I think at big companies, and this gets a little bit to the point I was making about headcount, I think what we found was in a pre-software world, it was hard for people to even understand how to deploy us. And they had problems all over the organization, probably in some way tracking back to not having the right piece of town, but it was actually quite hard to figure out and track what those were. And so we almost said, we need to interrupt people on the path to not knowing what to do and help land for them. Does it make sense to outsource this to a platform like Catalan? Maybe there's a great person internally who can do this piece of work. And to think about the flexible talent landscape in a more holistic way rather than, I need a barista at the Omni Hotel in Dallas on September 21st. Every year over 800 tech and staffing leaders gather in Dallas for the SIA gig e-conference. We sat down with seven of them. Here are their stories. So I'm here at SIA with Rob Biederman and I have to say Rob, we've both kind of been around the gig economy and I've seen you on the internets and I've read some of your things that I've read about Catalan, but I've never met you IRL. So it's great to see you in person. Great to meet you in person. For those that haven't gotten to see Rob, he's a lot better looking in person than his beautiful pictures. I was going to say people often say I'm shorter than they are. So tell me a little bit about Catalan and then we'll just get into some questions about your journey. Sure, of course. So to understand more about Catalan, you obviously have to think back to 2013 when we're starting the company, not today when gig economy is certainly a little less out there. People have started to work? Yeah, it's not strange. I think what was going on then was you had Uber, Airbnb, TaskRabbit, but there was no real enterprise-facing gig economy and certainly there was nothing for folks that had worked at McKinsey, Goldman Sachs. And at the same time, so if you go back to Pat and I, co-founders, Pat had been a management consultant, had not been a very happy management consultant. Wait, hang on. Are there things called happy management consultants? And I think what got under his skin was, you know, he was a talented person, but was never deployed in the right way and the quantity was too big and the quality wasn't very good. And I, as a buyer of consulting in my job and private equity, was always honestly pretty disappointing with the output. So we hypothesized you could put together a marketplace to connect companies or private equity firms that needed talent with people that maybe had just left McKinsey and were taking care of a sick relative or wanted to go out on their own. And that network today is over 100,000 people doing over $100 million of revenue, working on the most important, impactful problem for GE and Pfizer and Moderna and other really important needle-moving companies. So what was the moment that every founder sort of has a moment, right, where they wake up and they're like, hey, I'm not going to follow this road. I'm going to found a company because, I mean, other people do it. So I sure can do it. Like when was the moment that you realized, hey, I'm going to become a founder? Well, you know, as somebody who runs a VC firm right now, part of my job is kind of midwifing people through the, I'm going to found a company journey because we do a lot of hatches. The reality is back in 2013 and even today, founding a company is actually quite intimidating. You probably assume you have to be good at engineering or sales or design. Pat and I were none of those things. And if you don't have a really good, inspired idea, fundraising is hard. And if you're not probably in one of a handful of ecosystems, that feels weird. I think for us, when we put out the just test version of the product, just as a class project, what we kept seeing was that people from big companies were coming and checking out, using their Gmail and their personal credit card for projects that were clearly for the company and then getting them reimbursed. And we said, man, what does that suggest about how fatigued they are with all the options that are available? And that's when we decided to really go for it to start to stop being students in the main and really run the company while we're in business school. That's one of the stories I was actually talking to someone today. When I was at Microsoft, I actually paid out of my pocket my own money because I simply couldn't get things done in the structure, you know, the staffing or the full time. You just you couldn't get things done. You didn't have access to the right experts. So I paid out of my own pocket because I wanted to show up and get good work done. Let's go back to 2013. What were the early days like? Again, this is, you know, it sounds like a long, long time ago. It was a long time ago. But like, tell me about the early days of trying to get people, you know, remote work wasn't a thing. Totally. Yeah. So if you think back to 2013, all the assumptions you have now file sharing, remote video, honestly, high speed bandwidth connections in a lot of cases weren't real, right? This is presumed pre a lot of other things. And people were really not accustomed to the idea of flexible gig work because even when we started the company, Uber was still a relatively small thing. TaskRabbit was really not that relevant. And so we're really proving new ground. And we didn't. I think when we first went out to businesses, it was very much a we're here from Harvard Business School. We can do what can we do to help? And you can imagine how well that went over, which was not very well. What changed, I think Pat had this insight in a in a literal taco stand in Harvard Square was it wasn't about how good the business idea was. Nobody turns out your customers couldn't care less, how thoughtful your company is. They want to know if you have a reasonably priced solution to their problem that day. And we moved from kind of trying to convince people that we were really smart, which didn't really get us anywhere to try to convince people that they had a business problem we could solve and or people on our platform could. The supply side was completely organic. So we recruited a handful of people from other business schools and from that to 100,000 people, it's been substantially completely inbound. The corporate side was originally inbound. And then we realized sales and marketing could really actually really actually spur that. And so now we work with a pretty healthy fraction of the Fortune 100. And it's again, it's kind of not on the, hey, we need to make System A talk to System B. It's actually we have this big strategic dilemma and we're not really sure what to do. Give me an example of where you saw the magic of the model. Where you, you know, because I I always tell a story. There's a freelance researcher named Kosher that I've been working with for probably six years and he provides better market landscape analysis that I would pay other consulting firms a quarter of a million dollars for. Like the work product was better. It was delivered faster. So that's like an example of, and this is Fortune 50 research that you're looking for. What was the time when you saw the catalan, the magic of the catalan model? Yeah, you know, I think maybe one of the biggest examples and this is probably 2013 or 2014, one of our original VC investors was very focused on a thing called Bitcoin, which we'd never heard of. And they were going to load it up on it. Unfortunately, we didn't load up on it. That was the worst part. They went to Bain and Company and they got a bit of two million dollars to do a project on what is Bitcoin and how should we be involved, which obviously for VC firm is absurd. Somebody on our platform for five thousand dollars made this absurd 75-page deck, 75-page pit deck, making the argument for Bitcoin, advocating for it. Here's how it's going to work. There's going to be other coins. Obviously, Pat and I did not unfortunately take advantage of that insight. 2013, it would have been nothing. A fraction of a penny. Something probably cents, if not, maybe a couple of dollars. And we had another example of that where a customer was looking for a metals and mining expert in Ukraine. And we were really worried because at that point we probably only had five, six, seven thousand people on the platform and we not only had one, we had two. And it shows you, and I'm sure this is covered in your book, if you're a full time consulting firm with five, ten, 15,000 employees, undoubtedly they're all really smart, well trained people, but you can't possibly keep on staff the breadth and depth of all of the. Are you craning Ukrainian mining expert? Correct. Yeah. Exactly. That person is not economic to keep on staff full time. But if you can leverage this, the spare capacity of, as it turns out, over a hundred thousand people, people do other things. And then the day that number gets called, they're available to turn on. All of this makes complete sense. I mean, I couldn't imagine a world otherwise. What is the resistance you feel or what is the challenge? Why more? Why you're not a four billion dollar company? It's a great question. We think about that almost in every board meeting. What I would say is the Kavlin model undoubtedly produces better net promoters or better outcomes, better costs, cheaper all the way. And every application of the gig model does that. Better, faster, cheaper. Better, faster, cheaper. I think the difference is when if you think about your path, I assume you use Uber or Lyft or anything like that. There was nobody to stop. One day you said instead of getting a taxi or a black car chauffeur, I'm just going to use Uber Lyft because it's better, faster, cheaper. The reality, the practical reality within a large corporation in the US, at least, is that there are so many different bogeymen on the path to doing something cool and innovative. Part of it goes through, honestly, the budgeting procedure, because as we all know, in big companies, a lot of your validation and in fact, probably power in the enterprise goes through the number of full time employees you have. There are also legal and compliance things you have to set up along the way. And we work them all out. So eventually everybody gets on boarded to Catalan. But I think the biggest challenge is just speed of onboarding new customers. Because you do have to go check all of those boxes, which in a disruptive consumer context, you don't. So I've been following Catalan since I've been looking at the space. And I've noticed you pivot from a more traditional talent network to a platform. We're talking about software. Why? I think what we found was if you are a staffing provider, so let's say you're somebody who provides servers at events, there isn't really any behavioral change that's required. So let's say I'm a catering company and I've decided to have a completely flexible 1099 workforce as my barista and my bartender. Great. I every day I wake up and I have to go staff an event. So I go to my gig economy barista and bartender company and they give me people. I think at big companies, and this gets a little bit to the point I was making about headcount, I think what we found was in a pre-software world, it was hard for people to even understand how to deploy us. And they had problems all over the organization, probably in some way tracking back to not having the right piece of town. But it was actually quite hard to figure out and track what those were. And so we almost said we need to interrupt people on the path to not knowing what to do and help land for them. Hey, are we does it make sense to outsource this to a platform like Catalan? Maybe there's a great person internally who can do this, this piece of work and to think about the flexible talent landscape in a more holistic way rather than I need a barista at the Omni Hotel in Dallas on September 21st. So is it more to start understanding the outcome, saying, hey, if I if I go and create some technology that understands the outcome, then yeah, maybe you can source it from my talent network or maybe you can source it internally. But I'm going to understand the outcome first. Yeah, I think that's basically right. If you if you think about we have a sort of an enterprise offering now, when we work with enterprise customers, we want to understand their needs in a holistic way. So it's not just random VP and marketing decided to paint Catalan. It's actually here's the set of things that we should be working on for you this year in a kind of holistic, comprehensive, not last minute way. I've been coming to SIA for, I guess, three or four years. You're now in the you're now a VC, you're in the venture capital business. What are you seeing in the companies here or in the space? Like if you have to look at the trends that's happening in the staffing, the idea of of talent, where what are the areas that you're seeing that are interesting? Yeah, look, obviously, we make a lot of investments in flexible work platforms. It's very authentic to us. We we probably get a ping on every new one that starts. One one cool area that we've been able to exploit, I think, is a firm is areas of the flexible staffing industry that maybe aren't as obvious. So we all I even think Catalan now is is a little obvious. One of our most exciting companies, a company called Halo, where we actually announced our fundraising round yesterday. It's interesting. I don't want to cannibalize your future. It was actually the next question I was going to ask, because it's a really interesting application for the same sort of thinking. But yes, I'll go back to Halo when you ask the next question. So another great company we have is called Torq, which we actually hatched with me and the the former CEO and co-founder of Cognizant and the founding team members of founding team from Topcoder. The idea there is that there are a lot of online platforms where you can get a flexible engineer. There are not a lot where you can get a really high end flexible engineer deployed really quickly to be less of a execution person and more of a architect kind of thought partner. And we've been able to infuse that company with a lot of talent that had previously left Catalan. We've been able to bring in a ton of people from Topcoder. And what we're building there is really exciting and that company is growing unbelievably quickly. Halo, when we first met the guy, I think we gave him a term sheet in a couple hours because it was so apparent to us that university research scientists should not probably be full time employed by Pepsi or Pfizer or all the above. And yet when you need one of those people, there's really no substitute. McKinsey can do a bad job of what Catalan can do. But if you are the plastics person at University of Colorado, and you're the only one who understands it, there's really no substitute. And those people have very specific niches. Exactly. And if that person's a tenured faculty member, they're probably for 50 different reasons, don't want to come to New Jersey and work for you, you know, every single day. Well, they're not working in academia because they want to go work at Pepsi. Correct. Exactly. And that's been that's been pretty cool. One other platform that we actually. Let's go back. I just want to go back to Halo for you. For sure. Explain to me a little bit about what they do. Yeah. So Halo has a slightly different model than Catalan. What Halo does is you have two big segments of their customers. They call them planet savers and essentially drug discovery pharma. Those folks have typically probably open innovation platforms where they want to bring in a shot of expertise and they probably do that in an RFP model. So Catalan has a search process. And we don't really call it an RFP. And Halo is actually a SAS model where you. Basically, by access to the network of scientists, you're constantly posting RFPs, but then you're also kind of building towards partnership with them in the interim. So even when you don't have an RFP, so we call it kind of an always on external innovation partnering platform, more than an RFP platform, because the problem with RFPs is that they're completely kind of reactive. It's not a particularly interesting way. And what we want to help our customers do at Halo is actually form a ongoing relationship with the corporate. And so when they have a quick question, hey, we're going to ping, you know, Tom and bring him in for a half day. We don't need to go through the RFP process. We can just be able to work with him on kind of a as needed basis. Yeah, which I think is really cool, because obviously companies before Halo, broaden university talent for research projects, for sure. Nobody has done it in quite a incredibly spontaneous and dynamic way where you can atomize it down to a half day or a day or two. Give me an example where a customer for Halo specifically. Is engaging with the scientists just to make it real for somebody. Like, and you have to name the name of the company. It'll probably be very clear. Lots of companies in the US sell soda and plastic bottles and an aluminum cans, principally two companies. They're on a continuous quest to put less plastic and less aluminum in those receptacles. And material scientists at university are consistently pushing the membrane there. So it's not like they just redesigned the 12 ounce soda can. And then it freezes for six years, which is what I assume. It's actually that there's constantly new developments and making it better. And they obviously, for a lot of reasons, want to get, continue to get better at less aluminum cans. And so they will periodically ping them and say, you know, what have you done lately that could basically maybe shrink this from this many pounds of aluminum per one hundred forty four to this? Historically, it's been hard for the academia to get that is part of the friction removing the ability for those two people to connect. Yeah, I think the biggest challenge is you have somebody at the university whose job nominally is kind of licensing tech transfer corporate partnering. It's actually a big part of the research budget of these institutions is corporate funded research. I had no idea. In a pre marketplace world, if you think you're the person at generic soda company that wants to go out and find that person, you start with, you know, Google, what are the top aluminum material science departments in the world? OK, now I have to go through the faculty page. What did they do their research on? So it's an awful search process versus I'm going to post this and Halo is going to notify somebody who is focused on aluminum, focus on that. And so, you know, you can probably compress the search process. I think one of our diligence calls suggested it went from several months to a couple of days. That's the one thing I always liked about the top coder model, because you put a challenge out there and it's a, you know, Steve Raider over at NASA talks about it all the time. Here's on a podcast. I'll plug where we talked about how the toilets in the space station were created and they were actually created by a consultant who had nothing to do with either toilets or the space station. But the point being is that in these models where you put the idea out there and you make it open to anyone, you're surprised at what you always get back. Undoubtedly. And it's better, faster, cheaper. Yeah. And I think what I've always been a little skeptical of whether crowd sourcing can be helpful when you have a problem with a known solution. I've always felt crowd sourcing is great when you have a needle in a haystack and you want to essentially cheaply and quickly get many, many minds to work on a problem. If you think of crowd sourcing actually as the sourcing phase, so we want to find the person and then we're going to partner with them on something that is actually knowable. So it's not trying to spin the wheel 100 times and hope it lands on the right number. But it's actually that we know that if we have one of the seven people in the world who knows the answer to this question, we can do it. We just don't know who the seven people are. So when you look at the space, having been in it since 2013, when Uber was just a baby and well before as big as it is now, where's it going? Oh, I think we're in the first inning. I mean, look, obviously, Uber's done really well. To some extent, TaskRabbit and other platforms like that have done really well. But if you look at American headcount or global headcount, it's still full-time employed. It's a very, very large fraction. There are contractors and freelancers, particularly companies like Microsoft that have been pretty thoughtful about that. But as a percentage of all workers, it should be half, 60, 70 percent. And I estimate it's probably less than 10 or 20. And I think it's in some of the most dynamic value additive ways. Like, if you think about what's the value, let's say you're once again, you think of Microsoft has an events department. They sometimes have W2 bartenders or 1099 bartenders. Maybe those people are better, maybe they're less expensive, maybe they're more flexible, but it doesn't probably move the Microsoft innovation function by that much that they've gone W2 to 1099 at that. But imagine if in your strategy function, so Catalan primarily sells to strategy officers, you're capable of bringing in burst expertise and that unlocks a new 20 percent revenue opportunity. That is a huge untapped source of expertise. You brought up an interesting part about classification being a way to value or think of a worker. Part of what I'm buying in that relationship is, hey, they work at Mackenzie. When I show up and maybe I had experience at Mackenzie, do you find people drawing that line of finding more value because of how a person may be employed? I've seen it. The reason I'm asking is I it's really it's a it's a maybe even a deeper question than I think you might realize because I think in the first phase of Catalan, what we were trying to do was replicate whatever is going on in your brain when you see the Mackenzie logo, which was round one was you hired Mackenzie round two. We asserted to you, hey, this person worked at Mackenzie. They just happened to have left, but they're still equally smart. Mackenzie hired them. Yeah, Mackenzie hired them and trained them and they're no different. They might even work harder with with appropriate incentives. I think what we've done at Catalan really well is transcended the brand renting to a no, this is the actual right person to solve your problem. I think one of the interesting impacts of that is we have probably all things equal, more people with direct operating experience rather than pure consultants or MBA types. And I think that that's where you almost have to have a data driven algorithmic sourcing and staffing model because it's too hard to do that with human resume match. That makes sense. If you think of all hires happen, you say, oh, we need a finance person. Well, what do they probably do this scan resumes for those words versus something a little more dynamic and way more kind of based on historical outcome correlation. So when you think of the model, is there any space? Like what spaces do you think the marketplace technology gig economy model can be applied? One of the most interesting spaces and I presume the people in this ultimately become W2s, but a company we actually back to here in Dallas almost a year ago, it's called Upsmith. They take skilled workers that are probably not maximizing their economic potential, probably Uber drivers or something of that ilk and match them based on a bunch of factors about them to new jobs that would make them in some cases four or five times more. So, you know, they're an Uber driver today, they're making 30 or $40,000 a year in a pretty unpleasant way. Outcome of working with Upsmith is they become an HVAC technician who in the Southwest of the US makes one twenty one thirty one forty. The system there is basically predicting. Hey, if you have this person who is possessed with these fundamentally good traits, personable, on time, reliable, all the above, how can we actually up you know, up level their economic earning frontier? At least at least let them know that those opportunities exist. Exactly. And that's I think that's been one of the mild disappointments for me of the existing kind of here to date. Uh, gig economy is it's been really good at creating more flexibility for people who drive for Uber versus work at the same wage rate in a store. It's not clear that it's actually really increased their overall earnings profile that much. And so being able to use technology to actually identify you're currently doing this, but you could be doing this other thing and making more money. I think that company could end up telling you, hey, you're currently a, you know, Salesforce administrator. And if you were a Oracle administrator, you'd actually get paid 50 percent more. And everything that you're bringing to that Salesforce administration job is exactly the same skills. And in theory, I actually think it's a good thing for the United States because, um, if you're, if you're somebody who's truly that talented and get that job, it would be great to move you up to that. So then somebody else can go from Uber driver to Salesforce administrator. It's a good example. Rob, thanks for sitting down with me. I'll continue to follow not only what you're doing at Catalan, but look forward to seeing the companies you invest in. And your new job is a venture capitalist. Absolutely. My pleasure. Thanks a ton. Of course.
