What the New Freelance Economy Means for Your Talent Strategy

CURT NICKISCH: Welcome to the HBR IdeaCast from Harvard Business Review. I’m Curt Nickisch.

We’ve talked a lot on this show about how the pandemic has changed work and how artificial intelligence is shifting how we work, and even the skills that individuals need to cultivate. Related to all this, there’s another major shift happening at the same time, namely in how organizations secure talent.

Basically, the changing workplace and new digital technologies are enabling more of an open talent strategy. That’s where a global business can find skilled help quickly and affordably on an as-needed basis. And today’s guests say that we’re headed toward this new approach to hiring, one that sees talent as part of an open network, not a closed rank-and-file workforce.

To learn more about what that means in practice, we’re joined now by John Winsor, founder and chair of Open Assembly. He’s also an executive-in-residence at the Laboratory for Innovation Science at Harvard. And also Jin Paik, co-founder and managing partner of the AI consultancy, Altruistic, and a visiting research scientist at Harvard Business School. Together they wrote the new book, Open Talent: Leveraging the Global Workforce to Solve Your Biggest Challenges. Biggest challenges. John, it’s great to have you on the show.

JOHN WINSOR: Thanks, Curt. Really excited to be here.

CURT NICKISCH: Jin, thanks for being here.

JIN PAIK: Thanks. Wonderful to be here with you.

CURT NICKISCH: Why is hiring and developing talent in the old top-down way not the effective way to do things anymore?

JOHN WINSOR: Yeah. I mean, I just think when you look around the world, there are a couple of big pressures that have happened, right? Digital technologies allowed a whole new crew of micro-entrepreneurs to rise. I come from the advertising business. And back in 2012, there were about 6,000 people globally that worked in the advertising business. And today, the same number.

The difference in the advertising business is now there’s 60 million creators on social media that are making money from marketing. Those are people that don’t need to work for a firm anymore, that can make a really wonderful living. And when you look at the amount of money that creators on YouTube make, it’s about $39 billion. That’s larger than the U.S. furniture industry, and just right behind the rail industry. So you’ve got this rise of micro-entrepreneurs that like to go do their own thing and work when they want and how they want.

That’s one pressure. But also, on top of that, there’s a big lack of tech talent out there. Korn Ferry predicts between now and 2030 that there’ll be 85 million tech jobs that won’t be able to be filled. That’s even considering the latest disruptions from AI and the economy. So the reality is the best talent doesn’t want to work for you. And if they don’t want to work for you, you’ve got to figure out a new way to engage with them that’s not full-time, and that engages with them how they want to be engaged with.

CURT NICKISCH: Yeah. It’s funny, because there have always been freelancers. There have always been contract workers. There’s been a lot of talk for years about the gig economy. There have always been temp agencies, but the technology and digital platforms seem to have really just created a big shift in how you go to source people. It’s not temp agencies anymore, per se.

JIN PAIK: That’s right. What the platforms effectively are enabling is marketplaces with better validated talent. So rather than what’s on your CV, which no one can tell … Everybody has the same skills, everyone’s done the same projects. I think they’re getting much better at thinking about the specific skill required to master the specific task at hand. So if I’m a company, whether I’m a small enterprise or medium or large, I need something that’s going to help my team accomplish these tasks and goals. And that skill doesn’t exist, either on my team or it’s not available to me.

In the process of doing this, the talent is then starting to form a career out of this, to say, “Look, I have interest in getting better at this type of work.” It also allows me to be flexible and free, so that if it’s not a match with a client, I could move on to something else, but inherently the skillset is there. Organizations need to get pretty good at doing this in terms of being agile, not just in the way they come up with technology, but in the way that human capital works, and the way they think about teamwork and staffing and so forth. Assembling these things together so that it’s more fluid in the way that work is performed.

JOHN WINSOR: What we’re seeing is just the digital transformation of an industry. It’s no different than search. If all of us, 25 years ago, were sitting around in a coffee shop and said, “Man, I need a good dry cleaner,” we’d pull out this big yellow book out of the drawer and we’d flip through it to dry cleaners, and whoever had the biggest ad would probably be the person we would go to because they would look like the most successful person. And you’ve seen that, obviously, radically shift to the search, Google and all that stuff.

And I think that’s what we’re talking about here. If you needed a digital strategy person, even five years ago, you’d go to a big firm like Accenture or PwC or Deloitte. They’re pretty open about the fact that they charge five times somebody’s salary. They need to do that because they’ve got offices and they’ve got management and they’ve got marketing and all those things. They’ve got to support the brand, but those brands are just matching agents. And what we’re seeing is just a digital transformation of that industry to be digital matching on platforms. And that goes with staffing, temp agencies as well. It’s slow. There’s a lot of friction around the cost of matching those people. And so what we’re seeing is essentially just the digital transformation of the talent industry.

CURT NICKISCH: The economics are really interesting to me, partly because I have a lot of friends who have left full-time jobs to do full-time freelancing, essentially. And I always had the impression that you had to give up something to have that flexibility. A lot of my friends are making more money now than they were in full-time jobs, and I don’t quite understand the economics of that. And it makes you question, maybe you give up something by having the security of a salary and a daily office to go into. So how has this shift in the marketplace creating some of those winners in the freelance market, and is this a common thing that you see as well?

JOHN WINSOR: It feels like, and one of the things that Jin and I have noticed, is that the world’s just speeding up. And I find it just curious. I’m an entrepreneur and, over last 25 years, built a few companies on open talent, and so I have a very skewed point of view of how companies work. But most HR departments are dedicated to making sure that the talent is happy and talent is there for a long time.

I don’t know if those are the right metrics anymore, I think, if we’re looking at outcomes. I always ask, when I’m on the road, “How many companies had a budget for gen AI or AI in general before November of last year?” Nobody raised their hand. And I say, “How many companies have a budget today?” And everybody raised their hand. My point of view is that in order to get to the future and be innovative, you’ve got to have a really strong balance sheet. In order to do that, you’ve got to move more costs from fixed cost to variable cost. And one of the biggest places to do that is in talent, and so I think that’s one of the factors that’s happening.

The other one is the reality, and we write about in the book, is that the average employee works on the things you hire them to do 35% of the time, as an employee. There are a lot of other things they need to do to fulfill the cultural obligations and things like that, whereas you hire a freelancer and you hire them for eight hours and they work for eight hours. So the efficiency is just much higher.

And then on top of that, I think the third factor that’s really important to consider is in the space that Jin’s leading today, in the AI revolution, I always want to bet on the learners. Who’s willing to really learn the fastest? And one of the things that we’ve found in our research is the average company in the U.S. dedicates 0.3% of employees’ salary towards learning.

And you contrast that to freelancers. The average freelancer spends 15% of their time learning. So if I’m a betting man and I need somebody to do something new that’s an emerging category that I can’t find talent to hire full-time, I’m going to hire a freelancer. I want somebody who’s really ambitious and want to learn, and beyond things, not somebody who’s just fulfilling the current flow of things and the obligations.

CURT NICKISCH: How big of a driving force is artificial intelligence, generative AI, in this shift that we’re talking about here?

JIN PAIK: Generative AI is really allowing people the access to do their work in, again, more efficient ways, allowing them to solve problems, be creative. It’s not that the work is changing. It’s really that it’s being augmented, and so someone in an open talent community, a freelance worker or someone looking to do a project, they have more creativity to go look outside the scope of how they normally would do it, and they can approach these things.

So open language models like ChatGPT are fantastic at ideation generation. What you’re starting to see, effectively, is in the technical work that John and I have been speaking about, you can write code that would take you weeks. You can write it in a matter of hours, or you can debug codes. I just recently spoke to a student, sometimes he’ll get code and doesn’t fully understand it, and so he’ll be using these open language models to decipher, and then he’ll use it again with his own code to debug it, because it takes a long time. So it’s efficient.

Now translate that to work. You can hire someone who is going to be building you some analytics protocols and some code for you to work through, and they will be able to do that much quicker and much more efficiently. And then again, going back to it, it’s the learning aspect of it, right, you’re learning much faster because generative AI really is the digital collide as we see it. And because they’re learning faster, they’re able to move on and perform a little bit better on future projects.

CURT NICKISCH: What are some of the main aspects of an open talent strategy that you think leaders should be employing then?

JOHN WINSOR: So when we look at open talent, if you ask a head of HR, a CHRO, about their talent, they think about it in the employee base and maybe sometimes the temp part of the market, but they don’t even include outsourcing. So that’s a whole different thing that’s bought through procurement.

And so it’s the last thing in many companies to be digitally transformed. And so when we talk about open talent and the way forward, there’s really three aspects. One is creating external talent clouds that would be clouds of folks, or benches of folks, that would be freelancers to fit projects when you need them. On call, on time. And the real big reason to do that is that in hiring or even in deploying folks from temp agencies or staffing companies and outsourcing companies, it takes months to get the right person in the right seat. So really trying to address that part of it, the market, the friction of hiring.

The second part is building internal talent marketplaces. And those are all about empowering employees to learn, to manage their own careers, to upskill, to work on projects they might want to work. In every company, there’s lots of cognitive surplus that doesn’t get captured, and so we’re advocating for a way to capture that cognitive surplus, to be able to really deploy that to the tasks and outcomes that need to happen.

And then the third element is what the lab has been built on, and what Jin and I are really experienced in, is the open innovation capabilities. How do you use this massive cognitive surplus in the world to tap into adjacent knowledge to solve really difficult problems? So deploying an open talent strategy is really focused on those three legs. Creating external talent clouds, building open innovation capabilities, and then deploying internal talent marketplaces.

CURT NICKISCH: An open talent cloud sounds great, right? What exactly is that?

JOHN WINSOR: Open talent is the overarching idea, and external talent clouds are what we – It’s one of the legs of the stool. When we look at external talent clouds, what we’re seeing is a couple things. One is that even for folks that are in the talent business, it’s very difficult to find the kind of expertise they need and to hire folks on time, whereas you can go to a freelance marketplace, a thousand freelance marketplaces out there, and hire folks on a project basis and get that done in a couple days. So the time to hire is much quicker.

Building an external talent cloud really relies on organizations to rethink the difference between roles and skills and tasks. One of the examples that I always use is that, Curt, you just got hired or appointed to be the CEO of a Fortune 500 company, and you know that AI is going to really affect your business, and so there’s really two paths you could take.

You could go out and you could say, “I’m going to go to my CHRO. I’m going to go the traditional route. I’m going to go to my CHRO. I’m going to hire a SVP of AI.” And you know that’s going to take six to eight months to hire her, and then she’s going to want to hire a team. That’s going to take three to four months, and then it’s going to take three months for them to come together and do a strategy. That’s certainly a way that most companies think about solving a problem like that.

But in the world of AI, game over, right? 18 months is not a workable situation. The more modern way of doing it is to use external talent clouds and expertise. So you might instead say to your head of strategy, “Hey, let’s go to some external talent cloud platforms. Experfy, Business Talent Group, Catalant. Let’s find 10 experts in AI that have experience in the field that we work in. Let’s bring them to Boston for a two-day meeting. And let’s start not with the roles, but with the tasks. What are the hundred tasks that need to be done to complete an AI strategy?” And then lean in and assign those to the folks that you brought in, some folks internally, but really focus on a team effort.

And I’ll bet, or at least we’ve seen, those kinds of strategies come to the fore and be completed in three to four weeks. And so you’re looking at a strategy that takes three to four weeks. Let’s call it 80%, but any strategy in the world today is probably 80% correct, or you wait 18 months to get the strategy done, and that’s just not-

CURT NICKISCH: 95%, right. Yeah.

JOHN WINSOR: Yeah, exactly. It just doesn’t work, right? And so I think that’s what we’re seeing, is when there’s more disruption and more change, companies need to get other folks involved. And one of the ways to do that is through building external talent clouds, or going to the platforms and tapping into those external talent clouds, that expertise.

CURT NICKISCH: Now, that kind of shift has to come with some stress of culture. There are hiring managers and HR departments whose job is to figure out who the best people are and hire them and weigh in on things and manage the process and follow rules. How much of a roadblock is just the culture of doing things the way you’ve done it before?

JOHN WINSOR: Yeah. You’re right on, Curt. That’s the biggest threat, or the biggest hurdle to overcome. We’ve seen examples with one of our clients that we write about in the book, UST. They have a center of excellence. The CEO, COO, CIO, CFO all agree that this is the way forward. They’ve had a really hard time hiring enough people to deploy to their clients, and so one of the goals that they had for the end of last year was to deploy open talent to India, where they had the biggest shortage of folks and really struggled to hire folks.

And out of the blue, some mid-level manager at UST, in their HR hierarchy, found a memo from the early 2000s that said, “UST won’t hire freelancers.” It took the CIO, the CEO, the CFO, and the COO four months to overturn the bureaucratic policies, even though they were pushing this innovation. And so I think there’s a lot of folks. It’s a scary thing.

JIN PAIK: I’m of the belief here, also … We have this very dynamic shift that’s happening. You’re not going to be able to come up with a technology strategy on how your company’s interacting with AI and not be able to address the talent problem. And so if I were to have a CEO, and I’m on the C-suite, I’m thinking, “Look, this is an opportunity for us to address this both at the same time,” because the culture of our organization, the tools that we use, the refacing of what’s going to be happening with generative AI is … The train has already left. And so with that, our implications of talent shift, and so if we don’t go to, again, more of this variable cost model, it could be staggering for us, existentially. We might not make it.

And again, so it’s two sides of the same coin. You have technology that’s coming about, but then you have work that’s shifting, and you have really a neat opportunity to hit that right at the same time. And while that seems massive, and you might be thinking, “Okay, well, this is going to take a massive shift in the leadership to do this,” but it is actually the most opportune time to think in those terms because you’re going to have to do one, and so you might as well do the other.

CURT NICKISCH: You’ve given senior leaders a lot to think about right here, because you’re sort of changing to tasks and outcomes rather than jobs and budgets, in a way. So what’s your advice for people who are implementing this? What should they be telling the people who are still at the organization, and rank-and-file employees? What do you recommend for them to help manage this change?

JOHN WINSOR: I think we start with the perspective of it’s a journey. It’s a journey. And the reason to have a CoE, or a center of excellence, is really to start gaining the knowledge, to learn and experiment. Some decide to really focus on the contest to solve really difficult problems if that’s out of the ordinary, where their staff hasn’t been able to solve it. Some look at it as a training opportunity. Use internal talent marketplaces first. And others need talent today to deploy and look at external talent clouds.

My favorite example lately, it’s a company called SEI, and they’re a wealth management software company. They came to Jin and I and talked a lot and tried to use external talent clouds, but they’re a legacy software company with a software product that has 80 million lines of code. And so for somebody externally to get up to speed on that is really, really difficult.

CURT NICKISCH: You’ve got security concerns.

JOHN WINSOR: Yeah. That, plus just knowledge. How do I insert myself? They have 5,000 people on their tech team. So one of the things they did, I’m so proud of those guys. They did something really simple. They were like, “Well, why don’t we just create an Excel spreadsheet of all the tasks that need to be done? And let’s put a bounty, and let’s only do it internally.” And all of a sudden, a hundred tasks got done. A hundred projects got done that were just sitting on the sidelines. And so that worked out brilliantly.

And the next step was, Wow, there’s probably some cognitive surplus from our retirees. Let’s build an external talent cloud of our retirees and see if they can jump into the same thing. And that was really successful. And the third option is they went to focus on … Wow, I’m sure inside our contractors, our outsourcing contractors, there are a bunch of folks that have a lot of expertise in cognitive surplus. Let’s ask them to jump into this open talent marketplace. And they had to spend the time and do the due diligence of rewriting their contracts with their outsourcing folks to allow the outsourcing employees to work in this open talent marketplace. But again, there was a huge uplift.

And so they’re getting huge productivity gains, huge OpEx savings from just tapping into the cognitive surplus. First of all, starting from their own employees. Hey, employees, this is an extra way to learn. This is an extra way to make a little extra money. We’re all in this together. Let’s innovate together, to bringing in external talent clouds that become much more palatable because those teams want to get things done, and those employees want to make more money and want to advance their careers and learn.

And so I think it’s a journey.

JIN PAIK: You want to assess and learn simultaneously. The assessment of where you are. As John just mentioned on the example with the company SEI, to know these are legacy things that … We have to wait until they die out. Well, then that’s not an open talent project for you.

We ran into this with a lot of our projects at NASA, where they have code built and written in Fortran, for those people who are nerdy enough. That’s just not stuff that you can overhaul. And there are security and risks and all that kind of stuff. Those aren’t the best projects for that. And the managers of those people have to be forward-thinking about, well, can I build for what’s ahead, not what do we have that exists?

And so in the experiment process, you start to unravel the tensions in the organization, whether it comes to HR, legal procurement, these things. That’s when you start really knocking those bridges down once you have some early wins.

And those wins are experiential in many ways because you’re learning about your limitations as an organization. And so if you’re limited to: we can only have freelancers to do these types of tasks, that’s fine. You’re still learning quite a bit, and you’re getting to the next model with it. But if you end up unearthing new spaces or new avenues for there to be value creation and value capture for the organization, it’s perfect. It’s a … Hey, we need to start shifting our resources into thinking about this as a sustainable model, which is what a lot of companies have done to date.

Even in the early days of our work with NASA, they tried 20 different problems and started getting some results. And the way they articulated that across the org was an issue as well in terms of culture, because it is existentially threatening to have somebody who’s outside of the organization come in and solve your problem. They had to figure out, okay, well, there’s a reward system here for those who are saying, “Hey, I have an issue here. I think I want to pose it as a problem so we can collectively solve it.” And then so even NASA, they went away from highlighting the people who were the external talent cloud before that existed, the solvers, and more toward the … Hey, thank you so much for bringing this tough problem that you had a hard time solving, because we know that the collective power really could make progress around this.

And then people get comfortable with the idea of … And now I can spend maybe 15% of my time thinking in this way, or 100% of the time, and so forth. And that largely depends on the size of your organization. If you’re a startup or a medium-sized enterprise, again, you don’t need a CoE. You need to assess and learn quickly and get to that point where you can experiment and build much faster. If you are in a larger organization, that’s not going to happen overnight, and so you have to be pretty strategic about how these things work.

CURT NICKISCH: I wonder about commoditization of talent. Organizations and freelancers alike are flocking to some of these new ways of working and profiting from it, both sides.  Will that start to settle out so that it isn’t … It’s a very economic question, but I wonder if you can get to this place where all of a sudden, those designers just aren’t getting paid a lot, or there are just some big winners who seem to get all the top gigs in that space?

JIN PAIK: Yeah. Again, if their experience is good, there’s going to be continual relationship building. But on the economic side, there are those who are going to be new entrants into the market with new skills that is going to force other people to learn those skills as well, to be competitive. And then, of course, that’ll drive down wages and so forth.

But what is the end state of all this? I think there is more specificity in the skill and choice of how you want to work with somebody. I think the identification of that becomes more clear, and then the marketplace is flooded where there’s, again, more demand than there is supply. Right now, there isn’t. And so you have this off-kilter balance with many platforms reporting to have all sorts of members, but the members aren’t as active as we would like them to be, but there is a desire for those members to be active. They’re on the platform for a reason.

And so as organizations start to tap into some of the motivations, as well, that are along the lines of learning or belonging in a more social way, there’s also then the actual execution, the cash incentives, the payout, and getting the work done. So I think the platforms are actually more about community or the direction they’re going to rather than about inequality and equity and so forth, because the market’s always going to set the rate at what something is. And so then the end state, obviously, is companies being able to almost seamlessly plug in, platforms having to, again, navigate around some of the more difficult regulations. There is regulation out there that is preventing a lot of this type of work, or protecting in many ways too.

JOHN WINSOR: I think we can look at two really interesting examples that have happened in the last few years. I love the Intuit, TurboTax example, right? When you see an ad for TurboTax now, one of their big features is connect with a tax expert. Those are all freelance tax experts. So talent embedded into software. How can freelance talent scale a company like TurboTax so that it’s competitive with all these … I would say small to midsize tax firms, and compete on that service level, all the while empowering individual freelance tax CPAs to do the work. I think that’s a great example.

The other one that blows me away, and I don’t know if you guys have had this awe and shock over, it was during Covid, Amazon’s approach to delivery. We went from Amazon using United States Postal Service, and then they were using UPS and FedEx, to all of a sudden in two years hiring 750,000 people and standing up a substantial competitor just to deliver their own stuff. Now, I see more Amazon trucks than I do UPS and FedEx trucks. So I think those are two examples that have taken this open talent idea and not look towards platforms of saying, “How do I embed skills and new things in an organization, and scale them rapidly so that I can really succeed in satisfying the needs of my customers?”

CURT NICKISCH: What’s the biggest misconception about an open talent strategy that you want to clear up?

JIN PAIK: I think for me, it goes just deeper than hire a freelancer to do something. Quite often, I think even those who are very good at working on platforms are thinking of it in a very isolated fashion. I post a job, I get the job done because I got something from it. There’s a lot of communication that goes back and forth between an open talent worker and a manager. Then there’s a lot that goes on within the organization on how this is being used, how it’s being perceived.

There’s a lot to be addressed in terms of perception, policy, and then, again, implications on practice. And so I don’t think it’s as simple as go on upwork.com and do this, and then I had a good experience, I had a bad experience. There’s more to that in terms of strategic thinking that goes on with how to scale this across the organization.

CURT NICKISCH: Jin and John, this has been fascinating. Thanks so much for sharing your work, and just giving us a sense of how to navigate this new world we’re in.

JIN PAIK: Thanks for having us.

JOHN WINSOR: It’s been an honor. Really appreciate it.

CURT NICKISCH: That’s John Winsor, founder and chair of Open Assembly, and Jin Paik, cofounder and managing partner of Altruistic. Together, they wrote the new book, Open Talent: Leveraging the Global Workforce to Solve Your Biggest Challenges. And we have more episodes and more podcasts to help you manage your team, your organization, and your career. Find them at hbr.org/podcasts, or search HBR in Apple Podcasts, Spotify, or wherever you listen.

Thanks to our team, senior producer Mary Dooe, associate producer Hannah Bates, audio product manager Ian Fox, and senior production specialist Rob Eckhardt. Thanks for listening to the HBR IdeaCast. We’ll be back with a new episode on Tuesday. I’m Curt Nickisch.