The world of talent acquisition is constantly changing. How you keep pace — or even reach new goals — will come down to what tools you use and how you use them.
Today’s challenges are creating opportunities to try new approaches — like AI — that not only support your TA processes, but accelerate them so you can go beyond the status quo.
Watch this talk about how AI can give you time back and the freedom to focus on more valuable activities, like connecting with candidates. Learn how to go beyond traditional tasks like writing job descriptions and lists of outdated requirements to finding talent with the right skill sets, including the rising and adjacent skills you actually need. See how a talent intelligence platform can reveal the best-fit candidates with the potential to grow and excel in your environment. AI helps you find the people you need today who will become the leaders you’ll need tomorrow and give you the data you can use to share with hiring managers and senior leaders.
In this session, we will discuss:
SHRM Moderator 00:00
Hello, and thank you for joining us for the power of AI and talent acquisition, how advanced HR tech can boost recruiting results. This program is part of the SHRM cast series. You can learn about upcoming and on-demand events from our e-newsletters, and the webcast homepage at sherm.org/webcast. SHRM thanks Eightfold for sponsoring this program and our series of free work for the HR community. Now about today’s program, you’ll learn how AI can give you time back and the freedom to focus on more valuable activities like connecting with prospective candidates. To lead our presentation, we’re pleased to welcome Rebecca Warren and Connor Volpe with Eightfold. Here’s more information about our presenters. Rebecca Warren is Director of Customer Success at Eightfold. This one has been in and around the talent acquisition space for 15 plus years at a variety of organizations and industries and both full-time and consulting roles. She has been at Eightfold for three years in customer success, and is the president of the Arizona recruiters networking community and is passionate about helping people succeed. Connor Volpe is Director Product Marketing at Eightfold. His marketing role is for Eightfold the Talent Acquisition product, which helps companies hire high-potential and diverse talent faster than ever before. Prior to Eightfold, Mr. Volpe worked at Salesforce and product marketing with a focus on global strategic launches for Slack safety, cloud and service cloud. And now pleased to turn over the webcast microphone to Rebecca Warren and Connor Volpe.
Conor Volpe 01:41
All right, well, thank you, Connor. I’m also Connor, I hope that doesn’t get confusing. But welcome, everybody. We’re really excited to be with you this morning. As Rebecca and I were going through to kind of create all of this, we realized that there’s a lot to cover. So we’re gonna do our best to fit it all into the time that we’ve got. We’re really excited, like I said to be with you here today. Because we know this kind of a topic is really timely, AI has obviously been something that’s probably been on our minds for quite a while. But the last, I don’t know what, eight, eight to 10 months, maybe it’s gotten really, really popular. So we’re here to talk to you a little bit more about that. But I am not gonna be the only voice you’ve heard. As Connor mentioned, I am joined by the tremendous Rebecca Warren, do you want to say hi, everybody?
Rebecca Warren 02:23
Hello, everyone. Excited to be here. Thank you for having me. Tremendous talented, the adjectives could go on and on if you want me to, but vice versa. Um, but yeah, so we’re gonna do a few things with you all. So we’re going to talk through our perspective coming from the full world about how AI is helping to reimagine talent processes, we also spend a little bit of time on generative AI as well, because I think that’s what I was alluding to, we’re talking about the last eight to 10 months and how AI has gotten even more and more in the news and probably made us think about it more than we really thought we would be. But that’s where we are today. What we’re going to spend most of our time on is on the practical strategies and what AI can actually help all of you on the line, how it’s helping our Eightfold customers today, how people are using AI to reimagine, to rethink and ultimately be more productive and efficient in the TA world. Rebecca, anything you want to add before we kind of dive in? No, I think we are in a great space to be able to talk about AI. Like I think some people might be like, Oh, I’m so over it. And we’re like, we’re just beginning, we’ve been in this space for a long time. AI is not new. So we’re excited to talk about ways to make it work for us and to not be scared by it.
Conor Volpe 03:43
Perfect. And I think that last piece you mentioned is a really nice segue because obviously you’re gonna hear from folks who like Rebecca said, we work in this every day, we are excited about the promise and potential of AI. But we also recognize that there’s probably some trepidation, people aren’t necessarily all roses about AI and what it can mean. And we actually, we wanted to start there, which is that there’s you can see on the slide, but basically, the World Economic Forum, put out a report and said that, in large part due to the tech technology advances, AI advances generative AI, that almost a quarter of jobs around the world will be disrupted in the next five years. And in fact, there’ll be 14 fewer 14 million rather fewer jobs over the course of those next five years. So that understandably, when we see things like this out in the news, or from a body such as the World Economic Forum, it can make us get a little bit nervous about our future and how that impacts TA in particular, but again, there’s other folks out there who are really excited about how this can change jobs, how this can up level people and up level skills and all those different pieces. So before we actually get into too much content. We wanted to start with a poll, we want to see how everybody out there is feeling about AI and talent acquisition. And luckily with these polls, all you gotta do is click this Slide, click that letter you like and then click Submit. But we want to get a sense of how you all are feeling about AI as a role in talent acquisition, and what this might mean for you. Are you optimistic? Are you a little concerned? Does it make you sweat? Does it make you think of Skynet and Terminator? Or what exactly is it that this kind of triggers for you? But like I said, we understand it’s two sided.
Rebecca Warren 05:25
One thing I wanted to throw out there, well, folks are polling, is when we talk about jobs disappearing and jobs appearing. It feels a little, like, oh, my gosh, these jobs are going away forever. That’s not necessarily a bad thing, right? When we think about my grandmother, who was a telephone operator, right, a switchboard operator where she was literally plugging and pulling, you know, different connections, that job doesn’t exist anymore. That’s not a bad thing. Right? We’ve added new jobs that have allowed folks to move into different areas. So when we say jobs are disappearing, it doesn’t necessarily mean it’s a bad thing. It means that we’re evolving and using technology, hopefully, for the right reasons to take away that work, and allow us to move into other things.
Conor Volpe 06:13
Well said, well said, Okay, I think we’ve given everybody a chance to jump in there and give their responses. So it looks like most people are on the positive x, cautiously optimistic, too excited, which might explain why you’re here in this webinar today. But then we’ve got some folks who are neutral. And so people who are like I said, fair enough, are very concerned about the direction of AI. And part of our goal today is to help you understand, like we said, we’re going to spend most of our time talking about the practical implications of AI and how this will impact talent acquisition. So hopefully, we’ll walk away not just being, like I said, we’re not here to necessarily change your mind. We’re hopefully here to give you ideas and inspiration for what, what is coming.
Rebecca Warren 06:54
I’m excited about the answers to them.
Conor Volpe 07:00
Yeah, yeah. No, I thought it was, it was good to see. So coming from April, this is our CEO and co-founder, Ashutosh Garg, and this is basically our position very concisely summed up, which is that AI empowers machines and humans each to do what they do best. Together, they can perform a task faster and better than either could do on their own. And that informs how we’ve developed our products that informs Rebecca, the work that you do with our customers, that informs how we sell how we solution, all of those things, we recognize that our products, and our AI is here to uplevel, the role of talent acquisition professionals, wherever they may be, and again, we’ll go over some of that today. But to put an even finer point on it, we’re trying to find a collaborative middle between the activity that AI is best for and the activity that humans are best for their lives, this very large portion of the Venn diagram, where both can come together. And ultimately, like Ashutosh said, Be better together. And, Rebecca, I think you have some great examples of this collaborative middleware, we’ve, this isn’t the first time we’ve seen this in the TA world. In fact, like I said, it’s not exactly a novel concept.
Rebecca Warren 08:11
That’s right. That’s right. When we talk about changes, there’s been so many changes, not just in the workplace, but in talent acquisition in HR, not just evolving our roles and our place at the table, but also looking at how work gets done. So I have been in ta longer than I’m going to actually admit, but when we talk about where we started, right, I was in selection. And then ATS came out and we were like the world is ending. Jobs are done. We’re done. Right? And we said, Oh no, wait. ATS is just a tool for us to help build those relationships right away for us to keep that information in one place. And then we said, Okay, that’s great. We’re good with ATS is and then job boards came out, and then the sky was falling again. And we’re like, oh, no job boards are taking over the world. And you don’t need recruiters anymore. Then we said, oh, wait, no, that’s not really happening either. So all of the things that continue to happen, whether it’s using chat GPT, or whether it’s putting something in a tech form instead of manual, right, going from spreadsheets into a more advanced way of keeping our information. We still need human activity in order to make that work. So it can’t just be all on us. It can’t just be all on AI. We need to have that middle ground for us to confirm to approve to add flair, right add flavor. Ai on its own is pretty flat. And human activity on its own is an awful lot of work. So how do we put those two pieces together with those collaborative relationships using technology to work for us, while allowing us to still add that human touch
Conor Volpe 10:01
I think one thing that I kind of take from Rebecca is, I think if there’s something hopefully this isn’t cliched, but something that we’ve learned over the past three plus years is that change is, is constant. And I think that’s been very true of the TA space for a long time. But it’s about figuring out to your point how these things ultimately help us move forward. And that’s the goal for today is we’re going to hopefully show you some ways that AI can help the talent acquisition world move forward and do things even better than before. Right. So for today, for our practical examples of things we’re going to talk through, this is essentially going to be our model. And everything is centered around the idea that we think that the goal of talent acquisition, or really HR in general, is to help align a company’s most important resource, which is the people with the underlying business strategy. If those two things are moving in the same direction, then ultimately, the company and the people are happier, more productive and effective. And where that starts is by being able to analyze skills. And we’ll talk about why that’s important, how that sets you up for success down the line, but being able to understand the skills within your own company, the skills out in the market. And then using that understanding of skills to identify talent, figure out who you need to go hire contract upskill. But figuring out who the right talent is to go after engaging that talent, understanding the roles that are right to go out and searching for how to then turn those into organizational plans. And finally come benchmarking all of this against competition across the industry. And again, we’ll show you different ways that AI can help you do this.
Rebecca Warren 11:37
And I would argue a bit there, Connor, that we could start inside of a business, you could start at organizational plans, and then move to benchmarking or analyzing skills. So it doesn’t have to start at one place. I like what you said, right? We’re going to, we’re going to not swirl. But we’re going to continue to rotate around that idea of what is the business strategy, and then pull in the right piece to do that is the skill analysis, the first step maybe? But could it be like, here’s what we want our organization to do. And here’s how we’re going to get there. So we want to continually think about that business strategy at the core, not using tech just for tech. But what is it going to do to help make that business outcome successful?
Conor Volpe 12:23
Great, great clarification. Yeah, this does not need to be a step by step, honestly. I mean, you kind of mentioned it, you can start almost anywhere along this. But we’ll give you examples of why each of these are important. So let’s dive in, shall we? Let’s do it. Starting by analyzing skills, understanding the skills of your workforce in the market. And I think honestly, where the best places to lead off with this is some research that Deloitte has done recently, which kind of showed that skills based organizations have seen some pretty incredible results across a wide swath of areas, whether that’s more likely to retain top performers more likely to place talent effectively, more likely to be innovative, more likely to have a reputation is a great place to work. I mean, this kind of goes on and on. So, Rebecca, like, what do you attribute this to? And this is obviously really impressive, but it can’t, it can’t just be as simple as they pay attention to skills.
Rebecca Warren 13:18
Yeah, that’s a great call out. I think, when we look at this, we should be looking at it from a perspective, again, of what we are trying to accomplish as an organization. And I think old school ways of looking at an employee base, or even trying to bring folks in is we look at a, we look at a resume, right, we look at a person. And it’s not that we don’t want the right fit as a person, right? There’s more than just the skills that have to be the right, the right culture fit, as we say, right, our buzzword of culture fit. But we have to be looking at what somebody brings to the table, and it doesn’t necessarily mean that it’s the title that they had in their past job. So skills are allowing organizations to use folks in areas that maybe they haven’t thought about before, and allowing talent to be able to work in places that maybe they thought they’d never get to. A lot of folks feel really pigeonholed as to why I’ve been in, you know, the tech side of the house forever. So I’m never going to get to HR or I don’t have any opportunity to get to marketing, looking at skills instead of looking at a person as the be all end all looking at the skills that they bring to the table, you’re able then to make better matches and allow folks more engagement inside your organization.
Conor Volpe 14:41
I think what you’re getting at too is that there’s a relationship between skills that is beyond what meets the eye, right. I think that’s a place where AI can help understanding how skills relate to one another. And trust me we’ll get into this even more as we go along in this in today’s webcast, but there’s a relationship . They’re the AI that can kind of help you map Rebecca to your point. Just because someone’s title is x doesn’t mean they’re not a great fit for this other role over here with titles that have no similarity whatsoever. Right. And actually, I think you’re not a bad example of that, in your own career, having jumped into customer success, right? Like this is your living example of this.
Rebecca Warren 15:20
Well, and what was interesting about that is because it was somebody inside of eight fold, who had worked with me in the past who said, Hey, you should apply for this job. And I’m like, I don’t know what this job is. I don’t know what customer success is. But she was able to look at the skill sets that I brought to our former connection, and said, Hey, you would be good here. So she did it manually. And now we have opportunities to do that using AI and using those connections. Again, it’s not magic, it’s just taking out some of the work that as a human takes longer to do.
Conor Volpe 15:57
Yep, yep, exactly. Okay, that brings us to our second poll, which is kind of what we were just getting at Rebecca, which is, how confident are you out there online, in your organization’s ability to assess employees potential beyond what you see on a resume. And again, Rebecca, I think your example is perfect, because your resume might not have been a perfect one to one match to the job that you now have. By being able to look at the skill sets that you actually bring to the table, it becomes a really compelling match. And it can be kind of hard to do your own keyword matching to figure out what jobs are at a company, but understanding them on a skill level can be very helpful.
Rebecca Warren 16:38
Well, and I think another reason to use tech to do that matching is because I’ve been in TA for a long time, we would do that matching on our own, we would hire managers who say I need x well, like there’s six people in the world who do that. So I’m going to have to go and find someone who can do that. But it’s a lot of work, right, we have to convince that that candidate to talk to us, we have to convince the hiring manager to look at the candidate, we’ve got to figure out that match and there is some reskilling some training there, when we, though can look at data that AI provides and says, This skill works with this position. And we can bring the data to that hiring manager. It makes it so much easier, right? It’s all explainable. But it’s just connecting the dots in a way that we might not look at. I can’t tell you how many hiring managers said, I want you to clone Bill. I would love to clone Bill to find you that perfect person. But you know what, we are better when we have complementary skills instead of the exact same skills, right? So how do I find, you know, Sally, who’s going to come in and compliment they’ll still have what that hiring manager needs. But you’re not having a whole team of clones, because, you know, that’s a little weird.
Conor Volpe 17:55
And I think you brought up the data point, the data perspective, right to be able to show whether there’s a shortage of a particular profile, or role or skill base that someone has, and to be able to have that conversation using not just gut feel, but ultimately being able to point to hard data. Okay, it looks like we’ve got most people in here to answer. So we’re gonna go ahead and keep it moving and take a look at our results. So I’ve got a mix. There’s a lot of people in the middle about their kind of confidence to that really confident or doubtful, to a little bit doubtful. Got a nice little bell curve going. Which makes sense. I think Rebecca, you’re kind of getting it that in your previous life, that that it can be hard to kind of figure out what someone’s ability or potential is just looking at a resume, for example,
Rebecca Warren 18:41
There’s a lot of change management that needs to go into shifting from finding a person or finding a resume to finding the right fit for the role. It takes some time, whether that’s training from HR to external change management teams, it takes time, you can’t expect folks to be able to shift into that new way of thinking overnight. But by using data and continuing to push on using skills rather than saying, I want to clone this person, I think it’s easier to get there.
Conor Volpe 19:15
Yeah, and this actually, this is a nice setup. It’s almost like we planned it for our next topic, which is about identifying talent. And one of the things I think we really want to focus on here is the idea of hiring for potential. And that’s something that’s really easy to say, I think, right? Like I would love to hire for potential. But we mentioned being able to make a data back case for hiring for potential. And with AI, we can do some of that we can almost not. I don’t want to quantify someone’s potential but point to markers about what they’re capable of doing. So let’s give everybody out there an example of what that looks like. So this is some research that a fool did for the oil and gas industry. And we looked at some top in demand skill skills for this industry, in other words the most highly sought after skill sets that companies are looking to hire for. And then oftentimes are difficult to hire for because they’re so competitive. So right now on the far left, we’re looking at well testing, if you kind of move over towards the right, there’s that little gray bar on top of the big blue bar that says there’s only about 30,000 people less than 30,000 people in the world with this skill.
Rebecca Warren 20:22
So if you can imagine, I don’t know any Well, testers, we need a lot of weld testers, and I don’t know any of them.
Conor Volpe 20:29
And there’s not many out there. So what is a company to do besides getting to basically a recruiting race for weld testers? Well, what our system is able to do in our talent intelligence platform is to take a look at the well testing skill, and understand the relationship between that skill and all these other surrounding skills. And what that means is we’re able to see what we call adjacent skills. And what those indicate is that someone has a high potential to learn well testing at a very rapid rate. In other words, if someone knows drilling, well completion, formation, evaluation, well intervention, there’s a really high potential for them to be a good well tester. And if we’re able to look at that, and quantify that, that shows us that we go from about, like I said, less than 30,000 people in the world, who are who have the well testing skill, all of a sudden, we’ve got almost 160,000 People who know this, which over 6x, our talent pool. So instead of everybody competing for the same 30,000 people, we can now take a lens of, while it might be great to hire someone who has the skill right now, we can also not hire someone for their potential to learn the skills that we need. And this extends to other places as well. So machine learning is another example. And that’s obviously something that is needed beyond just oil and gas that’s needed everywhere. Well, if you look at adjacent skills, again, other ways for people that we can figure out if they have the potential to learn this, or if they might be a really good fit. To do this down the line, we went from 627,000 people to 1.3 million, we just tripled our candidate pool. Biofuels, obviously really important for oil and gas, they think about renewable energies, green energy, or even just alternate types of energy, while we also over 3x, our candidate pool looking at adjacent skills, something like carbon capture, again, thinking about renewable energies and this movement towards green energy. Again, we just 7x the candidate pool, looking at the adjacent skills, and maybe the most really interesting one was wind power. There’s only about 25,000 people in the world who know this. But if you look at the discrete skills that are adjacent to things like power generation, electrical engineering, energy, transmission, mechanical engineering, these are out there, right? Those skills exist. And from the data that we’ve got in spades, over one and a half million people are eligible based on adjacent skills to potentially learn wind power, which gives us almost a 60 times multiple on our candidate pool. So this is the kind of thing that AI can unlock, as we’re looking to hire for potential and provide a data backed way to do that. And then Rebecca, what do you think of something like this?
Rebecca Warren 23:07
Well, yeah, again, it’s not something that we couldn’t do by ourselves, right, as a TA professional, we’ve done this, we’ve done the work, it takes a lot of time. And again, you’re spending a lot of time convincing all the people that this is, this is the way to go, or this is someone to look at. Another thing that I look at as a TA leader, that I would continue to tell my teams is that we aren’t doing anybody any favors by bringing in somebody who is 100% of what that hiring manager is looking for, I tend to say we want to look at 80% of that skill. Because if you’re bringing in someone at 100%, guess what, that’s a consultant. And they’re going to be in that role for maybe six to 12 months, they’re going to get bored, they’re going to move on. So when you bring in somebody that’s got that 70 to 80% of that skill, it gives them room to grow. And it also gives your hiring manager an opportunity to pour into that person and to be able to mentor and coach and train. So hiring somebody with some of those skills, and then, and then molding them or shaping them to what your organization needs is a lot easier than bringing in somebody who’s already done this, and who maybe isn’t really ready to change to be what you need. So there’s some components to the data that also helps support looking at those potential hires or those adjacent roles as opposed to the straight on here’s every single bullet point that we’re looking for.
Conor Volpe 24:45
Really well said and also I mean, you have what I think is a shining example of this and one of the customers that you work with which is Activision right? They don’t have you, probably you’re gonna explain it better than I can then this awesome story about fine using adjacent skills. to hire someone into the video game industry, which they had a hard time doing.
Rebecca Warren 25:05
That’s right, looking at somebody from the dental industry who had a lot of the same skill set to be able then to move them over into a position that fit really well. And I’ll say I’ve done this in a past role I was looking for. I used to work for the hair care industry. And they were looking for a regional manager. And it’s really hard sometimes in the haircare industry to move somebody from a stylist behind the chair into leadership. And so they were looking for a regional manager and trying to figure out who that right person was. I was able to find somebody, and I don’t even think they exist anymore from RadioShack. Because RadioShack exists. But I was able to find a regional manager from RadioShack that had the exact skills that they were looking for. Everybody was super skeptical. It was like, you know, my head was on the line, like, yes, we need to give him a shot, one of the best hires they’ve ever had, because they focused on the things that they needed that person to do, instead of a particular narrow background of what they had to have, if that makes sense.
Conor Volpe 26:07
Does and I think there’s also a another important piece when looking at this, like to your point, this concept of adjacent skills, or hiring for potential is not necessarily new to ta with the data that we now have, not only can we perhaps make a better case internally, but we can help candidates better understand how they can be a really good fit for this job and help them understand that, hey, we are thinking about you for this role, there might be some upskilling that you need to do, there might be a burden in a learning period. But that’s a really helpful conversation that recruiters can now have using this as information, which is we think you’re a great fit based on XYZ, we’re going to need you to lean a little heavily into this area, that kind of thing. But it’s not just internal, it’s external to write and have conversations with candidates. Yeah,
Rebecca Warren 26:54
Okay, absolutely. We can stay on the side for a long time, but I think we have to move on.
Conor Volpe 27:00
I know, like I said, there’s a lot to cover. So hopefully we get through it all in time. So the analyzed skills, we have identified talent. And now it’s on to engaging talent and thinking about the roles we need to go out and hire. So we’ve looked at specific skill sets and adjacencies. And now we want to look at roles. And I think an important thing to think about here, which we’re going to cover, but roles evolve rather quickly. And one of the examples that we have here, again, all this data that you’re seeing is coming from our platform. So but I don’t think you needed the full platform to tell you that data scientists have been really in need. Or rather, there’s been a lot of hiring for data scientists over the past 10 years. So maybe that graph on the left, you didn’t need AI to tell you. But where I think it is really interesting is we can see the rising skills in 2010 versus 2020. And there’s not a single piece of overlap there. But that kind of tells us that if we’ve hired data scientists, and we’ve thought about that role, or thought about the skills required for that role in the last 234 or five years, there’s a chance that not skill sets are out of date, but that we need to think about how what a data scientist of tomorrow looks like, and how does that align with what the business needs of that role? And I’m sure Rebecca with some of the customers that you work with, they’re starting to ask these questions, which is well, how do I think about hiring not just for what I think a data scientist needs, but like, how can I get ahead of some of this? Like, how do you and your customers talk through this?
Rebecca Warren 28:34
Yeah, I think, again, it’s doing that analysis of what you actually need in the role. Even let’s pop off of the data scientists, let’s go to an admin assistant, right? You think about an admin assistant role, where it used to be scheduling, it used to be creating PowerPoint or slide decks, it used to be managing meetings, right? A lot of very manual work, maintaining spreadsheets, keeping your leaders, calendars, things like that. So the admin role still exists. But very few people are still doing that. Right. So the skills for an admin assistant are changing, right? They’re more strategic, it’s maybe getting into conversations that they weren’t in before. It’s not just scheduling on a manual calendar. There’s different things that happen now, in an admins, daily life that didn’t exist. So we talked about those positions that are going away. Is that the traditional view of an admin assistant? And now looking at what those skilled trends look like? The position needs to change based on what is happening in the business world? So our clients are all thinking about that, like, what do we need to pay attention to when we used to just hire this profile? And now actually looking at this skill base, we’re looking at completely different folks that we might not ever have considered
Conor Volpe 30:01
And I think you hit on something again, that was really important. But it’s like, what do we actually need this role to do? And this goes back to that side, we have a few concentric circles, but that middle part of how do we align the people strategy to the business strategy? What does the business need out of this role, and being able to get that down to a skill level and associate that with the rising skills and all that, but like, that is that is the art of being able to do so to have something like this, which you can see, okay, these are the rising skills. And now I know that writing skills might be competitive, to hire for or to go learn. So that helps inform a recruiting strategy. And ultimately, like you mentioned, the evolution of a role, which is really cool to kind of be able to see in real time,
Rebecca Warren 30:45
and internal and external to I know, we’re going to talk about that, but looking at what your current talent inside your organization needs to look like next year, three years, five years down the road, some things we don’t know. But what we do know, as you mentioned before, that change is constant. And it’s happening at an exponential rate. So even when I think about the position that I was hired into here, it is so different now than what it was. Because honestly, April’s gotten better, right, the things that we’ve put into place for our customers are easier. And so my job has changed to meet not only the client’s needs, but also because we’ve improved inside of our organization. So it’s that internal and external balance on what you’re looking for.
Conor Volpe 31:35
Yeah, great call. And I think to illustrate this a bit, you were actually already touching on this, Rebecca, but like thinking about roles that are becoming are either changing entirely, like you mentioned, like the administrative assistant role, or roles that we talked about this beginning with the Whole World Economic Forum, example rolls that are going away, it’s the hard reality that we need to think about that. And one of the beauties that we can use AI for is to help understand not just skill adjacencies, which is really important. But that’s the foundation of basically role adjacencies. So on this slide, we have someone who is a systems analyst, which according to our data, that’s a declining role, it is becoming less and less prevalent as time goes on. So someone who is a systems analyst, maybe looking to make a career change to make a pivot to try something different. And what we’re able to identify for them or for the organization, or for a recruiter who’s perhaps looking at hiring internal talent, we can see the skill sets that your typical systems analyst has, has a really nice overlap with a cloud engineer, which is going the other direction, we need more and more cloud engineers out in the market. And these are hard to hire for. So we can see if a systems analyst knows things like SQL, disaster recovery, agile methodologies, project management, and so on. A lot of those same skill sets are needed for cloud engineers. So this is an opportunity to really think about if we’re able to see it at this level, to help individuals make the transition to help me as a candidate who might be coming in looking for a systems analyst role, be able to identify a different role for myself, or, again, help a recruiter identify why this systems analyst might be a really good fit for a cloud engineer, but ultimately help make those switches in an organization going back to providing the data to be able to do that, right. It’s really compelling to see
Rebecca Warren 33:30
well, and if you’re looking at, you know, externally looking at, like you said, hiring a cloud engineer, rather than the systems analyst, and then helping that person get to that space, right? What does that look like for what your internal needs are, but then also helping your internal folks, if you’ve got somebody, right, doing some of that skills mapping and that talent planning to say, hey, we think we’re gonna get rid of this technology, right? We’re not going to use 400 anymore. But we love you. So how do we help you get to that next level, right, matching those internal and external opportunities for folks. And using the data to show that is really easy, right? Hey, here’s, here’s where you are, here’s where we need to go. Here’s the skill gaps. Let’s get you some training, let’s do some development. Let’s invest some time here to help people get to that next level. Instead of just saying your skill sets are this and we don’t need that anymore. So the FBI or yeah, we’re not going to hire that person. Because we need this even though in six months, we might need it.
Conor Volpe 34:38
And the example that we touched on just a little while ago with the Activision Blizzard example of hiring a video game designer, and they eventually hired someone from the dental industry. This was essentially the exercise that they did. This was the data that they saw that they got an application from someone who designs retainers, and they looked at well they do 3d mapping, and they know C Plus Plus and They have three or four other skills that we also need for this video game designer. Well, we can probably teach them the video game industry part that they need to figure out. But ultimately, they have all the skills, most of the skills that you said Rebecca, like, don’t be afraid of upskilling someone for the last 30 to 20% of the role. Activision basically said, yeah, we can do that. And they have changed a lot of their hiring practices from needing someone who has video game experience, which is not a massive industry. So it can be hard to find someone with experience in the industry, they’ve now been able to go out and hire people like someone from the dental industry, but this is the exercise essentially figuring out how skills translate from one role to the other. They’ve been the beneficiaries of that. But it’s just that I love that example. It’s kind of funny to think about selling retainer designs.
Rebecca Warren 35:47
Well, and then on the other flip side, right, so taking that same example of you can then show this candidate who never in a million years would have said, Hey, I’m going to apply for this position, you can Hey, but here’s what you’re going to get to do. And here’s how you’re going to use the skills that you have. So it also gives that candidate who never would have applied to me not applying for a customer success role, that data to say, hey, here’s how we’re gonna help you connect the dots.
Conor Volpe 36:14
Yeah, exactly. All right, poll question time. Do you feel confident in your knowledge of the skills your workforce needs for the future? And I think these are some of the things that Rebecca and I have been touching on the data science example, and how roles are evolving, and where all these different roles are going or how they transfer? But this is a sticky question, right? Like it can I think we all have kind of a gut feeling about where things are going. And we can take some educated guesses. But I’m curious to see what you were on the line for? Like what? How confident do you feel and being able to assess what skills your company might need to hire? For me, Rebecca, this is probably a difficult question to answer no matter what stage, let’s say organization.
Rebecca Warren 36:58
Right. But again, it goes to that organizational design and that planning of what is the company trying to accomplish? And then how do we know what we need to plan for?
Conor Volpe 37:11
So maybe that’s honestly the first step right is like, what are the organization’s priorities, then how do we map our talent initiatives to those priorities? So there’s certain sectors that need to hire more of their business units, or lean into whatever that looks like? But that’s probably the first one. Yeah. All right. We’ll give people a few more moments to submit looks like we got quite a few folks. Answering. Cool looks like slowing down.
Rebecca Warren 37:37
Let me ask you a quick question. Connor. Have you always been in marketing? I have an area of marketing.
Conor Volpe 37:46
Yeah. So it was always interesting, poking around with eightfold to see what other kinds of roles or like my own adjacencies and doing career pathing within some of the technology we have. So I’m always curious, like, what, what pops up, especially when there’s things outside of the marketing realm? Because I’ll get marketing roles, which are great. I’m always interested in seeing things like, Oh, can I do this? Can I do marketing ops? Katie, whatever it is, every once in a while, I’ll get something different. I’m like, oh, that’s that’s curious. I’ve never thought about that as well, I probably never would have really considered it. Because I mean, I’m, I’m, I’m the benefit in the curse of being in Product Marketing. My whole career is that I haven’t had to do too much keyword searching. It’s just what do you have the product? Marketing? I’ll do that.
Rebecca Warren 38:33
Perfect. Well, clearly, your skills are in demand. So
Conor Volpe 38:36
yeah, yeah. Luckily, luckily. All right. So it looks like most people are in this category. I have some ideas, but would love to get better and better at this. And then we’ve got another group of people towards the middle, which is, it’s hard. This is a hard thing to do. We understand.
Rebecca Warren 38:55
Again, it’s a lot of conversations with your leadership with understanding the business directives, which, you know, help drive that change management. The more transparent your organization is, the easier it is for HR and TA to be able to help shift that landscape. To go knock on the door, ask all the questions.
Conor Volpe 39:19
Amen. All right. So we were talking about organizational plans, which is our next section. And one of the things I think is really important to look at as we think about these plans is where an industry is headed. And so we did some research, we showed you some of the oil and gas research, we did some of this for the airline industry as well. And we looked at what skills are declining in the airline industry and going and declining rather quickly. So we have things like some programming languages or tools that are not getting used as much anymore. Then we also compare that to the skills that are rising in the airline industry and being able to have information like this at your fingertips to be able to make talent acquisition strategy decisions. I mean, Rebecca, this has to make the concepts of like build, buy, borrow, bought, and being able to see not only the skills we have within our organization, but then outside in what’s rising, what’s declining, that has to make those conversations a bit easier, I would think.
Rebecca Warren 40:25
Yeah, absolutely. Again, it’s understanding what you’re trying to accomplish. I think I’ve said that 12 times already, but it’s understanding what your organization is doing. Because I and I will tell you this, I have hired folks in the past for hiring managers, where they’ve said, This is what we need, we get the person in the role. And then they’re like, oh, no, that’s not what we need, then you’ve got this really weird, like trying to fit that square peg in a round hole? Have we not hired the right person? Because we didn’t do all we didn’t ask all the right questions, we didn’t understand how this was going to align all the way up to that senior level. So we certainly don’t want to bring somebody into the organization that’s not going to be successful. Right? That’s, that’s really, really tough.
Conor Volpe 41:17
Yeah, yeah, I think one of the other things to take away from a slide like this, too, is, just because a skill is declining doesn’t mean it’s not needed. Right. So as we think about the whole idea of building by borrowing, some of these declining stills might be still essential. So maybe that helps inform the well, maybe we hire a contractor to patch us over for a bit, maybe this isn’t something we invest in with a full time employee. But again, being able to look at these through that lens and going to hire a full time employee, maybe we need them to know about digital marketing or Jira, or commercial aviation, whatever that might be. Whereas if we’re looking to hire contractors, maybe the contractors help us out more with some of these skills that we still need. We just don’t think we’re going to need them as much over the next 2345 years. And that changes the shape of your workforce. And Rebecca, it goes back to I guess, is our favorite phrase of the day, which he goes back to what are what are the priorities? What is the plan? And how do you kind of prioritize all this?
Rebecca Warren 42:17
Well, yeah, and then flipping that a little bit to how can you take some of that work off of the plate, right? Like, if you know that in your positions coming up that there’s a ton of scheduling to be done? Can you get an automated scheduling tool to come in and do that for you? And one of the things that is, I think, really important is, again, that transparency across your organization. For instance, in our day to day, we’ve got the sales team who are using a couple of tools that when we in customer success heard about and we’re like, Oh, I think we want to use that tool, too. So how do you, inside of your organization, say, Hey, can we take the work off of everybody’s plate, not just this particular department or this particular area? Could we employ some technology that’s going to help everyone in the organization and see those organizational benefits, not just in a particular department? So again, that transparency of hey, we’re thinking about doing this in our department? Could somebody else inside the organization benefit from that as well?
Conor Volpe 43:24
Hence, organizational plans. Not crazy.
Rebecca Warren 43:27
Conor Volpe 43:30
All right. So we have done analyzing skills, we have identified talents, we have engaged talent, we just did our organizational plans. Now it’s time for competitive benchmarking. And this might be my favorite section, because I think the example we’ve got here is really, really powerful. And this comes to us courtesy of some work that we’ve done with the Josh person company. So they use our April talent intelligence platform and the market insights and market data that we have in there to do research and to pull out trends and to look at particular industries. And this one, they looked at healthcare. And the lens of this research was Josh Burson company was trying to figure out well, the companies who do set themselves apart are performing really well, what they refer to as pacesetters. What, what are they doing differently in talent, like ours? Are there trends we can identify that set them apart? And so when we look at this, there’s a lot there’s a lot to take in, so I’ll try to walk you through it a little bit. But on the right, we have the roles that the pay center organizations are hiring or have more concentrated in their organizations than the standard healthcare company. And if we look all the way at the bottom, it turns out that the standard health care company is hiring more nurses than pay centers, which is odd, because I think we’ve all heard for years now that there is a nursing shortage. My mom was a nurse growing up and I would hear about this all the time, and it’s true today. So what gives? Why are pacesetters doing better with fewer nurses than the standard? Clearly, the secret is not hiring more of that role. So if we look at what they are hiring for, we can start to realize we can start to see the strategy that they’ve used, which is essentially that we want our nurses and our other health care professionals to be doing what they do best. And Rebecca, we were kind of talking about this earlier, what is the point of the role. And for nurses, we want them spending time with patients, we want them providing health care, we want them doing less data entry, or filing or working in systems throughout the organization, we want them focusing on the patients. So these companies have gone out and hired Well, let’s create applications, let’s create scalable processes, let’s have better software infrastructure, so there’s less burden on the people on the front lines. And that means that ultimately, well, we do need less roles, like we maybe need less front office managers or data entry. But we need more innovation managers and process managers and people who can ultimately create the scalable processes. So a role like a nurse, which is in really high demand, can focus on what they do best. And instead of asking nurses to work double time, we can just say, focus on the patients, we will do our best to offload the rest of it from your plate, so that you can do the job that frankly, you signed up for, and that we want you to do. So I think this is really powerful to see excellent research from the Burson company to kind of bring some of this out. And I think there’s a lot we can learn from something like this. I mean, Rebecca, like, what do you take away from, from seeing something like this?
Rebecca Warren 46:47
Well, I think the parallel is very easy over TA in HR, right. Like in talent acquisition. It used to be so many manual processes between emails back and forth, we’d be you know, looking at spreadsheets, trying to schedule folks getting on calendars so much was manual, and lots of of administrative work that stopped us in ta from being able to do what we’re hired to do, which is talk to candidates, right, get folks in the door. And so I think the same model applies to how you get the work in the right place. I’ll give you just a quick little thing from where I am and what I’m doing right now. I really enjoy customer success. I love working full time. And I continue to drive the role, like I want to continue to add value, I want to have fun. So how do I get the stuff off of my plate that I don’t love to do so that I can do the stuff that I do want to do? Right? Those are the things that we need to continue to look at? How do we help people do the work that they love by using tech to do the work that maybe they don’t. So looking at this from a perspective of what am I going to get out of it as a TA leader as an employee, it’s using tech for tech sake, right? Again, that human component, but using your ability to add different solutions in to make your life a little easier, right. It’s very applicable to what is happening in TA and HR right now.
Conor Volpe 48:26
And I think that’s why this is not a bad capstone to this presentation, which is the pacesetting organizations and healthcare have basically done that they look at this for their entire organization are clearly making changes to help certain roles, or honestly, if nurses and healthcare professionals are more productive, they’re better with patients patients are happier, the company’s more successful. And ultimately, I think that’s our message when it comes to AI in TA, which is yeah, this could change some things for organizations. But ultimately, we think it’ll change it for the better. And that are, the TA professionals out there will be doing less and less of the mundane manual and more and more of the strategic and being able to look at market insights, competitive insights, help inform organizational plans, all the things we’ve just talked about for 45 minutes, and put those into into action. So
Rebecca Warren 49:16
well, I can give you just a quick example of that, where I was on a project and our project is to look at developing a charter for our customer success team. Our team is relatively new. I was the first hire on the team a couple years ago, and we’ve built it up and developed and created a whole bunch of things. And so one of the projects on my plate was creating a charter and I have a team of folks, you know, that we’re working together on and I was so stuck. I could not figure out how to actually write the charter itself, right. What is the goal? What are we trying to do? So I went to chat with GPT and I said, Hey, and I asked it to give me a statement. It gave me a ton He’s information. But here’s the thing. If I were to take that and just plug it right over there people would go, like, people would say, What are you doing that does not sound like you, that does not sound like us. So it was a thought starter for me to get me out of that hole that I was stuck in. It didn’t do the work for me. But it helped me think through what I really wanted to say. My motto was to steal from the best and make up the rest. So take that at the start that little bit of inspiration using AI or machine learning. And then add your own flair, put your own, you know, twist on it, the human piece is always going to be important. But we can use it to help us think a little differently or come up with a different answer than maybe we would have thought of just on our own.
Conor Volpe 50:47
Yeah, to make the human element really shine, perhaps I guess yeah, what to think about it.
Rebecca Warren 50:52
That was really good, I had a really good goal statement. I was pretty happy with it by the end.
Conor Volpe 50:56
I believe it, I bet. Alright, so we’ve got one last poll for everybody. Again, we just kind of ran through the whole gamut of analyzing skills, identifying talent, gauging talent, organizational plans, competitive benchmarking. And along the way, we kind of slipped in some examples of how AI is changing some of these things. And we’re curious, where do you think AI can make the most significant impact in TA? Are any of these things jumping out to you, are your brains starting to turn? Are the gears moving and going, Wow, if I could use X, Y, or Z for this part? Honestly, we’re just curious to see what you all think about where this could have an impact? Because I really don’t think there’s a right answer. That’s
Rebecca Warren 51:35
no. And there’s a lot more answers than what we just have on the screen. So if there are other things you think are going to be significant, throw them in the chat, ask some questions. We would love to hear other things other than what we put up on the screen here. We were chatting with our producer here like can we have 17 options here? And he said, No.
Conor Volpe 51:59
No, we can only do five but no, it’s great. It’s a great call that like there’s I’m sure there are some things that people Yeah, throw them in the q&a. Just give us a sense. But yeah, we want to give you some thought starters to get this going.
Rebecca Warren 52:11
And I think we have time for some questions, right?
Conor Volpe 52:14
I think we do. So let’s go ahead. And we’ve got enough in here for now, just cuz we want to get to the questions. So let’s see what people’s answers are. All right. 45% for sourcing and candidate matching. Even I know right. But that makes sense. We’ve spent a lot of time talking about how skills can help identify the right candidates, help us source candidates and help us understand our pipelines better. I mean, you won’t get there’s no right answer to this, but you won’t, you won’t hear us disagreeing with that being the 45% answer, because it is a really important part. Okay, great. We’ve got about five minutes left. So with that, Rebecca, and I just want to say thank you to everybody, for giving us an hour of your time. We know everybody’s really, really busy. So we appreciate you spending some of your busy day with us. We hope this was helpful. from one corner to another. I think we’re ready for whatever questions we’ve got throughout this whenever we can answer in the last five minutes or so.
SHRM Moderator 53:19
Wonderful. Thank you Connor. We will turn to audience questions in just a moment. This program is sponsored by eightfold eightfold delivers the talent intelligence platform, the most effective way for companies to retain top performers and rescale the workforce, recruit top talent efficiently and reach diversity goals. Eight fold deep learning artificial intelligence platform empowers enterprises to turn talent management into a competitive advantage. For more information, please visit www.eightfold.ai. All right, let’s get to audience questions. The first one. The sector in which I work is the Middle East. When we release a job spec, the candidates have a tendency to include all research and all search points in their resume. A potential candidate who may not be looking for a job can be frugal and express or use keywords that end up in processing a lot of unnecessary vacancies. What is the solution to this?
Conor Volpe 54:26
So it sounds like depending on candidates interests, their resume has varying degrees of built out. I think that’s kind of what the question is about. So what do we think? A lot of that I mean, this is actually our talent diligence platform doesn’t just use what’s on a resume, but compares that person’s experience and their title and how long they’ve been in particular roles in organizations to other people around the world. We don’t rely on just what’s on the resume but we use our market data to help inform what this person could be capable of, their aptitude and their potential. So the resume is certainly helpful. But ultimately, we compare their experience with what we know about this to other people. I mean, Rebecca, you go ahead, I’m sure you got, right.
Rebecca Warren 55:08
No, you’re right. I was just gonna say, to build on that we don’t do keyword matching when we use AI and machine learning. It’s explainable. But we’re making those connections, just as Connor said, those connections get made underneath the surface. So if we see something on a resume, we look at others as you said, we look at other folks who have been in current positions like that, or have been, you know, what, what are their backgrounds, their experience, the companies that they’ve been in. And so we can make that connection of saying, if they’ve done this, they most likely have done that, because people who are similar to them, or who have worked in similar companies have done that as well. So it takes a lot of the keyword matching, like, oh, my gosh, you know, we used to say on resumes, put that pile of, of skills at the bottom of your resume, and then whitelisted, so that folks don’t see that just to get it picked up. That’s not how it works. So AI really does make those connections and the more we give it information, the more it learns and says, Okay, we understand that these skills connect with those, those needs. So great question.
Conor Volpe 56:15
And in fact, on the addition of the bunch of skills, the bottom and the white Tech’s, our system lacks all out if there’s a particular skill that someone says that they have. And when we look at all the other, let’s say store managers, right, like Walmart, retail store managers we go, they don’t typically know SQL, but this person had SQL on their resume. So just an FYI, for the recruiter, as you’re going through here that there’s something a little bit off, I want to ask about it. So we’ll do that as well. It’s that so it’s not just beyond keyword matching. It’s also instead they have this that is outside of usually what we see what could be the case, it could be the case, it’s more so just bask just That’s right.
Rebecca Warren 56:52
I mean, I think if people look at my background and say, Oh, she says that she writes and facilitates murder mysteries, people would probably go, That’s not typical for a day leader. But that is actually true.
Conor Volpe 57:06
Awesome, Colorado. We have time for one more.
SHRM Moderator 57:08
Yes, we can ask one more question. What are the declining and rising skills and talent acquisition industry?
Rebecca Warren 57:16
Oh, that’s like a whole nother webinar? No, I think I would. So I can start with that one. I think what we need to pay attention to in talent acquisition is that we are not order takers. Our role should not be to just do that keyword search, put a whole bunch of folks in front of the hiring manager and just pray, right, we need to be very embedded in the business, we have to be very educated. It used to be, I think, where it really was just a resume shuffle. And now it’s about education of what not only does that role need today, but the role of TA and the skills needed are also that change management, that education piece, and that ability not just to foster relationships, but absolutely, absolutely to become that strategic business partner. So not just sitting inside of the, but getting embedded with that business unit, being able to foster those relationships, but also to understand what that long term strategy is, and to be able then to pull out what that’s going to look like for current as well as future hiring. So that strategic business connection is critical for the TA folks up today.
Conor Volpe 58:33
I think that’s why we spent a decent amount of time on organizational planning, competitive benchmarking and understanding how those things inform hiring strategy. Right. And using that data, we kept going back to that, but use the data to have some of those conversations and AI can help you with that. Yeah,
Rebecca Warren 58:50
That’s right. Connor, I think we take that away as maybe our next webinar topics.
SHRM Moderator 58:57 Before we sign off, we want to thank our presenters, Rebecca Warren and Conner Volpewith from Eightfold for the information they provided today. And we also want to thank everyone tuning in for being with us, and for choosing SHRM for the HR webcast. That concludes this program.