Podcast: Make Clunky HR Systems Work and Discover Overlooked Candidates with MojoHire.ai

Tincup podcast 1

On RecruitingDaily’s Use Case Podcast with William Tincup, MojoHire’s Spencer Liu describes some of its unique features and benefits that set it apart in the TA/HR Tech ecosystem, such as overlaying on top of existing systems and drastically improving usability and function, and instantly sourcing from all HR data to speed up hiring .

Listen to the full podcast, or review the transcript below:


William Tincup:   Ladies gentlemen to William Tincup and you are listening to The Use Case Podcast. Today, we have Spencer on from MojoHire. We’ll be learning about the business case to the use case for why his prospects become customers and why his customers stay customers of MojoHire. So let’s just jump right into it. Spencer, thank you for on the show. Would you introduce both yourself and MojoHire?

Spencer Liu:   Excellent. Yeah. William, thank you so much for having me on. It’s just a pleasure to be here, to talk about what MojoHire is. Yeah. My name is Spencer Liu, and I’m the head of product development for MojoHire. I have been a serial entrepreneur for the past 10 plus years. I’ve done startups, not only in the United States, but around the world. I’ll give you a little bit of my background. So, when I finished my last startup journey overseas in Asia Pacific, I came back in 2018. And I took some break, but I wanted to get back into the workforce.

And what I realized is with all my, I believe, very robust experiences from around the world, I was completely unhirable, because these companies, they were just looking for a UI/UX designer. They were just looking for a product manager. They are very tactical in terms of, “Okay, I have a hole and I need somebody to fill that hole,” right? “But here you are. You’ve been a fundraiser. You’ve had the title of a CEO. You’ve done product. You’ve done design. We don’t know what to do with you.”

So I came back, and then it’s very interesting. So coincidentally, I met it up with Renée La Londe, our founder and CEO, and she was telling me that, “Hey Spencer, look, I have this great global consulting agency, but we have a hell of a time recruiting talent. We have job openings. We have a lot of people applying. But all of these people, or not all, but a majority of these people are just not qualified. It just seems like they’re not even reading the job description before they submit the application.”

So that perked my interest about this whole talent acquisition, HR talent management space. So I spent a whole month like researching into this space and I realized how complex it is, how many competitors or technologies there are out there, all try to fix a silo of a problem. But then we come back and say, “You know what? What is the problem.” For me, if I may overly simplify it, the problem is jobs and people, or projects and people. So if we can figure out a way to bring all the people together or all the database of people together for our customers to grant our customers speedy access to all of the people database, regardless of whether they are external or internal and overlay matching technology that can very quickly help hiring managers and recruiters or HR business partners to find the right talent to be in touch with. So offering that speed of matching and also provide a great experience. So that’s what we venture out to do.

William Tincup:   So two things come to mind. One is the ATS, historically, it’s a 50-year-old software category, so it’s not new. I think we’ve all made this mistake in our past where you’ve got your ATS, you’ve got a database of candidates, but yet you put a brand new job description on Indeed or LinkedIn or wherever, and you cast new. You don’t really go back and look at your ATS. I mean, that’s just a bad habit that we’ve all kind of fallen into, right. So one is your take on ATS is in the data that’s there. The other is explaining to the audience the differences in matching technology. So when you say matching, I’m assuming you mean something specific and different from other ways of matching because they’re not all built the same.

Spencer Liu:   Definitely. Yeah. So I will explain at a very high conceptual level, right? So when we knew we needed to match, we needed to match people to jobs, jobs to people, or people to people, right? So we need to match, “Okay, how do we want to approach matching?” Okay, we can do a keyword based matching, or we can do a skill sets based matching. And the other thing is most of the companies out there in the space, they are all doing some kind of AI matching. But ultimately, when we come back and we say, “You know what? What do we want? What is the right approach that we want to take?” So we are thinking about, “Okay, ultimately, we’re in the people business. We’re in the talent management business, right?”

In my own case, I’m not just a UI/UX designer guy, right? I am a person with 20 plus years of history and experiences. That all needs to be accumulated and also taken into consideration besides just skills. So we wanted to, from the get-go, approach matching as if a world-class recruiter is reading Spencer, right? So our matching technology, what we call is the MojoHire Topic Discovery and Neuron Matching Technology. So what we set ourselves to do is we can read a piece of documentation, just like a human brain, and be able to compare similarities between the documentations, right?

So a piece of documentations could be a candidate’s profile or a LinkedIn profile or resume. And on the other side, it could be a really well written job description or a project description. And with that philosophy, what we can do is that encompasses keywords, that encompasses skillsets, that also encompasses themes and topics that we can extract from these documents and be able to match the similarities between them. Does that make sense?

William Tincup:   A hundred percent. So it gives context and sentiment to two things. So you’re not just relying on keywords, which there are folks that that’s their bit, they match, and it’s based on keywords. There’s nothing wrong with that. And there are folks that look at skills and say, “We’re just going to be in the game of evaluating skills, the breadth and depth of skills, and matching people based on skills.” And so you’ve added a layer. You combined those two, and then you’ve added a layer of context.

Spencer Liu:   Yes, exactly. So we also developed our own parsing technology. So we understand the different entities within a piece of documents, right? We are able to pick out job titles, company names, locations, and so on and so forth. Then on top of that, we understand, we have the capability of understanding, “Okay, this particular company name is related to this particular job title, is related to this duration of time.” Right? So we understand context. We understand words in context of sentences. We understand sentences in context of paragraphs. Then we understand paragraphs in context of a segment within a piece of documentation, literally like a human brain reading through a documentation.

William Tincup:   So you built your own parsing engine. Of course, there’s parsing engines that have been out there that a lot of folks use for … They’re hard to build, turns out. Yes. As you’ve probably discovered. Not easy. So a lot of folks in our industry, they white label a parsing engine. And so why did you decide to build your own parsing engine?

Spencer Liu:   It’s interesting because a partner yesterday on a call, he asked me the exact same question. It seems like a lot of investment for little return. Perhaps for little return in the short term, right? But in the long haul, if we want to be able to enhance our matching technology in a very granular way, we need to have full control about how we dissect a piece of document, right? So we started off using great technologies out there doing parsings, absolutely. But we also, on the sideline, we dedicated all the resources to see if we can do parsing better, a more reliable way, and most importantly, will give us that architecture, that scalable architecture, where we can go into each word, each sentence, and start making that relationship. All through parsing. So we look at parsing also a little differently as well. It is a long-term investment, but we have our own parsing up and running, and we already have plans to start merging parsing with our matching engine. So these two possibly can become one. If that makes sense.

William Tincup:   Totally makes sense. Totally makes sense. So the the first question was about the ATS database.

Spencer Liu:   Yeah.

William Tincup:   Because you had mentioned data. There’s data, both internal data and external data, and I focused on the ATS data. So what’s MojoHire’s take on the ATS data that’s sitting there?

Spencer Liu:   Well, I will give you a real case scenario. We have a great customer who came to us and say, “Spencer, look, I’m spending all this money promoting our jobs on different job boards, advertising our jobs, advertising our brand. And we are getting really good qualify as well as large quantity of applicants coming in to my ATS. But Spencer, I have no access to them. I cannot search. I cannot browse. I barely have a CRM that works. But my CRM is a separate system, again, that my recruiters don’t have time to get into.” So they are working 100% in ATS.

So for example, I get 50 or 150 applicants for my job. At the end, one person gets hired. What happens to the 149 of them? They’re sitting in my ATS in some dark corner and collect dust. But yet these are valuable candidates that have already expressed their interest to work for us and have taken the time to submit their applications. They should be my first default pool of sourcing. And yet we are right now jumping out of our ATS on LinkedIn or whatever, all these great tools out there, sourcing externally, trying to convert passive people into active people, versus we already have 250,000 candidates sitting on my lap that we own, and yet we don’t have access to.

So what MojoHire does is we fully integrate with any HRIS or ATS, and we give you instant access to this entire database that you own with artificial intelligent match overlaying. So with a click of a button, you can literally see at the moment of job creation, “I have actually 45 great candidates that matches my job for my database that I can call on today.”

William Tincup:   So do you see a future for MojoHire in helping people? Because you said HRIS. That’s got me to internal mobility. Do you see a future there that we don’t just use it on the front end with talent acquisition, which is fantastic if we just stay there, but do you see a future of helping people find internal jobs, like candidates that maybe we don’t know. It’s a big company. We’re worldwide. We don’t know about Susie or Jan or Michael. We don’t know about them. We don’t know their skills. We don’t know those things. So do you see a future there as well?

Spencer Liu:   Absolutely. I personally think we are living in such an interesting time with COVID, with the whole Great Resignation, where everyone in the TA space or in the HR space are under a tremendous amount of pressure to keep and retain talent as well as getting new talents into the application flow. Going back to our original philosophy, we see talent as talent, right? Companies own talent databases and companies need talents. And these talents regardless of what system they live in, the whole idea is this is a people problem. This is a people database problem. This is not a workflow problem per se, right?

Today, these people databases are siloed off in the ATS, in the CRM, and in the HCM. It’s because of the limitations of technology. But our whole philosophy is people are people. So we love to come alongside of our customers that have that holistic talent management strategy or vision where, for example, they bought an Oracle or they bought a Workday. They want that whole database to live in one place. However, what we do is we step in. We are in overlay to these massive systems that give you instant access with speed and with quality matching to all of your database, regardless of whether they’re external or internal or ex-employees.

William Tincup:   I love this. I love this so much. So a couple things. One is, as you had mentioned speed at the beginning, and I want to get, just because again, we are living in a world with, as you said, by the time, sometimes, if you’re slow … The process is slow. Let’s just say it that way, or the technology for whatever reason is slow. By the time a recruiter gets back to candidates that they really fall in love with, they’ve already got offers or they’ve already got jobs.

Spencer Liu:   Oh yeah.

William Tincup:   They’ve already moved on. So speed, especially in a tight market like we have right now, speed and quality, always. Speed is critical. So the question is, job matching technology isn’t historically on HR or talent acquisition’s budget. It might be buried in some other category, but it isn’t a line item. Generally speaking, it isn’t a line item. So how do you frame that up, your sales of marketing team, how do they frame that up for folks to understand where to put it in their budget and how to use it? Because ultimately, it will become a part of their budget, but initially they don’t have … Excel budget. Most HR budgets are all in Excel, and they’re just rows and columns, right? So there’s not a row that says, “job matching,” or “skills matching.” They don’t have that.

So how do we frame it up for them to understand, “Okay, here’s what it is. Here’s what it does.” We don’t have to get into, “Here’s what it costs,” but, “Here’s what you get. Here’s the outcomes of which …” This is why it’s important. So we’ll still budget from programmatic advertising, let’s say, and we’ll move programmatic advertising or some of the budget from programmatic advertising or staffing. We’ll move that into job matching.

Spencer Liu:   Right.

William Tincup:   So how do they currently do that?

Spencer Liu:   It really depends, William, who we are speaking to. Right? So I’ll give you an example, a real case scenario. One of our best awesome customer/partner. Initially, the conversation started, “Spencer, I have a corporate mandate to increase our internal mobility application to 20%. But right now I don’t really have a technology. I don’t really have a way … Well, I have a way to promote internally. ‘Hey guys, we have these jobs open. If you are thinking about internal transfers or whatever, feel free to take a look at this job board and submit your application.’”

So that was the initial mandate. They can push this message to their employee base through marketing programs and so on. But ultimately, if I am an employee, if I’m very happy with my job or if I am not that dissatisfied with my job, I’m not going to hop on the job board, right? So in that case, what we do is we do reverse job matching where we ping the qualified employees who are ready for a job transfer. We ping them because we are doing 24/7 job matching between and jobs. We can ping them and say, “Hey, you know what? Here are the top three jobs within your organization that you should probably consider.” So that’s one particular use case of our technology, where HR comes to us and say, “You know what? I want to retain our employees. There are 40% of them who are actually open to internal transfer. We want to nurture that. We want to encourage that. However, besides just doing it through marketing messaging internally, we don’t really have the technology to do it.”

So that’s one use case when we sit down with a HR business partner, per se, where they had that kind of strategy, that’s how we come alongside and support them. Then there is the specific TA use case, right? Things like I just migrated to a big HCN or HRIS. We are all using the recruiting module of that system, and it’s difficult to use. Okay? It’s not only that it takes 10 clicks for me to download a resume and continue with the workflow. There is no intelligence in it, right? It’s a very time consuming tool to use.

So what we bring is not only we bring in matching, so this is now a very TA focused conversation, right? Can you give me a better user flow? Can you give me a better digital experience? On top of that, can you help me to, with a click of a button, find the right candidates within my database that my recruiter should be calling on? And we can absolutely do that. So we are an overlay solution on top of your Workday or Oracle, and we deliver this great, beautiful experience. However, still using your Oracle and Workday as the source of truth, right?

So we are able to speed up that whole recruiting process as quickly as possible by giving you artificial intelligent access to your entire database in the ATS, as well as a beautiful digital experience. Then what the TA folks said is, “You know what? Now we are getting access to all the external candidates. Can you actually, now, since you are integrated with our massive HRIS, now can you actually also show me internal candidates that are good matches for the jobs that I’m recruiting?”

So now you’re furthermore expanding the recruiting pipeline to not only evaluate the direct applicants, but also doing matching on top of passive applicants that are already in your system, on top of that, your existing employees who are qualified for internal transfers. So now we are bundling all of these talents together onto our platform and providing this great, intelligent access instantaneously to the recruiting team.

William Tincup:   I love this. So job matching technology, and especially in the ways that we’ve described it at the very beginning, there’s different ways to think about it. There’s different keywords, skills. There’s different ways that companies are marketing it. And I’m not sure the buyer, as the practitioners listen to this, there’s no offense, I’m not sure the buyer understands all the different nuance, different ways. What questions should they be asking of, let’s just say MojoHire? What questions should they be asking you to get at the heart of the outcomes that will help them?

Spencer Liu:   Well, I think the first thing is we love to sit down with our customers to discover what their real pain point is, right? So I will give you another example. One of our customers came to us and I interviewed the business owner, the vice president of talent acquisition. He gave me a set of his pain points from a business and TA strategic level. Then I spent hours on end with their recruiting leaders, and they gave me a whole set of pain points, right? So I think what interests us is really going pretty deep with our customers to understand their pain points. Is their pain points just the fact that “It takes 15 clicks for me to download a piece of resume,” or is it that, “I want to be able to process all the candidates. I want to be able to batch process, batch disposition all of the unqualified candidates in a very intelligent, automated way,” right?

So I think sitting down with and also strategizing with our customers is step one. Then, from there, they will start asking us questions around, “Okay. How do you guys do matching? Why is this person recommended and the other person is not? And why did you decide to design certain workflows certain ways?” So I know I’m not answering your question, but I think really it all depends on what the business pain points are for the customers.

William Tincup:   Well, no, that is answering my question, actually, because if you start there, then it’s nuanced to their specific needs, and their specific needs are important. You had mentioned the company that’s feels like they’re overspending and not realizing the [inaudible 00:   21:   50], or worse than that, they’re spending and getting too many candidates. Scarcity and surplus are equally problematic for folks, right? You have 20,000 people that apply for a job. We used to look at that as a badge of like, “Oh, success.” And that’s not necessarily the case. So if you have something like MojoHire that they can filter through that and then say, “Okay, 20,000 people. That’s fantastic. But here of the 100 out of those 20,000 that you should actually spend time on.”

Spencer Liu:   Yes. That’s the whole point, and regardless of whether they are your direct applicants or they are people that are just sitting in your database, your existing employees that is sitting in your HRIS. I mean, we were talking to a potential customer a while back, and they were on average getting anywhere between 1,000 to 2,000 direct applicants for every open rec. I mean, that’s physically impossible for a recruiting team to sift through. So what do they end up doing? They end up subconsciously abandoning all the direct applicants. Now they’re completely relying on internal referrals because a recruiter comes into the office …

Well, they don’t go to the office anymore, right? They come to their desktop every day. They open up their inbox. “Congratulations. You just got 250 resumes in the past 24 hours,” because they’re a big brand, because they are very attractive companies to work for. So the recruiters, what do they do? They freeze, right? At best, they spend maybe an hour. They go through maybe 20 different resumes or whatever. But the thing is, physically, they cannot catch up.

So there is that problem, right? Companies with big brands, great attractive companies that everybody wants to work for, they’re getting too many. Okay? So MojoRank says, “Out of the 2,000 that you’re getting today, here are the top three. Here are the top five, or here are the top 25.” So we very quickly narrow it down to help the recruiters focus their precious time on the right talent.

William Tincup:   Right.

Spencer Liu:   Okay? So that is an extreme use case of a big brand, big company that everybody wants to work for. Then you have the other extreme, right? A medium enterprise, maybe they are in some kind of niche industry where they are not getting enough candidates. So therefore, the recruiters and sourcers are spending most of their time in LinkedIn, right? Trying to push a big piece of rock up the hill, converting somebody, finding somebody, connect with somebody, getting your invite accepted, start dialoguing with that person, try to persuade the person to consider submitting an application. That’s one route.

But with MojoHire, if you have a substantial enough of a database already, if you have been on your ATS, your HCM for three, four, or five years, with 20, 50, 100, or half a million, or even more candidate records, with a click of a button, we will tell you once again, “Here are the top 10 folks that you should call right now. Look at their resume. Look at their record. Look at their candidate profile, and get in touch with them.”

William Tincup:   Well, I guess-

Spencer Liu:   So that’s almost … Yeps. Sorry.

William Tincup:   No, sorry to interrupt. That gets to speed and quality. So if you get it down to that 10, now the recruiter … That’s manageable. That’s a winnable game as a recruiter and a hiring manager. I now can spend time, which is one of the things we’ve talked about is that this is helping people, especially talent acquisition professionals and hiring majors, get some of their time back. What we don’t talk about too often enough is hiring managers are busy. They’ve got a job to do. I mean, you know this because you’ve done this bit.

Spencer Liu:   Absolutely.

William Tincup:   They’ve got another job that they’re working on. They’re not in the business of hiring, but yet they have to hire. And so we can’t waste their time. And so-

Spencer Liu:   Exactly.

William Tincup:   This actually really helps with speed, which helps with quality. With the remaining minutes we have, I want to do two things. A, the demo. When people look at MojoHire for the first time, I call it an “aha moment.” It’s probably really dumb and cliche, but what do they fall in love with? What’s that moment where they’re like, “Oh, wait a minute. This is cool.” What is that moment with MojoHire?

Spencer Liu:   The moment, right? It’s not only we have a very user centric design flow. That just makes sense. When you think about some of these ATSs or these big HRIS systems, they’re essentially built for compliance. They’re essentially built to store files and records, right? But recruiters need a set of tools that works the way that they want to work. So number one, right? Number two, the biggest aha moment is the moment, the literal second when a job is created. I have 200 candidates, really good matches from your database that you can be looking at right now. So that’s the aha moment. I mean, people can’t believe it, right?

You create a job, for example, in Workday, which instantly synchronizes over to MojoHire. You go to your job detail page on MojoHire. With a click of button, click on “active.” You have active candidate matches that match your job. So who are these candidates? These are candidates who have applied to any other jobs within your organization less than 30 days ago. So these are, again, not direct applicants, but applicants who are ready to go that was not exposed to your job, but applied for some other job inside your organization, who happens to be a great match for the job that you’re recruiting for.

Then there’s another click of a button, which is passive. That’s basically all the good high-quality matching candidates from your entire database. So I’m talking about the literal second of the job creation process, you already have two automated qualified candidate pool that you can be sourcing from, your active pool and your passive pool. And these are the databases and candidate profiles that you already own. You already spend a lot of money to accumulate and store. It’s just historically, you’ve never really had that kind of instantaneous and quality access to these folks. Now we are opening up that Pandora’s box. Now we are opening up this magic. With a click of a button, just go and start calling people. Sorry. I get overly excited about what we have built.

William Tincup:   Well, if you weren’t overly excited, I’d be worried. I like that you’re excited. Lastly, without brands or names or company names, et cetera, what’s, right now, your favorite customer story? Something where they’re using MojoHire, and you’re like, “Yeah, that’s cool.”

Spencer Liu:   Yeah. My favorite customer story are always customers that have a holistic talent management strategy, right? They see things eye to eye as we see things. They are sick and tired of the siloed approach. They are sick and tired of their siloed ecosystem, right? “I have a system for this. I have a system for that, and none of the systems are talking to each other, and yet these are my people. These are my database. These are my talents. So why don’t I have one holistic view to manage all the talents moving from inside-out, outside-in, or inside-to-inside?”

So, number one, I get excited with customers who have that kind of vision. Over time, they want to move their whole TA and HR. There is that conversion that’s happening right now, right? More and more companies are realizing these siloed approaches won’t work for the long term. So number one, vision, right? That’s what I really excited. And once we had that vision, we know where we want to go together in the next X months.

But let’s start, “Okay. So where is your biggest pain point? Is your biggest pain point internal mobility or your biggest pain point is to support the TA folks, or the internal pain point is to do automated candidate matching for hiring managers?” Right? Let’s start small and we can always build it up to that big vision. So I get excited when I talk to customers who had that vision in mind, but we’ll take baby steps toward that. So we want to create value incrementally for your TA team first, then for your hiring manager, then for your candidates. Then we can move internally, and so on, so forth.

William Tincup:   I love it. I love it. I love it. I love it. Spencer, thank you so much for carving out time for us and the audience.

Spencer Liu:   Anytime. Really appreciate your time and reaching out.

William Tincup:   Absolutely. And thanks for everyone listening to The Use Case Podcast. Until next time.

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