The workforce industry is quickly adapting to meet the needs of a fast-changing world of work. In this episode, AGS Global Head of Strategy Bruce Morton is a guest on the Recruiting Future podcast, hosted by Matt Alder, to share ways organizations can adjust their workforce strategies to stay competitive and thrive in the future. Morton discusses the role of skills-based hiring, AI and automation and engaging all types of workers – gig, FTE, contingent, contract, etc. – in order to get work done.
Bruce Morton: Allegis Global Solutions (AGS) presents the Subject to Talent podcast, a hub for global workforce leaders to unleash the power of human enterprise. Listen in as we explore the most innovative and transformational topics impacting businesses today.
Bruce Morton: I recently joined my friend Matt Alder on his Recruiting Future podcast to discuss the shifting world of work, how AI and automation can make recruiting more human, the importance of engaging all types of workers and developing a task-first workforce strategy to stay competitive in the market. Let’s listen in.
Matt Alder: Hi there. Welcome to episode 634, A Recruiting Future, with me, Matt Alder. Traditionally, hiring has been anchored around getting the right talent into organization. However, is this still the right way of operating in our fast-changing world of work? Looking at the skills needed to do the work offers organizations the flexibility to expand internal and external talent pools. And consider outsourcing, offshoring, gig work, process improvement and AI-driven automation as alternative ways of getting the work done. So how does this work in practice, and what are the implications for the future of recruiting? My guest this week is Bruce Morton, Head of Strategy for AGS. Bruce is a deep thinker about technology and the future of work and has some valuable insights into how some of the organizations AGS works with are thinking differently about talent. AGS has also implemented a large-scale program of automation in its own business. Something that Bruce believes will facilitate a much more human-centric approach to recruiting. Hi Bruce, and welcome to the podcast.
Bruce Morton: Hey Matt, great to be here.
Matt Alder: An absolute pleasure to have you on the show. Please, could you introduce yourself and tell everyone what you do?
Bruce Morton: Yeah, thanks. Yeah, my name's Bruce Morton. I'm Global Head of Strategy for AGS, a managed services, advisory and transformation organization in all things workforce. Originally from Birmingham in the UK, some might spot that accent if you listen really hard. But now living in Tampa, been in the US for 15 years now. Yeah, that's me in a nutshell.
Matt Alder: Fantastic stuff. Now I'm sure you won't mind me saying, but you've been in this industry a long time, so obviously there's been a huge amount of change, and technology, and things going on in the last 25 years. How would you give us an overview about what's changed in the industry during the time that you've been working in it and what's still the same?
Bruce Morton: Yeah, well if I go back all the way to 1980, when I got into the industry, the only recruitment really the organization understood was if their receptionist phoned in sick and they needed a temp that day, that was about it. And then, so in the early days when I was doing sales recruitment, it was an education of what an agency actually does. So I think that it's now, organizations obviously realize the industry, and so we don't have to explain anymore. But I think that over the years there have been so many cycles when new technology or new ability to promote a vacancy or so on. The doom and gloom, so that's it, that's going to kill the staffing industry. You and I were together at TMP a million years ago and when we launched Monster. That's it, people could just put a job on Monster now and people can apply, they won't need a recruitment company. But we all know there's plenty of room for everybody.
So I think that the biggest difference there, of course, is an individual and a candidate's ability to apply to many, many positions with a couple of clicks. And I think that was the advent of organizations getting swamped with trying to drink water from a fire hose, as the saying goes. So I think that's when sorting, searching, matching technology really started to get into our industry. And I think for a while the industry did get a bit dehumanized. If we put a date on that, let's say 20-ish years ago, relying too much on technology. And then of course we had, COVID (pandemic) hit and that had different impacts, which I'll come to later. But I think what we're now seeing with the advent of AI, and automation, et cetera, is in a bizarre way we're actually allowing the industry to become more human again.
Because if we can get all those tasks that should be done by robots, done by robots, that does leave the recruiters actually time, space to think, be more strategic, and actually have more meaningful conversations with candidates. So, I'm pretty bullish and excited about the way that it's almost going back to the old days, of bringing a candidate in and spending an hour with them before we'd even represent them. That seems crazy now. But I do think that recruiters that get in the industry because they want to help people, because they like that human aspect of it, I think there are more efficient times ahead, because we can reduce the amount of administration, etc.
Matt Alder: Yeah, I mean think that's a really interesting angle on it. And certainly over the last few decades, there's been various waves of technology and the way the industry reacts to them has often been the same. The same kind of denial then frantic adoption. But each one's kind of been different as well, I suppose. Let's talk about the pandemic a bit, because the pandemic was a big catalyst for lots of different things. But a huge amount of recruitment technology was adopted during that, and that's continued to be the case. What do you think organizations have learned over the last few years when it comes to technology and recruiting?
Bruce Morton: Yeah, and I think that's such a great question. What have they learned? But I think that it's the crux of this, I call it the biggest social experiment in the world's ever been through, when COVID hit. And in our organization we have 15,000 employees and every one of them was working normally within three days – online and connected. We would have never ever gotten to that point if we didn't have the need to. So I think that some organizations will benefit from what they've learned, which I'll comment on more in a second, and some unfortunately will hark back to those days that don't exist anymore. And I think that, I seriously believe that it will impact organizations’ success in the future. Leadership really, really needs to embrace what we learned through that period. And to me, the number one thing that impacts our industry is organizations taking seriously the distribution of work, as I term it, in terms of we don't have to do work like we used to.
That isn't just geographically, where can we put this in the world? It's also what type of worker can we get to do this? Is this best suited for a contractor or a freelancer, or should I bundle it up and put a price label on it and pay on the outcome? Can this be automated? Should we be even touching this or should it just be done by AI? All of those in my mind is really doubling down on that simple question of, how are we getting work done? And I think companies are finally, finally starting to wake up to that and say, wow, actually there's something in that. Let's start with the work, because historically we've always started with the talent. It's always been about I need to hire somebody, I need a job spec, then I'm going to match against some CVs or resumes. Probably not the best way to do it now.
Matt Alder: No, absolutely. And I think that's such a critical point and just the most important area. And it is interesting because I think we see a lot of publicity about the organizations that are trying to go the other way. So the organizations that are dragging everyone back to the office, especially when they promise that they never would. We don't actually hear much about the organizations who are embracing the opportunity. I mean, you're seeing many of the people that you work with starting to think like this, about talent and work?
Bruce Morton: Yes, absolutely. And I think that, it's interesting, the latest trend that everybody is talking about now and reading is the whole concept of skills-based. Skills-based organization, skills-based hiring. To me that is just a symptom of organizations realizing that they need to be starting with the work, and then what are the skills required to do that work? And those skills might be through a bot by the way, as I said earlier, but it's thinking about it that way. Because then once you start thinking about skills as opposed to resume, it changes the conversation. If somebody says, oh, Mary's left, I need another Mary. They're like, well, hang on a minute. What is it that Mary was actually doing? Let's talk about the work itself. And then when you deconstruct that work, it's much easier then to be more objective and say, actually half of this can be automated. A third of it we don't even use. The other part, we could actually give to somebody in Manila, as an example. And that's because you're looking at the work, not the individual.
But it does get very emotional because organizations are used to having people around them that they know, and they turn up every day. And now there's this slight, slight distance. So, the key to it is understanding what are the tasks that we need to get done and that it doesn't matter if we don't know who did it.
And what staffing firms are doing here in North America, I'll talk about that for a second, is similar in the UK but certainly more in North America is because there's such a massive shortage of IT talent – we're just not producing enough people with those skills – they have the jobs to fill, so they're looking further afield, and you're seeing now the rise of LATAM (Latin America) with Mexico, and Brazil, and so on. And having the ability to find that worker, get them paid compliantly and get paid locally, but invoice the client back home in the US, that's becoming the key to success now to open up those talent pools.
Matt Alder: We've mentioned AI already, but obviously this really is the main event, in terms of the way forward over the next few years. I think there's some interesting questions about how it's going to evolve and what its capabilities are going to be. But based on what you're seeing now, where is it proving to be most useful in terms of recruiting and talent?
Bruce Morton: And I'll answer it slightly wider lens of automation and AI. If you're okay with that? Because we've been on this journey to automate, let's call them menial tasks or repetitive tasks, for four years with earnest. And we finished last year. Within the year we had automated 12 million actions that humans used to do and are now done by machine, which is just phenomenal when you think about it. And it makes us feel bad that we used to get the people, force the people to do the job of robots, but anyway. So that started us on the journey and now the AI, if you like, is the action taken. So, you're doing the looking at the processes, the workflows, what areas that can be automated, and then how do we do that? Then the AI is completing the task in a way. But we've taken a, I guess a fairly bold stand as an organization, that we don't use AI to do the final match because of all the concerns around bias and everything else.
We're called the human enterprise for a reason, because we believe we're still in the human business and people business. But what we do use it for is, I'll give you a couple of examples, if you think about from a skills-based perspective, how do you create a brief for the skills that you need? So we have the ability to look at a job description and pull from that the skills required to be successful doing that piece of work. And then the same with an individual, we consider three different levels of skill, or three different types of skill rather. One is, where it is assumed or inferred by, if you have been a Java developer for last two years, we can infer you probably have these skills. That's fair to pull those out of that individual. The next would be self-reported, where those individuals are saying, hey, I also speak French fluently and adding that to their profile. And then the third one, would be validated or certified. And the example I use is, if you're a nurse, it's so okay to say, I have a good bedside manner. If you're a brain surgeon, we probably want to see a certificate, so that's the example we see.
So, we see that at scale is almost impossible to do as a human and it would hold companies back from going on that journey. So AI, it's not really that smart in that case. It's just able to work at scale, at a million miles an hour that you couldn't possibly, an organization with 2,000 different job descriptions in their ATS. Having humans doing that would be, just take too long. So we're putting AI to that type of space. Another area would be in the services world where services procurement, SOW type work that we manage, is to give us the ability, again at scale, to track the success of projects.
So if somebody's found an organization to complete a piece of work for them, they're going to pay on the outcome. How successful was it? Did they do what they said they were going to do on time and the right quality? And that then is feeding back constantly into that supply chain, if you like, for democratization of the queen rising to the top. And again, it's a scale thing, that's how we see it really. We like to use technology to augment more than we replace really. How do we make our people look like rock stars, because they've got that tech behind them.
Matt Alder: There are quite a few things I want to follow up on, actually, because you touched on some really interesting points. Probably the first one, is to go all the way back to when you said about automation you've automated, was it 12 million different kind of steps? If someone's looking to do that in their organization, because we don't have much conversation about strategy, and process and how AI fits into all of that. How'd you go about doing that? Because that's not just about buying some technology to do it, there's a lot of thinking and work that goes in before, isn't there?
Bruce Morton: Great, great question. And I'll start with the example of, a good friend of mine, John Boudreau, I'm sure you know John, Matt. He wrote the book Lead the Work, probably 15 years ago now. He was a in workforce at the time. And his whole pretext to that was that, we used to have managers and everybody who had management books, and then we said, no, you need to lead from the front, not manage from the back. So we became leaders, but they were only leading people. And what we now need is the ability to lead the work. And it isn't a skill set that, it hasn't been taught really. So how do organizations start thinking about that? So in our mind it's like, okay, well let's start the conversation with what is the work you're trying to get done? What will make you look really good in the next 12 months, two years? What are those big projects you're trying to get done? Okay, now let's deconstruct those into tasks, and then look at, okay, what are the processes we are going through right now to bring that skill into the organization?
And it's a good old-fashioned sharpie on the whiteboard, what are the different steps? When we went and started doing that, sort of not unexpected, but it was still a bit of a surprise where you look at 20 steps and six of them are like, why do we do that? We don't need to automate that, we'll just put a line through it. Where's the border razor? And that exercise in itself, even if you didn't automate it, is incredibly powerful. But you get to the point where say, okay, what are those tasks that can be automated? And then pick them off one by one, as always, get some quick wins, start communicating that internally.
And we no longer have to go and find cases now, use cases. People are queuing up saying, hey, I've just thought of another idea. I've just got another one, I've got another one. And it just takes off and it gets a life of its own, but we were able to do that. We partnered with UiPath now, in the early days we partnered with an organization called Catalytic, which was all around the low code, no code, and everybody could write their own bot in a way. Which made it much easier, because the other thing would've held it back is, we know we got a hundred developers sat on a bench waiting to do this stuff. So, technology definitely helped with that because it was just so easy to write that code itself.
Matt Alder: You anticipated my next point there when talking about UiPath, because I was going to say, as you've done this automation and also the AI part of it, what I'm noticing is a lot of large organizations are actually building this themselves with the AI tools that are available. What's the best route for this do you think? Is it the organization kind of creating its own technology or is it partnering with experts and is that shifting?
Bruce Morton: For us, that was a relatively easy conversation because we're a very risk-averse organization, and we didn't want to be building something ourselves with an off-the-shelf [tool], ChatGPT as an example. Because I don't think the world is, we don't really know yet what you're sharing out there with ChatGPT to educate her or him and make them better. What if your IP is going with it? And if you let all of your staff say, hey, yeah, use all the tools you like and have at it, that's a bit concerning. So by partnering, I guess that is a bit more of a, it's a safer option, because it's tried and tested and they have the controls and the know-how to make sure that our information stays within our firewall. To me that's one of the key criteria. If I was a startup, I'd probably just play with ChatGPT. I mean, what's the worst that can happen? But when you're a $15 billion organization like Allegis Group, you have to put some guardrails around it.
Matt Alder: And in terms of, you mentioned at the very start of the conversation, that you felt that AI was all about bringing the human aspect back into recruitment that's gone missing for quite some time. How is that kind of working in practice? Where is AI working in the talent acquisition, contingent workforce part of this to free up people's time to work more strategically?
Bruce Morton: Yeah, the biggest advantage we get from it in the process itself is the matching at a very high level and having the ability to pre-text search within a large database. So to be able to type into a Google type box, show me all the software engineers that are in a 15-minute commute of Amazon's HQ. And that used to, you need to use experts, Boolean search experts, and everything else, and then create these armies. Whereas now getting to that point is like, great, oh, okay, now show me people that amongst that group, show me the people that used to work at Meta. Boom. Okay, great. Now you're finding your talent pool before you pick up the phone. And now there's so much technology and data that we can fairly accurately predict when an individual is more likely to take the call. I guess, it isn't even call these days, showing how old I am. We used to pick the phone up.
Matt Alder: Instagram direct message or whatever the chosen channel is.
Bruce Morton: That's right. If you're in this organization and you came from these two organizations previously, at two years one and a half months, you'll be at your point where you want to take the call. So again, it's giving, it's increasing the chances of success. It's the win ability ratio, as we call it. Let's get the recruiter speaking to those people, they got a higher chance of success with, quickly. And we don't want them spending all day creating that long list of 10 people they're going to speak to. How can they do that instantly at their desk? And I think the other, and then the other piece of it is, again, democratization of labor market data and talent intelligence, which is the sexy name for it now, is having at the recruiters' fingertips how much somebody should be earning in that zip code with this much experience and those skills, etc, etc.
And in the contingent world, we're able to track that daily. It's almost like a ticker feed of the stock market. And when you start breaking down the work, this is where it gets really, really exciting. Instead of an individual saying, well, with five years’ experience we pay them this. With seven years’ experience, it’ll be worth that. No, no, no, no. What are those skills they have, and I'll use java developer in our ontology and taxonomy, there's 14 skills that a java developer has. How much is each one of those worth today on an hourly rate? So, if I take these three out, not only does it open my talent pool up, but look what it does to the hourly rate that I need to pay today to attract the right level of person. And that level of science and detail, I geek out about it, but I mean I wish I had that when I was a recruiter back in the day.
Matt Alder: Yeah, I think it's incredible. I've seen some technologies like this in action, and it is just really taking all of that data that's out there and just giving people what they need exactly when they need it. I know you are someone who likes to think about the future a lot and where things might be going. Based on what you're seeing at the moment, what are the implications of this? What do you think the talent industry might look like in two or three years’ time?
Bruce Morton: I think that at a macro level, and it's already started, but at a macro level, the world of work in terms of how that work gets done and where it gets done will be dramatically different. If you think right now, great example, that would be the rise of global capability centers (GCCs) in India, where so many North American companies now are putting their front-end R&D, really high-level tech enablement and development in India. That's just going to continue to grow a pace. If you look at the stats on that, it's phenomenal. It's a $46 billion industry right now, it'll be $110 billion by the end of the decade. And we're just not producing enough people in the so-called developed world. So the work has to find the talent. I think if you look on the end of five years, the world will have woken up to the fact that we have to have an ability to send work to Africa.
It was good to see Microsoft's investment recently of $3 billion, but they've got two of the top 20 universities in the world. By the end of the decade, a third of the world's working population will live in Africa. So, we better find a way of sending work there, helping them get out of poverty and all the great things that comes with that. And I think that there will, the trend of what we call contingent, which is completely the wrong word to use now, but that will continue to grow. I don't think it's ever going to go backwards. I think organizations will be made up of a third employees, a third contractors, and a third ad source to service providers, as pockets and packets of work. So I think companies will start to look very different. And then, if you take an economic view of that, what does that mean of their value?
It is look at a market cap of an organization. A lot of it was around, what's your profit per employee? Well, that's just the wrong measure now. And even the way the governments measure unemployment and measure the level of the workforce, is completely out of date with what's actually happening. So a bit of a soapbox moment, but I do think that the smart companies will understand that the new competitive advantage is truly understanding how to get high quality work done in the best way. And get out of these silos of the first question you ask a hiring manager, well, do you want an employee or a contractor? Probably the wrong time for asking that question.
Matt Alder: Bruce, thank you very much for talking to me.
Bruce Morton: It's been a pleasure. Great to speak to you, Matt.
Bruce Morton: If you enjoyed this episode, please subscribe, rate and review us on Apple Podcasts, Spotify, or wherever you get your podcasts. And if you have questions, send them to SubjectToTalent@AllegisGlobalSolutions.com. Follow us on LinkedIn with the #SubjectToTalent and learn more about AGS at AllegisGlobalSolutions.com, where you can find additional workforce insights and past episodes. Until next time, cheers.