empresas pasaran por crises existenciais nas que cambalearon ao bordo do colapso. Foron conversas francas e desgarradoras. Moitos choraron ao lembrar. Así que lles preguntaba: "Que che axudou a seguir adiante?"
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."
E todos respondían exactamente o mesmo. "Non foron os datos nin a tecnoloxía", dicían "Foron os meus amigos e os compañeiros os que me deron forza para seguir."
One added, "It was pretty much the opposite of the gig economy."
Un engadiu: "Foi máis ben o oposto á economía baixo demanda."
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.
Pero entón fun falar cun grupo de xoves executivos emerxentes e pregunteilles: "Que amigos tedes no traballo?" Quedaron mirando.
"There's no time."
"Non hai tempo."
"They're too busy."
"Están demasiado ocupados."
"It's not efficient."
"Non é eficiente."
Who, I wondered, is going to give them imagination and stamina and bravery when the storms come?
Pregunteime quen lles vai dar imaxinación e resistencia e coraxe cando cheguen as tormentas?
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.
Calquera que trate de dicirnos que coñece o futuro só intenta posuílo, unha forma espuria de destino manifesto. A verdade máis dura e profunda é que o futuro é territorio inexplorado, e non podemos facer mapas ata chegarmos aló.
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.
Pero non hai problema, porque temos tanta información -- se a empregamos. Temos un profundo talento para a inventiva e a exploración -- se o poñemos en práctica. Temos valor abondo para inventar cousas que nunca antes víramos. Se perdemos esas destrezas, quedamos á toa. Pero se as perfeccionamos e as desenvolvemos, podemos crear calquera futuro que elixamos.
Thank you.
Grazas.
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