Support for this podcast comes from Smart Recruiters. Smart Recruiters is your all-in-one platform for faster, smarter hiring, making recruiting easy and effortless. Smart Recruiters are making some big changes, revamping their user experience, adding AI features and refreshing the UI. I know from experience that they truly are a company that really values the recruiter and the practitioner. They understand the intricacies, of the recruiting business, and this has always been reflected in their functionality and customer support. So it's exciting to hear that they're making a bunch of updates. If you're ready to be part of the future of talent acquisition, head over to SmartRecruiters.com and find out what they're up to. Trust me, your team and your future hires will thank you. There's been more of scientific discovery, more of technical advancement and material progress in your lifetime and mind at all the ages of history. Hi there, welcome to episode 634, a recruiting feature with me, Matt Alder. Traditionally, hiring has been anchored around getting the right talent into the organisation. 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 organisations 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 Allegest Global Solutions. Bruce is a deep thinker about technology and the future of work and has some valuable insights into how some of the organisations Allegest works with are thinking differently about talent. Allegest has also implemented a large scale programme 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. Hey Matt, great to be here. It's an absolute pleasure to have you on the show. Please could you introduce yourself and tell everyone what you do? Yeah, thanks. My name is Bruce Morton. I'm Global Head of Strategy for Allegest Global Solutions, a managed services and advisory and transformation organisation in all things workforce, originally from Birmingham in the UK, so might spot that accident if you listen really hard. But now living in Tampa, been in the US for 15 years now, and that's me in the nutshell. Fantastic stuff. Now I'm sure you won't mind me saying that 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? Yeah, what if I'd go back? All the way to 1980 when I got into the industry, the only recruitment really organisation understood as if their receptionist phoned in sick and then needed a temp of the day. That was about it. And then so in the early days when I was doing sales with recruitment, it was an education of what an agency actually does. So I think that it's now organisations obviously realise 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 vacancy or so on, there's the doom and gloom and so that's it. That's going to kill the staffing industry. I mean, 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. I think that was the advent of an organisation getting swamped, 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. But the, and I think for a while, the industry did get a bit dehumanised. If we put a date on that, let's say 20 years ago, relying too much on technology. And then of course we had COVID hit and that had different impacts to 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 we're almost going back to the old days of bringing a candidate in and spending an hour with them before we even represent them. You know, that seems crazy now. But I do think that recruiters that get in the industry because they want to help people because they, you know, they're like that human aspect of it. I think there are loads of your times ahead because we can reduce the amount of administration, et cetera. Yeah, I mean, I think that's a, it's a really interesting angle on it. And, you know, certainly over the last few decades, it's sort of, there's sort of 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 these ones kind of been different as well, I suppose. And 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 and 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? Yeah. And I think that's such a great question one of their learn. I think that is the cost of the crux of this. I think that the, I call it the biggest social experiment in the world's ever been through when COVID hits. And, you know, our organization, we have 15,000 employees. And every one of them was, you know, working normally within three days online and connected. We'd never ever got 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 come on to in more in a second. And some unfortunately will harp back to those days that don't exist anymore. And I think that, well, I seriously believe that it will impact organization success in the future. You know, leadership really, really need to embrace what we learned through that period. But to me, the number one thing that impacts our industry is organizations taking seriously the distribution of work, as I determined, 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. And because it started, we've always started with the talent. It's always been about, I need to hire somebody. I need a job spec. They're going to match against some CVs or resumes. Probably not the best way to do it now. No, absolutely. And I think that's such a critical point and just the most important area. And it's 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. Are you seeing many of the people that you work with starting to think like this about talent and work? 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 behind. 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. Because 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. Because you're looking at the work, not the individual, but it does get very emotional because organizations have been used to having people around them that they know and they turn it with every day. And now there's this slight distance. So the key to it is understanding what are the tasks that we need to get done, that it doesn't matter if we don't know who did it. And what staffing firms are doing in here in North America, I'll talk about that for a second, is similarity in the UK. But certainly more in North America is because there's such a massive shortage of IT talent because 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 the rise of Latin 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. 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? Yeah, and I'll answer it slightly wider lens of automation and AI if you're 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, in 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 to push 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, whatever that can be automated. And then how do we do that? Then the AI is like completing the task in a way. But we've taken a, I guess, a fairly bold standards and organization that we don't use AI to do the final match because of all the concerns around bias and everything else. And we're called the human enterprise for this. And because we believe it, 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, too. 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 the last two years, we can infer you probably have these skills. So 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 fluent in adding that to their profile. And then the third one would be validated or certified. An example is, if you're a nurse, it's so dedicated to say, I have a good bedside matter. If you're a brain surgeon, we probably want to see a certificate. So that's the example. So we see that at scale, it's almost impossible to do as a human and it would hold companies back of 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 to protect you along. So we're putting AI into that type of space. Another area would be in the service as well, where service is procurement, SOW type work that we manage is to give us the ability again at scale, to track the success of projects. So when somebody is found an organization to complete a piece of work for them, they're going to pay on the outcome. How successful was it? Do they do what they said they were going to do on time at 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. So we see it really and it's a we like to use technology to augment more than the place really. How do we make our people look like luck stars because they've got that tech behind them? There's 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 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 kind of fits into all of that. How do 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? 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 got the book lead the work probably 15 years ago now, he was a little bit 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 leave 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 trying to get done? Okay, now let's deconstruct those into tasks. And then look at, okay, what are the processes we're going through right now to bring that skill into the organization? And it's a good old fashioned, you know, Sharpie on the whiteboard. What are the different steps? And when we went started doing that, sort of not unexpected, but it was still a bit of a surprise where, you know, you look at 20 steps and six of them and like, why do we do that? We don't need to automate that, we'll just put a line through it. You know, where's the border razor? And that exercise in itself, even if you didn't automate it, is incredibly powerful. But you know, you get to the point where, say, okay, what are those tasks that can be automated and then pick them up one by one, get some, 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 sort of another idea, I've just got another one, I've got another one. And it just takes up and it gets a lot of its own. But the, you know, we were able to do that, we partnered, we partnered with UIPark 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 have held it back is, you know, we've never got 100 developers on events waiting to do this stuff. So technology definitely helped with that, because it was just so easy to write that code itself. You've anticipated my next point there, when typically talking about UIPark, because I was going to say, as you've done this, this automation, and also the AI part of it. Well, most things, a lot of large organizations are actually building 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? For us, that was a relatively easy conversation, because we are very risk-averse organization, and we didn't want to be building something ourselves with an off-the-shelf chat GPT, as an example, because, you know, I don't think the world is... We don't really know yet, right? What you're sharing out there with chat GPT to educate, who or him and make them better, you know, what 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 how about it?" It's a bit concerning. So, by partnering, I guess that there's a bit more of a, you know, it's a safer option, because it's tried and tested, and, you know, they have the controls and the know-how to make sure that our information stays within our firewall. So that, to me, that's one of the key criteria. If I was a startup, I'd probably just play with chat GPT. I mean, what's the worst that can happen, right? But when you have $15 billion organization, like you just, you have some guardrails around it. And in terms of, you know, 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 been missing for, it's gone missing for quite some, quite some time. How is that kind of working in practice? Where is sort of AI working in the talent acquisition contingent workforce part of this to, you know, free up people's time to work more strategically? 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 free tech search within a large database. So to be able to type into, you know, Google type box, show me all the software engineers that were in a 15 minute commute of Amazon's HQ. And that, you know, that used to, you need to use experts, Boolean search experts, everything else, right? And then create these armies. Whereas now getting to that point is like, great, okay, now show me people that it used amongst that group, show me the people that used to work at meta. Boom, okay, great. And now you're, you know, you're finding your talent pool before you pick up the phone. And now there's the, there's so much technology and data that we can fairly accurately predict when a, an individual is more likely to take the call. I guess they didn't even call these days. I'm, you know, showing a lot of iron, we just picked the phone up. But you don't have to be Instagram, Twitter, whatever chosen chance, you know, if you're in this organization and you came from these two organizations, previously, at two years, one and a half months, you will be at your point when you want to technical. So again, it's, it's giving, it's increasing the chance of success. It's the winnability ratio, as we call it. Let's get the recruiter speaking to those people that got our fire chance of success with quickly. And we don't want 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, you know, having the recruiter's fingertips, how much somebody should be earning in that zip code with this much experience on that skills, et cetera, et cetera. And in the contingent world, we're able to attract that daily. It's almost like, you know, a ticker feed of the stock market. And when you start, 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 to be worked with that. So no, no, no, no. Whatever those skills they have, and I'll use job developer in our ontology and tax on them, and there's 14 skills that a job 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 be 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 recruited back in the day. Yeah, I think it's, I mean, 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, you know, what they need exactly, exactly when they need it. I know you're someone who likes to think about the future a lot on where, you know, where things might be going. It's sort of 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? So I think that at a macro level, and it's already started, but 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, the greatest example that would be the rise of GCCs in India, where so many North American companies now are putting their front end R&D really high level tech, you know, enablement and development in India, that's just going to continue to grow a pace. It's just, 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 over the recently of three 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 come with that. And I think that the trend of what we call contingent, which is completely wrong word to use now, but that will continue to grow. It's not going to, I don't think it's ever going to go backwards. I think the organization will be made up of, you know, a third employees, a third contractors, and a third outsourced to service providers as pockets and packets of work. So the companies will start to look very different. And then, you know, if you take an economic view of that, what does that mean of their value? Just look at a market cap of an organization, a lot of it was around, you know, what's your profit per employee? That's just the wrong measure now. And even the way that 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 high manager, "Well, do you want to employ your contract?" That's probably a long time to ask another question. Bruce, thank you very much for talking to me. It's been a pleasure. Great to speak to you, Matt. My thanks to Bruce. You can follow this podcast on Apple Podcasts, on Spotify, or via your podcasting app of Joyce. You can search all the past episodes at recruitingfuture.com, and on that site, you can also subscribe to our weekly newsletter, Recreating Future Feast, and get the inside track about everything that's coming up on the show. Thanks very much for listening. I'll be back next time, and I hope you'll join me. This is my show. [music]
