[00:00:00] JASON C: No, that’s all right. Well, here’s what I was going to ask is that when you talked about shifting the mindset around go live to go now, and you know, it’s not the goal, it’s the beginning. I’ve also heard you talk about using the terms implementation and deployment. Very differently, that what implementation means versus what a deployment means and how people need to think about these things differently and they serve different purposes.

[00:00:20] JASON A: So, you know, and just, and once again, terminology is so important to you guys.

[00:00:23] LIGIA: Mm

[00:00:24] JASON A: It really is in everything we do. I mean, you know, as a parent, you know, of teenagers, how I phrase something, I think, I don’t know, I don’t know if you guys

[00:00:35] JASON C: Has a big impact, yes.

[00:00:38] JASON A: how you phrase things have, have major impact. And sometimes we’re careless. In my personal opinion, with language. So, you know, in my mind, implementation is the implementation of the technology. Deployment is the deploying of a strategy. Okay, so if I have a strategy that says I’m going to do X, Y, and Z, how do I deploy that strategy? Part of deploying my strategy is the implementation of technology.

[00:01:10] Okay, but there’s other things that go into the deployment. Like changing the mindset. Et cetera, et cetera. So oftentimes we find that we work with organizations where they’re like, we’ve, you know, we’ve budgeted two X the price of the software for implementation. And I’m like, okay, cool. Let’s see the implementation plan.

[00:01:31] And the implementation plan is only the flipping the switches of the technology. And I’m like, well, where’s the change part? Where’s the rest of it? Did you guys see those balloons that all of a sudden popped up on my screen? That was a little bit weird. I guess. Someone liked what I said, but, you know, all of a sudden, you know, you start saying deploying is a is a much longer program

[00:01:56] LIGIA: Mm hmm.

[00:01:56] JASON A: than just the implementation of tech implementation of tech might take three months, but the deployment of a strategy might take nine months to get people bought in, et cetera, et cetera, et cetera.

[00:02:06] So Jason, thank you for that question. That’s why that’s what the way we phrase this is. And by the way, implementation of technology is much easier Than deploying a strategy. And what I don’t like to,

[00:02:19] LIGIA: the Yeah,

[00:02:19] JASON A: oops, sorry. Go ahead.

[00:02:19] LIGIA: No, no, finish what you don’t like.

[00:02:19] JASON A: What I don’t like to do is I don’t like to put too much weight on the technology.

[00:02:24] ’cause if you only implement technology, you stand it up and all of a sudden you don’t achieve the outcomes, then who do you blame? The technology.

[00:02:33] LIGIA: Mm hmm.

[00:02:34] JASON A: And that every time you blame the technology, basically what you, the next thing you do is say, Hey, we need to do an RFP for new technology. Someone goes out and buys new technology to do the same thing, and all of a sudden they’re like, this isn’t any better than the last technology.

[00:02:48] So it’s really important that we think that in a different kind of way.

[00:02:52] LIGIA: Any practical, I was just thinking two things, because I think it’d be easy to get overwhelmed, with some of this, the changefulness and rethinking and really about driving business outcomes. What’s your practical advice? I’m thinking on two topics. One is to drive the alignment with the business, but also to drive that different mindset to be able to reframe a lot of that change that we’re driving towards business outcomes.

[00:03:15] Where, where do you see your clients getting stuck?

[00:03:17] JASON A: Well, you said that actually earlier, not, I mean, in a better way than I, I mean, you have to keep the lights on.

[00:03:18] LIGIA: Yeah.

[00:03:19] JASON A: So, you know, the day to day, while you’re doing the day to day, it’s really hard to take a step back

[00:03:26] LIGIA: Mm-Hmm.

[00:03:27] JASON A: and say. I’m going to think different, okay? So, the first thing is, is, is, is making the space.

[00:03:35] That’s what I call it. Making the space to think a little bit different. The second thing, Leah, that I see organizations getting stuck on quite a bit is benchmarks.

[00:03:47] LIGIA: Yeah.

[00:03:48] JASON A: And I hate to say this, and I, you know, there are going to be some of my friends who are benchmarkers, quote unquote. that are going to be mad at me.

[00:03:58] But benchmarks are, actually, let me rephrase that. Benchmarks are important because they can help you understand a perspective. But every organization has its own unique signature.

[00:04:08] JASON C: Correct.

[00:04:09] JASON A: And I think it’s very dangerous to say, hey, because X did this, I should do it the same way. And, you know, that’s not, I mean, that’s like saying that, you know, hey, the way that you Go out to dinner with your spouse.

[00:04:24] You have the exact same conversation as the person at the table next to you. Like everyone, everything, there’s different cultures, there’s different histories, there’s different things going on at the current moment. Etc. Etc. That I really want to understand what my unique signature is and we’re watching this right now with skills You guys is where people like hey, we we’re gonna become they just became a skills organization So we’re gonna become a skills organization.

[00:04:49] I’m like, okay, hold on

[00:04:51] LIGIA: Mm-Hmm?

[00:04:52] JASON A: What’s your why and I want to get too deep into a Simon Sinek discussion here but like why do you want to become a skills-based organization a and the answer shouldn’t be because my competitor is It’s something you have to believe in, and it’s something that you have to actually think through.

[00:05:10] So that’s the second thing, where do I see organizations struggle, is that. And then the third place where we see organizations struggle is understanding that this concept of, I call it a shiny object syndrome, where people, you know, all of a sudden, yeah, you know, hey, there’s a, I just saw this amazing piece of technology.

[00:05:31] Cool. Awesome. And let, let’s go buy it. Cool. Awesome. Without understanding what it takes to make that techno, what’s the fuel that, that, that fuels the car. Okay. In most cases in today’s world, the fuel that fuels the car is data.

[00:05:51] LIGIA: Yeah.

[00:05:51] JASON A: And if I don’t have good data, my car is not going to move. If I use that fuel analogy, does that make sense?

[00:05:58] So we watch vendors all of the time that will do great demos. And like, this is once again, where I said we have the best technology in the world we’ve ever had. In the, all of the time I’ve been doing this, but what we don’t understand is that we don’t understand what the fuel is required on our part in order to make that technology work.

[00:06:19] And then people get disappointed in the technology. So, yeah, I’d say those are the three things. Is the alignment to the business, not what matters to HR, but what matters to the business. B, making sure that I truly think through that concept of the value. And then C, what’s going to be required. To make it run.

[00:06:39] LIGIA: Mm hmm.

[00:06:39] JASON C: touched on the skills based topic, but we’ve been talking now for some time and have yet to mention generative AI. So, I want to ask you a couple questions around generative AI and get your thoughts. I know a few weeks back you even posted, something on LinkedIn that was you speaking delivering a video, and it was entirely created by generative AI.

[00:06:52] So when we think about organizations transforming and transitioning to try to become skills based, there’s also a lot of them that are trying to get their arms around understanding generative AI. What are, what are your, some of your thoughts on that, Jason?

[00:07:03] JASON A: Oh, man. What a great question. I was how much time do we have? So I don’t know if you guys know I mean basically it I don’t know when this when the podcast is dropping But generative AI is basically a year to a year and two months old You know about when it comes to how long it’s been available to the public Okay And when we think about that behind the scenes generative AI has been being developed as neural network models for 30 to 50 years Okay, what we haven’t had is we haven’t had the technology to bring it to life.

[00:07:28] Now, lucky enough, somewhere down the line, in my PeopleSoft days, I started studying neural networks. So I’ve been studying them for a long time. I’ve been knowing this is coming for a long time. And if some of you have ever heard me speak, I’ve been trying to get people to say data is sexy for a long time.

[00:07:44] Not because I want people to do better single dimension reports. Because we knew eventually that the time would come where I would be able to start to use data to have conversations and to be able to make bigger impact than what I’ve been able to make in the past. Generative AI now is, like I said, a year to a year and a month old, or a year and a quarter old.

[00:08:09] And if you think about your kid at a year to a year and a quarter old, what could it do? It could maybe walk, and it could maybe say two words. Okay? Generative AI today is in the same place. It’s in an early, early phase as far as the impact that it’s going to have, people seeing the value that it can have.

[00:08:28] But it is also in that OSM moment, oh shoot moment, where it’s like, whoa, this is going to be different. Now, you all probably remember moments with some form of thing in your life where you had that oh shoot moment. Where all of a sudden you’re like, whoa, this is going to change things. It could have been the first time you saw a phone.

[00:08:52] It could have been the first time you went on America Online. You know, the CD ROM fell out of a magazine. You’re like, oh, I wonder if I put this in here, what’s going to happen? You know, all of a sudden you got that. It could have been the first time you used a mouse. It could have been the first time you sent a fax.

[00:09:06] But we’ve all had these oh shoot moments where we’re like, and that’s not, by the way, the S means something different usually when I speak, but I’m being clean. The, the Generative AI is an oh shoot moment. Okay? You know, it was like, whoa. I mean, I asked my kids, the first time I ever went on ChatGPT, I showed them something, they’re like, Oh my god, I’m never gonna have to write a paper again.

[00:09:17] LIGIA: yeah,

[00:09:18] JASON A: And I’m like, wrong. But, it was an oh shoot moment. So if we think about generative AI, Generative AI is our printing press moment of our time.

[00:09:29] LIGIA: mm hmm,

[00:09:31] JASON A: And it’s going to change every single job in the world.

[00:09:35] LIGIA: that’s right,

[00:09:35] JASON A: Okay? Like, stop wondering if it’s going to.

[00:09:41] LIGIA: embrace it,

[00:09:42] JASON A: Right. Stop wondering if the government’s going to put regulations on it that’s going to say, Oh, uh, let’s dial back, you know, everything we did, forget about it.

[00:09:54] You know, we’re past that moment. It’s, it’s, it’s working. Okay. Now, is it going to get better? Is it, are we going to learn? Are we going to have governance? Yes, yes, yes, yes, yes, yes, yes, yes, yes, yes. But generative AI is our printing press moment of our time. Okay, it will make, it’ll have the biggest impact, DOS, Windows, Client Server, Internet, all of those things impacted the IT organization. For the most part. What generative AI do it is going to do, excuse me, is it’s going to impact the function, It’s going to impact the business, and it’s going to impact the workforce more than any of that other stuff did. Okay? It’s our electricity moment. So all that being said, right now, based on what it does, our main job is to educate.

[00:10:42] Okay, and Jason, like you saw that video, I posted that video only as a purpose to say, guys, careful what you trust.

[00:10:51] LIGIA: yeah,

[00:10:52] JASON A: Okay, because you could watch a video of something, someone saying something, thinking it’s them and it’s not them, okay? Now that, by the way, that’s not meant to say don’t do it. That’s meant to say that you don’t go from everything that you see is human to everything you see you don’t have to have a human, okay?

[00:11:16] There’s a major concept with generative AI that not enough people think about, which is this concept of human in the loop, HITL, okay? There’s a reason that generative AI has tools called co pilots, not pilots. The co means you still need a pilot. There’s a reason they’re called second brain, not first brain.

[00:11:37] It’s not your only brain, it’s a second brain to help you. Okay, so generative AI will change all of our jobs. But, it’s really important to understand it’s going to amplify us as people. It’s going to make our jobs and lives more rich as people. It’s not going to replace us. You’ve all heard the quote, hopefully generative AI is not going to replace us, but it’s going to replace people that don’t know how to use generative AI.

[00:12:08] JASON C: Sure.

[00:12:08] JASON A: Okay, and I think that’s a, go ahead.

[00:12:08] LIGIA: Do you think this is going to be then the impetus to help, maybe HR understand the need to move to skills? I mean, I just think there’s anyone on earth who hasn’t heard about generative AI at this point and hasn’t experimented with it and used it, like you said, at their own risk in their jobs, I think we see multiple examples.

[00:12:29] But is this going, do you think this is going to be the big thing that’s going to make, accelerate that shift to skills?

[00:12:35] JASON A: Yes, so, uh, to answer you, if I just wanted to answer your question in one word, yes. Uh, if I could expand on it quickly, the generative AI part is not the skill that’s going to do it, but generative AI is going to provide the visibility. into the fact that I can’t see what skills my organization has.

[00:12:55] LIGIA: Mm hmm.

[00:12:55] JASON A: I can’t see, or I will see, where my gaps are more than I’ve ever have before.

[00:13:02] And I will start to do talent planning and workforce planning in different ways than I’ve ever done it before because of the visibility that generative AI is going to give me.

[00:13:14] JASON C: Yeah. I think, I think one of the things that I’m interested in is right now we’re at, we’re at a time where people are thinking from themselves first, how does this going to impact my, my job and the work that I’m doing? But we’re getting to a point now where we need to start thinking beyond that to say, how is it impacting everyone else’s job in the organization in which I work?

[00:13:34] Because at the core of it, my job is to help them in their job. So part of the impact of generative AI in changing the way everyone is going to get their job done, leads towards a conversation around understanding skills, because the skills you’re going to use to help support those businesses and support those roles.

[00:13:52] is going to change and the work they’re doing is going to change. So you have to start to understand it at the skills level to understand how the work is changing and you can’t rely on a job description and you can’t rely on how the manager did it yesterday because how it’s going to be done tomorrow is different.

[00:14:07] So I think these conversations, this is why they’re, they’re starting to get closer and closer aligned.

[00:14:12] JASON A: Yes, yes, and, but, I also want to add one more thing to it, which is, we’re not dealing with machines.

[00:14:21] JASON C: Correct.

[00:14:22] JASON A: Okay, so, you know, I have a broken dishwasher at home right now. My date night tonight is going to be going with my wife to look for a new dishwasher. I, on my phone, she texted me the measurements not that long ago.

[00:14:31] For me to match a new dishwasher to the old dishwasher, it’s fairly easy, right? People are different. People are much more nuanced and complex than that. Okay? So, does that make sense?

[00:14:48] JASON C: A hundred percent.

[00:14:49] JASON A: There’s a mass, right now, there’s this massive, we’re watching this thing called FOBO. Which is the fear of becoming obsolete.

[00:14:56] Okay? And I’m worried about it. Because there are people who are not exploring the powers of generative AI. And the impact that it can have on the workforce, because they’re saying we’re going to lose our jobs.

[00:15:10] LIGIA: Mm hmm.

[00:15:11] JASON A: And that, does that make, so that mindset is really important to say, guys, forget what you read in the media for a second, about, hey, all these jobs are changing, because guess what, when the calculator came out, everyone’s job changed.

[00:15:28] Okay, when all of a sudden, you know, I had webcams, everyone’s job changed. Why? Because I could see them now. Generative AI out, everyone’s job’s going to change. That doesn’t mean everyone’s job’s going to go away. So when someone says jobs are changing, that doesn’t mean jobs are leaving. Does that make sense?

[00:15:47] They’re just changing. They’re becoming, hopefully, becoming more rich. So, like, we have to get over this fear of becoming obsolete. And this concept that, oh, we need to have all these AI people. Because We don’t need AI people. We need people that can reason. We need people that can add perspective. And we need to realize that what AI is going to do is it’s going to replace a lot of hands work so that we can do more heads work and hearts work.

[00:16:16] JASON C: Yep.

[00:16:17] JASON A: Okay? So, that just means from a people standpoint, it’s going to change the nature of what our jobs are and what we do.

[00:16:25] LIGIA: Don’t you also think that, Jason, I, I think it’s a great point that there is FOBO, and there could be a certain level of refusal to maybe adopt it, but don’t you think there’s also, of the, again, the, the amount of people who are actually experimenting with the amount of press coverage it’s getting, everyone understand it comes with inherent efficiencies.

[00:16:46] And I, I don’t know if it’s because I live in the tech bubble, but I think most CEOs, most functional leaders, COOs are going to be asking their different functions. How are you leveraging generative AI? How are you leveraging co pilots in your area to drive efficiencies?

[00:17:04] JASON A: Oh my gosh, Leah, that’s happening every single, I was on the phone with someone yesterday Who said that they’re, you know, because of generative AI, they’re going to reduce their size of their benefits department from 250 people to 50 people.

[00:17:17] LIGIA: it’s insanity. I was on another panel where it was like discussing, you know, where generative AI was, was being used across marketing. And I thought it was funny that people actually didn’t admit that whether or not they’ve implemented it with, you know, a formal sort of like, co pilot that comes with your software.

[00:17:37] The reality is everyone’s playing with it. Everyone is using it to do their job at some level of risk.

[00:17:43] JASON A: Totally, but, and, Leah, at the same time, I was at a dinner last week in Switzerland after Davos, where the conversation was, we’re going to wait to do anything until government regulations kick in.

[00:17:57] LIGIA: yeah, too

[00:17:58] JASON A: And, and, and I was like, um, um, um, um, hold on, like literally I couldn’t eat. Uh, at this dinner because like, whoa, whoa, whoa, whoa, whoa, whoa, hold on a second.

[00:18:07] Like the government doesn’t regulate how you use PowerPoint, right? You know, like the government doesn’t regulate how you send what you put in your emails. Okay. Now there are going to be parts, and this is why one size, a all, excuse me. One size AI descriptions doesn’t fit all. Okay. When I say AI, like 60 percent of the free world is going to vote in 2024.

[00:18:34] Could there be a massive and will there be a massive disinformation campaign leveraging AI? Yes.

[00:18:40] LIGIA: we’ve already seen that, yeah,

[00:18:42] JASON A: Yes. And is that going to make people say, I don’t trust generative AI? Yes. Is that something that technology vendors are going to have to overcome? Yes. Because guess what? People are going to say, Oh, we don’t trust it.

[00:18:55] We don’t trust it. We don’t trust it. We don’t trust it. Like guys, that’s different when you’re looking at the whole world interacting in a single large language model than a. Closed small language model that’s being used to move skills from one place to the other that the, that the rest of the world doesn’t have access to.

[00:19:15] And right now we’re in this moment where it’s just everything’s getting mish, sorry. No, I’m glad this is a podcast, no one can see that. Everyone’s getting mish, everything’s getting mis-hmashed together in just this big thing called AI.

[00:19:29] LIGIA: hmm.

[00:19:31] JASON A: is it’s causing a lot, it’s causing more people to not do it than do it.

[00:19:36] And what I, and my biggest fear is that because we don’t, we question some of this stuff so much, and I forgot which one of you said it earlier, that we’re, we’re used to dotting our I’s and crossing our T’s so much, that we’re like, this isn’t exact. Guys, it’s not supposed to be, art isn’t exact,

[00:19:57] LIGIA: Mm hmm. Mm

[00:20:00] JASON A: of these jobs, they are art.

[00:20:02] How do I communicate? How do I build connection with employees? That’s an art.

[00:20:10] LIGIA: Yeah, I mean, we can resist it from many angles, but I, I think it’s already upon us. I don’t think, I think the adoption rate has already shown. I mean, you, you can’t, you can’t assume it’s not gonna happen, and you can’t assume it’s not gonna be bottoms up and tops down at the same time.

[00:20:25] JASON A: Yeah, and Leah, just really quickly on that word you used, adoption, like, uh, value has already happened. Like, that’s what I want, that’s what I want people to talk about in my, like, I know what you’re saying with adoption, but I want people to say, and I’m hearing it every single day, I’m already getting value.

[00:20:43] LIGIA: Well, it goes back to your original comment, right? Which is, you talk about the change management and you’re like, well, I don’t need change management when I use LinkedIn, for example. I don’t need change management when I use your phone. And guess what? You don’t need change management to get, use chat GPT in front of your son

[00:20:58] JASON A: Yep,

[00:20:58] LIGIA: because it’s that easy to use.

[00:21:00] JASON A: exactly.

[00:21:00] LIGIA: an instruction manual.

[00:21:02] JASON A: Yep.

[00:21:04] JASON C: Now we’ve, we’ve covered a lot of ground here, Jason. And I know you’re talking to clients every day, as you mentioned Davos last week and all these other meetings, the retailer the other day. To, to kind of wrap things up and summarize for the listeners out there for the new talent code, to think if you were to give them one or two pieces of advice as takeaways around, around how to think, how to operate, how to manage differently.

[00:21:26] Are there any things that you’re seeing consistently? Uh, again, we just talked about and, and moving beyond tips and tricks, but I’ll go against myself and say, do you have tips and tricks that you can share with some folks out there in the audience?

[00:21:33] JASON A: So the first one that I would share really quickly is that it’s really, really important in a world of, I mean, in a world of HR, which is complex. Yeah. Yeah. It’s very complex, and it’s very multifaceted, is that HR, as a function, asks themselves and answers the question, what do we want to be great at, versus what is it okay to be okay at?

[00:21:59] Okay, it’s a really important question, because what ends up happening in organizations, unfortunately, in HR organizations, excuse me, because we have COEs, is every COE says they have to be great. And at the end of the day, no HR organization is going to be great at everything. So, you know, do I want to be great at payroll?

[00:22:21] No. I want to be performing, which means I’m 100 percent accurate. I don’t want to be 125 percent accurate. Do I want to be great at skills? Yes, if the organization is going to use skills. Do I want to be great at skills if the organization is not going to do anything with the data? No. Right? Because it, what’s the value?

[00:22:45] So it has to tie back to that strat, corporate strategy, business strategy, organizational strategy, and then the HR strategy to say what do we want to be great at? And I highly recommend you do this exercise with your teams. Sit in a room, say what do we want to be great at versus what is it okay to be okay at?

[00:23:04] And prioritize. And don’t do it every three years. That’s

[00:23:08] JASON C: Correct.

[00:23:08] JASON A: Do it every quarter at the minimum because that’s how fast things change. Does that make sense? So that’s the first thing. The second thing I would say is that it’s really, really important to understand that no matter what you’re doing, that you have a strategy that works east west, not north south.

[00:23:26] Okay? When I say that, what I mean is that you have a strategy that says, that you say, that says, data quote unquote, is runs East West. So, marketing data per se, to show the value of marketing on sales, do I just need marketing data? No, I need sales data. To show the impact of HR or a skill on business, what do I need?

[00:23:39] More than just skills data, I need business data. Does that make sense? So that East West perspective is really, really important to keep in mind when it comes to that concept of digital. And then the third thing I would just say is that education, right now, is the number one asset that an organization can invest in.

[00:24:02] Almost more than new people.

[00:24:04] LIGIA: you mean specifically education for HR? Yeah.

[00:24:04] JASON A: yes, I’m sorry, thank you, education for HR on how to design, on how to think about what does skills mean. On how to understand data, on how to tell stories, on how to think about the impact that AI and generative AI is gonna have and can have. So in order, you know, I, you know, Jason and I talked about, you said, and we mentioned earlier, unlearning.

[00:24:04] Now what’s next? Learning, you know, I, I don’t just unlearn , I have to learn how to build the future. So those would be the three things that I, you know, whenever I do sessions for HR leadership teams. You know once or twice a week. It’s constantly talking about those three things.

[00:24:04] JASON C: That’s great. Thank you for that.

[00:24:06] LIGIA: Love it. Thanks so much, Jason. Again, I think we could go on for another hour teasing each other, but delving a little bit more into this. So, I think we might have to ask you back. But, listen, this has been great. Really appreciate it. And, uh, we’ll see you next time.

[00:24:13] JASON A: Hey, Ligia and Jason. Thank you so much for having me and uh, the one thing I just did I can I just say one thing in closing I? Think the thing that’s so important is that We’re all human

[00:24:20] LIGIA: Oh, yeah.

[00:24:20] JASON A: You know and I you know, it’s that we sometimes forget the fact that Outside of work and inside of work are one

[00:24:27] LIGIA: Mm hmm.

[00:24:27] JASON A: And as we move forward, it’s really important we keep humanity at the center of everything we do.

[00:24:33] And if we do that, we’re going to end up achieving our goals in much more Empathetic and meaningful ways than if we do work the way we think of work in the past, which is just driving Financial means.

[00:24:51] JASON C: Well, I know you said you didn’t want to preach, but amen. Thank you, Jason.

[00:24:55] JASON A: Thanks you guys for having me. I really appreciate it.