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How can business leaders make the new world of work better for people?

| Podcast

How can CEOs stay ahead of the curve in training and developing their workforces for using automation and artificial intelligence (AI)? Since companies are doing the hiring and creating the jobs, what role do they play in talent and development? How should companies think about hiring as work changes?

In this episode of the New World of Work podcast, McKinsey Global Institute director James Manyika speaks with two leaders on the forefront of applying AI techniques, such as automation and machine learning, in the business world. John Donahoe, president and CEO of ServiceNow, and Jeff Weiner, CEO of LinkedIn, tackle the tough questions facing companies today.

Podcast transcript

James Manyika: When it comes to the issue of the future of work and automation, businesses are at the center for several reasons. For one, they are large employers of people and workers, and they are embracing these technologies that are starting to automate work. They play a central role through the choices that they make in using these technologies. Sometimes, they’re also in the business of building products and services that also change and transform how we do work. And then sometimes, you come across rare business leaders who are far-forward-looking, think beyond their own businesses, and think about what these things mean for society.

With that note, I’m quite delighted that we have two business leaders who satisfy all three of those criteria. They are employers, they are innovators building products and services, and they’re also thinking beyond their own businesses to what this means for society. John Donahoe was CEO of eBay and is now president and CEO of ServiceNow. Jeff Weiner is CEO of LinkedIn and has been at LinkedIn for a decade.

I want to start with one issue. Right now, there’s something in the air about the idea that businesses, especially tech businesses like yours, are limiting the opportunities for people to prosper and do well. And so, let’s talk about that quite directly. Jeff, you’ve been talking about an economic graph. What is it? And what does it have to do with LinkedIn?

Jeff Weiner: The economic graph is the manifestation of our vision at LinkedIn to create economic opportunity for every member of the workforce. There are more than three billion people in the global workforce; some would estimate as many as three-and-a-half billion people.

We draw a clear distinction between vision and mission. The vision is the “true north”—it’s the dream, it inspires us. But the mission is the overarching objective that we measure ourselves against—it’s realizable and, hopefully, inspirational. And the mission is to connect the world’s professionals, make them more productive and successful.

Around six years ago, as we started to recognize that we were on a path to connect the world’s professionals, we started asking ourselves: What’s next? Although there’s plenty of work still to be done regarding the mission, we decided that we should start taking the vision seriously and thinking about how to operationalize it. And so, that’s what the economic graph is all about.

A graph refers to the mechanism through which you map nodes or connections. At LinkedIn, historically, we always had this idea of a professional graph where we connected professionals, and we created value for them through those relationships. The economic graph is digitally mapping the global economy, and we want to do that across six different pillars or dimensions where, ultimately, we’ll have a profile on LinkedIn for every member of the global workforce, all three-billion-plus folks.

And we’ll have a profile for every company in the world. When you include small and medium-size businesses, there are an estimated 60 million companies in the world. We’d like for there to be a digital representation for every available job in the world. There’s roughly 20 million available jobs that can be digitally accessed and made available to people online.

Finally, we’d like for there to be a digital representation for every skill required to obtain the jobs offered by those companies. With the acquisition of several years ago, it’s not only about creating a structured database around these skills and the skills that would be necessary to get those jobs; it also involves providing the coursework that enables people to acquire those skills.

James Manyika: You basically want to be able to connect people to jobs and give them information about the skills that are needed out there. Is that right?

Jeff Weiner: Yes. The idea is to enable all forms of capital—intellectual capital, working capital, human capital—to float to where it can best be leveraged and, in doing so, help lift and transform the global economy.

James Manyika: John, in the businesses you’ve been involved in, how have you created opportunities for people? Because you’ve mostly run and created technology-based businesses on some level.

John Donahoe:  I think these technology platforms can create opportunities. I got to see this firsthand at eBay, which used technology to help people, entrepreneurs, and small businesses earn their living.

About 1.4 million people make their primary or secondary living on eBay. When you get to see who these people are, they are sometimes unemployed when they started their businesses. They’re often people who were laid off. They’re not coming from privileged circumstances. What technology has done is to augment their ability to compete on their creativity and their hard work. What the technology did was take what is complex and mundane about building a business and take that part out so that they could compete. It was a fascinating use of technology to enable people to create economic opportunity for themselves in the work they loved and create a job out of it. No one was thinking about creating a job out of collar stays, or selling collar stays, or selling all the hundreds of thousands of different items people sell on eBay.

James Manyika: Is the analogy in your case that we shouldn’t think of wages but of incomes? Because you provided a way for people to get incomes in a much wider range of things beyond just their wages.

John Donahoe: The broader income-inequality issues are very complicated. Minds far bigger than mine can solve those. But I do think technology can help people do higher-value-added work and bring the very best out in themselves so that they can create jobs.

James Manyika: Right. Well, take that to what you’re doing now, with ServiceNow.

John Donahoe: It was a similar thing that led me to ServiceNow, in an unanticipated way. We all know how technology and cloud-based applications have transformed our lives as consumers at home. They’ve taken what used to be complex, tedious, or mundane and made it easy and intuitive. They’ve added value to our lives. But as I reflected about technology in the workplace, no one would say technology in the workplace is easy, intuitive, or adds value. It’s frustrating. It’s complicated. We spend huge amounts of our time at work dealing with the complexity of technology. When I got introduced to ServiceNow, I realized that cloud-based platforms have the power to transform our experiences at work in the same way that this technology has done at home. And increasingly, millennials are demanding the same experiences at work as they’re getting at home.

That’s what ServiceNow does—we make the world of work better for people. I’ll just give a small example that’s mundane, but I often think these big topics like automation and AI get down to our own mundane lives. Say you have your money in PayPal. If you can’t get into PayPal, you can reset your password in about one minute, safely, anywhere in the world, from your mobile phone. And you do it safely. That’s convenience. That’s adding value to your life.

How many people here have had trouble resetting their email password at work? Why is it that at work, if we can’t get into our email, we have to call the IT person? It’s a frustrating experience. The IT professional hates it. We hate it. It’s frustrating because it’s not our money, it’s our email. What ServiceNow does, in simple terms, is to provide the same kind of self-help automation to reset your email password as you would be able to use to reset your banking or PayPal password at home. Just look at the amount of work that goes into menial, redundant, frustrating tasks and how technology can help simplify those, automate them, so that you can spend more time at work on value-added activities, creative activities, much like eBay sellers could spend more time selling.

James Manyika: Both of you are CEOs; both of you employ lots of people; but at the same time, you’re also clearly embracing these technologies. You’re probably embracing machine learning. You’re probably embracing automation in one form or another. Let’s talk about that and the choices you’re making. Jeff, where are you embracing these tools in your business, and how are you using them? And what does it mean for the people who work for you?

Jeff Weiner: So, we can segment it across at least three different constituents: members, customers, and our employees.

Regarding members, machine learning has always been a foundational part of LinkedIn. And we’re trying to make the best recommendations we can to create the most relevant experience our members, whether that’s in the feed or whether that’s regarding a skill that you should be learning or a job that we think is going to be well-suited for you based on your experience, your background, or who you know. For members, we can make better matches by virtue of leveraging that technology. We can also better understand where skills gaps exist. So, if a member is interested in a particular job, by virtue of their profile, we can see what skills they have and what experiences they have. When we think there’s a gap, we can make a recommendation in terms of the kinds of skills they should be picking up—which, by the way, are not necessarily relegated exclusively to technology. Interpersonal skills, leadership, and some of the softer skills that were mentioned earlier will continue to be essential.

Regarding customers, all of our business lines are oriented around making our customers more productive, more efficient, and more effective across multiple value propositions. We just announced a new product suite called Talent Intelligence. In use cases for the economic graph, we would talk about it in the context of locality and geography. You could pick any place in the world and understand skills gaps within that locality. You could understand the fastest-growing jobs and the skills required to obtain those jobs. You could understand the skills of the aggregate workforce within that locality. You could measure the gap. And then, you could equip those that could make use of it—vocation-training facilities, junior colleges, four-year universities—with data that demonstrates where those gaps exist. They could close the gaps, create just-in-time curriculum, and make sure that they’re training the workforce for the jobs that are and will be, and not just the jobs that once were. We can now do that for customers. Within any company anywhere in the world, we can help them develop a workforce strategy that is going to better position them considering all the changes that are taking place based on our infrastructure, our data, et cetera.

Finally, for employees, it’s similar to what we’re doing for our customers, to the extent that we can find these repeatable, high-volume tasks that don’t necessarily require the kinds of talent that we have within the organization. If we can take the robot out of the role and leave them to the parts that are higher value added—that are uniquely suited for our kind of talent and our team—then that makes them more efficient and more effective.

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James Manyika: Let’s just imagine you’re the CEO of a large retailer or the CEO of a large manufacturing company—a large, very people-intensive business. And, suddenly, these technologies come along, and you can automate things. How would you think about that? How should CEOs think about that question, when there clearly are business benefits to using these technologies, but, at the same time, you’ve got these large workforces?

John Donahoe: The word “automation” and the word “AI” evoke a very binary, almost emotional, reaction: it’s going to be the takeover of the machines, and humans will be gone.

Jeff Weiner: Makes for better movies, John.

John Donahoe: It makes for better movies—yeah, exactly. And then, to be honest, I think the other side of the equation is that there are Silicon Valley companies with their heads in the sand saying, “Well, technology’s great. There’ll be no second-order effects.” And neither of these is true.

The way automation really has the biggest impact is in what you said in your report, Jobs lost, jobs gained: Workforce transitions in a time of automation. It’s taking pieces of jobs. It’s taking the parts, often the redundant, the mundane, the not very exciting parts of a job, and simplifying them and automating them. I’ll give two examples.

At ServiceNow, we make automation software for customer-support operations. On our own customer-support operation, we have 400 engineers that solve our customers’ problems when those customers call. About 10 percent of those engineers’ time is spent trying to figure out—categorizing—what the problem is and getting it to the right person to fix it. So, we turn the machine learning on in our platform. And within a week, the machine was more accurately categorizing what the inbound customer problem was and getting it to the right person so it could be solved more quickly and solved the right way the first time. So, you could say, “Oh my God, that took away 10 percent of the jobs of the 400 engineers.” Of course, that’s not what they felt. They felt like it was the bottom 10 percent of what they hated to do. And now they took that 10 percent, and they applied it to solving customers’ real problems. And that’s a case where automation—in this case, machine learning—is taking a piece of a job or role—and often the lowest-value-added piece—and freeing them up from it.

Second example. We had the privilege of having dinner with Doug McMillon, the CEO of Walmart, and his team about a month ago, talking about this very issue. And Walmart’s the largest private-sector employer in the world, and he was so articulate about saying that Walmart is a people company, not a technology company. And yet, their store associates spend a reasonable amount of time restocking shelves and doing tasks that they don’t really like to do and are not particularly creative, customer-serving tasks. So, they’re now trying to use automation to simplify and automate some of the restocking tasks so that their store associates can spend more time with customers, calling upon their customer-facing skills and their creativity. And what I thought was so nice about that is Doug has declared, “We are a people company, first and foremost. And technology is in service to our people,” not vice versa. By the way, Pierre Omidyar said that at eBay, Fred Luddy said that at ServiceNow, Reid Hoffman said that at LinkedIn—technology is in service to people, not the other way around.

James Manyika: Do you think most CEOs think that way?

Jeff Weiner: I don’t know if I would overgeneralize across the board. I think it depends on the industry. It depends on the CEO, depends on the leadership style, depends on the talent they have around them. I think increasingly, people need to recognize it. I agree with everything John said, but I’m reminded of the old adage, “You can’t fix it if you can’t measure it.”

I think you have to start by measuring your workforce. You have to understand your workforce. And, as you well know, there are companies with gigantic scale on a global basis. And, surprisingly, leaders within some of those organizations don’t know where all the people are. They don’t know the skill sets of their workforce. They don’t know the fastest growing jobs. They don’t know where the skills gaps exist. They don’t know where there are geographic surpluses of talent and where they can tap that talent and where they should be shifting resources from one locality to another locality.

So, to the extent leaders can proactively get ahead of these trends, you don’t want to be on the reactive side of this. You don’t want to wake up one day and see that you’ve got a double-digit percentage of your workforce that doesn’t have the right skills for the work that any organization needs to undertake to remain competitive and to grow. So, you want to get ahead of that. And whether it’s LinkedIn, whether it’s ServiceNow, whether it’s any organization that’s now in the business of helping organizations digitally transform or better understand some of these future-of-work trends, you can measure it. You can get ahead of it. And then, once you measure it, you can do something about it. You can iterate and improve upon your workforce strategies. You can try to figure out how to make sense and make use of automation. As James’s team has reported previously, roughly half of all work activities and work processes are susceptible to automation.

I like that language, “susceptible.” It’s not that every worker’s going to be displaced. As a matter of fact, the more work you do and research that your team does, the more it appears that people won’t be displaced so much as they’re going to end up changing roles or needing new skills to take advantage of the work that exists. And so, how can you get ahead of that trend and see where people within your organization can be reskilled to take advantage of a job that’s going to be growing that your organization is going to become dependent on?

James Manyika: On that note, Jeff, you must have probably the most unique vantage point out of anybody in this ecosystem in the sense that you probably see more than anybody what’s happening in terms of what skills are in demand, because now recruiters come to you and employees are changing their résumés. What are you seeing in terms of the evolution of changes in skills?

Jeff Weiner: First, not surprisingly, tech remains king. And if you were to look at the fastest-growing, emerging jobs, unsurprisingly, they’re related to some of the trends that we’re talking about regarding data. So, machine learning, data science, big data engineers—three of the top fast-growing, emerging jobs. So, that’s one.

Two, maybe a little less intuitive because it’s kind of the converse, is that it’s not just about technology. And I think this is going to be a trend that people really start to embrace going forward. Computers, machines—all the things you see if you watch some of the videos circulating right now in terms of robots trying to replicate human behavior—we’ll see how fast that gap gets closed. But hopefully, it’s going to be a while before machines can replicate the human touch and intuition and creativity and interpersonal skills. And so, you see jobs that require those interpersonal skills that continue to grow very quickly. So, sales-development representatives, customer-success representatives—these are jobs that require interpersonal relationships.

James Manyika: Can you make a list so we can take notes?

Jeff Weiner: We can do better than make a list and take notes. We’ll distribute this information very broadly. We have a monthly workforce report, and we’re starting to do that on a global basis.

And then I guess the third is a trend we haven’t touched on yet; we’ve been focused on AI and automation. There are two additional areas that we may get into; one is what we believe are multiple skills gaps that exist depending on locality.

The third is the rise of independent work and independent workers. We see that manifesting itself in some of the fastest-growing skills and roles—for example, realtors. People becoming real-estate agents is a byproduct of the flexibility that is afforded folks with that kind of independent work. Also, I think, it is a reflection of the bounce-back in the housing market. It also demonstrates the rise of independent work and trends in demographics and psychographics. Is anyone here familiar with barre? It’s the barre in the dance studios, for those of you unfamiliar with this. People being certified in teaching workouts that leverage barre is one of the fastest-growing skills that we’re seeing. It’s off of a relatively smaller base.

James Manyika: Are you qualified?

Jeff Weiner: I am not qualified and, for the life of me, could not get my leg on top of that barre if you asked me to. So, anyway, these are examples that I think are somewhat illustrative of some of the secular trends taking place.

James Manyika: Go ahead, John.

John Donahoe: Just to build on that, I think there again, there’s a sense of, if you’re not a computer scientist, you don’t have a future. What a lot of these technologies do is to create jobs where you work with technology. ServiceNow creates ServiceNow administrators. They don’t have to have technical degrees. They’re working with the technology. There’s a whole host of jobs being created where you have to work with technology. You don’t have to be a technologist.

Some of the job reskilling and retraining is to get people comfortable with that. How do you build those skills? And those are skills for which you don’t need a four-year degree. It’s breaking down barriers and boundaries so that there’s a comfort of working with the technology, because a lot of the jobs of the future will be working with technology, not being the builder of the technology.

Jeff Weiner: I couldn’t agree more. And I think it’s so important. Oftentimes, when we talk about technology, it is in terms of advanced technology skills, but there are also basic technology skills that enable people to be better positioned.

James Manyika: Such as?

Jeff Weiner: Being able to use a word processor. Being able to navigate your way around a spreadsheet.

I think one of the reasons it’s so important is, not everyone has access to the kind of prestigious four-year universities that historically have been required to obtain jobs. And trust me, there are plenty of people out there that can do amazing work if given the opportunity and if organizations widen and broaden the aperture of the kind of talent they’re bringing into their organizations. But if, exactly to the point of your research, people are going to need to learn new skills, especially in a digital economy, this becomes a foundational element of that. And there’s kind of a slight pivot, a softer pivot, and a hard pivot. And if you have to start from scratch, it’s going to be very, very difficult to compete for those jobs.

James Manyika: But here’s the thing. Our track record on skilling and skill development has not been great—as countries, as societies and communities. The facts are not in our favor here. Companies are spending less on job training, and countries are spending less on job training. And the rates of success are not as high. We’re all saying that skills are going to matter and reskilling is going to matter. So, how do we break the fact that we haven’t been able to solve it and it’s probably about to get more challenging?

Jeff Weiner: For starters, companies have to step up, period, full stop. You know, there’s an ongoing debate—I don’t even know if it’s a debate so much as a discussion. Is it the responsibility of governments? What’s the responsibility of companies?

Companies are on the front lines. Companies see the trends; companies are doing the hiring. Companies are creating the jobs. Companies should be responsible for reskilling, upskilling, learning, and development. So, I think it’s critical.

John Donahoe: Just to build on that, what are the implications for their own employees? And then, for the implications of our products—particularly in technology, with the implications of what our platforms do—we have to take responsibility for that.

Jeff Weiner: Absolutely. And it’s not just up to companies. It’s not up to any constituency in isolation. We’ve been working with Markle, and NGOs [nongovernmental organizations] become critical. And we’re trying to figure out middle-skill jobs. We’re trying to figure out how to create opportunities for people that don’t have those four-year degrees, who can learn new skills, who can become certified, get their foot in the door, and kick ass. And we see it all the time.

We’ve got programs at LinkedIn designed to broaden the aperture. We have one guy who became homeless and developed an application to figure out how to assist people finding shelter. He was brought into this program that we call REACH, which is designed for people that don’t have the traditional engineering background but have been certified or have completed a coding boot camp. And these people have the growth mind-set. They have the resiliency, they have the perseverance, and they’re amazing. And of a class of roughly 30 people, we had80 percent yield in terms of becoming engineers at LinkedIn.

Whether it’s LinkedIn or ServiceNow or any company, I think it’s incumbent upon us to get involved and to start thinking about how to create these opportunities to partner with NGOs. By the way, maybe governments aren’t doing as much as we’d all like, but there are governments that are allocating billions of dollars to reskilling. And hopefully, they’re going to be able to take advantage of data and infrastructure that didn’t exist previously to make those investments count.

James Manyika: So, are you both optimistic? At the same time, what do you worry about?

John Donahoe:  I think the last ten to 15, maybe 20 years, have been sort of the glory years, if you will, of this new round of cloud-based, mobile-based technology. It’s Silicon Valley–based technologies that have enhanced the quality of our lives as consumers and increasingly at work. And so, there’s some very good news. It’s improved the quality of many people’s lives.

But there are the second-order consequences of that, which we’re talking about here. I don’t think Silicon Valley leadership stepped up to owning and at least confronting that no one can solve some of these unilaterally. But engaging in the dialogue on these.

James Manyika: So, let me press you on that. If you’re going to make a call to action to you peers, your business-leader peers, what would that call to action be, John?

John Donahoe: It’s to think about your business, your platform. Think about the impact it’s having, the positive impact, which we focus on a lot. But think about the second-order implications of what it’s creating and how you can use either your technology, your product, your innovation, or just yourself—as a platform, as a company, as an employer, as a voice—and engage.

The solutions aren’t going to be easy on any of this. And I don’t think any one company or any one NGO or any one government is going to solve it alone. We were talking earlier, one of the frustrating things right now is, there’s a little bit of a divide between government and business on constructive dialogue around this in this country. I sort of personally was hopeful. I didn’t particularly like the results of the election, but I thought one of the root causes of the election was this issue of people saying, “I have lost economic hope. And so, I want change, some kind of change.” I guess I was hopeful, given that was the case, that we would’ve had in our political narrative constructive engagement on this, because it’s not an easy solution. But it feels like it’s been the last thing. It’s been off the radar screen. And I think we need to take leadership roles in engaging with NGOs, with governments where that’s appropriate, to try to find solutions. “Try to find solutions” is almost the wrong term, because no one’s going to solve it, but try to make progress.

James Manyika: Would you add anything to that, Jeff?

Jeff Weiner: You asked whether or not we’re optimistic. I would say cautiously optimistic. I think if you look at some of the longer-term global secular trends in terms of quality of life, the Bill & Melinda Gates Foundation’s been doing a ton of work on this, and it largely goes overlooked in a society that increasingly wants to find the most titillating headline and the most negative thing to talk about. But there’s a lot of good things happening in the world in terms of quality of life improving for the seven-billion-plus people on the planet.

The caution comes in part by virtue of the unintended consequences of these technologies and the rate of advancement, the rate of innovation, which continues to accelerate. And I don’t know that we always have the time to fully understand or appreciate the implications and the consequences, particularly the unintended consequences.

So, the advice I would have is to manage and lead with compassion so that people who are responsible for these products and these services and these companies understand the impact that they’re having, not just on shareholders. It’s not just about long-term shareholder value creation. It’s about the value these companies are creating for society as a whole. And so, the more we understand those consequences, I think the more likely we are to have good outcomes.

James Manyika: Well, I’m glad the world has the two of you as CEOs. I’d like to thank both of you for being part of this session. Appreciate it very much. And thank you all for being here.

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