The strategic underpinnings of most companies’ workforce plans should change dramatically as a result of technological innovation. Digital transformation, the industrial internet, advanced analytics, artificial intelligence, robotics, machine learning, and a plethora of other innovations are fundamentally changing the nature of work. Machine learning, for example, may not eliminate many jobs in their entirety. But it will impact the way many jobs are performed, requiring new skills and making many existing skills less valuable. The World Economic Forum predicts that “by 2020, more than a third of the desired core skill sets of most occupations will be comprised of skills that are not yet considered crucial to the job today.”
由于技術(shù)創(chuàng)新，大多數(shù)公司勞動(dòng)力計(jì)劃的戰(zhàn)略基礎(chǔ)應(yīng)該發(fā)生巨大變化。數(shù)字轉(zhuǎn)換、工業(yè)互聯(lián)網(wǎng)、高級(jí)分析、人工智能、機(jī)器人學(xué)、機(jī)器學(xué)習(xí)以及其他許多創(chuàng)新都從根本上改變了工作性質(zhì)。例如，機(jī)器學(xué)習(xí)可能不會(huì)完全取代一些工作，但它會(huì)影響許多工作的執(zhí)行方式，需要用到新技能，使許多現(xiàn)有技能變得不那么有用。世界經(jīng)濟(jì)論壇預(yù)測(cè)：“到2020年底，超過三分之一的大部分核心職業(yè)技能將由那些尚不被認(rèn)為是工作重要組成部分的技能組成?！?/div>

Beyond the skills required to perform specific jobs, technology will also determine which jobs matter most in the years to come. New innovations will change the basis of competition in many markets and alter the sources of advantage for most companies. Business-critical roles — that is, the jobs that are central to differentiating a company from its competitors and successfully executing its strategy — will also change. And companies will be forced to rethink the talent they will need to play these business-critical roles in the future.
除了完成特定工作所需的技能外，科技還將決定今后幾年最重要的工作是什么。新的創(chuàng)新將改變?cè)S多市場(chǎng)的基礎(chǔ)競(jìng)爭(zhēng)，并且改變大多數(shù)公司的優(yōu)勢(shì)來源。企業(yè)關(guān)鍵角色也將隨之改變，也就是說將公司與競(jìng)爭(zhēng)對(duì)手區(qū)分開來并成功執(zhí)行其戰(zhàn)略的核心工作。公司將被迫重新考慮在未來發(fā)揮這些商業(yè)關(guān)鍵角色所需的人才。

Take insurance, for example. In years past, an important source of competitive advantage for insurers was the ability to price risk better than rivals. Armies of actuaries worked tirelessly to estimate the cost of underwriting certain risks (or risk pools). In the future, much of this work will be done by machines. In this world, insurance companies will require fewer actuaries and more data scientists — individuals with the ability to mine data to tailor insurance offers to specific market segments or even individuals. It may be possible to retool some actuaries as data scientists, but the vast majority of these roles will probably need to be filled with new talent.
以保險(xiǎn)為例，在過去的幾年中，保險(xiǎn)公司的一個(gè)重要競(jìng)爭(zhēng)優(yōu)勢(shì)是有比對(duì)手更好的定價(jià)風(fēng)險(xiǎn)的能力。大批的精算師孜孜不倦地估計(jì)固定風(fēng)險(xiǎn)（或風(fēng)險(xiǎn)基金）的成本。未來這項(xiàng)工作將大部分由機(jī)器完成。在這個(gè)世界上，保險(xiǎn)公司將需要更少的精算師和更多的數(shù)據(jù)科學(xué)家，那些有數(shù)據(jù)挖掘能力的人給特定企業(yè)或個(gè)人量身定制保險(xiǎn)需求。它可能會(huì)用一些數(shù)據(jù)科學(xué)家替換精算，但這些角色的絕大多數(shù)可能將需要有新的人才。

Most companies have been slow to react. In part, this is because the impact of technology will be felt over time, and not overnight. This creates the illusion of having time to react. Also, with technological innovation, there will always be a high degree of uncertainty regarding the kind of talent your company will need in the future. This makes it challenging for leaders to plan ahead and place bets early.
大多數(shù)公司反應(yīng)遲緩。在某種程度上，這是因?yàn)榧夹g(shù)的影響會(huì)隨著時(shí)間變化，而不是一夜之間。這就產(chǎn)生了時(shí)間反應(yīng)的錯(cuò)覺。此外，隨著技術(shù)革新，未來公司需要的人才類型總是會(huì)有很大程度的不確定性。這使得領(lǐng)導(dǎo)者提前計(jì)劃并提前下注很有挑戰(zhàn)性。

But building a winning workforce for tomorrow starts today. The best-performing companies are already taking steps to attract new talent and widen their lead over rivals. Here are three lessons every organization should learn from what the leading companies are doing:
但為明天建立一支成功的勞動(dòng)力隊(duì)伍要從今天開始。業(yè)績(jī)最好的公司已經(jīng)開始采取措施吸引新的人才，擴(kuò)大他們比競(jìng)爭(zhēng)對(duì)手的領(lǐng)先優(yōu)勢(shì)。這里有三個(gè)教訓(xùn)，每個(gè)組織者都應(yīng)該從領(lǐng)先的公司那里學(xué)到：

Delineate the skills and capabilities that will be required to win in the future, based on your company’s strategy
要想贏在未來，建立在公司策略上的描述技能和能力是必不可少的

When Bain & Company examined the talent management practices of more than 300 large companies worldwide, we discovered that the most productive and best-performing organizations cluster their star talent in a few business-critical roles. This “intentionally nonegalitarian” model ensures that scarce difference-making talent is put in roles where it will have the biggest effect.
當(dāng)貝恩公司對(duì)全球三百多家大公司的人才管理實(shí)踐進(jìn)行考察時(shí)，我們發(fā)現(xiàn)最具生產(chǎn)力的和表現(xiàn)最佳的組織在一些關(guān)鍵的商業(yè)角色中聚集了他們的明星人才。這種“刻意不平等主義”模式確保不同的天分被帶入不同的角色，充分發(fā)揮最大影響。

But the roles most companies specify as business-critical will need to change as technology changes. Advanced analytics, the Internet of Things, artificial intelligence, and other innovations are making it possible for companies to compete in new and very different ways. This should lead to new strategies and, with them, new business-critical roles.
但大多數(shù)公司所指定的關(guān)鍵業(yè)務(wù)角色將隨著技術(shù)的變化而改變。先進(jìn)的分析、物聯(lián)網(wǎng)、人工智能和其他創(chuàng)新使公司能夠以新的和不同的方式進(jìn)行競(jìng)爭(zhēng)。這將導(dǎo)致新的戰(zhàn)略和新的業(yè)務(wù)關(guān)鍵角色。

John Deere is a case in point. The company has always focused on providing farmers with the tools they need to feed the world’s growing population. But new sources of crop, weather, and other data have created new opportunities to boost farm productivity. John Deere’s Intelligent Solutions Group has turned real-time data, crowdsourced from thousands of the company’s customers, into services enabled by Big Data. As Deere’s strategy has shifted, so have the business-critical roles at the company—from traditional manufacturing positions to analytics and services roles. Attracting workers skilled in advanced analytics will become increasingly important for the company (as will the technology and processes required to translate these skills into real sources of advantage); industrial engineering and plant management skills will become less critical to fueling the company’s long-term growth.
John Deere是一個(gè)很好的例子。該公司一直致力于向農(nóng)民提供他們所需的工具來養(yǎng)活世界上日益增長(zhǎng)的人口。但是農(nóng)作物、天氣和其他數(shù)據(jù)的新來源為提高農(nóng)業(yè)生產(chǎn)力創(chuàng)造了新的機(jī)會(huì)。John Deere的智能解決方案集團(tuán)已經(jīng)把實(shí)時(shí)數(shù)據(jù)以及成千上萬的公司客戶轉(zhuǎn)變成了基于大數(shù)據(jù)的服務(wù)。隨著Deere的戰(zhàn)略轉(zhuǎn)移，公司的關(guān)鍵業(yè)務(wù)角色也隨之轉(zhuǎn)移——從傳統(tǒng)的制造業(yè)崗位到分析和服務(wù)的角色。吸引高級(jí)分析師對(duì)公司將會(huì)越來越重要（科技和過程將會(huì)把技能轉(zhuǎn)化為真正優(yōu)勢(shì)資源）；工業(yè)工程和工廠管理能力將在推動(dòng)公司長(zhǎng)期增長(zhǎng)方面發(fā)揮越來越少的作用。

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