Storytelling About Cadient Talent With Jim Buchanan
Welcome to the Use Case Podcast, episode 169. This week we have storytelling about Cadient Talent with Jim Buchanan. During this episode, Jim and I talk about how practitioners make the business case or the use case for purchasing Cadient Talent.
Jim is an expert in all things talent acquisition and hourly hiring. His passion to provide managers with a constant pipeline of quality candidates really comes through during the podcast.
Give the show a listen and please let me know what you think.
Show length: 27 minutes
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Jim has been involved in the talent acquisition industry for over fifteen years and has seen both changes and advancements in the recruiting process. The dream of Cadient Talent was conceived several years ago as he saw a great opportunity in the distributed hourly hiring sector.Follow Follow
Welcome to RecruitingDaily’s Use Case podcast, a show dedicated to the storytelling that happens, or should happen, when practitioners purchase technology. Each episode is designed to inspire new ways and ideas to make your business better as we speak with the brightest minds and recruitment. That’s what we do. Here’s your host, William Tincup.
Ladies and gentlemen, this is William Tincup and you are listening to the Use Case podcast. Today, we have Jim on from Cadient who we’re going to be talking about the use case, business case for how practitioners justify working with Cadient. So without any further ado, let’s do some introductions. Jim, will you introduce both yourself and Cadient?
Yes. Well, William, thank you for having me on. It’s great to be with you again. I’m Jim Buchanan. I’m the CEO of Cadient. I have been in this industry for a while in various roles, mostly financial roles, but I’ve been working with HR companies in the talent acquisition area for many years. We saw an opportunity to do something a little different and to start Cadient, we carved a talent acquisition business unit from a larger workforce management company who was not putting much emphasis on the talent acquisition piece. So we did a carve out, which if you’ve never done one, it’s pretty hard to do. I didn’t realize that at the time. A lot of people tried to tell me how hard it was, but I thought how hard can it be? It’s pretty hard.
Yeah, it’s not easy.
But we got it stood up and we renamed it Cadient. What it is William is we have a focus really on hourly employees and helping companies that have a large contingent of hourly employees, particularly ones that have them distributed across the country and local hiring managers making hiring decisions. It’s a support system, an ATS and onboarding, and decision support system to help them make better hires. 60% of the U.S. workforce is paid hourly. It’s an area that we felt has been neglected in human capital management, particularly in talent acquisition.
It’s an area that we felt there was a big need that companies should do better in that area because the turnover is very high among hourly employees. It’s been a great opportunity. It’s been very enjoyable for me to lead this company. The pandemic happened and that’s been a speed bump that everybody has to deal with, but it’s been a lot of fun. It’s a big opportunity and we think that we can create a lot of value.
Love it. So what markets are we trying to go after? Because ATSs can be built a lot of different ways and we’ve seen it, obviously you and I have seen it, cut kind of hourly or professional, or those that kind of go after the staffing market or those that go after to the corporate market, global ATSs versus domestic. I mean, we kind of keep cutting it a million, jillion different ways. But what is your sweet spot?
The sweet spot really is the hourly market. Again, if it’s a distributed hourly workforce, it really… That’s where we really shine. We have two offerings on the same platform. We have a solution for salaried or professional employees and we also have a solution for hourly. So they’re different modules. They work on the same platform. They share the same platform. But you and I both know that most of the ATSs that have been brought to market are designed for the professional hires and they’re designed for recruiters to use and people who get on the system and use it eight hours a day, maybe more than that.
What we really see a need for and the market that we address is for those hiring managers, and sometimes recruiters, who don’t have a full-time job in recruiting. If you think about a local store manager, they have a lot of responsibilities of which recruiting is one. They can’t really deal with a very complicated system that has a lot of bells and whistles. So we offer a very easy to use system that local hiring managers can deal with. They’re only on this system a few hours a week as they’re going about doing their work, and part of that work is recruiting.
So it has to be easy to use. That’s who we cater to. We do have clients who use the salaried recruiting system. But there are a lot of offerings around that. There aren’t many that are designed specifically for hourly. There are more, a few more that are popping up on the market, but by and large, most of these systems are designed for salaried and they’re kind of adopted to an hourly situation. Some of it’s not really natural. So we address that from the ground up, the hourly hiring.
I love that. Ease of use, as you mentioned, it’s very important, especially as you also mentioned, they’re not recruiting full-time. They’re in it just a few hours a week, some days, some weeks probably heavier than others. So it’s burstable. What are you displacing? I don’t want to lead the witness. But how are they doing it currently?
Well, the ATS market is in a state now where most people have an ATS of some sort. There are a few greenfield opportunities, but you don’t see nearly as many as we did several years ago. Most people have decided they need an ATS. So there are a couple of things that happen in a displacement. One is that it’s a company that has a system that was designed for a very small company and they have grown and they’ve outgrown the system and they need a more robust system and a more scalable system, as one that we offer.
Then sometimes you’ll see just the normal replacement of the people that we compete against, the people who offer something similar to what we do. We all try to get three year contracts. At the end of three years, every client pretty much wants to do a jump ball and at least see what’s out there, see if I can do better from a pricing standpoint, or is there some new functionality that I’m interested in that I’d like to use into my system.
I mean, we all know that if we look at net promoter scores for ATS systems, they’re generally not that high. People just sign up for a term. At the end of the term, they’re looking to see if there’s something better. Sometimes we get introduced to companies who want to look at alternatives and we can win the day there. But I would say mostly we’re replacing systems that people have just outgrown over a period of time.
Could be proprietary, could be displacing other systems that they’re using. In any cases, are you displacing Excel?
Yes. Yeah, that’s a good point. Yeah. Some people I’ve put them in the homegrown category. Some people are still using Excel to track.
It’s proprietary homegrown.
I prefer Microsoft Office products.
When you onboard folks like this, again, when you talk about corporate recruiters, they’re in an ATS, they’re used to this, they’re used to sourcing and hiring managers and a lot of complexity. This isn’t that, clearly. They’re not in it full-time. So the ease of use, as you mentioned, is really important. But what’s your onboarding process for them? How do you kind of bring them into this new world of using a recruiting application that’s going to be easy for them?
Yeah, It’s a fully, I won’t even call it an integrated onboarding platform. It’s baked into the system and deepen the roots of the system. It’s not something that is bolted onto the ATS. So it’s a natural flow from you go through the hiring process, you find a candidate that you like, you can schedule a interview, you can go through whatever process that you want. You make a decision that you want to hire this person and you immediately click into the hiring process. So that’s a seamless transition into the hiring process. It’s configurable however you want to set it up, whatever workflow you want to use. Most onboarding systems would do that. It’s storing the records all in the same database. So it’s very easy for them to use. Once they go through it once, the hiring manager, he or she can really easily follow it.
I love that. So hourly is, reading and watching some of the popular press, is almost impossible.
So normally, you see a bunch of front of funnels stuff, you see background checks and all kinds of screening and assessments and things like that. But I mean, I’ve seen, locally here, I’ve seen Taco Bell, if you start today and get paid today.
So maybe not as many of those things, but so what does it look like? You’re in this world all the time. So your clients are dealing with this shortage of talent. How are they having to change kind of how they approach hourly talent?
Yeah. Some of our clients are under siege, William. Yeah, they’re having trouble filling open positions. They think their applicant flow has dried up. It has dropped, but they still get a lot of applicants. There are more and more applicants coming from job boards. But what we see is that an applicant who applies through a job board, it’s very easy to apply to multiple jobs at the same time. So they’re applying to a job with your company, but at the same time, they’re also applying to maybe 10 other companies through that one process, through an Indeed or ZipRecruiter or somebody like that.
So what they’re facing is they have to act with lightning speed. They cannot talk about weeks to make a hiring decision. You really can’t even talk about days. You’ve got to act within hours in order to get the top candidates. So really, our mission and the way that we help our clients with that is by this, I mentioned a decision support system that we call Decision Point. Decision Point is a machine learning system that evaluates candidate data against proven employee data.
So we look at the full cycle for 75% of our clients. We look at the full cycle from candidate through to hire. We look at for which candidates are you retaining the longest and we’re learning from that which… What did those people who were quality hires, what did they look like when they were candidates? Let’s go find more candidates who look like those quality hires and have the same traits and characteristics in the data that the quality hires, and machine learning is perfect to do that kind of activity.
So we can rate candidates in seconds. As soon as they complete the application, we can rate the candidate. We can give you a score. We score based on predicted tenure, how long will that person stay in this job. You mentioned assessments and other kinds of tests. We’re seeing those things being used less and less primarily because it adds to the time-
That’s right, that’s right.
To complete an application and-
Well, it’s a barrier. It’s a barrier for that hourly talent.
You’re going to ask me, this is what we had with software engineers years ago is we wanted to do a bunch of skills testing and all this kind of depth analysis to find out what they knew. It would just add more and more things. It’s like software engineers at the time are like, “Yeah, I’m not going to do that. You should go to my GitHub or go to my-”
“Stack Overflow and just look at my stuff.” If we don’t want to talk, that’s great. But they refuse to kind of do some of those things. Some of that’s softened a little bit, but I can see that in the hourly market. You’re going to add a step, if you’re adding a step, you’re probably losing a step with the speed. I’m so glad that you use lightning speed because I was thinking the thought, but I was also thinking about how do you gauge their interest because you’re right, that reply or apply in all of the job boards, including LinkedIn, it just makes it super easy to click one button and go, “Done. I’ve applied to all of these positions.”
I love the back part of this where you looked at the DNA of what works in the organization, DNA of the candidate and kind of match that up and then go, “Yes, this.” So that is, first of all, genius. Love that. How do you gauge their interest? I say you, how do your clients engage the candidate’s interest in actually working at Applebee’s or whatever the company is?
It’s a good point, William. It’s an additional step in the process. I mean, we really can’t gauge the interest. There are some ways that you can get a clue as to how interested an applicant is in working for your company. One is how long did it take them to complete the application. If they sat down and did it in one sitting, in five minutes, that’s some indication, that’s not something that you can totally rely on, but it gives you some glimpse of is this person really interested in this job or did they do the application over a couple of days. So I would call that the metadata that we would acquire in the application process.
But the real issue is that you have to communicate with that client. You have to have someone, apart from machine learning, you have to have a human being interact with that candidate to judge those kinds of things and ask those kinds of questions. So we’re not replacing human interaction. What we’re trying to do is to prioritize which candidates… You’re not getting as many candidates as you used to get, perhaps, but you’re still getting a lot of candidates and you’re still getting more than you can then properly analyze. You need a machine learning system to help you with that.
So let’s narrow it down to the top five that we think will… That have a predicted score to stay a long time on this job. They look like a really good fit on paper. Now, have your or hiring manager or your recruiter talk to those top five. Those top five are buried. If you got a hundred candidates, they’re buried in that hundred. If you don’t use data and don’t rely on data driven decisions, you may never get to those top five and you’ll settle for something because you need somebody on the floor, you need somebody in the restaurant or at the cash register. You’ll settle for something that is less than optimal, or you could have made a better decision. So your question about intent and their real interest in the job, that comes through the personal interview, I think. But we’re just about helping you get there quick.
Well, yeah. First of all. That alone is helping them because I think you’re right. We’re moved mentality wise. They are still getting candidates. The rumors of them not getting any candidates is grossly kind of over reported. But the candidates are applying when they go to the mall, they’re applying to every place in the mall. So they could easily get a job at Taco Bell or at Walmart or Applebee’s or Aeropostale. So literally, whoever gives them kind of the best offer and response to them in a timely manner.
Do you think with the top five, in the future, do you see your clients moving that process and trying to move that? Because, okay, you found your top five, which is great to sift through all of that data and then say these are the ones that you really should be spending your time with. Do you then think that there’s another layer additionally or down the road that you add, text or chat bots or something to that, so that you can… Some of these candidates, they’re not great on the phone, but they’re great on texting. So getting them into a kind of a process of getting the recruiters to talk to them or getting the hiring managers to talk to them on the phone, that might be impossible. We can speed up all the other stuff, get them to the top five and then fumble there because we’re not working the way that the candidates want to work.
Yeah, that’s exactly right. That’s something that we do offer today. I mean, we offer ancillary services around the ATS. We offer texting. We allow candidates to apply via text. We have a system where the recruiters or hiring managers can communicate to the candidates via text, either two-way text or one-way. If they want to blast out a one-way message, we give them the capability to do that. I would say, by and large, most people in our market, they prefer to be communicated through text and they’re going to answer text messages more than they’re going to answer phone calls. But it’s still a matter of urgency whether you’re calling them or texting them.
But to your point, I mean, I mentioned the top five. We want to get to those people immediately, whether it’s by phone or by text or however we’re going to communicate with them. But we want to communicate with the other candidates as well. I mean, there are still some good candidates in there. They don’t make the top five, but texting gives you a way to continue a relationship with that candidate. Because you never know what your needs are going to be down the road and that person did show interest and it’s just a good way to communicate with them.
I love that. So when folks look at Cadient for the first time, I call it the aha moment, or when they look at software for the first time, especially folks like this that aren’t in software, probably aren’t evaluating a lot of HR software daily or weekly or whatever. What’s that moment where they look at this system and they say, “Yeah, I really love this”?
They really love it, William, when we start talking about the data driven process and how you can use analytics and data to make better decisions. They understand, generally, that they’re hiring managers don’t always make the best decisions. It’s understandable why they don’t because they’re very busy. They have a hundred different responsibilities. They aren’t trained in recruiting. It’s probably not their favorite thing to do, but they need to get somebody hired and they need to get it done quickly because there is pressure, operational pressure on them.
So they love that part of it. That’s the aha moment when they say, “Wow, I can do this a different way.” Our vision statement as a company is that we want to revolutionize the way the world makes hiring decisions. We think we’re doing that through this Decision Point offering, so that we can come them alongside you and give you a better insight into each of these candidates instantly and you can make a better decision on which ones you’re going to hire from that. The aha moment is quickly followed by the, well, what about this moment, which generally travels towards is this going to create discrimination in my hiring process. That’s where the fear factor kind of shows its head. That is an important, very important element to be dealt with.
Absolutely. Well, I mean, it’s great that we’re even talking about it. It’s been a long time coming. So it’s good that it’s on their mind. It’s easily defended, it’s easily talked around and make sure that they understand kind of the rules, the laws, all that stuff. So actually, I think it’s helps that they’re bringing it up. Okay. The last question as we roll out is your favorite or your most recent customer story, and without names of course.
Well, I would say my most recent is a company that is using Decision Point, using our ATS and onboarding and Decision Point. It’s a person that loves to talk data and analytics and it’s a partnership because we work together. One of the things that we made a decision early on with Decision Point, it’s not the kind of a… If we license an ATS to you, we help you get it implemented, we work with you on what your workflow is going to be, and then you’re going to run it. I mean, you’re going to use the software. You’re going to check in with us and we’re going to check in with you to see how we’re doing. But basically, it’s your system and you’re running it. I think that’s the way most ATSs are set up.
With this machine learning system, however, it’s a managed service. It’s not something that we just hand over to you and say, “Here you go, hope this works for you,” because it is constantly tweaked. Our data scientists are constantly trying to find a better way to do it. How can I get a little bit better answer than what I got before? How can I improve the accuracy by just a fraction? I don’t know why this pops into my head, but I used to live in Speedway, Indiana. So I kind of fell in love with Indy car racing when Indy car racing was a big deal. It’s not so much anymore.
But I was always fast by those crews who are trying to get one more mile per hour during the time trials. How can we get one more mile per hour out of this car? That’s kind of what we do with these algorithms that we use in machine learning. How do we get one more percent accuracy out of this thing? I am amazed by how our data science team, the things that they come up with. So my favorite client story is that we have a client who likes that stuff too. They are part of the pit crew and they’re coming back saying, “Hey, what about this? Have we tried this? Can we do that?” It’s really a collective effort to try to keep getting that one more percent, that one more mile per hour out of the system.
I love that.
It’s fun to do and it’s just it’s nice to have a partner like that.
Well, and it’s 1% both in efficiency of the quality match, but it’s also 1% in making it faster. They’re just looking to make it faster, better, stronger, all of those things. So thank you so much, Jim. I absolutely appreciate you coming on the podcast and explaining Cadient to everyone.
Thanks for the opportunity, William. It was great to talk to you again.
Absolutely. Thanks for everyone listening to Use Case Podcast. Until next time
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William is the President & Editor-at-Large of RecruitingDaily. At the intersection of HR and technology, he’s a writer, speaker, advisor, consultant, investor, storyteller & teacher. He's been writing about HR and Recruiting related issues for longer than he cares to disclose. William serves on the Board of Advisors / Board of Directors for 20+ HR technology startups. William is a graduate of the University of Alabama at Birmingham with a BA in Art History. He also earned an MA in American Indian Studies from the University of Arizona and an MBA from Case Western Reserve University.