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People don't spend enough time thinking about the onboarding plan for a role before they start hiring for a role. And if you do that, you can both really radically improve the candidate, experience your ability to sell and close that candidate and you'll make it better. I am rubbing shoulders you at higher suites and we are sourcing automation software that helps companies hire the best talent at me. And follow me now only Jeanne who want to keep an eye on this.
OK, so today we're coming may may eventually see you at Liver Liver as a big excuse by, what is it, 20, 500 companies in the world. Right? Three thousand. Now, face to face my numbers.
So thanks a lot for joining us today. We'll be talking a lot about tools, obviously about levers, vision on hiring, and also about his own experience as a funder who as CEO and then CTO and then CEO again. So thanks a lot for joining us today. Can you tell us more about Leever? Absolutely.
So thanks for having me. Leever is an interesting company in our space because we got started as a founding team without a lot of experience in H.R. Tech, my background and my other co-founders backgrounds from Google, Zynga, other pretty big companies. And we noticed that hiring was a huge part of what we and our our friends were experiencing as challenges and got to doing a lot of research about what were the challenges facing companies and discovered that talent acquisition was actually the biggest problem that many companies now faced.
And that's what inspired us to start the company. So we were going in with a really open mind about what the future of recruiting needed to be and what the future of recruiting platforms needed to be and really tried to learn from the environment, see what great companies were doing, and then build a software platform for them.
Makes sense. And what's your vision now? What have you achieved over the past eight years and what's on the roadmap for the next eight years?
Yeah, and so like I said, we were definitely looking to build a platform that was resonated with what great companies were already doing when it came to recruiting. And what we discovered as we really dug in was that a lot has changed about the world, frankly, and that's what brought a lot of challenges to companies and why they were having trouble with talent acquisition. And this is still relevant today. So what are the key themes? We noticed is that companies weren't really looking for a tool just for attracting applicants, even though that is the name of the software category.
Applicant tracking systems is the traditional name. But ironically, companies didn't want to hire applicants very often. In fact, they were typically going outbound to find talent from a variety of channels. They're really taking a multichannel approach, a lot like what you see marketing teams doing. And so it was a really interesting evolution of the talent profession. And the software, frankly, didn't keep up. And when we looked at that, we realized that what companies need today is a system which is built to integrate an applicant tracking system as that is still an important source of hires, as well as sourcing tools, nurturing tools, the ability to do internal hiring, going and getting your team mobilized, doing referral programs, then either passive or active referrals, getting people who might want to take a job right now or also those who you might be developing a relationship with over a long time.
So there's always been built for the modern recruiting reality, which is that hiring critical hires, hiring key talent is often the limiting factor of ultimately the success of many companies today. And we've really built the software platform that is ideal for those companies to craft whatever talent strategy they have and really build a software platform that is a lot more open ended and supports all the different channels for recruitment. And looking forward, I think that the next vanguard in our category is truly being data driven.
So this is something people talk to a lot. And the reality is that a lot of times talent teams need a lot of help and they don't necessarily have all the answers when it comes to how to be data driven. But they're really motivated to do it and they understand that it's how. They'll be able to build credibility within their organization, so it's really our mission to elevate leaders and the way that we think about it is we want them to have the forecast of a sales leader.
They should have the data to look at what they're doing in their talent organization, refine those practices, and therefore be able to forecast with clarity their ability to hire in the future and to hit hiring plan with a given amount of resources. We also want to elevate them to have the reach of a marketer so marketers don't just wait for people to show up. A lot of the job is going out and building talent pools, building the relationships with future pipelines for goals that may be coming down the road or those evergreen rolls that you're always hiring for.
And that's something that a lot of talent teams know, that that would be really valuable if they were able to do that. But because they do it in advance and they don't really have a platform designed to help them do that in advance, they find themselves forced to use agencies. At the end of the day, which are, to be honest, a lot of times companies don't really believe that the cost of an agency justifies the value they're getting, especially when people may be in a role only for a couple of years.
And twenty, twenty five percent of that person's first year salary is frankly really exorbitant. So finally, we really think that talent leaders should be elevated by having the insight of a finance leader. So that's kind of how we think about their ability to articulate their own capabilities as a function and really engage in the discussion about what is the appropriate amount of resourcing to put on recruiting, given the other plans that the business has. A lot of times the recruiting team is overstaffed or understaffed for what the company really needs and tends to go through these cycles, which really slows down the overall effectiveness of recruitment and or leads to recruitment being over resourced and then overly costly.
So especially in today's climate, companies are really looking to operate efficiently and we think being data driven is ultimately the the answer as to how recruitment teams should be focusing their time this year.
In particular, you don't mention at all. And from a previous conversation, I think you don't trust that a lot. Right?
Well, truth be told, in a former life as a product manager at Google, I worked on Google Search and Image Search. And honestly, I is a great solution for a lot of problems, but it is specifically a good solution for specific problems and it is not a panacea. So for what it's worth, our head of product and engineering actually has a PhD in machine learning and worked on one of the earliest machine learning projects at Google that was targeted toward enhancing search, which is called Google Squared.
It was never released publicly under that brand, but it actually is what led to, for example, when you're on Google and you search for celebrity photos, like the way that those results get brought up came out of the work of Google Square. So between myself and our head of product engineering, I would say that we actually do have a pretty strong understanding of AI and what it can do and what it can't do. And in fact, it is actually excellent at enhancing search retrieval.
So what it's really good at is if you have a search problem and this applies to talent, by the way, if you have search problem and you want to be able to augment your data, let's say you have a well-known corpus of data and there's a high correlation between different characteristics. Sometimes you can make assumptions that can really aid in your ability to find records where you otherwise might not be able to. So that might help you to find candidates potentially within your database and rediscover them.
That's actually something that we do have within our product and we do believe is a good application of AML. But frankly, I am skeptical of it doing much more than enhancing things that are already existing features within the application. It's not going to it's not going to automate the ability to build a relationship. And I think that that's ultimately the most critical thing that lenders really always built around is the idea that what we're trying to do is connect human potential to meaningful work.
And humans, frankly, are this is a big deal, taking a job, building a relationship with the people you're going to work with for most of your day. That's an extremely personal thing. And interviews aren't going anywhere. People like interviews and ultimately hiring will continue to be human. So we really want to build the tools that we do, remove a lot of the manual work. They do automate things that ultimately are laborious and repetitive, and that creates the space for really pure human interaction and building those relationships.
And so while I do believe that there are some very specific features that. Can be incrementally better with an animal that's really the value, it's not an industry where I believe that it's going to radically alter the economics or the way that we do recruiting. It'll just make things incrementally better.
Yeah, and what you're seeing is that ATSDR slowly evolving into what's probably closer to the category, naming CRM today and then more and more CRM and share the same features like nurturing the database, being able to send email sequences, et cetera, et cetera. Right. Yeah.
I mean, honestly, our belief is that there is no difference and that the difference is largely just kind of a historical accident. So if you trace it all the way back to let's talk about it, even before software was a category, the way that people did hiring looked shocking, like Azziz worked today. So when you go back to a time long ago, it's actually not that long ago. It's like 40 years ago before we had enterprise software for this.
What people did is they put an ad for a job in the newspaper or in the classifieds section. People from the local area would see that ad and they would send in their resumes and then companies would look at those resumes. They'd move them from one state to another. And then that really, honestly maps to kind of our stages today. Ultimately, they'd make a hiring decision, move those resumes into a filing cabinet for all the people that they hire with a resume, for the person they do hire to a different filing cabinet and never look at those records again.
And that's just how people hired. Then Azziz came along and they did resolve a problem, a really important problem. You may or may not remember this, but the terminology in the 90s a lot of people were using was the paper overload problem. Computers were really just getting rid of paper. That was kind of the goal and that was great. Honesty is a huge step forward. Moving from filing cabinets to databases is actually a radical and really important innovation.
And we went from what I just described, to a world where people would post a job online on a job board sounds a lot like the newspaper classifieds. And then people would see those job postings. They'd submit a digital resume, which shockingly, it still looks a lot like a piece of paper. And then people would move those digital resumes from one state to another, a stage in their 80s, and then ultimately archive that with some sort of archive reason or disposition for why they didn't want to hire that person or why they did hire them.
And that's what it is. It's honestly just a electronic version of this paper resume process. And that's important. And frankly, it is required by law that for equal opportunity employment, you accept applications under most circumstances from pretty much anyone. And you look at them and there's various regulations about how you enforce that fairly in various states and various jurisdictions, various countries. But ultimately, that's now baked in to how we think about fair employment. Until you do need an it is a critical set of features, but that's really what it is.
It's a set of features. It's not a platform. And when you think about CRM, it's also a really important thought. It's the idea that you're building relationships with people over time and you want a database of all those people in the terminology of, say, Salesforce, it's contacts. That's how they talk about people. And you have different records which represent those people's relationships with you, which in Salesforce as well as whatever is called an opportunity and salesforce.
It's thinking about that as a opportunity to close a deal. In the case of Leever, it would be a job opportunity, kind of handy that the same board works for both. So we think of it as if you use the CRM data model, which is how lever has been built from the very beginning with this concept of people, contacts and particular job opportunities happening at particular times, then you can actually build all the features on top of a CRM data model.
So that's actually what levers done. And it really is a unique take on the market because what other approaches have led to typically as you start with a product and then you build a separate CRM product, it's not actually integrated very well at all. And typically you have a really difficult time getting everyone within the organization to be fully in the loop about what's going on with your relationships with candidates, because they only have access to data. They don't have access to the CRM.
And I think that vision is shared by a lot of people in the industry. So there is definitely some evolution going. And we're seeing there is the sense I mean, ultimately we think that this isn't a far cry and people have used this word before. We think the concept of combining AIt's and CRM is something we refer to as talent relationship management, just like the analogy and CRM stands for customer relationship management. I think it is kind of. Useful to start defining this term of talent, relationship management or TREM, because it really helps to tell the story about how this is the evolution where you bring together all the capabilities of an eighth and a CRM into something that's actually new and more valuable because it is the combination.
Can you tell us more about your own experience as a funder, know how you build the team, how you studied? I think you study lever using and the JS framework that you created. Right. It was the leader of that. Can tell us more about the beginning story. Sure.
Happy to. So there's definitely the two sides, as you allude to, both the sort of technical side that I kind of started down the road of building some interesting new technology to build more collaborative enterprise software and then also the understanding of the talent market and where that was going. And so I ultimately think that the best innovations typically are a mix of a really great understanding of business and value that you are providing to ultimately your customer, your users, as well as thinking about the technology that enables you to do that better than anything that's been before.
And so one of the things that I really strongly believe this is for context. Back in 2011. Twenty 12 when I started down this road, was that ultimately all enterprise software is moving to a very different reality where real time collaboration is expected. I think that there's been this interesting progression of technology where when you look back far in time, we've gone through centralized and decentralized phases of innovation. So when you go all the way back to the very beginning, computers, we had these giant computers that filled rooms that were used for business, the very first computers used for business.
And there was one computer. So we didn't really have a sharing problem because there was only one computer and everyone use the same computer with some. Either there was one programmer and so they took all the punch cards from everyone. And that's how we coordinated or there was time sharing. And then later more people on to use computers. And so many computers became the thing that companies use. But typically you still only had one mini per department around this time.
People also were really developing a lot along the lines of the Internet. And that was mostly kind of in the research world. But it was starting to be realized that by email was really exciting in businesses as well. Not a joke in Andy Groves book. If you read high output management, it's shocking. He dedicates basically an entire chapter to how email is awesome. It's a good book, by the way. And then from there, what we saw was that even more people, a lot of computers.
So PCs became the thing because everyone wanted a computer. But then exactly at the same time, there was an incredible challenge of how the heck do I share information? So you actually saw a lot of people printing stuff way too much. In fact, usage of paper increased rather than decreasing. And the initial PC era and Ethernet became a huge, important technology at the same time as PCs really coincident with it, largely because people immediately realized that once everyone has a computer, networking is incredibly important, because now the problem is that people having access to computers, the problem is now how the heck do we get all these digital files shared among all these people at different computers?
So Enterprise on prem software really helped to solve that, where you moved to a server that was hosted by enterprises internally, typically a mainframe that then people could connect to and have all their files in one place. But boy, that was a huge overhead cost. And having every company have this incredible CIO department with tons and tons of people just to manage the operations of all these networks and computers was extremely costly. So cloud software came along and said, great, we can solve that, we'll just manage it for you.
So there are many evolutions of this model of first of all, we have everything in one place with mainframes, then everything distributed with PCs and networking, which is a huge pain to coordinate. And then things came right back together with cloud software. And so now we're in a world where things are centralized again, which is excellent. But the challenge is that you want to provide a really great editing experience for the individual that's using your software. So the greatest editing experiences are fast and fluid.
They're very responsive to your input and that's actually really challenging to do on the Internet because of the latency the server that you're interacting with. Isn't it physically different place than you are? And there are actual physical limitations, like the speed of light, the speed of the electronics that are switching and servers and just the realities that nothing's ever going to be perfect. So at a minimum, you're talking a few hundred milliseconds, so a fraction of a second for you to get from yourself to some sort of centralized server.
And that's actually No. Well, people can feel the difference between something that's 20 milliseconds from when you hit a keystroke to seeing it on the screen versus 200 milliseconds that's observable. So you have to do things locally within the browser window, for example. And that leads you to really interesting challenges where you're editing a text box, the text boxes on your screen, on your computer. But when does that get trued up with what other people see and how does that happen?
And how do you make sure that if two people want to edit the same thing at the same time, they're not stomping on each other's work? There's actually been a lot of research in this area. There's a couple of really great models. And the model that Google uses for Google Docs, for example, is called Operational Transformation. And so this is a technology that allows you to have real time collaborative editing of data and that ultimately allows you to have really engaging experiences where people feel like what they're editing is right there in front of them because it is and other people can see what they're doing in real time.
And you, as someone editing, can see if someone else is editing. And this is a really fundamental concept that I believe is going to be present in all enterprise software. And already we've seen a lot of movement in this direction, but more and more so we're going to be seeing more and more real time collaborative editing just be the default. Just like now people expect they can search in every application. You'll expect that every application is real time and collaborative, whereas today that's still a mixed bag.
So that's kind of the technology story of liver. And that may sound like a bit of a different angle, but I do actually think it's really relevant to recruiting specifically because when you think about recruitment, it's a team sport. You have a hiring manager, you have a recruiter, you often have a coordinator that's helping to talk to the candidate. You've have a candidate. You have an interview panel that consists of a number of people. There's typically an approver within your team and or finance.
Sometimes there's a chain of approvals going up multiple steps. So when you really break it down, you're like, boy, to hire one person often takes something between 10 and 20 people. And it's not necessarily always real time collaboration, but some of these steps are. And for example, one of the cool things you can see and lever is you can watch people write their interview feedback in real time, which is pretty neat. And honestly, a lot of recruiters have told me they really appreciate it.
And that's because we've built on this model, that real time collaborative editing just should be the default. Everything should work that way.
And you have that idea before you launched between the Third Bitchiest and Leever, which was first, you know, I'd say the idea is built off of each other, frankly.
So the framework idea did come out of just my observation of where I felt enterprise software was going broadly. And I do think that that is something that has proven out to be true. And as we look at other applications, this is a broad trend that many people have really embraced in their software. And it's a lot more table stakes today than it used to be. The reality of Leever was looking at what's the business problem that people are trying to solve.
I didn't want to start a framework company that other people would use as much as I really wanted to start a product company that really solved the problem for users. It understood what was a challenge and provided business value. And so it kind of happened at the same time, actually, we just sort of did both.
And if we took a bit the A players and you can then both questions. But what's your advice for CIOs and trying to hire a players to perform this for the team?
Yeah, well, luckily I have had to do a little bit about this and sometimes I have succeeded. Sometimes I failed. I think we all do. And we have to admit that to ourselves. And so one of the things I would say is just do a retrospective. I think this applies for all roles, but it's kind of hard to do. It's kind of hard to be honest with yourself. And I see a lot of people go through the process of bringing someone on.
They don't want to admit that that person was the wrong hire and it takes them longer to let that person go than they want is the common story in management and then have to backfill that person and bring someone else in. And a lot of times I see people make the mistake of moving too far in the opposite direction. I think I've made this mistake myself where you bring someone on the team and then for whatever reason, there's a challenge and it wasn't quite the right fit.
And you bring someone else on. And a lot of times you look for the opposite of the last person. And that's often not actually what you need to do. A lot of times what you need to do is think about all the things they did really well. And I remember thinking about, for example, Quito's you're thinking about I bet you've done these retrospectives or when there was a production problem or when a product launch is complete, whether or not it went well or a sprint is done.
You have a rigorous process usually of doing retrospectives because you learn a lot from it. I think it's a great thing to do. Once you do a hire, you can do a retrospective on how that went and what you like. And also, you can do it when someone ultimately either left the company of their accord or you had to fire them. You can look at that and go, what did I do right? What I do wrong? And I think you'll discover oftentimes, if you're honest with yourself, that a lot went right and you shouldn't lose sight of that in your next hire.
You should just identify those key things that you want to be different. And that kind of ties into something else I would talk about, which is people don't spend enough time thinking about the onboarding plan for a role before they start hiring for a role. And if you do that, you can both really radically improve the candidate, experience your ability to sell and close that candidate and you'll make it better. So we had never had a format that we used to write job descriptions in that's actually pretty non-traditional.
And we call it the impact description because job description really isn't getting at the heart of what you're trying to do. You're not trying to hire someone to fill a job. You are hiring someone because you want them to have an impact on the business, on the team. And this applies to all roles. But I think in particular, it's really, really important to do for the first time you hire a role and you really want to think through.
OK, so I want to have someone join my team. There's going to be something in it for them and there's going to be something in it for us. And what are those things? So I encourage people to start off by describing four sections. The four sections are what are they going to own? What are they going to teach? What are they going to learn? And what are they going to improve? So Owen is effectively what's their responsibility?
I think it's useful to use the word own because it creates kind of an ownership mindset, which I believe to be a more effective phrasing than responsibilities. But largely it's what's this person's job ultimately? What are they responsible for? What are other people going to expect them to do for the company in terms of domain? The next sections are probably a little bit people are probably a little bit less familiar with filling these out. So what are they going to teach is a way of talking about their skills that really puts you in the mindset of how is this person's skills going to enrich and raise the bar at my company?
So teach is all about what do they already know that they can bring to our company and make our team stronger? How can they raise the bar by teaching us something or teaching their colleagues, teaching their person their reporting to teaching the people that report to them to really thinking about how they will up level all the talent around them? The learning section, I think, is really important and I frankly almost never see this in a job description from anywhere else.
And what it's about is when this person joins your company, they are thinking, I want to join this company for a reason. Maybe it's maybe it's equity. Maybe they're thinking about this might be really valuable one day. But actually, most people are thinking about more than just money. Most people are thinking about the environment. They're thinking about what they're going to learn. The best hires are typically people who have a growth mindset is something I believe.
And so you want to bring people in that are taking the job because they're going to learn something.
It's a challenge for them. And those people, in my opinion, are going to perform stronger, be more loyal to the company than anyone else. So ultimately, I think it's really important that you you consider what might be in it for the level of person that I'm looking for is actually when you compare the teach and learn a really great way to understand the level of the role, I think a lot of times people hire someone to hire to low level and really thinking through well, they should actually come in knowing these things.
That's really important. They should be fully capable of owning this level of work and responsibility and independence. They should be able to already know these things and teach people these things, but they're still learning these things. I'm comfortable that they don't know everything. I'm comfortable that they're still learning some things. And these things are things I'd expect them to learn. That together gives you a really clear picture of someone's level. It's super useful when you're thinking about exactly what title and which level to use and then the final section improve.
This is very much kind of with the mindset, if you're familiar with using OK, it's thinking about similar to the objective in an OK are what is the difference, what is the difference that I am trying to affect with this higher that I expect them to bring to the company. So right now, how are things in the future once this person works at our company after six months or a year, what's going to be different? How can I describe that?
And I think that's really motivating. If you have a very tight story on what can they improve, it'll help your interview panel to visualize. Can this person do that? It'll also help you as a hiring manager to make your final decision because you're going to encounter people and no one's perfect, even the very best talent. And you have to ask yourself the question, what am I looking to do here? And can this person do that? Can they have that impact?
So I think that that. Ultimately, it is the most important part of it that you really need to do, answer those four questions and then the final thing we do is we set really clear expectations for what people are going to achieve within their first month, their first three months, their first six months and their first year. And we really write that out as a series of very specific objectives that we expect this person is going to be able to do and a little bit of information about how that person will be set up for success, especially in the first month.
There's usually some amount of context gathering or training. It's really good to outline that for people. And people really appreciate seeing that you're being thoughtful about how they'll be able to ramp up and how they'll be able to come up to speed and put themselves in their shoes. That's something that's really unique. And people normally don't get that experience in a new job like this framework.
No one is. What are they going to own, teach, learn, improve and how they can ramp up and what they should achieve should copyright that.
I don't want to copyright because I want everyone to use it. It's been so useful for us in it on frankly, every candidate like, boy, why doesn't everyone do this? Or like, I know everyone should do this. Cool. Thanks a lot Nate. Thanks for that.
Will spread the word on this is doing great today and listening Dutch. Thank you Chad. Thanks for listening. That still the end. If you're still with us, it's probably that you enjoy the players. Eight players is brought to you by myself and higher suites. Well, building a sourcing automation software. And we already helped nine other tech companies hire the best times to know more about us. Go to W-W the hire suites dot com or you can add me on LinkedIn.
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