The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
Welcome to The Breakthrough Hiring Show! We are on a mission to help leaders make hiring a competitive advantage.
Join our host, James Mackey, and guests as they discuss various topics, with episodes ranging from high-level thought leadership to the tactical implementation of process and technology.
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- Shift your team’s culture to a talent-first organization.
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The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
EP 153: Skill-based hiring and AI's role in evolving talent acquisition with Daniel Chait, CEO of Greenhouse
Join host James Mackey and Daniel Chait, CEO of Greenhouse as they discuss skill-based hiring, emphasizing the shift from traditional qualifications to assessing candidates based on their capabilities. They highlight the benefits of this approach, such as broader talent pools and internal career development. They also explore the consolidation of recruiting tech, noting the trend towards all-in-one solutions and strategic partnerships. AI's role in talent acquisition is debated, with a focus on its potential to enhance job descriptions and interview processes, while acknowledging regulatory and bias risks.
0:00 Skill-based hiring
9:39 The evolution of job skills
15:13 Evolving buyer needs in recruiting tech
21:30 Strategic partnerships in recruiting tech
28:54 LinkedIn integration and AI in recruiting
34:11 AI filtering in recruiting tech
37:21 The Future of recruiting technology
44:29 Machine Learning for evaluation in recruiting
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Hello, welcome to the Breakthrough Hiring Show. I'm your host, james Mackey. We are joined with Daniel Che today. Daniel, welcome back. Thanks great to be here. Looking forward to it yeah, me too. So we have a few topics for today. We're gonna discuss skill-based hiring, recruiting, budgets and consolidation in the talent acquisition tech space, and then we're gonna get into AI use cases for talent acquisition. We're gonna talk about the most sought after use cases. We're going to talk about the use cases that may be more or less so technically feasible, risks associated with different use cases, and also maybe just brainstorm a little bit on what AI's use cases are essentially just going to become table stakes. But then also, what does the future look like? What types of issues are people going to try to tackle over the next couple of years?
Speaker 2:Awesome. It's going to be a lot of fun. Looking forward to it.
Speaker 1:Yeah, yeah, me too. So I guess let's just start with skill-based hiring. You mentioned that this is something that's top of mind for a lot of people right now. Could you provide maybe we'll just start with a definition of skill-based hiring and then we could just riff back and forth on that for a little bit.
Speaker 2:Yeah, great question, because it's one of those jargon words that people throw around and what do you really mean by it? And are we doing it, or is it the future or whatever? The way I think about it is very simple. It's hiring people based on your assessment of their capabilities, as opposed to based on a set of qualifications or on, maybe, like a degree or a college that they've gone to or a place that they've worked, which is the traditional look at their resume. And we want to hire people from quote good companies or from quote good universities, and I think people have started to wake up to the idea that not everyone who worked at Facebook is the same. Not everyone who is awesome at the skills you need for the job went to an Ivy League university, and so if you're going to hire the best people for your company, you need to think about how do you assess what those skills really are, and then how do you separate that out from what's on their background, which may or may not reflect that perfectly at all.
Speaker 1:Yeah, and so when you talk about how to assess the skills that they have right, the transferable skills, is there a specific method that you recommend to customers in terms of a cover? Is it as simple as just like jotting down a list of different things that they're doing in their current role and then trying to find match, different parallels, stuff like that, I mean yeah, look at a high level.
Speaker 2:It's about assessment and it's about identifying, like you say, here are the skills that we need in this role and here are the different assessments we're going to run to identify who has those skills and to rate them on those skills.
Speaker 2:Obviously, depending on what the skill is, you're going to use a different technique If you're looking for a programmer versus if you're looking for an accountant versus if you're looking for a delivery driver, you're going to do a different assessment, obviously, but the methodology, the approach, is the same, which is like what are those key skills that you need and then match up the right assessment to it all.
Speaker 2:I think the great opportunities that you have are number one, you can attract a much broader and more diverse group of talent for the same roles, because you're not fishing in the same pond as everyone else. Number two is, you can find new career paths for people within your organization, as opposed to having to take on the cost expense and risk of going outside, because you might have people in your, for example, at Greenhouse, in our SDR department, our kind of entry-level sales roles that have gone on to roles in programming and software development and QA and customer service, and other areas, because you don't just look at what job title they've had, but you can look at what the skills are that they bring to the table, and so I think it gives you a number of advantages.
Speaker 2:But it takes some doing and it takes some. It takes really, first and foremost, an intentionality and a commitment on the part of the organization that you're going to look past the headlines on the resume and you're going to get over your hangups about certain companies and certain schools and you're going to get on with finding the right people for the job.
Speaker 1:Yeah, and I think also probably some of the some of it comes down to trying to analyze which roles it makes more sense to do this with. Of course, there's going to be some roles in which that transferable skill, if they're doing something else necessarily isn't going to be as relevant or doable. It's like certain finance roles, for instance, or just different, more maybe technical senior positions that require the subject matter expertise. But I think that's also somewhat intuitive, right, Like when you're looking at the types of roles in the organization that this would work for, maybe more so like individual contributor roles or no, I don't mean that it's only individual contributors.
Speaker 2:I just hired a CFO, for example, who, while he has many years of CFO experience, he also worked in the past as a strategy consultant, and so that gives him certain skills that he's exercised in the past that are very relevant to this job. Obviously, there's other skills like that you really can't learn on the fly, that you have to already bring to the table if you're going to have that job, going to have that job, and so there obviously are certain background markers that one needs, or qualifications that one needs for certain jobs. To your point, if you're going to be a CFO at a company at our scale, for example, you have to have a track record of being a successful CFO at scale. You have to have worked in certain software industry and things like that. But other parts of many jobs, including that one, are very much a transferable skill that you can pick up in other areas. And so I think when you're looking at most roles that you're hiring for, you probably have the opportunity to identify some or all of the skills that you need and find people who bring those skills inside and outside your organization, as opposed to just looking at the kind of background markers that they have.
Speaker 2:And I think the pandemic era was really a big change in mindset for a lot of people because all of a sudden kind of remote work was everywhere and the office dissipated into work from home and so everybody's just a different zoom box on your screen and it opened people's eyes up to the fact that hang on a sec, if I don't even have to be in the same room as you to get work done like maybe my beliefs about where you used to work are also don't even have to be in the same room as you to get work done, maybe my beliefs about where you used to work also don't necessarily hold up. And I think it opened up a lot of people's Because you get the great resignation you had, tons of people moving and changing jobs and rethinking lots of things, and so I think that created the conditions under which we're now seeing skills-based hiring take on a more central role in how companies hire.
Speaker 1:Yeah, I think so and I think to some extent to people that are in talent acquisition have always tried to broaden the qualification requirements right, maybe bias too far in the other direction to some extent, but so it's. I feel like it's. If you come from a recruiting background, it's. This is a little bit more intuitive of a concept. So the reality is there was, of course, a middle ground and just in the early days of starting Secure Vision, we working on a lot of sales openings and the qualification. It was closer to 10 years ago.
Speaker 1:There was still a big push for college degrees and that was something that was, and sometimes like specific types of degrees and from certain types of schools, and it was just, it was a little interesting and even if somebody had a great quota, accomplishments or references, it was there was like these hard requirements. Another one that I thought was a little bit overkill was the. It was there was a huge demand to have people that come servicing the same industry, so a salesperson that was selling a SaaS product to a specific type of, maybe a company that has customers in real estate or just very nuanced things, and some cases I think that kind of stuff might be relevant If it's a really technical cybersecurity product, I don't know, but generally speaking it's like the transferable skills of, but generally speaking it's like the transferable skills of okay, has this person sold enterprise SaaS products, like a similar sales length deal cycle?
Speaker 2:Yeah, can you do discovery calls, can you take good notes, can you do the right type of follow-ups, and probably, if you can sell a 300K ACV SaaS product to, for example, real estate, you could probably also sell that same product or a similar product to a different industry.
Speaker 1:Yeah, I don't know. I just think that a lot of folks over-index how difficult selling to their customer base is. And sales is hard. It's not necessarily because of the types of customers you're selling to. It can be, but I think we over-index, a lot of folks over-index on that. And the other thing that, like the one hangout specifically to stuff like that is they're like well, it just takes so much time for someone to learn what we're doing in this. You want people that are adaptable and, quite honestly, you do need somebody that has, in some of these roles, maybe a fair amount of raw intelligence. The right person should be able to figure it out.
Speaker 2:That's right and look, I think it's. Also it reflects a really outdated mindset about what's available today to learn and how easy that is. Versus when I began my career in the 90s, it was like, oh, that person has a Rolodex. To take your example one step further, that person brings a Rolodex in the real estate industry. That's really helpful Because, like you, didn't have any other way to get those people. So if you wanted to sell to that industry and you had a salesperson that knew the top 100 accounts and had their phone numbers, that was really an asset.
Speaker 2:Today, needless to say, all that information is out there. I don't need that Rolodex, quote unquote. I have the same 700 million LinkedIn profiles access that you do, and that's on the ground kind of knowledge of, like how to get ahold of someone or how to learn about a particular industry. You had the World Book Encyclopedia. It was like a shelf full of 20 books. That was all the knowledge you were supposed to have and beyond that, it was in people's heads. Now there's so much available information, there's classes online, there's so much ability to connect with other people, and so I just think the whole notion of learning on the job is way different than it was half a career ago and I think in hiring we're just starting to come to terms with what that means and the fact of what a transferable skill is, I think is a lot broader than it used to be.
Speaker 1:For that reason, yeah, and I think honestly, I was recommending skill-based hiring before I even really knew that was the term for it. I mean, that was typically what I was going for. I think that one way that I put it I did I would post about this on LinkedIn and it seemed to get a lot of traction or resonate with a lot of people is there's I feel like there's, and not only can you do skill-based hiring and that makes sense, but in fact sometimes you can get more ambitious, hardworking people if they haven't done everything you're hiring them for. So I would say, like, hire for some roles, it makes sense to hire somebody who's done 70% of the job, and it's the 30% they haven't done. The 30% they haven't done is why they're going to accept your offer.
Speaker 1:It's that growth right that and, honestly, many of the best I don't know if all, but many of the best employees that I've hired at secure vision and I've helped my customers hire are folks that that haven't done a hundred percent. They've done 70 of it and 30 30 that they haven't done and that's just like a rough estimate. I don't have like data per se, it's just my own experience, what I've seen. I try to get people to have a foundational understanding but there's stuff that they haven't done and I it just never concerned me too much. There's different roles, like for a cfo I I want them to have done everything that I need to have done.
Speaker 2:I don't want them you should know how to. You should know how to like present to a board and, yeah, financials to the company and stuff for sure, yeah.
Speaker 1:Yeah, that's like the strategic person that's supposed to be, like way better than you at a specific, very strategic function. That's like very high risk if it's done wrong. And but for a lot of jobs, yeah, like sales roles, recruiting roles, even a lot of programming.
Speaker 2:There's an empathy on programming. Can you learn a new programming language or a different database or a different architecture? Absolutely.
Speaker 2:Do you have the kind of fundamentals and I think you'll see that in a greenhouse scorecard that a customer of ours will put together. Here's the kind of must-have, non-negotiables that they can't learn on the job. Here's the sort of nice-to-have It'd be great if they brought it to the table. And then here's some growth opportunities and it's a great way to think about, as you say, what's the? Not only how are we assessing that person, but what open space are we giving that person in this job to grow and learn, which is a big part of why people take jobs. So I think and to your point that you made earlier, I remember when I first heard this jargon of skills based hiring, I was thinking like, yeah, duh, obviously you hire people that are good at the job you're hiring for.
Speaker 2:But it took me a minute to learn that there's a whole other philosophy that people have around credential-based hiring, and so you just look at these markers on their resume of what companies they've worked at, what schools they go to, what degree do they have, and for some of us, it's really obvious that you should look at the skills, but there's a whole group of people that are still not there yet. Yeah, and I think too.
Speaker 1:There's a whole group of people that are still not there yet. Yeah, and I think too it's. There's that nuance of understanding when credentials really matter and specialization, like when we're going to a doctor, we want somebody who's specializing in that very small, specific thing like your ankle, somebody who's like focusing on one specific little thing, but that's just there's. There needs to be this awareness that there's different approaches and when to use one or the other is the point.
Speaker 1:Yeah, I think, just for us it probably just comes very intuitively, just as a result of our life experiences in this space, but it's certainly not, it will admit, a lot fewer companies and leadership teams that are driving hard on some of the things we were talking about in terms of the credentials and whatnot.
Speaker 2:They're more so, yeah, what it means, though, and then maybe we can. Maybe this is maybe an offset on this topic, but I think the last thing I would say is what it means is, as an organization, if you're going to make this shift, you have to be good at assessment. You actually have to be able to develop some conviction internally that you've figured out this person and you know what their skills are, because you're not going to just rely on the credential, and that can be hard. It's. The first question you ask is where we started this conversation. To bring a full circle.
Speaker 2:So how do you know if I'm hiring, say, a programmer or a salesperson, to take some of those examples? How do I know that they have the required skills? And that can be a process where there's some change management involved. You got to roll this out to your hiring managers and to your interviewers and let them know here's the way we assess these people. Here's what a good answer. Give them a rubric. Here's what a good answer looks like. Here's an okay answer it looks like, so that they can come away from those meetings with some confidence that they've actually done a good job assessing those particular skills. And so the prize is high. If you get that, then you have those abilities that we talked about. But it can be some change management and it can be some work to get the organization there.
Speaker 1:Yeah, I think so. For some of the programming roles too, we've just had companies simply do technical evaluations on okay, we really need somebody to know this language. But if they know this, these couple of things, then we know they can pick up X, y and Z, and so the primary evaluation is on the foundational stuff that they know is super important, and then they know okay, if the candidate aces these things, then we might be able to ask some broader technical questions about hey, so in this project, how would you think about solving X, y and Z? And you can understand some more behavioral and technical like acumen. But that's usually just a fairly straightforward way of determination. I think it's the hiring manager's understanding of the role makes a big difference there too.
Speaker 1:Okay, what's really the hard stuff to learn?
Speaker 1:And assuming that they understand more of a skill-based hiring approach or they value a skill-based approach, I should say Yep, cool, yeah, I think that's a good stopping point for that topic, and then we can move on to recruiting budgets and consolidations episodes or whatnot, and I have this has been a common theme with recruiting tech leaders that I'm talking with in particular when it comes to their product roadmaps and how they're thinking about the future. They're looking at ways to essentially get stickier, offer different products, thinking more of a product suite approach to their solution. I'm seeing a lot more people talk about acquisitions, looking at different startups that can make their product suite more comprehensive or have a workflow that goes from end to end for the hiring process, and there's just a lot of thought and consideration in terms of how companies are thinking about positioning and offering different products, and then, of course, that's influenced directly by how companies are buying. So this shift is happening. Companies are looking for all-in-one solutions. It's just interesting now because it just seems like that's almost like across the board right now.
Speaker 2:Yeah, absolutely so. Just to start with, on this it's a great topic that you raised. Just to start with, we're now in the third year of this kind of elevated interest rate focus on profitability versus growth across the board. This is not about hiring or recruiting tech. Every company, especially every SaaS company, is feeling this.
Speaker 2:Every B2B seller is in some way or another grappling with their buyers, having an elevated level of scrutiny around every purchase, looking to save money, looking to be more efficient, and it's very much become the norm in any kind of technical sales environment, save for a very small number that seem to be immune to the laws of gravity.
Speaker 2:But for most of us out there selling technology, whoever you are, to businesses, you're feeling this pinch, and you have been now for going on three years, and so start with that. Then you zoom into what's happening in our little neighborhood and, to your point, our buyers are often hiring less recruiters themselves to handle more candidates and, at the same which we'll talk about the more candidates thing when we get to the AI stuff and, at the same time, having less resources available, having less tools, having less automation, wanting to simplify, wanting to consolidate, wanting to buy fewer things from fewer vendors, spend less money, have it all be more efficient, and so those are great goals for teams to have as a vendor. It creates challenges and creates opportunities, and so I think it's an interesting moment of transformation within recruiting tech right now.
Speaker 1:Yeah, definitely. It's really interesting to see the different strategies and I'm wondering too it's like from a buyer position it's looking at what are the primary use cases that they're considering with different product suites. I think, yeah, again, I'm seeing this shift of there's yeah, there's products at different parts of the workflow that are plugging in and integrating with tools like greenhouse, for instance. I'm starting to see, okay, the category leaders of all those different parts of the workflow are now just purchasing startups that can provide, like, the additional parts of the workflow for this all in one, and so I'm just curious is there anything you could share in terms of when you're speaking with customers or prospects or when your team is? Are there key pieces of functionality that they're looking for, maybe outside of the applicant tracking system or the hiring operating system? Rather that you do, what other use cases are they pressuring you guys, or are they really asking you about right now?
Speaker 2:Yeah, I think you said it. It's this idea that you have this applicant tracking system, and then you had all these other point solutions that you were going to do to be the best at everything. And now they're saying, okay, but the truth of the matter is I have to have an applicant tracking system. If I'm doing anything, I need a place where the candidates can come from my website, I can move them through a process and ultimately disposition them. That's the must-have. Now, how do I enhance that functionality to get what I need without sprawling around and taking up all these budgets that I don't have and complexifying my stack with a bunch of tools? And so they're coming to vendors like us and saying what do you got? And so for us it's you just look at the investments that we've made and the products that we've launched. It tells the story. It's, first of all, some sourcing tools so you can do more of your sourcing natively in in greenhouse, Whether that's hey, I've got a candidate, I want to look up their email address, and I don't have to buy third-party technology, I can do that right in Greenhouse. I want to send them a cadence of emails and get them outreached as a prospect and ultimately recruit them into being an applicant in a hiring process, Whether it's internal mobility and posting internal jobs on a company job board, whether it's more sophisticated tools for scheduling and logistics and like the candidate experience side of it, where I think just the basic calendaring becomes difficult.
Speaker 2:I think certainly reporting and analytics is an area where we've released tons and tons of new features dashboards, visualizations, schedule automatically, schedule, reports that can go to hiring managers, like all the stuff. So you don't have to have greenhouse and a reporting tool and visualization and business intelligence software. You can do it all right within the product. Those are some of the main use cases. But we're seeing even e-signature. We just bundled an e-signature tool with Adobe eSign texting.
Speaker 2:We're now in market with the ability to bring in a third-party texting tool from Grayscale and bring that in under greenhouse as like one purchase, one buyer, one throat to choke, one order form, and so we've really been the system of consolidation of recruiting tools in those ways and at the same time as I say it's an interesting moment of transformation because I think what you're seeing from the recruiting lens is it's consolidating around the ATS and so our customers are buying more and more of that stuff just from us. But when you zoom out, you've got like Oracle or Workday or whomever, saying oh we're the all-in-one tool and you should get it all from us. And success factors Okay, We've got a recruiting tool and so you don't even need the greenhouse and all that stack, you can just get it all from the workday. And so the everyone looks at their own universe through that lens and it's interesting to see where the lines are actually going to end up being drawn.
Speaker 1:Yeah Well, I think also you've made a really interesting point about the e-signature solution, where it's you're just basically co-selling be the right term. You're not like you didn't acquire them or they didn't, it's just vice versa, yeah. Yeah, or the vice versa, rather. But you guys, it's just essentially, if they purchase through Adobe, they can purchase you at the same time, or vice versa, essentially.
Speaker 2:Yeah, so basically Greenhouse comes with a bunch of credits, signatures, so you save money. Basically what it is. Our customers typically are having to go to market and buy a third party call it, whether it's Adobe or DocuSign or HelloSign or all these other tools, and that can cost thousands of dollars.
Speaker 1:Yeah.
Speaker 2:And instead now you get a number of e-signatures with Greenhouse. You don't have to buy anything, you don't have to have a third party, anything, it's just there. It doesn't cost any extra money. And then if you go over and you end up signing like hundreds and hundreds of more documents, you can pay per unit but you're still saving a bunch of money. So that's an example of it's a simpler purchase from the customer standpoint, Security purchasing, IT are all satisfied and it costs a lot of money.
Speaker 1:Yeah, that's also, in a way, that's really nice too right, because you're not just even if you do an acquisition, then it's like everything becomes your problem in terms of the product and making everything work. So this is it allows people to, in a sense, stay in their own lane but provide that, that shared functionality. So I'm wondering, like, if we're going to see even more of that. I think I've just I've seen some other companies. They're just basically trying to acquire, like crazy, to build this entire end-to-end workflow. So I am seeing a couple companies do that too.
Speaker 2:So it's, just it's interesting.
Speaker 1:How do you like, is there a way that you decide? I'm just really curious about this, honestly, yeah, you decide whether you're going to acquire a product, a point product or partner with a company like adobe. How do you? Yeah, we call it.
Speaker 2:It's literally that it's like build by partner. Okay, this is the solution we want to be able to offer. What's the path? Build by partner and pros and cons to each. To your point, some of it has to do with is this a technology that we can differentiate and build our own? E-signature was pretty clearly an area where it was like nope, that's been done.
Speaker 2:Yeah, that's fine, we're not going to build a better, more reliable e-signature infrastructure than Adobe. That's too big of an admission. And so it's widely accepted among the customers and it's very mature technology and that's a great way for us to bundle it and include it, and we've done that with background check tools. We've done that with all kinds of stuff. On the other end of the spectrum, when we did our approach to sourcing, when we did our approach to onboarding, we decided to make acquisitions because we identified companies who we thought really solved the problem nicely, really had built good technology, was very compatible with what we had. That was essentially what we would want to build, but already built, and so it was just like, hey, we could build it ourselves or we can make the acquisition and you're two years ahead of the game, which is a speed to market thing. So often, if you're in that question of buy versus build, it comes down to is the right company or product available on the market when you want it in a way that gets you to market quicker and that the economics make sense?
Speaker 2:The partnership is really interesting because on partnering we have a huge number of partners we have 500, some technology partners and our customers use a ton of that stuff Our customers on average use like a dozen partners, and so they enjoy a lot of that. But when do we decide to say we're going to do a more targeted, more strategic partnership? A go-to-market like we've done with, say, grayscale or Pave or Adobe or Checkr or on and on is when we have an opportunity to create a win, meaning a benefit for the customer. A benefit for the customer, a benefit for the partner and a benefit for us all. Through these partnerships we can add value, we can make the buying process easier, we can save you money, we can put it all together under one umbrella, we can deliver it more efficiently. That's a great win. And so we look for those opportunities and increasingly we're now a one-stop shop for recruiting technology through those kind of more strategic go-to-market partnerships like that.
Speaker 1:Understood, and so my assumption would be that, in addition to an applicant tracking system and I'm curious if you could validate this or your thoughts I would assume sourcing would be the next most valuable, the next biggest value proposition. Is that accurate?
Speaker 2:Yeah, sourcing is where a lot of the money is for sure, especially historically right, because companies would spend a huge amount of dollars on everything from LinkedIn to ZipRecruiter to Indeed, to Seek, to staffing firms and recruiting agencies and on. So there's a huge amount of dollars there. The issue for us the reason that those dollars go to those places is because those places offer access to candidates that you can't otherwise get, and the question that our customers have is are they spending that money efficiently? Are they aiming their dollar at the right source? Are they getting the right bang for the buck, and is it strategically aligned with the type of hiring they're trying to do, or are they actually spending it somewhere that they could be spending it more efficiently? So those are the kinds of questions our customers are looking to answer.
Speaker 1:So one of the things, too, you mentioned is that you're talking about doing more sourcing natively within Greenhouse. How does that work with LinkedIn? What is that workflow?
Speaker 2:Yeah, so again, we're not going to replace LinkedIn. You're never going to have. Linkedin has basically everyone's professional profile online. It's like this one-of-a-kind asset in the world. It's fantastic. Many of our customers, most of our customers, use it, and so the question is, how do we help them use it better? How do we take advantage of that connectivity? So there's a program called LinkedIn Recruiter System Connect.
Speaker 2:We've been longtime leaders in that space. We've got a fantastic integration. You can send in-mails, which is LinkedIn's kind of proprietary messaging system, to a candidate through LinkedIn. It shows up in Greenhouse in their activity feed and vice versa. So it's like a really nicely integrated experience as a recruiter. You don't have to worry about data being out of sync between those two. I know, if I come across your LinkedIn profile, that you're already in my Greenhouse database and vice versa, so that all works great.
Speaker 2:There's a financial component to it that's quite separate. Like customers today, they buy their LinkedIn seats from LinkedIn. They buy their greenhouse from us, then they go in and they enter the program keys and then the tool gets connected up and we aren't involved in that at all. We definitely hear a lot from our customers that they're starting to feel like LinkedIn's a bit pricey and they worry where does this go from here? Like, how much? How many more years are we going to keep giving so much money to LinkedIn for access to that database? When? What more are we getting out of it? And so I think we're starting to see some pressure from customers on LinkedIn to because it's so expensive.
Speaker 1:Yeah, I am seeing that as well. I'm seeing that as well. I'm seeing that as well, and I think LinkedIn's pricing strategies is interesting and they've really stuck to their guns. Right, they're sticking to their guns. They're really not budging.
Speaker 2:And God bless them. I have a lot of, I have a lot of respect for them. I've worked, we were very closely with LinkedIn, and they do occupy this really unique space in the ecosystem where they can command that sort of premium, monopoly pricing. And so they do, and they're good at it, and so you hear this pressure, but you don't yet see anyone leaving it because you still can't get away from it fully, and so I'm just more saying it as observers, like I wonder where that heads, I wonder how long they're able to maintain that or what the pressures may end up being.
Speaker 1:I don't know. I think people are looking at a lot more data sources and looking at using different sourcing technology, and also there's this feeling too that in some cases, in-mails might be a little oversaturated. Anyway, that's a whole nother create an opportunity if and I'm not sure I would want to see more data on that specifically to the extent that emails or whatever, just different data sources, different outreach strategies, could potentially increase response rates and then allow you to bring down the number of linkedin licenses you have. So you have a more, a better split between in mail and email yeah, I think, and ultimately not to just say it's about LinkedIn.
Speaker 2:It's about more than that. But, excuse me, ultimately, maybe where we can leave this topic is, I think, for a customer with a budget constraint and this mandate to try to be more efficient and consolidate systems. What they're asking us is not just about oh, can you compare greenhouse to another ATS and say, okay, I'm paying 23 grand for greenhouse and I got a pitch from another ATS for 18 grand? There's $5,000 in there. No, but you're probably spending like 200 grand on recruiter agency fees and LinkedIn seats and indeed, ads. And like, how do I affect that overall budget? How do I use your tools to be much more efficient and don't worry about the ATS budget, which is like 3%, 4% of my budget, but all my sourcing fees, and that's where I think you talk about consolidation of budget.
Speaker 2:Like I had a conversation with a customer around that very topic. It's like let's show you the overall business case. If you come on to Greenhouse, how do you actually spend a whole lot less money? How do you take a zero out of that bill? And then the ATS is like a drop in the bucket compared to where the real dollars are, and so we're seeing a lot of that pressure on those companies in that space too.
Speaker 1:And I think we have a lot to say about how customers can do better. Yeah, I think that it also is a mind shift for the customer to for companies that are buying to really think about this budget consolidation, because they have their separate budget line items and it's been done a certain way for a very long time and getting them to rethink is particularly coming in. As an existing vendor that's expanding services, it's you're starting to get them like oh, we don't just do this, like we can also package it with this, this and overall, like the pricing is a lot more competitive. Right, it's interesting.
Speaker 1:Yeah, let's move into ai, and I think we've had a couple of prior conversations on ai and talent acquisition, I think primarily concerning more like top of funnel activity, particularly when it comes to number of applicants and how companies are leveraging ai for resume matching and and potentially qualifying to leveraging AI for resume matching and potentially qualifying to some extent based on resumes and whatnot. But I'm curious are there any? Let's just go through a quick update on the use cases that you see are in the most demand and the use cases that are like the most technically feasible, like they're the ones that people are really using right now, and then we could just maybe move on from that into okay, what's the future really going to look like?
Speaker 2:Yeah, yeah, so it's a great question. Look, the one hot button question here is using AI as like a matching algorithm at the top of the funnel to weed out or select in who gets to the hiring manager. And the reason I say it's a hot button issue is I was just having a chat on LinkedIn. It happens almost every week. Someone raises this question like the ATS is filtering me out. Right, there's an AI in the ATS and when I apply to jobs like I'm not getting through and the AI hates me, and then me and all the other ATS companies jump on the thread and we're like we don't do that.
Speaker 2:That's not how our product works.
Speaker 2:We don't use AI in a filtering capacity and a matching the top of funnel capacity and like candidates are persistently worried, that's what's happening and I think there's reasons for it, very understandable.
Speaker 2:But that's always a big hot button issue, both because it's the thing that candidates keep worrying about because they're not getting through and they assume it must be that the machine is unfairly filtering them out, and on the other side, the customers keep asking for that feature, like they actually want it, until they realize what the risks are and they realize, oh, got it. So there's regulation around use of AI and hiring decisions. That places us at regulatory risk. There's bias there's proven bias in these algorithms that jeopardize our ability to actually find the right talent. These algorithms routinely mistake facts confidently so-called hallucinations. There's a lot of problems with that, but it's the number one thing people want is they're awash in candidates and help me filter it down, and we don't do that. And yet it's the one thing that candidates keep over and over imagining is in the way of them and their dream job. It's a bad situation.
Speaker 1:This is not going to be a perfect analogy, but I think it's going to make sense to folks.
Speaker 1:There are so many other ways in terms of how ML is leveraged and not even ML, but that we use technology to filter. I think everybody likes the fact that their inbox filters out or is able to put together priority messages versus spam. Nobody these days wants to live without that feature, so it's just like this thing is. The reality is it's it hurt. It could be an emotionally painful thing when you're not picked for a job, and I think the reality is people are not going to like it, whether it's a person reviewing it or a technology, but the reality is that the technology is going to get to a point where it's evaluating the profiles more accurately than a human will. Now there's risks, right, and there's risks I think you had mentioned before, like of it compounding or whatnot, and everything you said about the hallucination is true and there's these issues, but in my opinion, this is just going to be how it's done, like you would hope so, and you would hope so, and you would think so.
Speaker 2:So I think it's a smart bet to say it'll get there. It's very much not there now, yeah, and so the whole question is what can we do? What can we do now? And there's a lot of stuff to say there. We should talk about that, and then how will we know when it is the right time or to what degree can we bring, can we invite AI into the loop on human decision-making, and what's the right way to do that and what's the path there. So to me, those are the questions we have to pay attention to.
Speaker 1:Yeah, yeah. I think that a lot of people are talking about resume matching. I think there's companies now that are getting more into screening calls. To me, I don't see any reason why phone screens in the even over the next few years are really necessary to be had with recruiters. In my opinion, I, I, I just don't, I just don't see it. I really don't because Because at the end of the day, it's like people First of all scheduling phone screens with a recruiter when you have a full-time job it's not easy, it's not easy and the ability to just use a system to get the information that you need quickly and submit the stuff that you need to submit, I think is a better experience, a better candidate experience.
Speaker 1:To some extent, I think it's like a bit of a mental shift for companies and for candidates. But I think we're going to get to the point where people are going to actually see a huge benefit to not having to speak to that recruiter on the phone screen. At the end of the day, too, they probably want to speak to the hiring manager, but they don't necessarily want to speak to a recruiter, and there's so many examples of industries where you needed a salesperson, for instance, like, think about like stockbrokers, right, and now you could just do trades online all by yourself, and I think it's like that's the direction we're going to. So I also think that for me, like phone screens, I think it's going to be table stakes that stuff is done through large language models. Like I don't see any reason why it wouldn't?
Speaker 2:It's an interesting point. I think you're probably right. I think it's probably a safe bet. That is where it's headed. I may not be as optimistic as you sound about how good that's going to be. I think you're right, that is probably that could happen. But I think, if anyone's ever spent time with the chatbot at their airline or the phone company, I don't think anybody loves it and I think it's obviously more efficient and there's good reasons why those companies do those things. But I do think it comes at the cost of the experience to the end user and I think in this case, when you talk about candidate experience, it's absolutely true that the ability to do the interview on your terms, on your schedule, at night or off hours is a big benefit. But I think people struggle to get the same feeling out of talking to a computer that they get out of talking to a person and I just worry there's something lost in that process.
Speaker 1:I think there's a balancing act and I also feel like it's going to be a gradual shift. And I also feel like it's going to be a gradual shift, yeah, but I think it's like think about how many phone screens where you qualify somebody out in the first five, 10 minutes, like whether, and even if it's on the JD about anything related to salary or experience or commute or whatever else. There's just so many things where it's just like why did everybody take their time scheduling yeah, manually and putting stuff into the system, doing a reschedule, take time away from work or things I think you'd be working on other stuff and it's there's. That is just a huge inefficiency in the process and it also that's expands the time it takes to hire. Just doing this coordination and qualification, that is not. I don't think it requires a lot of mental force.
Speaker 2:I think a lot of the workflows and processes absolutely can be highly automated without losing a whole lot. I think the phone interviews and kind of the interactions will get to your point, will get automated eventually, largely because of the kind of brutal logic of the efficiency of it and just like that math overwhelms any other concern. I don't think it comes at zero cost. I think it comes at the cost of something getting lost in terms of the experience and we're all just going to have to live with it. I don't know, Can I use a? Can I use a four letter word on this podcast?
Speaker 1:Yeah, of course.
Speaker 2:The term is in shitification, right. You've heard heard that in other contexts. It's this relentless focus on efficiency that works really well, but it comes at the cost of making so many of the experiences we go through in life just worse.
Speaker 1:And.
Speaker 2:I think it'll probably happen in phone screens too. Yeah, I agree with you that it's performing. At the same time, I think there's tons of ways where AI is already and can continue to make things much better. So I think I go to the other end of the process.
Speaker 2:When you're just kicking off a job today, most recruiters and hiring managers are sitting down and writing a job description and thinking about interview questions to do and thinking about what goes on the scorecards and how that whole process is going to work, and they don't do it very well.
Speaker 2:It takes too long, the content isn't very good, there's no continuous learning, there's a complete lack of consistency, and I think there's a world in which AI really helping solve those problems and make everything much better, because you're probably not the first person to write a job description for a data science expert or an accountant or a sales development representative, and so when you go sit down at Greenhouse in the future to hire that person, my vision is that Greenhouse can be a lot smarter at partnering with you on how do you write that job description, even what do you call it? What do you pay that person? What should you assess for? How many interview stages should you have? Who on your team should do which of the interviews? All of the things can be made much better with the amount of data that we have and the amount of intelligence that we can apply to that data. So I do think there's a ton of promise in making things better through AI and machine learning that we're actively pursuing.
Speaker 1:Yeah, absolutely. Do you have a hard stop in two minutes, or can we run a little over, because I have questions?
Speaker 2:I do. Unfortunately, I'm going to have to run.
Speaker 1:Okay, yeah. So I think what you're talking about is like taking role requirements from hiring managers and then basically creating, maybe even doing some like automated prompts to do, ask follow up questions, to put together a job description. Like that stuff is happening. I think from there it's also there's some cool interview note takers. That's pretty basic stuff. If there's a way to train that to where it's like showing, if that can help companies evaluate consistently right, Because we might write different types of notes for different candidates and if there's a way to consistently extract the information so that you can have a more accurate comparison, that's interesting.
Speaker 2:Yeah and look. I think ultimately, the promise for a SaaS tool is not about greenhouses, not about ATSs, not about hiring any SaaS company today. I think the promise that you have of the role that your product can play vis-a-vis the customer is tremendous. It used to be that the computer screen was like a form and the user would fill in the form and hit save and store it in the computer and that was what the computer did and, like the first version of Greenhouse was like a nice version of that when. And that was what the computer did, and like the first version of Greenhouse was like a nice version of that when we are now and where it's going.
Speaker 2:I think for SaaS businesses of all types is your product can play these two really important roles for your customer it can be a concierge and it can be a coach. A concierge is someone who does stuff for you, makes your life easier. You give it a simple request. It intuits what you really mean, helps you do it more efficiently and better than you could on your own. And a coach they give you feedback, they look over your shoulder, they make you do it better, they help elevate your game. And I think SaaS tools armed with tons of data and with AI and machine learning, can play those two roles much more effectively. I think if you think about the future of where AI is headed in SaaS, it's in playing those two roles better.
Speaker 1:Last thing I'll say. It's interesting, though, is that it seems that you think, in a sense, that help with evaluation is actually a more realistic use case and tell me if I'm wrong more realistic use case for ML than actually matching in an early stage qualification, which is a mental mind F. I would not use that word, but it's just that's interesting to me. Did I say that?
Speaker 2:Yeah, because I think, in my formulation of it, it's there with you and it's helping you do your job better, either by taking stuff off your plate or by helping you imagine or do things in a more elevated way, versus putting the person out of the loop and replacing you with a machine which I just think can go South in a number of different ways, some of which, as we talked about, are inevitable and are just going to make things more efficient, but worse, and other ways are like ah, they may be still risky and may create more problems than they solve, and so it may take longer to get there but yeah, yeah, that makes a lot of sense.
Speaker 1:So this is a lot of fun, daniel, thanks for coming back on the show and sharing all of your insights with us. Always a pleasure, great conversation. Thank you, all right, thank you Bye.
