Welcome to Death Match, North America 2020, which took place at TAtech on May 19. For all of you NOOBS who have never experienced Death Match - Death Match is a competition which pits 4 innovative, early-stage companies against one-another, only one can win and emerge with the coveted Death Match Chain of Champions.
This Chad and Cheese Death Match episode feautures Scot Sessions cofounder and CEO at TalVitsa. COVID-19 might've locked us all in our homes but never fear! The home bars are always stocked, pints were flowing and Chad and Cheese questions and slurring snark was flying. Luckily Joveo's CEO, KJ, stepped in to provide a smart and sensible juding voice to this TAtech event...
Enjoy while Scot picthes TalVista and then ducks, bobs, and weaves for the balance of his 15-minutes on the virtual Death Match stage.
PODCAST TRANSCRIPTION sponsored by:
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Intro: Hide your kids, lock the doors, you're listening to HR's most dangerous podcast. Chad Sowash and Joel Cheesman are here to punch the recruiting industry, right where it hurts. Complete with breaking news, brash opinion and loads of snark. Buckle up boys and girls, it's time for The Chad and Cheese Podcast.
Chad: Welcome to Death Match North America, 2020, which took place at TAtech on May 19th. For all of you newbies out there, who have never experienced the Death Match, Death Match is a competition which pits four innovative early stage companies against one another. Only one can win and emerge with the coveted Death Match Chain of Champions. This Chad and Cheese Death Match episode features Scot Sessions, co-founder and CEO at TalVista. COVID-19 might have locked us all in our homes, but never fear, the home bars are always stocked, pints were flowing and Chad and Cheese questions and slurring snark was flying. Luckily, Joveo CEO, KJ, stepped in to provide a smart and sensible judging voice to this TAtech event. Enjoy while Scot pitches TalVista, and then ducks, bobs, and weaves for the balance of his 15 minutes on the virtual Death Match stage.
Chad: Here we are again people, it's Death Match.
Joel: What I'm talking about.
Chad: North America, TAtech, a little drink.
Joel: Beer disappears, and it's there. It disappears and it's there.
Chad: We've got Scot Sessions, CEO and co-founder of TalVista, getting ready for his two minute pitch. Scot, are you ready?
Scot : I'm ready.
Chad: Joel, are you ready? Hit it.
Joel: Scot, in three, two.
Scot : Hi. My name is Scot Sessions, CEO and co-founder of Televista. We help companies see beyond the obvious, but if they could do that already, I wouldn't be on this Death Match talking about it today. We all have bias, a preference for things we've grown accustomed to, both likes and dislikes. This can even happen subconsciously, called unconscious bias. When we combine our bias with recruiting, a lack of diversity takes place. In the hiring process, women and minority groups are overlooked when we write job descriptions because they include words that, based in scientific research, are known to be problematic. Candidates have even taken to using a nickname when they are submitting the resume to increase the likelihood they'll be called for an interview. Group think is a common problem in today's structured interview process. Any and all of these challenges, reduce opportunities for diverse candidates to apply and advance through the recruiting and hiring process.
Scot : TalVista addresses each of these challenges, and our clients are seeing a 30% to 50% increase in diverse candidates, applying and progressing through the process. We are a decision support SaaS platform that enables conscious inclusion to take place in the process. Our proprietary technology, based in science helps to improve job descriptions, it helps hiring managers focus on what matters most like experience and skills in the original and redacted resume review process. Group think is halted with our structured interview, ensuring interviewers are mindful and present for each candidate response. My partner and I stood up TalVista two years ago and worked with TA leaders at Fortune 500 companies. We have many clients who are experiencing improvements in their diversity recruiting. Our platform is available through an annual subscription based on estimated number of hires, not seats or number of users. We're pushing a million in sales to date and see no end in sight to companies requiring our decision support platform. Thank you.
Chad: There it is. Excellent, Scot.
Joel: Thank you, Scott. Very tight. Very tight.
Chad: KJ, you are the first one to ask questions.
KJ: Thank you very much, Scot. That was great. Scot, so when you create gender unbiased job description, what does it do to metrics which are key to a talent acquisition manager, like cost to apply or time to hire and things like that?
Scot : That's a great question, KJ. See, we focus on ensuring that more diverse candidates are going to apply for those roles. Right now job descriptions are written for white males, 25 to 45 years in age. If you continue to write that way, you're not going to address and bring in women and underrepresented minority groups. So it really doesn't matter time to hire if you're not addressing and inviting those minorities to apply. Otherwise, once the job description is optimized, now you're going to attract those diverse candidates and all of the same metrics apply to time to hire. It's just bringing in a diverse candidate set.
KJ: So when the world is going to come back to business as usual and companies ... It's easier to go from 100 to 10. It's much more difficult to go from 10 to 100, and the speed to hire is going to become the key in getting the workforce back. Time to hire becomes the single most critical metric.
Scot : I hear you, time to hire is always important. But if you're not taking time, a few seconds, to address and ensure that your job description is going to attract diverse candidates, you're going to be missing out on a whole plethora of great candidates who are qualified, when you're only targeting white males, because that's how job descriptions are written.
Joel: I want to point out that there are four white dudes, well, one Indian, I guess, on the panel, but four dudes. Anyway, I want to talk about the competitive landscape real quick. And doing my homework, it looks like Textio is an obvious one. I've got TapRecruit. I've got GapJumpers. How are you guys cutting through the clutter and differentiating yourself from the competition?
Scot : Great question. So there was some research that was done several years ago out of Duke University to identify these problematic words that I talked about. Textio, us and others, that's where we based our technology. However, we continued with our own PhD sociologists to continue researching, to expand that problematic word list from beyond just female, to people of color and people with disabilities. Nobody's doing what we're doing in that set today. That's one differentiator. The other is, we're tackling three problems that are addressed throughout the recruiting process, not only job description, but redacted resume and interviewing. No one else combines all three of those assets together to improve the diversity hiring process.
Chad: Excellent, Scott. Conscious inclusion, which is the total opposite of unconscious bias, I totally dig it. Love that. Can your platform lay over existing resume databases? Are you integrating with applicant tracking systems and CRMs?
Scot : Absolutely. In fact, those are the systems of record. We can do a stand alone, but we highly recommend that our clients integrate with Taleo, Connexus, SmartRecruiters, iCIMS, et cetera, et cetera. So we have open APIs to do that so that resumes can be brought in seamlessly, original resumes. We're not stripping out content and then showing it in form fields, we're showing that hiring manager the original resumes so they can see how the candidate organize their thoughts, how they represent themselves and prioritize, but we redact out PII, personal identifying information, so that keeps that hiring manager focused.
Chad: So what about job boards in different job sites with resume databases? I would think that that would be an amazing partnership to be able to get you as an add on for any of those huge, huge piles of resumes that are out there. Are you currently working with any vendors to offer this?
Scot : We have several partnership discussions going on. As I said, we've been around for two years, we're attacking things by priority, making sure that we're delivering what we say we can deliver. And now looking to expand to say, "All right, client A, you have this tie-in with this partner. We can help you bring those resumes in, but you need to select them." Remember I said, we're a decision support platform. We are not making those decisions for the users. They need to have that human touch to say, "This person meets the minimum criteria. Now let's pass them on." Otherwise, hiring managers are going to be pissed. There is a plethora of crap.
Chad: I agree. But here's the thing, it takes a recruiter, they say, six seconds to scan a resume. I don't believe that. But if I'm upgrading my system right now, I want to become more automated and I want to match those candidates to my requirements. Why would I want a recruiter to even review my resumes? Can you, or have you actually partnered with any types of matching organizations to be able to bring candidates that are meeting the requirements into the funnel as well? So that my recruiters don't have to actually go through those six seconds and those hundreds of perspectively, thousands of resumes.
Scot : It's something we're looking into most definitely. But it's not just the recruiter, it's the hiring manager who ends up reviewing, and it is six seconds based on research that they're spending. But when it's redacted, now they're doing a quality review, ensuring that that candidate is somebody they want to move forward with.
KJ: Sure. So, Scot, I was wondering, if there is a large company which has about, let's say, 1000 jobs and they would like to give you a feed of 1000 jobs and have you get it all right, you said it has to be manual, so does it mean that every recruiter has to go manually in every single job description?
Scot : So, a job description can be added through a drag and drop first, in a manual process or in automated, it can be brought over from the ATS. That job description has to be written at some point. This is one added editing step to ensure that diversity is included. What we're seeing is, when companies are employing AI and scouring the web for a bunch of stuff, who knows if it's validated against scientific research that yes indeed, they're going to be improving for attracting diverse candidates. That's why I say we're a decision support platform. I get that companies have thousands, many times, those are evergreen roles, and so you do it once and then you reuse it, and reuse it, and reuse it. But when you're doing executive or upper level management, you're going to pay attention to those job descriptions and make sure you're attracting the best and most diverse candidates who have the qualifications, so you attract them in.
Joel: Scot, there was a Forbes article recently entitled, What Happens When White Women Become the Face of Diversity. And I know you know about it because it's linked from your website and you're quoted in it. Basically the gist was that, if we're putting women as diversity, what's to stop just white women becoming the diversity of the future? I want your commentary on that and how your technology can maybe thwart such a future.
Scot : When it comes to diversity, if we have blinders on, and we're only looking at white women, we're doing ourselves a disservice. What we're doing, as I shared during my two minutes, is we've expanded out beyond just gender parody. In our research, we've expanded to include for people of color, male and female and people with disabilities. That's how we're ensuring that our job descriptions, once improved to be made more inclusive, they're going to attract a broad set of diverse candidates, not only women, not only people of color, but across the board. And so long as they have the requirements of skills, they should move through that funnel very rapidly with the other two aspects of our platform.
Chad: So real time feedback from your website, and again, you've been saying it over and over, real time feedback helps you create job listings that equally attract male, female, and minority candidates. That language doesn't represent what you're trying to embody. Where's trans, nonbinary, queer, people who don't identify with the non-gender traditional roles? Where's that at?
Scot : Yeah. So again, we'd been around for two years, we're tackling one problem at a time. We have a product roadmap that is long and extensive to address, not only those items, but ageism as well, because that's another issue that we see. And so as we continue to progress, and as clients say, "Hey, this is more important than another thing." Our product roadmap is fluid to ensure that we're meeting those needs. But we're taking them down one at a time. It all comes with money, and if anybody wants to drop 10 million in my lap, hallelujah, we'll get those things done tomorrow.
Joel: Talk to KJ. Talk to KJ.
Chad: Yeah. So, scientific research based, what science is actually impacting your algorithms to identify the problematic words? Number one. And number two, give me some examples of said words.
Scot : Okay. So with our algorithm, first, we don't delineate between a female problematic word and a person of color, problematic word, if it is highlighted in our platform, it is an issue that you need to address. So the research that was done, as I shared, out of Duke University several years ago in partnership with the University of Waterloo in Canada, set out to find out other words that cause women to not apply. They found a plethora of words to do that. We've expanded on that research to accommodate for, like I said, people of color and now people with disabilities. So that's what we're doing to expand. And that's the scientific research, versus scouring the web, or even a client's hundred thousands job descriptions to say, "Well, this is what we found," garbage in, garbage out.
Chad: One of the biggest issues that we've seen, and research also shows is that women will not apply for jobs unless they are a hundred percent into that position, and they meet all the requirements, right? Where dumb men, like all of us, it doesn't matter, we meet about half and we're like, "Ah, we can do that job." That is an issue that's more cultural than anything else. How can just changing the words, especially when the requirements are mainly the issues, can you help companies with the requirements to be able to kind of re-target to get more females?
Scot: Come on Chad. I think you've heard me speak before, because you've taken those words right out of my mouth. You're exactly right.
Joel: He cheats. Say it. He cheats.
Scot: So, women, they could be the strongest individuals in the world, many of them are. However, their own self perception when they read a word like, strong analytical skills, most women would be self-deprecating it, "Oh, well, I can do that okay." Whereas a male who can do it okay, sees strongly like, "Yeah, I can do that." Just to your point. And so by optimizing those words and using, instead of the word strong, again, not that women aren't strong, but optimizing that to another selection that a woman is like, "Oh, yeah, I can do that," they're more apt to apply. Additionally, on our website, instead of putting 50 requirements, put three or four, because like you said, men will say, "I can do one out of 10, I'm applying," and a woman will say, "I can do nine out of 10, I guess I shouldn't apply." So really tailor it to ensure that you're going to address those candidates in.
KJ: Do you have a feedback loop, which provides continuous learning data to the machines or is it not there?
Scot : So our algorithm again, is always validated against science. So we're not going out and saying, "Hey," like I said, "Scour these job descriptions, and then work from that." If it's not been validated in science, we're not going to employ that into our software. And so that's where we come in as a research driven tool, so that people can rest assured that it's been validated against many, many research pieces and surveys to the public and subsets to ensure that that's a word that's a problem, or it's replaceable with a word that is inclusive again, based in that research.
KJ: From there and then you make your algorithms, right? There's no learning loop or feedback loop?
Joel: Scot, I'm curious more of your opinion than it is a question, but in our work from home environment and all accounts say that we're going to work more from home in the future, how does that impact diversity hiring? Is it no impact at all? Is it a little bit?
Scot : Time's going to tell that, Joel. I think in some cases, it won't impact it at all. I think in some other cases, it's going to impact it, especially with companies who are old school, who are like, "If I'm not watching you do the work, the work's not going to be done. And if I have a pre-conceived bias against women, or against people of color and lack trust of, ah, they're not going to do the work," then it then working at home could impact it. And so using our platform will ensure that people with qualifications, regardless of their walk of life, should be considered. And then the culture of that company needs to move closer to more comfortable working at home.