John Winsor: You know, they asked us, like, well, this is one they'll never get right. They'll never get this one. It's been way too hard. And we went out to a platform, and sure enough, in two days there was a guy who was the world's expert, you know, at high altitude forestry.

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Clinton Bonner: Welcome to Catalyst, the Launch by NTT Data podcast. Catalyst is an ongoing discussion for digital leaders dissatisfied with the status quo, yet optimistic about what's possible through smart technology and some great people. Today, I've got one of those great people in studio. I've got John Winsor. John is a thought leader and global authority on open talent and the future of work. John's ideas, expressed through writing, speaking, companies built, his experiences you're going to hear about - well, they all place him at the intersection of innovation, disruption and storytelling, which means he makes a pretty good podcast guest. John is the Executive-in-Residence at Harvard Business School's Laboratory for Innovation Science at Harvard, also known as Lish, and the founder and chairman of Open Assembly, a company that provides the world's first digital aggregation platform to help organizations reduce friction in the adoption of open talent and freelancing. One more really important thing you're going to love about John, he recently released his sixth book, entitled "Open Talent: Leveraging the Global Workforce to Solve Your Biggest Challenges." He's here to talk about all that and then some. Welcome to the podcast, for the very first time to the Catalyst Studio, John Winsor. How you doing, John?

John: I'm doing great. Thanks, Clinton. Great to see you again.

Clinton: Yeah. Absolutely. Great to see you as well. For the listeners out there, John and I... Well, we have a history. My past life was working at a company called Topcoder, and it is a crowdsourcing platform. So, a topic near and dear to my heart. And the concepts around the future of work, leveraging talent outside the four walls, and really, also, pushing the status quo forward on how you could use that talent and how you could adopt some open talent philosophies and bring them into the enterprise, which can be challenging. And we'll talk with John about that today for sure. John, I do want to first check in. So, your book, Open Talent. Last I looked, number six on USA Today's Bestsellers for business books. I see the big smile. I know you're proud. First of all, congrats.

John: Yes. Thank you so much.

Clinton: Of course. And then second of all, why do you think this book is landing with such precision?

John: Mm, I mean, I think there's a lot of pent up demand, right? Like Korn Ferry says that, you know, between now and 2030, 85 million tech jobs will go unfilled because there's not the talent.

Clinton: Is that all? (Laughs)

John: Yeah. That's it. Just a few, you know. And it's going to cost companies $8.5 trillion. And so, it's a big deal. And so... You know, companies have to figure this out. And I think one of the things that a lot of companies are really frustrated with is they go, you know, try to hire full-time folks or even contingent workers, and it's really hard to get those folks in-house. It takes, you know, two months, six weeks, whatever. Instead of using these kind of new platform-based technologies that can do it, and... same thing in two to three days.

Clinton: Yeah. And, you know, two months might be very generous. I know you're trying to give an example there that's not true left or right of what the average might be. However, I think lots of listeners to this podcast work and live inside the enterprise world. And sometimes you can't get a JD approved in two months, because there's just friction and things just to get that approved. Make sure the headcount's there. Just, things that traditional enterprises and businesses have to churn through that now, through newer ways to get to talent, they just go away. 

John: Mhm. Yeah, I totally agree. I mean, I think, if you think about it historically, right? It's like... And I've been using this scenario a lot, it seems to resonate. You know, Clinton, you might be too young to remember this but...

Clinton: Well thank you.

John: We used to have these things that are usually in our kitchens called phone books. Right? These big fat things. And, you know, just,  let's say that you wanted to go, you know, I was over at your house and I was like, hey, Clinton, what's the best dry cleaner? I've got some spots on my shirt here. Where should I go? Well, we'd open up the phone book and we'd probably, the decision would be made on how big the ad was for the dry cleaner, going wow, they must be, you know, doing good business if they're spending this much money in the phone book. You know, and usually those things are a year late and a dollar short, right? So you don't know if they're in business anymore or change ownership or whatever. I mean, just think about the world we live in today. You know, somebody has a bad experience at a dry cleaner, and it's uploaded onto Google in an instant and you can see exactly what the latest quality of that service. And, you know, just the time and effort it took to, not just produce the information, but also for the customer to find the information. I think that, just that same principle is happening in talent, right? You need work done. And I think one of the big things that we haven't thought about is, most companies go through this process, right? Of hiring for a role that they need certain skills, that they are going to do some tasks to get to an outcome. I think we're entering a world where we've got to focus on the outcome. Like, what's the outcome that needs to happen? What are the tasks that need to be done? And then what skills that somebody has to have to get those tasks done. But let's forget about the role, right? The role is something that's archaic and it's an old matching system. It's the phone book of talent.

Clinton: Yeah. Well, you know, I thank you for the comment about my potential youth, but I definitely remember the phone books. And besides the largeness of the ad, you also might be going to, you know, Aaron Arnold's Dry Cleaners because they happen to be AA and be positioned first, right?

John: Exactly.

Clinton: So you get all those companies that happen to have A names back in that time, and very few Z names, right? So it kind of conforms, the type of name you might even choose, based on how you might be found back then, right? So, which is an interesting piece of it, too. So, you mentioned it earlier, like, these concepts, though. Whether it's open innovation, crowdsourcing. Grand challenges back in the day. Gig work, now, gig platforms, and then on to modernized talent platforms. It's been around business for over 20 years, and it's been in society, historically, for hundreds of years if we look back at something like the Grand Longitude Challenge, so ships could locate where they were on the sea, longitude-wise, because before that they couldn't do that, they'd get very lost and they'd get shipwrecked or just out to sea forevermore. That was a grand challenge put out there by the British government back, I think, in the early 1900s. So, it's been here for a while. Where do you see the enterprise adoption level as it is right now in still early '24?

John: Yeah, it's amazing, right? I mean, I think you and I have had this conversation a lot. It's like, why isn't adoption, I think, faster. When I helped Jeff Howe write Crowdsourcing back in 2006, we thought that was the tipping point, it was all going to happen. It was like, we're here, it's arrived. And yet here we are, you know, almost 20 years later and it still hasn't arrived. I think there's the talent industrial complex inside organizations. There's lots of bureaucracy, and, you know, it's all centered around security and control and compliance and all those kinds of things. You know, my sense is, is that what's going to break that is just the, like we talked about earlier, is just the lack of ability to get talent fast enough to get the job done. I think you're seeing that a lot in this world of AI, right? The AI companies, OpenAI, Google, you know, Microsoft, are all using crowdsourcing and open talent to be able to build those databases, right? And so, they're kind of going really, really fast. They're not telling everybody that it's all human driven, you know, that everything's being, at least the first round of collecting and verifying the data. But that's a really important part of the process. So, you know, I would say, I think that the frustration really has to do with the, you know, with the bureaucracy. And I think that's a mindset shift, right? We've got to go from a mindset of, you know, scarcity to a mindset of abundance. I was on the call with the CHRO from NYU, and she was just talking and lamenting the fact, saying, you know, I need a data scientist to work for my group. And I know six other divisions inside NYU that need a data scientist. But we all need those data scientists, we need about a sixth of their time. And when I threw out the idea that we should have one person do those six projects, it was summarily, you know, rejected, because there's six different budgets which demanded that six full-time people need to be hired to get the job done that really is the sixth of the size that it needs to do. And there's a battle, you know, in that same conversation. You know, people are saying same kinds of stories, and even saying that because there's not the budget to spread over the six jobs, then they put out a full-time job req, but it's such a low salary that nobody that has the talent would even consider it. And so, I think we're really caught in this place where companies have to rethink the way they think about interacting with talent. And it's, you know, it's even harder now, right? With RTO stuff and with the digital nomads and, you know, it's a complicated world for leaders and leaders in talent.

Clinton: You mentioned abundance, which always makes me think of Peter Diamandis's book titled Abundance, right?

John: Yeah. Yeah.

Clinton: And, you know, I think Elon Musk called Peter Diamandis the most optimistic person on earth, like, just because of the way he sees all things like, no, it's actually, we're going to solve all these things and there is abundance. And as you're saying, look, there's more talent - this one's pretty obvious, any logical person could realize - there's more talent external to your four walls and even your networks within, you know, that branch out from there, versus what you have available to you currently. There is more talent existing globally than there is within whatever your four walls are as you define them. Even if that's a liberal definition and gets a little looser as we have work from home and, you know, third parties you're working with, et cetera, et cetera. Doesn't matter. The numbers still are overweight, that there's more talent externally you don't know yet than you do know currently. Yet, the systems seem to be the thing that cause this friction. As you're saying, that NYU example is absolutely perfect. There's no way... Except for, you know, for someone just to go do it. But there's no way, governance-wise, for those people to split it in a way that makes sense for their rigid systems, based on a talent philosophy that is, you know, last decade's or, you know, still prevalent, just not a modern one that allows for open talent to fit in and be part of that solution. So that's an OCN thing. That's a change management thing. That's an HR systems thing. That's different than the individual director who wants to get to the talent.

John: Right. Right.

Clinton: Because the talent demand, I think, is extremely sincere. They want to get to the people.

John: Yeah.

Clinton: They will figure out how to use them. So, in the last, let's say, you know, 5 to 10 years, what kind of progress have you seen on the front of the systems side and the adoption from governance side? Are there some examples you could call out of some leaders who you think are doing it really well? Or organizations that you essentially are like, you know, just want others to know about and replicate?

John: Mm. Yeah. I mean, I think there's a great, you know, evolving case study with SEI. You know, SEI software, they went out and tried to, I guess it was in 2019, tried to use Topcoder. You know, wasn't that Topcoder wasn't the right solution. It was that they have some legacy software, 80 million lines of code in their package. And, you know, it took somebody so much time to get up to speed exactly how it worked and the quirks of that. And... You know, so, one of the things they did, you know, Sanjay Sharma and Ryan Hick, at the time Sanjay was CTO and Ryan was the CIO. They just were under huge constraints, not just because of the pandemic and the lack of hiring and the ability to get right people, but they had a lot of demands from their clients. They'd sold a lot of their product into clients globally, and the clients just had this backlog of tasks to get done. And so, you know, Sanjay just took a really simple approach. He just created an Excel spreadsheet with all the tasks that needed to be done. And then he put a bounty on each one of those tasks and said, hey, anybody inside, you know, if you want to do this task on weekends and nights, have at it, here's the bounty. Go to it. In the first month, they got 100 projects that had been backlogged done. So, that was the first step. Second step, you know, they're very progressive, they have a pretty big stipend for training. And so they suggested that, hey, if teams want to come together and do some kind of, you know, database work on a newer software like Snowflake, you know, go aggregate your training money, hire an expert at Snowflake, have them train you, and then go attack this problem in a group, not individually, but as a group. So that was kind of the second step. And then, because there was so much momentum, a couple of months later, they were like, wow, there's so many great folks that are retiring from SEI that know so much about the systems. Let's let them tap into the database of open talent projects. And that accelerated it even more. And then, you know, the third step was to go out to the, you know, outsourcing vendors that they had, and they've actually rewritten a couple of contracts with outsourcing vendors to say, the outsourcing vendor still, you know, has employees that work through the vendor during the day, but at night, they can also go on to the open talent platform and actually accelerate their earnings as well, even though they work for one of the big, you know, outsourcing companies. That worked well. And then the next step, they're in the middle of and we're studying at Harvard to see how it goes, but they're going to unleash that open talent, you know, database or open talent platform to their clients. So their clients are now coming in and experimenting with putting their own projects up. So let's just say you've got a bank in England that needs an API built into some system because their software is quirky and they need to kind of, you know, be able to connect it. And it's something that's been in SEI's backlog for a long time. Well, all of a sudden they can just put it up on the open talent platform, put a bounty on it, and people in the ecosystem of SEI can get the work done. And I just love it because it's exactly what we're talking about earlier. It's not about the roles or the jobs, it's about the work, right? It's about the work and outcome. And so that to me is a very modern way to look at it. Not even thinking about, is somebody internal or external? But to say, here are all the tasks that need to be done. Here's what they're worth to the company. Go get 'em done, right? Like, what's it going to take to get 'em done? Whoever can jump in and get it done, let's get it done. Take all that friction out of doing the work. 

Clinton: Yeah. And we talk about that word a lot. Friction. And this, these concepts of, around having what it is to achieve a frictionless enterprise. There's a lot of jumping-off points here, John, which are really cool. And the marriage of modern technology stacks, and the ability for them to serve open talent and vice versa. Open talent that can serve into modern technology stacks, versus rigid technologies from, let's say, a decade, 15, 20 years ago that are still very prominent, though, again, in the enterprise world.

John: Right. For sure.

Clinton: Where it's difficult for internal teams to get in and out of work.

John: Mhm.

Clinton: So you can imagine what it's like when you try to bring in someone that is other stuff, that credentialization, whatever it is. They're not excuses. There are real things on the enterprise level, but they are blockers.

John: Right. Yeah.

Clinton: They're legitimate blockers. And I think a benefit of, as companies... Not just migrate to the cloud. Migrating to the cloud is one thing. It is migrating to the cloud and taking advantage of cloud specificity, which gets you the modernization, and then through that, and having an API-led, you know, mindset. That actually opens up the gates so that you could let more people onto your work safely, securely, ways in which infosec will eventually be okay with. But to actually let them on and have knowledge share and have things like your dev communities and your dev stacks, your dev knowledge centers, so that work can be picked up by folks who are hungry. And really, self-selection. That's what you were getting at earlier. Like, hey, here's a bounty list. What interests you? Or hey, you gotta go learn Snowflake to go get good at this, but go ahead. There's a backlog of work here, if you just do a little bit of the education. What do you think about that marriage of, as the technology stacks modernize, so, too, the opportunity to invite in open talent into the organization. What do you think about that duality?

John: Yeah, and I think it's an important one, right? I think people need to remember that the average organization in the US gives their employees 0.3% of their salary to do job-specific training, whereas the average freelancer spends 15% of their time upskilling. And so, you know, I don't know about you, but I'd go with the learner every day of the week, right? Whoever's learning fastest is going to be the winner. And things are changing so fast. So, you know, today you've got.. I think, you know, it was crazy, because I remember Mike Morris saying this a long time ago, maybe 2018 at a SIA conference. His point was, it's not that your internal software engineer is going to be competing, you know, is going to write 100 lines of code in a day, and you're going to be competing against a freelancer that writes 100 lines of code in a day. It's going to be that your internal person is going to be competing with a freelancer that uses something like... Mike didn't mention it then, but, you know, obviously now it's, you know, a copilot, right? One of the Microsoft copilots. And that person's able to write a million lines of code in a day. So, it's because they're learning, they're using those new tools, they're allowed to use those things, they're bringing it in a much bigger way. And so, it's... There's just no way to keep up with that. One organization can't. I... You know, I think what's going to happen is, it's the same thing that certainly happened in the CRM world with Salesforce, right? Like, there are legendary stories of how large organizations just banned Salesforce. But yet, you know, salespeople and sales managers said, it's something we gotta use. Our CRM's so broken that it doesn't really work. And... You know, and the reality is, is that Salesforce, because they worked with thousands of different companies, they just could learn a lot faster. They could find those edge cases in there, you know, break things and figure out how to fail so much faster across a thousand clients than one client could do in a lifetime. And so, that's kind of going to be the same thing, right? I think it's going to be the same thing in labor. And I think, especially in this age of gen AI, when the best freelancers are out there, you know, using tools really quickly to accomplish a lot more work. So.

Clinton: And you mentioned Mike Morris, and Mike is the CEO and founder of Torque, which is a talent platform out in the marketplace as well, doing some great things. I've known Mike for many, many years now as well. So again, most folks listening to this podcast are going to come from the angle of, that they work within either an enterprise or a growth business, usually a technology bend, and they're working with, you know, they're working with their full-timers that are their peers. They work with the networks that might be third-party providers. Some might be tapping into the Upworks of the world to also get some things done on the side. But I don't think too many people yet have a more holistic view of what a fully blended workforce could be. And I had Paul Hlivko on a couple of months ago now, and Paul is the chief information, and now chief digital, officer at Wellmark Blue Cross Blue Shield out of Des Moines. And I always loved the way Paul talked about his mindset for talent in, like a three legged stool, saying, I've got my full-timers, I've got my third-party and I've got crowd, I've got this extension. And he was always looking for an optimal blend of these three things, and then figuring out, how did he put it together? So another part of, like, enterprise adoption... I don't think you're saying, and certainly I've experienced all sides of it, it's not hey, throw your developers out, we're going full crowd. That's not what we're saying.

John: Yeah.

Clinton: It is this, these concepts of a blended workforce. Where have you seen examples of that working well? Or just lessons of, well, how the heck do you do that? How do you start to bring in, not just as a one-off, but like, philosophically blend in open talent as part of it? Like, I think Paul had called it like an all-in talent strategy.

John: Mhm. I love that. Yeah, Paul's such a great guy. So philosophically, the way I've been looking at it lately is that, you know, if you think about all the disruptions or, you know, I usually, when I'm out on the road, I ask crowds, like, how many people had a budget for AI before November 2022. And nobody raised their hands. You know, how many people have a budget now? Everybody raised their hands. And so, you know, my perspective on a macro level is, if you're going to make sure that your organization overcomes the inevitable disruptions, especially in technology, you gotta have a really strong balance sheet. And so, in order to have a strong balance sheet, that means moving more costs from fixed cost to variable cost. And the best way to do that for most organizations is with talent. That's their biggest cost, right? So if you can move that fixed costs, the fixed headcount, to a variable cost model, whether it's contingent or it's open talent, then you're in a much better place to be able to do the inevitable pivots that need to happen. You know, one of the things that I'm seeing, we, again, it's in the book, and we wrote a case study, or actually, Chris Stanton wrote a case study at Harvard about the job that UST is doing. UST is an organization of 32,000 folks, and they have a real hard time. You know, the clients sign up for them to help build tech. And sometimes they have to wait, you know, like you said, a long time, 2 to 3 months to get the person. And we're experiencing that they can get, through these open talent platforms, they can get people spooled up in 2 to 3 days. Ready to go. So, we're seeing a lot of really great adoption there. You know, they've adopted at the C level. They're looking at it as a strategy for real modernization. At the core of what they do is, in the thing that we built for them, was a center of excellence, a center of excellence for open talent. And really, the focus of that is around, you know, first you have to assess where you are and what the opportunities are, but what the roadblocks are, and then get into, you know, a learn phase where you're learning, you know, what are the new ways to do it. Then experiment with some things. How would it work and how would I work with a platform? And then, thinking about building stuff out. And obviously last, which not too many organizations have got to, is really scaling this across their organization. I mean, you've got organizations like UST and SEI is probably a couple of the good examples. But even places, you know, you remember back in the day, you know, Balaji Bondili being at Deloitte.

Clinton: Of course.

John: And he did such an amazing job. But the reality is, is that, you know, Balaji tried and tried and tried to get that going in Deloitte, with a lot of celebration. We wrote that big case study, five-part case study at Harvard on the successes. Yet, you know, in the end, the machine just ground against Balaji, and Balaji just decided it was just too much and now has left Deloitte. And that's a typical thing, right? The people that are really innovative, that's... It's such hard work and such lonely work, out... Being a scout ahead of the troops, right? So dangerous and so fraught with all kinds of issues that, you know, it's hard. You need that kind of C-level support, but yet you've got to have kind of the culture to support you as well, to make sure that you're not seen as a rogue element. And, you know, the first whiff of something's going to be disrupted, some bureaucracy is going to get disrupted, you risk your career. So, you know, we're really in interesting times, and I agree with you 100%. It's more of a corporate change management issue than anything else. Because, you know, with the research that we've done at Harvard and with Oxford, there's no doubt that we all know that these new models work better, faster, cheaper. Just like, you know, using Google's a lot better, faster and cheaper than using a phone book. Same thing, right? But yet it's hard for organizations to adopt them.

Clinton: And I do wonder if it will take the ChatGPT moment, or if we've already had that for open talent in 2020 with COVID, with everybody being like, okay, we need to be dispersed. And those that were into open talent at that time and already, at least somewhat on the maturity level, could lean into it as others had to figure out how the heck are they going to ship all these laptops across the globe...

‍John: I know.

‍Clinton: And others could dial up and dial into an open talent marketplace to meet those needs. Part of me is like, I think we already had that moment because I was in it and living it. And part of me still understands what you're saying is like, yeah, Deloitte Pixel, that entire team of Balaji, they did some amazing stuff and took it to a very mature level with polished governance and repeatability.

John: Yep.

Clinton: Like, hey, we could do this and we could do it again. Let's show you again, we could do it again. And still it was, like you said very eloquently, grounded, right? Ground down by the machine.

John: I know.

‍Clinton: But yet it's still... I think, it's not just a passion thing. It's like, the people that still can see through that and be like, well, look, it's still a better way to, in a future state, figure this out. Like, start now. Figure out how to incorporate blended workforces. And how to get it right. And you mentioned COEs, which, I think, you know, very much needed for something like this, where there is really change at the core of it. You mentioned also discussing it with the C-level to begin with. Who is typically in the room? Or if you had the magic wand to say, okay, hey, you're serious about this? You're serious about understanding open talent and then looking at, how do you bring it into an organization with the thought that you actually want to scale this? If you had the magic wand, John, who would you want in that first few meetings at any organization?

John: Yeah, it's interesting, right? I think that, you know, first of all, it is a C-level discussion. And one of the things we found, that we didn't write about it because it was too controversial, but when we were in Deloitte with Balaji, we spent... Mike Tushman and I spent a year and a half doing that case study, and we ran across a guy who was just retiring as a C-level player in the strategy department. (Laughs) And, you know, pretty aggressive guy. And he told us to turn our tape recorders off, and he just said, hey, I'm going to make it my personal ambition to kill Deloitte Pixel.

Clinton: Jeez, Louise.

John: I know, right? And we were... Mike and I were like, what do you mean? And he's like, look, you know, I'm a partner. I'm compensated by the number of people that work for me and how many people I put on a project. My compensation is for that. It does me no good, and it does the company no good, to do things better, faster and cheaper. We make money when it's slower and it's more expensive. And that's the reality. So, you know, a lot of this has to do with the alignment, right?

Clinton: Right.

John: Not just the alignment of the company. And certainly open talent is aligned with the company because, you know, people get employed faster. But a lot of times executives are compensated by their team size. Or, you know, their budgets. And, you know, and I think that's what's happened in the startup world, right? Like, you know, you look at the way startup financing runs with, you know, with VCs is, a VC goes to a startup and says, well, you know, what's your headcount? How many people are you going to have to hire? And like, well, I need to hire ten people at $100,000, and that's going to be a million bucks. So I need to raise, you know, $1.2 million. I mean, if you could get that work done for $100,000 or $200,000 instead of $1 million, what do you say to your VC? Like, you're going to be... You're really cutting your nose off to spite your face on your raise. Might be better for the company, might mean more flexibility, might create more acceleration, it's just not the way the system is set up, you know, to orient and to qualify these relationships. And so, I think those are the things. I mean, the reality is, this is going to happen whether anybody likes it or not. And, you know, when we look around the marketplace, really what's happened is it's been a bottom-up movement. I mean, I think one of the interesting figures that always sticks with me is that, you know, in our work at Harvard, we did a bunch of work with Freelancer.com. And, you know, they have a couple dozen relationships, enterprise relationships, with Fortune 500 companies. Yet 70% of Fortune 500 companies have active emails in Freelancer.com as customers that work on the platform weekly. And so, you know, the reality is, it's the mid-level marketing manager that just did the big study and then said, you know, oh man, there's some great market research I did here. This is going to accelerate my career. And they go to their kind of their deck writing department inside the organization. They have a meeting next Monday, you know, it's a week away and they have plenty of time to do it but their deck writing, or their graphic design department inside their company is like, well, sorry, we're three weeks out in scheduling. And so, you know, the mid-level marketing manager is freaked out, so they go online and they say, who can do a deck? And you come up with Upwork and Fiverr, and they hire somebody from Fiverr. For a couple hundred bucks somebody just does a rocking job, you know, on the deck. They have their meeting, they get the promotion, they're going to have their own little team of folks. They're not telling the bureaucracy that that's happening, right? And I think... That's one of the things that Balaji really talks a lot about when he went in to start running all of contingent talent, he said, you know, when he tried to get his handle on all the open talent being used inside Deloitte, he figured that even though they were really explicit that they wanted to know everybody working with the talent platforms, he figured that 50% of the folks didn't tell them the work that they were doing. Because I think people were really fearful for the re-bureaucratization of the work. Right? They didn't want to get into a situation of like, before it was, you know, three weeks to wait for their internal graphic design department. Now it could be, you know, two and a half weeks to wait for a requisition to use an open talent platform. And so to me, in any of these things, in any kind of innovation scenario, it's always the... I guess I look at it as water, right? Like, the things succeed because they're like water. Like, I think we're seeing that in AI, right? Like, most companies probably are leery of mid-level people using, you know, GPT, whether it's for marketing or, you know, Copilot for the software development. But I'll guarantee you, everybody out there that mid-level is really being crushed by content creation or code creation are using those tools to get it done. Right? And so, you've got this kind of bottom-up movement nobody's going to admit to, but they're having a lot of success with it. And so, sooner or later that's just going to tip the organization over. Because those organizations that accept these new models, whether it's gen AI or it's open talent, will be a lot more successful. They'll be able to do things better, faster and cheaper. And the ones that don't use those new tools are just going to become irrelevant.

Clinton: One thing that I think folks that have not experienced the use of, you know, crowds, gig, open talent. And again, nomenclature aside, using external folks on demand as you might need them. One thing that I think is like, hey, we're all used to at this point, pressing a button and hopping in a car with a stranger. Talk about that all the time, right? Uber, Lyft.

John: Yeah, exactly.

Clinton: And it's not just that it's trusted. It's far superior than a taxi ride. And now you earn points and you get your food delivered that way and that's a platform unto itself. They've done a brilliant job scaling that technology. But we've gotten used to it, right? That's just now part of how we get around, and that's part of infrastructure, of how people literally move through society, which is pretty important. What I think is that lots of folks probably don't have full vision yet into the scale and breadth of the different types of talent. Because we think about, oh, someone who's driving a car for me. Or someone who's delivering me my food. Hey, it's good work and we appreciate them as part of society. And we also recognize, well, if you've got a car and the ability, you could do it too. That's one of the nice parts of, that you can enter that and just go do... Go do some side hustle work if you were so inclined to go do so. Very low entry point. However, when we're talking about getting work done at an enterprise level, and specifically in our world, the technology level, maybe that veil needs to be taken off a bit with, what type of talent is out there? So, either in the book or just, I know your experiences with different clients through the years, what are some of the more daring and bold things that you've seen attempted and accomplished with the use of external talent?

John: Yeah, that's a great question. It's interesting because in the work that we've done, the research we've done with UST, one of the great examples is, one of their clients was looking for a high-altitude forester that had experience in Indonesia on high-altitude forestry. And, you know, it was a job that UST had been trying to fill for, you know, eight months and they couldn't find anybody. So, you know, I think it was just a provocation. You know, they asked us like, well, this is one, this is one they'll never get right. They'll never get this one. It's been way too hard. And we went out to a platform, and sure enough, in two days there was a guy who was the world's expert, you know, at high-altitude forestry with a portfolio of experience in Indonesia that was for hire, you know, on a daily basis. And we put him to work in three days. And so they were totally blown away, and the client was totally blown away. And I think that's what you see, right. You know, you've seen it. All the great work that you did, you know, at NASA, it's all this kind of adjacent knowledge, right? Like, there's so much out there. Whether it's inside your company, the cognitive surplus inside your company, or external talent, that really does amazing work around the globe. And so, being able to connect with people in a new way, you know, it's the digital transformation of everything.

Clinton: And I know at Open Assembly, the company you founded out about seven years ago, you're... I don't want to misalign or miss-call what your mission is. But my perspective is, you're looking to make it a lot simpler for those who are interested to understand... Understand the ecosystem, understand how to begin with open talent, and then also provide lots of value where they could come, they could get to your platform, and ask very specific questions about, okay, I need this type of talent, or I'm looking for this band of people with these type of skill sets. And then, you've developed technology that does that for them, right? They could kind of, like, in a crowd of crowds way, point them to other crowd platforms, other gig platforms that have that. Or maybe help them get down to the individual or two thereafter. Is that accurate, and how has that evolved since we last spoke?

John: Yeah, that's a great question. Yeah. I mean, I think it's still all under the banner of, you know, the idea of the book and the work at Harvard and every, you know, everything we do is all around creating common language and common process. Because we felt like one of the issues, you know, there's a thousand platforms out there. And one of the issues that the industry struggles with is every platform has a different, you know, nomenclature, and every platform has a different process. And for, you know, enterprises, it's super confusing. You know, you interview ten different platforms and it takes months to do that, right? And a lot of it's not just the interviewing and understanding the system. It's understanding ten systems, and, you know, what language is the right language and all that stuff. So it started with that idea of the book of common language and common process. But when you start pulling on that thread, you realize really quickly, well, there's, you know, you can do that in an analog way or you can do that in a digital way. And is it better to build the software that starts bringing these, you know, this thread of common language, common process together. So that's really been the goal of Open Talent on the technology side of things. Like, really focused on, you know, how do we take the principles in the book and then put those into enablement, and then into technology that allows people to find talent faster so that they get around the whole enterprise adoption issue.

Clinton: Yeah.

John: Right? That's really difficult.

Clinton: It is. Again, it's another reason for someone to balk internally, or just look at it and not start. Which I think is what often happens. They like it in principle, and then they approach it and it might seem so harrowing, like, I can't even, I can't, I can't start this, right? With, you know, I'm with Launch by NTT Data, and we talk a lot about innovation. We have a program we call Innovation OS, and it's the programmatic-level setting up of the true governances on, how to repeatedly, not just once, because most times people could do something once and either you fail or you get lucky. You didn't learn too much if you did it just one time. Or at least, it's difficult to see if you can scale it, if you just did it one time without thinking through, well how the heck can I do this 100 times over.

‍John: Right.

Clinton: Setting things up so that they are repeatable, scalable. Because I look at the same type of person who might own a charter of innovation within an enterprise, and the same type of person who might own the charter of, hey, go figure out our global talent posture. What are we doing and how will open talent be part of that DNA? I think those person types are brethren in a certain way, that they have to think through and be willing to really get their hands dirty in helping to craft a system that breeds predictability in something that innately, from the outside, whether that's innovation or open talent, it might seem unpredictable. But if you can build the right system so that you're consistent with what you're putting through it and in it, not to say you're always going to hit a home run, right, John? It's not like you get to the crowd every single time, or you get to an external town, you always hit a home run.

John: No.

Clinton: But juxtaposing it versus your hiring percentages, you're not hitting home runs there all the time either, right? Long-winded way of getting around that I think there's a common thread between an entrepreneur inside the enterprise who needs to innovate and figure that out with scale, and a global talent person who's chartered with, what are we going to do, the next 10 to 20 years, when it comes to making sure we can answer, how the heck are we going to meet this talent shortage? Do you think they share DNA in a certain way as well? Like, what have you seen, or... And do they differ in certain ways, too, that you might be able to, you know, talk about?

John: Yeah. I mean, I think that people inside organizations, human nature, right? They tend to think that, you know, it's us versus them, right? It's the business unit managers versus the HR folks, or whatever those are. I'm finding it different. It's really humans against the bureaucracy, right?

Clinton: Yeah.

John: It's back to that CHRO. You know, the NYU CHRO conversation we had a bit ago. And that's really where it is, right? It's like, even the best people throw their arms up with the bureaucracy because they can't... It's nameless and faceless. It's just part of the system that's really, really hard to overcome. I mean, one of the things that one of our clients, we were scaling, we're helping them scale globally, and they were having a lot of success here in North America and Western Europe, and they were like, wow, we got to really... our talent shortage is in India. And, you know, as we helped implement that, and this is a client that, you know, CEO, CIO, CFO, they're all aligned with this innovation, right? They're really pushing it. They have a COE. And you know, lo and behold, some mid-level HR manager in India pulls up some memo from 2005 saying this organization is forbidden from hiring freelancers in India. And even though the CEO, CIO and CFO, you know, were committed to this, it took 'em four months to change that policy. Because the bureaucracy just would not let it change, right? There were just, there was a system to go through changing those kinds of global rules. And it's just where we are. Right? Like, you've got to have, like Sanjay and Ryan at SEI, you've got to have leaders that are willing to really shake it up and do new things. I mean, interestingly, to capstone that story, you know, those guys were... Not only did they do great work, but coming out of the pandemic, Al West started SEI and was... He had about, you know, 8 to 10 folks at the next level and then, you know, Sanjay and Ryan were down on the third level with a bunch of the folks. And when Al decided to step back, he actually jumped over his next level and tapped Ryan to be the CEO, and Sanjay to run the biggest division. And so, I think there's, you know, those are the kind of hopeful signals that innovators need to hear, that, hey, if you kind of put your neck out there to risk something, then it could be that, you know, things could come off right, you can kind of jump ahead, you know, go past go or whatever it is, right? In Monopoly. And so...

Clinton: Do not stop, right? So, yeah, do not, go directly type thing.

John: Yeah, or whatever that is. Yeah, exactly.

Clinton: Go directly to that thing. I really understand that, and it's such a vivid example of, like you said, some dusty piece of paper from 2005. And that bureaucracy being that... I love how you described it, that faceless monster, because you can't just go pick up the phone and have a conversation with that thing. Because it's not...

John: No, no, exactly.

Clinton: It's not a thing yet.

John: Exactly.

Clinton: And yet it permeates. Yeah. And with all that, like making sure we're on the positive side of this, as optimists, that there is this incredible progress and this incredible desire for those to still trailblaze and figure this out and set new examples and set new governances, and really, create platforms, because that's what we're talking about here. It's like, not just tapping into a talent platform, but then the ability for you to internalize, making a miniature, if you will, platform for your organization, so you could use this thing at scale. So we can do all the things that... Make sure infosec is okay with it, and you could use it as a piece of your philosophy, as in blending in open talent with what is your global talent strategy? Because I think another ten, 20, 30, 40, 50 years into the future, it's just going to keep on happening that this should be part of the fabric of how you go solve for global talents, because it's not going to get any easier to continually fight the battle to secure that top talent. So that blended concept is nearly a must at this point, to keep progressing and keep a growth mindset from C-level. Like, stay on a growth mindset and not get choked down by your own weight of your own bureaucracy. And John, I want to ask one more question, landing here.

John: Yeah, man.

Clinton: And kind of get back to the book. Now, you've been an absolute leader on the forefront with lots of people that you're bringing along with, and they're bringing you along with, you know. And yet I could almost guarantee that when you wrote the book and when you researched and went in, I can almost guarantee you still learned at least one or two brand new things yourself, as you dove into the book. Is there, like, is there a story or two that you're like, wow, I went to go write this book, and then this thing blossomed, and I had to include that. Is there something in the book that's along those lines?

John: I mean, there's a bunch of stuff. And I even think since the book, there's so much new stuff that's happening. It's almost like that story of Back to the Future, right? It's like... I talk about a little bit in the book, but I, I'm really intrigued by what Michael Kern and Dean Bosch did with Verdussen. You know, they went from Top Talent to Verdussen. And they got really, really focused on delivering outcomes. And the outcomes were, you know, having a consulting firm, helping other firms convert to cloud computing. What they don't talk about is the fact that they've got 5,000 freelancers working for them. So their whole organization is freelance. They just say, we do cloud computing better, faster and cheaper. And I think that's kind of, you know, the productization is really focusing not on the talent and not on the security and compliance and all the ingredients, but really on the outcome. Like, we need this, you know, how do we get this? Let's get the vendor that does this the best. And it really harkens back to what, you know, I was trying to do at Victors and Spoils. Right? It was like, I knew it was too early to say, hey, advertising agencies, buy talent in a new way. It was better to say, proof of concept. Hey, you know, come compete against us. We can do it better, faster and cheaper because we have 10,000 people working, you know, in a variable cost way across the globe. And so, you know, I think it's always the case, right? Like, those early things that you think about, oh, it's time to move on from that. They always get recycled and kind of re-morphed. And I think we're going to see more of that, right? Like, as we go from roles and jobs to kind of outcomes and tasks, it's going to be really easy to figure out, is like, okay, I need these three tasks or five tasks or ten tasks to accomplish that outcome. And I can package that up and sell that outcome, and then not worry about how people think about labor. But just say, I'm selling you this product. And that's, to me, a really interesting advancement in the whole open talent ecosystem.

Clinton: Yeah, the continual shift to a focus on outcomes. And, like you said, less about sometimes how the sausage is made, and the outcome's that, you got what you were after in a fashion that makes sense for you and makes sense for the business. And as you said earlier, the dirty little secret is, the mid-level folks, they already push the button on that Uber ride.

John: Right. Yeah, yeah.

Clinton: They are fully in. They are using open talent and they're using gig platforms to get work done on a daily basis at this point. And then it's the maturity of, and I really like the notion we hit on earlier, about that team doing cloud migration, but using a lot of technologists that are in the crowd. And it really is also the maturity of the technology landscape itself, the newer wave of tech and the API-driven landscape, it is more open to and more permissible, the documentation of how to pick up a certain piece of software, how to how to get going, it's all there. And the barrier for other folks to come in, get good at it quickly, get around it very quickly, and still securely, right? Still securely. And get to high-value work, every single year that gets lower and lower and lower in a positive way. And as the, as one thing gets more mature, and then as the pinch gets more acute for that need for talent, which I think is happening on both sides, you're probably going to get this, this good homeostasis of where the markets meet each other, right? That exact right moment. And we're probably in it. We're probably in it right now. It's just going to take, I think, take still a little bit longer for it to fully adopt and fully mature. And we'll still be looking at a, you know, a future state where most enterprises have understood that value of that blended concept of really leaning into the open talent aspect of, how do they bring that in to get this work done at scale? So. Really cool stuff, John. Very much appreciate it.

John: Yeah. Thanks, man.

Clinton: Appreciate you being here.

John: Yeah, absolutely. Really psyched to be here and really psyched to be on with you, and good to see you again.

Clinton: Yeah, absolutely. And of course, the book is "Open Talent: Leveraging the Global Workforce to Solve your Biggest Challenges." The author is John Windsor. John, best way for folks to find you? Is it Twitter? Is it...

John: JohnWinsor.com, or, you know, LinkedIn or Twitter. I'm all over the place.

Clinton: (Laughs) He's everywhere you want to be, folks. Alright. So John, thank you so much. And for those out there enjoying the Catalyst conversations, please share these podcasts with your colleagues and friends. And remember in this studio, we believe in shipping software over slideware, that fast will follow smooth, and aiming to create digital experiences that move millions is a very worthy pursuit. Join us next time as the pursuit continues on Catalyst, the Launch by NTT Data podcast.

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