Ep 810: End-to-End Hiring Intelligence

Recruiting technology can be very good at making individual hiring steps faster and smarter. What it hasn't done is connect those steps into something that learns and improves over time. What does it take to build intelligence across the entire hiring journey? Keep this name, to find out. Support for this podcast comes from Mackey. Mackey began by replacing the resume screen with a fair structured voice interview that assesses real skills before anyone formally applies. Now that same intelligence is extending across the whole funnel, from the first conversation to the final decision. They recently launched Tomo, an AI interview assistant for hiring managers. The next step towards one connected system that screens, interviews and gives every candidate a consistent fair experience at scale. See how the end-to-end picture comes together by going to mackeypeople.com. That's mackeypeople.com and Mackey is spelled M-A-K-I. There's been more of scientific discovery, more of technical advancement and material progress in your lifetime of a month. At all the ages of history. Hi there! Welcome to episode 810 of Recruiting Future with me, Matt Alder. AI has been applied to multiple steps of the hiring process. Sourcing, screening, assessments, interviews, each has its own tools and many of them are very effective. For a lot of organisations though, the gains from optimising individual stages are starting to flatten out. Higher quality is shaped by the entire journey, not by any single step, and most hiring technology was never built to connect these steps together. The focus is shifting towards connecting the whole process so each stage learns from the others and improves over time. So what does it take to move from optimising separate steps to building connected intelligence across the hiring process? My guess this week is Ben Chino, co-founder and CEO at Mackey. In our conversation, Ben explains why improving hiring one step at a time has hit its limits. What end-to-end hiring intelligence looks like in practice and what it means, both for recruiters and for candidates. Hi Ben and welcome back to the podcast. Hi Matt, thanks for having me again. An absolute pleasure. You were my guest co-host on the June Roundup edition. For people who may not be familiar with your work or seen that particular episode, could you just introduce yourself again and tell everyone what you do? So my name is Ben, I am one of the co-founders of a company called Mackey and what we do is that we provide a platform to run hiring end-to-end, obviously using AI to do that. And I really want to dig into that end-to-end aspect to this because I think, sort of thus far in the evolution of AI and automation in recruiting. There's been a real focus on specific use cases and automating, almost automating individual parts of the hiring process. What's changing and what are the sort of the big companies that you work for now asking for when it comes to AI and automation? So it's funny because we actually come from that, right? So we tried to really nail one specific step which was assessments and so what we've seen is that that phase of really like improving specific steps in the process is really mature. And so there's not much more that we can do, it's not going to save more time, it's not going to fundamentally change the quality of the hiring outcome if you only focus on optimizing several steps. And so what we hear from our customers is that we basically need to reinvent the way we do things. And the great news is that AI is actually an opportunity to connect the dots and make sure that those different steps actually work together, learn from each other, right? So that the actual quality of hiring increases in an era where intelligence becomes abundant. At least this is how we view things. And I think this is also the conversation that we're having with most of our customers because they really want to switch the focus from optimizing one single step in the process to actually reinventing the entire process. What does that look like in practice? How does that end to end flow actually work? What was different from what we've seen before? You know, if you think about the way hiring is traditionally run in companies, right? They're going to use an HTS, which by the way remains an essential part of the hiring stack, right? But it's going to be basically what we call a con bond board where you move candidates from one box to another. And there's no real intelligence powering that move, right? And so what we're seeing is that storing information and improving hiring are fundamentally two different things. And so whilst an HTS can actually show you where a candidate is in the process, it cannot really like elevate the quality of the judgment being applied to that candidate, right? And so what we're seeing and what we're trying to build, by the way, is actually doing that, which is helping people create roles in a very effective manner, understand the skills that you need to assess within that role, and then distribute those assessments and different touch points that range from screening to assessment to interviews. And obviously helping each step learn from another so that the process becomes super complete for recruiters. It becomes super seamless for candidates. And so this is what we're seeing where HSS struggle to reinvent that model. And you have newcomers, mostly agentic platforms that are doing that very, very well. Obviously we try to be one of them, but there are others that are doing that very, very well. I think that's really interesting because if you're going to look back at the history of the HTS, it was designed almost as a digital version of a filing cabinet. And over time, it's sort of tried to sort of twist and turn into various things. But really kind of what you're saying is it's just the very different center of things now rather than basing things on filing cabinets. Yeah, exactly. I think the way to describe it is that an HSS is a system of record. But what we're seeing from customers is that they need a system of intelligence. And I think the next generation of hiring technology will be those system of intelligence. It doesn't mean that we're replacing the HSS. It means that we're building a layer around that helps people interpret information, apply better judgment, and continuously improve also the quality of the process. And I think that's super-super important, which is you want a system that learns automatically in that improves over time. And I think it's really interesting because I think anyone who's sort of seriously kind of experimenting with some of the capabilities that these AI models have, it's just that the integrations, their ability to look at different sets of data and go into different systems and create that intelligence, isn't it? Absolutely. And again, what's fascinating is that it can be applied all the way from job description to assessment and deep assessment, but also interviewing. And potentially also everything that happens around that. So keeping the candidates engaged, helping them understand where they're in the process, what happens next. Maybe re-engaging with them when all of a sudden we lose them. So I think what's fascinating with that is that it can be applied to multiple use cases, but what matters is that how do you coordinate the different steps and make the entire journey super-assumeless and extremely transparent for candidates? I suppose bringing this to life for us a little bit more. So the companies that you're working with, the other companies who are making genuinely better hiring decisions, what are they doing in practice that's different from everyone else and you know, have you got an example of that? So I think, if we look at our customers, what we're seeing is that better hiring outcomes don't come from only improving one stage in the process. So you can have excellence-worsing but weak screening. You can have strong assessments and yet inconsistent interviews. So I think hiring quality, as I said, is shaped by the entire journey. And so what we're seeing is that the companies that have the best processes are the one that utilize intelligence in every step of their process because it helps them define what good looks like before they begin hiring. They know exactly what type of skills they want to assess, what type of profiles they want to go after. And so sourcing becomes easier, but once you've sourced candidates, then you know exactly what are going to be the first steps, what are the skills that you're going to be looking after and so on. And throughout the process, everything is more structured, everything becomes more useful and everything support better decision-making, ultimately also with a speeding gradient because since everything is done automatically, You already have the output as soon as a candidate is done with an experience and so you can literally make an offer in just a minute instead of having to spend days collecting the information, reviewing the information, maybe pushing back because you feel that the output from a human is not objective and so on. So this is what we're seeing and again I think what's very very important is that the best companies that we work with are the ones that utilize intelligence in every step of the process and not just in individual steps. From the human judgment perspective, I mean I think every single sort of podcast conversation I have has a question like this, you know, where what's the future for recruiters, where does human judgment sit in, what are we, what are humans doing, what the where's the automation sit. What's your perspective on where human judgment should sit in that process where it's essential and how might that be different from the way people might be thinking about it at the moment. One very important thing is that, you know, this is not about removing people from hiring, it is absolutely not about that. I think when you think about it from a legal perspective, but also from a candidate experience, having people is quite central in the entire process, right. What we want to do on the other hand is help people operate at a level they could not consistently reached on their own for many reasons. We're asking recruiters and hiring managers to make complex judgments, often under time pressure with incomplete information, right. And so this is why intelligence should be there to support them. And honestly, even with super season and experienced people, the output can be inconsistent. And we see that a first thing from our science studies, which is, you know, whenever we release a scale model, we compare that with human reviewers and sometimes certified human reviewers. You would not believe the type of differences we see in reviewing exactly the same candidate input from two different people, right. Even though there is season, even though they're experienced, so we know that human judgment can also be inconsistent. What matters to us is how can we equip them with the data signals that they need in order to make a good judgment. And the second thing is that if you feed time from mundane tasks for people, you also allow them to spend much more quality time with candidates. So it's not only about simply judging candidates, it's also about convincing them, so do sing them, making sure that you can actually close an offer with a candidate. And so we want people to be spending much more time on one making quality judgment, but also two spending time with candidates so that eventually you can convince them to join the company. And I want to talk about candidates a little bit more because a lot of the conversation around AI and hiring focuses on the role of the recruiter, get our efficiencies, speed, all these kind of things. What is this kind of approach? What did it give to the candidate on the other side of the process? I think there are a couple of components to that. And maybe to start, there's one example that I love, which is a big customer that we work with. They have around 800,000 applications per year, right. Before using our platform, they used to ensure 220,000 candidates. So the very vast majority of candidates would apply. And by the way, it was a very long boring process. I think it lasted 15 minutes. And it was just an ATS format, but it was still a very painful experience. So after having gone through that experience, they never heard back from the company. And I think this is a completely terrible experience from a candidate perspective, especially from a B2C aspect where those candidates might also be customers. So what the bank was telling us is we're afraid that we're not only losing candidates, we're also losing customers. And to them, that was a big, big issue. So I think when it comes to candidate perspective and experience, it is very, very important to provide a good experience. And the first thing that we can do is have them be valued for what they're worth. So going after the skills, asking questions, and hearing their answers and so on, is already a first step. And so this is where a lot of companies that we work with start with our AI interview because candidates feel valued. And by the way, the metric that we get is that the average satisfaction rate of candidates on that experience is around 9.3 out of 10. So genuinely candidates like the experience. The second point is that they can also ask any questions they have about the company, about the role. And so that feels very bidirectional where also candidates can understand that maybe this role is not for them. So they value that transparency and the value that experience. The last thing is that, you know, there are a set on capabilities that actually matter for that role. And so they're not asked to repeat the same information at every stage. Since the process is better distributed, you know, interviews or better prepared. They're more focused. And so the entire journey feels just more relevant, more consistent and more respectful towards candidates. And again, I think collecting metrics around candidate experience is super important. And we see that first hand from those metrics, which is candidates value the process and they actually have a better perception of the companies they apply at. Then they use them to have for that company in the past. This is really one of the biggest shifts that we've seen in recruiting. Certainly since the internet was invented potentially even in a couple of hundred years in terms of how it's changed in the process and how we're thinking about things. That's a lot to take in for employers. And there are some really big things that TA leaders need to think about. So what advice would you give to the TA leaders listening who fully appreciate that they need to rethink how hiring works in their organization. But they just don't know where to start. What would your advice be? That's a great question. I think the way I see it is that, you know, from our perspective, we're not selling software. We're actually selling change. And so the first thing to do is really embrace that change opportunity. And accept that, you know, we're going to have to change the way we think about hiring overall. And I think this is super, super important in terms of distinction because it's not about, you know, technicality. Yes, you can buy software and you can probably, you know, change part of your process. But I think the biggest thing that they should have in mind is we need organizational change. We need to accept it. We need to embrace it. And then obviously we need to find the right partners in order to help us support that transition. Right. But I think ultimately this is much bigger than just adopting a new tool. This is really about understanding, okay, where should AI be used in my process? Where should it not? Which decisions should remain fully human? Which ones should be partly automated? How should my recruiters and hiring managers work moving forward? How do I build trust internally? How do I build trust externally with candidates as well? How do I measure quality? So again, this is, this is a vast, vast change process. And this is also why what we're seeing from our customer deployments is that we take it step by step, even though ultimately the entire hiring end to end is something that needs to happen. But it takes time. And again, I think there are people and companies and vendors that are here to support as well. Final question for you. What does the future look like if we were having this conversation again in two or three years time? What would have changed? What would hiring be like? So fundamentally, if you ask me and this is something that I often discuss with my business partners is we believe that CV is going to be dead. So there will be no hiring process that starts with collecting CV. We believe that most of those processes will start with an interaction. And that interaction between an agent and a candidate can be very skill focused. And perhaps can even be seamless in the sense that maybe in a near future there is a platform that knows you enough because it's assessed your skills. And maybe it's assessed your skills in a continuous manner not only during hiring processes, but also in your work. And so this is where talent management can become very, very interesting. And so if that platform knows you enough, it can accelerate your hiring processes, meaning that it can help you find opportunities and tailored opportunities. It can help you understand also where you could go in an adjacent manner. So maybe you're missing one or two skills and it can help you upscale or rescale in order to access those opportunities. And so maybe the entire hiring journey becomes extremely, extremely seamless and automated because we know so much about you that you don't even need to apply. We can literally just. help you access those opportunities in a more seamless manner. This may sound a little bit futuristic, but I think this is where things are going. And so obviously we want to be a part of that journey because there's a lot of things that can be built on top of that vision. Ben, thank you very much for talking to me. Yeah, it was a pleasure. Thank you so much, Mac, for having us. My thanks to Ben. You can follow this podcast on Apple podcasts, on Spotify, or wherever you listen to your podcasts. You can search all the past episodes at RecruitingFuture.com. On that site, you can also subscribe to our weekly newsletter RecruitingFutureFeast and get the inside track on 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.