HR Tech Integrations – A Strategic Imperative

Full Podcast Transcript:

[00:00:01] Jonathan Duarte: Alright, hey everyone, this is Jonathan. Great to have you back. We’ve got a great show today. I think you will learn a lot from Jim Griffin. Jim, why don’t you give me a little background about your background in HR tech and what you’ve been doing over the last 20, what, 32 years?

[00:00:17] Jonathan Duarte: Is that right?

[00:00:17] Jim Griffin: Hey JD, 35 actually. As Andrew was saying earlier, I’m in my fourth decade of human capital management software, all the way back to the days where HR software was an oxymoron. So my, my career, I’ve spanned a lot of things. I’ve had a decade of selling payroll. I’ve had a decade of talent management.

[00:00:35] Jim Griffin: Last decade seems to be in and around recruiting and specifically AI tied to decisioning around talent mobility and talent acquisition. It’s been a lot of fun. Probably more innovation in the last six to seven years. Probably more so in recruiting and learning than I’ve seen across the previous, [00:01:00] 25.

[00:01:00] Jonathan Duarte: And what are the things you’ve been doing? I know you’ve been doing partner ecosystems. Describe that for, the layman in HR that may not know exactly what that means from a vendor side.

[00:01:13] Jim Griffin: So one of the interesting things about the HR industry, The ecosystem, meaning the partner interconnection is more critical than any other industry I tell organizations and CEOs, I do a lot of consulting for ecosystem, go to market and strategy, I can pick the winner in every single category. Invariably, it’s where you’ve got the most mature, most capable best oriented ecosystem strategy and connectivity. I don’t care whether it’s recruiting HRAS, talent management, learning, your level of readiness.

[00:01:50] Jim Griffin: From a partnering perspective, and it goes down to the attribution model itself, meaning what is the strategy and how do you [00:02:00] reward your partnering go to market that’s critical is we all know the plan. Decides the outcome. Yeah. You have the proper plan, focused on what should be the outcomes and partnering strategy.

[00:02:15] Jonathan Duarte: Yep. Another way of saying that for the layman’s who are the users are, if you’ve got an applicant tracking system and you need a new tool, someone’s got to connect those tools together. So you aren’t opening 15 browsers. We’re reducing data costs error costs, entry costs, automating.

[00:02:35] Jonathan Duarte: That’s what we’re talking about when we talk about partner the technical side of making sure your data comes in, goes to the right place at the right time, and is correct.

[00:02:44] Jim Griffin: And there’s so many different systems that are overlaying each other now especially if you’re an enterprise client.

[00:02:51] Jim Griffin: By enterprise, our industry would term it an organization with over 5, 000 employees. When you have over 5, 000 employees, you have [00:03:00] complexity and complexity. And when in that category, almost nine out of 10 of any client in that category has invested heavily in one of three.

[00:03:12] Jim Griffin: Very capable talent platforms. Workday, SAP SuccessFactors, or Oracle. Then there’s tier 2, which is ADP, Ceridian, UKG, Infor. In the top tier category, Clients get upset when they uncover that the solution they overpaid for is not going to comprehensively cover recruiting engagement, for instance.

[00:03:39] Jim Griffin: Suddenly they need a Phenom or a Beamery or an Averture that has to overlay the ATS that they’ve overspent for. And they’re typically not happy about it. They don’t fully understand why it’s not covered. Innovation never ceases and there’s a tremendous amount of innovation within this HR ecosystem.

[00:03:59] Jim Griffin: Every time [00:04:00] you create something cool, they’re looking at the triangle of time, resources, and money and deciding in the finite spend that they can on development. Typically, it’s not just going to be in candidate engagement. They’re going to look at something far more impactful for return on investment.

[00:04:19] Jim Griffin: So that’s when you see either an investment in third party tools or the ecosystem start to consolidate and buy up a lot of these tools and become part of the larger ecosystem, the highest, Or top shelf happens to be SAP, Workday, or Oracle. They rock the entire ecosystem.

[00:04:41] Jonathan Duarte: I think it was Bennett Sung who said this as a startup you’re doing innovation.

[00:04:45] Jonathan Duarte: As you get into enterprise, innovation turns off and it’s integration. It goes from innovation to integration and then you have another wave of innovation from a different vendor who [00:05:00] then gets integrated. It all starts at the bottom, trickles up, and it’s all get back into the top of the funnel, right?

[00:05:06] Jim Griffin: And the latest example we saw was HiredScore getting acquired by Workday. I think that’s going to be a positive disruption. They’ve internalized some of the decisioning as it relates to scoring and matching technology where AI is at the forefront.

[00:05:22] Jim Griffin: What we’re about to talk about is what’s, what is the EU going to do regarding legislation with this new AI set of rules that is four times more onerous especially as it relates to penalization. than the previous GDPR ranks, which is still having a massive impact around all HR systems and source of record.

[00:05:46] Jonathan Duarte: Yeah, so let’s, we’re going straight into this, but let me set the tone for everyone. Jim and I and others in the HR tech influencer, partner network. A lot of us talk to each other and we have a group, and Jim, on one of our calls, [00:06:00] was talking the other day about the EU and its impact and so I said, Jim, we gotta get on video no one is talking about this stuff, even in the ecosystem of HR tech, No one’s talking about the EU side because it’s almost like we’re just putting our head in the sand and waiting for them to tell us exactly what’s going to happen, which happens.

[00:06:23] Jonathan Duarte: But the other side is you still have to plan for it. And the reason I think that you’re an expert on this from an interesting perspective is that, the ecosystem and you’ve seen GDPR’s impact over the last eight years or so this is, going to be a completely different And way more substantial change.

[00:06:44] Jonathan Duarte: Why don’t you lay it just like we were talking about in the green room what got you interested in it and how’d you start looking at the EU stuff?

[00:06:51] Jim Griffin: About six years ago I was working for a small boutique in the SAP SuccessFactors ecosystem.

[00:06:59] Jim Griffin: [00:07:00] We sold our company to a much larger one within the ecosystem. I spent the required year and a half there and then I was looking for what’s next. I did a lot of intense review around what was coming, and I saw this new thing almost seven years ago, it was formatively AI, and the impact specifically around skills.

[00:07:23] Jim Griffin: Now, anyone that’s been in the space for a long time, skills is like the DNA. I don’t care if it’s recruiting, HRES, goals and performance, compensation, learning, skills is at the root level in every single one of these things. And if you buy a platform such as SAP or Workday, it comes if you get all of the talent modules that I just referred to.

[00:07:48] Jim Griffin: Ultimately what you’re buying is a whole bunch of workflow. Each one of those workflows is informed by a compare and contrast on typically [00:08:00] the job or the role, and then the talent profile. And that talent profile can be a candidate profile, it can be an employee profile, it can be an alumni profile or former employee, and it can be a temporary or a contingent profile.

[00:08:14] Jim Griffin: But they’re essentially the same. And at the root of all of those, are a set of tables which describe the talent or describe the role. Root level of both on whether it’s the left side or the right side are skills. And they’re doing a compare and contrast, looking for the delta, and then informing you so that you can make decisions on that workflow, whether it’s a pay for performance and comp decision, end of the year performance review, so it’s timely to talk about that.

[00:08:44] Jim Griffin: One of those inherently has a skills. this analysis. Yep. Because skills informs what’s required based upon the tasks in the role or what level experience and the proficiency in that skill [00:09:00] that gives you a level of readiness or your capability to execute or in a look back how well you did in these tasks tied to this role.

[00:09:08] Jim Griffin: Then you’re scored. You might get graduated into a more comprehensive role. Or you may be put on a performance improvement plan, but ultimately all of these things root level looks at the skills tables. Now, I spent all of that time because what AI does, and there’s multiple forms of AI for HR purposes, I’m going to look at generative AI and then AI ML.

[00:09:35] Jim Griffin: AI ML was first. What that does in machine learning and a deep neural network. as it relates to skills. JD, you may have submitted your resume, your CV, at, the root level in your CV, are the skills that you’ve learned and the level of aptitude that you have within those skills.

[00:09:55] Jim Griffin: On the other side is the job description, if this is a talent acquisition [00:10:00] scenario, they’ve got skills that are required. Assuming they put the right skills on that resume, which I like that assumption. But say there are three skills that A. I. from machine learning you didn’t have on your resume, but through the process of normalization, which is what deep neural network will do.

[00:10:20] Jim Griffin: It can infer that J. D. Has these three likely skills. That you did not overtly post in your CV, but now it’s adding those and now the system can match and score you based upon the skills in the job and the skills to you more accurately depicting your fit for that role. So it’s a massive impact because that was not capable and you’re automating something that never existed.

[00:10:52] Jim Griffin: The other side of the equation is the job description itself. If the job role is informed by the [00:11:00] tasks required to execute that role, Generative AI can look at the job, both the name and the tasks, and generate the entire job description. With the tasks there, it’s now informed on the skills necessary to execute that task and recreate that entire job description on the fly.

[00:11:22] Jonathan Duarte: And I’ll do it in super layman terms Skills are the stuff that we do. The abilities that we have. I don’t write on my resume the stuff that I know how to do. It would be a bible, right?

[00:11:37] Jonathan Duarte: And no one would want to read that. So our advertisement as a job seeker does not have the Bible behind it of all the stuff that I know how to do. But the computer can infer that if I say I was senior product manager of conversational AI at the largest healthcare system in the United States, [00:12:00] it probably knows enough about what that means,

[00:12:03] Jonathan Duarte: but that’s that mapping behind it. As a recruiting team member, helping build those job descriptions that we’re going to put into the computer or advertise it can know that if you have a position that talks about JavaScript and there’s some new technology that requires JavaScript, but someone doesn’t talk about JavaScript on their resume, it can figure that out.

[00:12:23] Jonathan Duarte: This is a technical example. You really helped me clarify something about using Gen AI as far as building job descriptions. Because there’s a lot of people using ChatGPT and, generative different bars and whatnot to build job descriptions. And I think what’s critical that you mentioned was, You have to play with this stuff.

[00:12:43] Jonathan Duarte: It’s just not going to spit out the first time, but if you take your existing job description, put it into generative AI and say, Hey, spit me out. This is what this person’s going to do. And then you work with your team lead or, your client as a manufacturing lead or the [00:13:00] salesperson and say, look, this is what I put in.

[00:13:02] Jonathan Duarte: We’re gonna play with this thing in Gen AI and see if we can get the skills that you want see if we can pull that together. That’s a critical distinction because that’s where we’re all going. The tools are already starting to give everyone that stuff, but there aren’t that many people who know how to use it that way, that’s the next step.

[00:13:21] Jim Griffin: I always try and simplify it down you’ve got skills which inform the job and skills which inform the talent. The old term was readiness, but potential needs to go to high performing. The level of proficiency tied to the skills aligned to that role is your readiness and your capability to do the job.

[00:13:41] Jim Griffin: AI on both sides is improving the description and the resume, and then it’s doing scoring and matching at scale. It can look at your fit for that job and every other job that may or may not be open in the [00:14:00] entire organization. This is what we found about, skills based hiring

[00:14:04] Jim Griffin: better fits, but hey, there’s these seven positions we’ve recognized. Now, if you start looking at reductions in force, most organizations are trying to save employees. They don’t want to pump and dump, right? I’ve seen organizations have to restate earnings in a single quarter to the tune of multiple millions of dollars because of what I’ll term the repatriation rate.

[00:14:26] Jim Griffin: In a rift of 20, 000 employees, which unfortunately is happening, you’re trying to save as many of these folks that want to be at your company. You have to do this reduction, but at the same time, you know that you immediately need or will shortly need all of these other roles filled that aren’t impacted by this RIF.

[00:14:46] Jim Griffin: And if you can find adjacencies and readiness from a skills match and fit, companies generally, had maybe a 22 percent success rate in repatriation based upon adjacent roles, but now [00:15:00] they immediately have the ability to raise it up to 49 percent because they could immediately see the fit at scale for everyone impacted by that RIF.

[00:15:10] Jim Griffin: Unbelievable positive outcome from that It costs a lot to have to reduce an individual because you’ve got to pay up. Oh Comp and benefits.

[00:15:19] Jonathan Duarte: It’s a huge issue to the corporate culture

[00:15:22] Jim Griffin: that is a significantly positive outcome of a very negative event So things like that can now be automated with this technology.

[00:15:32] Jim Griffin: That’s a high side. Now everyone’s talking about ethical AI. We’ve always had algorithms to help us do a lot of these formative decisioning. Ultimately, you want better insights, whether it’s for talent acquisition decisions or talent mobility decisions.

[00:15:51] Jim Griffin: And you want to be as informed as possible before you make a decision. regarding the company and the people that you have, or [00:16:00] the potential talent that you’re going to be bringing in. That’s simply stated what these technologies can do. When misapplied, you can add bias into that decisioning.

[00:16:11] Jim Griffin: And where we’ve seen AI go wrong is when you let it loose and you don’t manage it and attend to it and keep it in its swim lane, so to speak. And you can make bias laden decisions that have unfair outcomes on certain people. Whether it’s gender, whether it’s race. to the point where some organizations are even masking the picture and the gender in early stages for talent acquisition decisioning or talent mobility decision.

[00:16:42] Jim Griffin: The EU has recently come out with a large set of regulations that actually have penalties four times more onerous Then what we see in GDPR and anyone that’s had, lived in everyone in a [00:17:00] space for human capital management knows exactly how impactful GDPR has been on our space.

[00:17:06] Jim Griffin: Ultimately, the underlying objective was protect personal information. Very laudable objective. Very difficult to execute in the day to day operations of enterprise HR because you’re dealing always with personal information. Now we’ve got the EU putting its sights, and it’s not just limited to the EU.

[00:17:27] Jim Griffin: New York started this, California’s in this. We’re going to see similar legislation around ethical AI applied to hiring and talent decisions in the US. They just did it first. And once again, it’s got its sights squarely focused on AI in decisioning for hiring. It is looking and evaluating every company that has applied AI for insights, whether it’s on the job [00:18:00] description or the talent profile itself.

[00:18:02] Jim Griffin: If you are using AI to help inform you on what that is, that’s where that legislation is squarely focused. Now, why do we care? We’re still in about 10 percent penetration. We’re still in early stages for AI applied to human capital management. Everyone’s talking about it, but everyone’s a little bit cautious because it seems like magic.

[00:18:26] Jim Griffin: How can it tell me that JD is the most qualified person? I see his resume I’ve got to validate and verify what’s on his resume. And then I have to make sure that my job description, most companies have. 10 times more roles than they need. They suffer through trying to sometimes it’s down to the job description.

[00:18:47] Jim Griffin: It’s a hundred times more than what they need. Can you imagine? Your company’s that large that you’ve got 100 different iterations. of a very similar job description. That actually happens. They need to [00:19:00] consolidate that into a more reasonable fashion. AI can be used for that, as we mentioned before.

[00:19:06] Jim Griffin: Now we’ve got this legislation, companies are going to have to make sure that they are aligned to what is ethical AI, how am I in alignment, and how is this solution that I’m considering adhering to this new legislation. And by the way, what other new legislation are they considering in U. S.

[00:19:30] Jim Griffin: regulatory and compliance or other countries? Everyone’s global. If you’re falling into that category that we mentioned before, you’re over 5, 000, you are absolutely impacted by all of this.

[00:19:42] Jonathan Duarte: Yep. And it’s going to be even like in New York now, over 50 employees or something like that?

[00:19:48] Jonathan Duarte: 144?

[00:19:50] Jim Griffin: And that’s a great point. In some places it’s 50, other places it’s 100. And you think of hiring decisions way back when, similar, right? When you have EEOC [00:20:00] rights, when you have to go through all of the basis for decisioning around gender and race how you source this candidate, and you have to report on it.

[00:20:11] Jim Griffin: Similar guidelines are being leveraged as it relates to AI decisions. Specifically talent acquisition it’s literally called the red zone in the EU regs. Wow. Got there squarely on AI, helping to inform you on decisions for hiring.

[00:20:36] Jonathan Duarte: So this is I like this.\ I guess the biggest way of saying this is, in the late 90s, I think was it 99 when OFCC came about, or was it 2000 when they made the decision on the definition of a candidate and the tracking at that point? Yeah OFCP compliance, etc. If we look at that,

[00:20:54] Jonathan Duarte: I would say that regulation was the start of the applicant tracking system en masse. That [00:21:00] probably forced it.

[00:21:01] Jim Griffin: Formative years were spent selling payroll. You know why ADP is so big? Not because they process payroll better than anyone else, because they assuage regulatory and compliance in all of these workload decisions.

[00:21:17] Jim Griffin: Tied to paying people all the way down through tax filing. And if they screw up your tax filing, they’re on the hook for whatever penalty applies. That is huge for decisioning in whether you choose this company A or company B. It’s because of their willingness to assuage you of the compliance adverse impact.

[00:21:40] Jim Griffin: We’re going to see a huge number of organizations pop up, aligned to compliance as AI is never going away. Pandora’s box has been opened, and there is way too much positive impact. We’re going to see a lot of fits and starts in this space [00:22:00] based upon emerging compliance and regulation tied to this new magic capability.

[00:22:06] Jonathan Duarte: Yeah, this is great. I think one of the next things I’ll have you on, cause I know we got to cut short, but I’ll have you on again, I think one of the next things I want to talk about is what this is actually going to look like. We don’t know everything yet, but we can start planning out what’s ethical AI.

[00:22:23] Jonathan Duarte: From the VP of HR’s perspective and VP of Talent, when they’re looking at, their vendors and they have to talk to the vendors. They have to start engaging to say, how are you solving it? How are you thinking about it? Because this is stuff that’s here. The question is, how are you going to respond and create your game plan?

[00:22:43] Jonathan Duarte: Because you said, if you got 10, 000 job descriptions And they’re all in multiple languages. How are you going to consolidate that so you can match this to this, if you don’t know what’s over here, how are you going to match this? So there’s definitive steps that people are going to, have to take.

[00:22:59] Jonathan Duarte: [00:23:00] And no one’s talking about that yet. I think we’re going to start seeing this, and there’s going to be vendors we’ll help. But there’s lots of these little crevices that aren’t going to be crevices anymore.

[00:23:11] Jim Griffin: It’s an onion. The more layers you peel back, you see a level of sophistication.

[00:23:16] Jim Griffin: We’re already wrestling with these issues. Look at Accenture, and you’ve got, what, eight, nine hundred thousand employees globally now. Seventy billion company. I think they hired, in the last year, a hundred and fifty, a hundred and seventy five thousand people. That’s unreal. And that’s just one company.

[00:23:34] Jim Griffin: Interestingly, I’ll give a shout out to IBM, because they are thinking about this, and they’re the godfather of AI. All the way back to Big Blue and a chess match. But with Watson X, they are indemnifying decisions.

[00:23:50] Jonathan Duarte: That’s what you mentioned.

[00:23:50] Jim Griffin: They are ahead of the curve. And I don’t know how many companies, you’re never going to see this from a Beamery or an Eightfold.

[00:23:57] Jonathan Duarte: They can’t do it anyways.

[00:23:59] Jim Griffin: They can’t because [00:24:00] even the penalties from the EU tied to hiring decisions are more than any company can risk. So it may halt somebody’s desire to move forward with one of these technologies.

[00:24:12] Jim Griffin: Because now they have to understand these regs because they’re already in a global economy.

[00:24:17] Jonathan Duarte: Yeah, it’s interesting. I met Jen Kilpatrick at IBM. She is in charge of ethical AI or responsible AI, speaks at the Davos Conference and World Economic Forum.

[00:24:33] Jonathan Duarte: She’s going to come on the show. I think that’s going to be a great one. My guess is we’ll probably have panels after that, because this is going to be one topic we’re going to talk about for a long time. If we can get the best and brightest to start opening it up and sharing the word.

[00:24:47] Jonathan Duarte: That’s, my goal in life at this point.

[00:24:49] Jim Griffin: When you become an enterprise company you take on the world of risk because you’ve built something. And if you’re public. Risk has to be internalized because [00:25:00] you’ve got shareholders, and if you’re found to have made decisions that adversely impact your shareholders, it’s going to be significant.

[00:25:11] Jim Griffin: IBM coming out and indemnifying through Watson X. All of the AI based decisions is huge and they’re trying to lead the way. I don’t know if anyone has considered anything like this.

[00:25:25] Jim Griffin: And the ability to indemnify at scale, very few companies could ever even begin to imagine how onerous that’s going to be based upon the penalization outlined in just the EU regs. Once again, that’s the first shot in this face. Yeah, there’s a lot more to come. So it’s going to be very interesting because now you’re going to have to be very well informed before you make any buying decision on how well aligned this is to global regs and compliance In context of [00:26:00] AI informing decisions, whether it’s hiring or talent mobility.

[00:26:05] Jonathan Duarte: Awesome. Jim, what’s the best way for our audience to reach out if they have questions to find you?

[00:26:11] Jim Griffin: So find me on LinkedIn, Jim Griffin. I’ve been a figure in this space for a long time. Where I’ve been having the most fun lately is consulting, ecosystem integration working with organizations build.

[00:26:28] Jim Griffin: And ideally, you’re doing this early, not late. Build out a ecosystem strategy, and what I mean by that is, what type of partnering elements and infrastructure do you need in order to outcompete whoever else is in your space?

[00:26:44] Jonathan Duarte: Yeah, I love that stuff. You and I could sit at a bar for a week straight, depending on how much the credit card could hold, right?

[00:26:51] Jonathan Duarte: Just talking about integrations in HR and in pipelines so I know

[00:26:57] Jim Griffin: We’re gonna need some good bourbon for that JT.

[00:26:59] Jonathan Duarte: Oh, I got three bottles over there All right, so [00:27:00] we’ll definitely catch up and love to have you back. Thank you so much for your time Jim This has been fantastic

[00:27:05] Jim Griffin: My pleasure, JD.

[00:27:06] Jim Griffin: Thanks for having me.

[00:27:07] Jonathan Duarte: Thanks for spending your time here with GoHire Talks and listen to our guests. My intention has always been to create incredible content to help you in your career in recruiting and marketing, business and leadership. We appreciate all of the insights and feedback you provide. If you’ve got guests you’d like us to have on the show, please let us know.

[00:27:26] Jonathan Duarte: Again, thank you for all your support.