#63: Workforce Risk – On Navigating Demographics, AI & the Changing American Dream の全文書き起こし

00:02:26.383 Wow. 00:02:26.383 --> 00:02:30.152 Well, I can say speaking for everyone that's listening to the podcast. 00:02:30.152 --> 00:02:37.526 I think there's going to be a lot of jealous minds when they hear you say you had a team of 50 people working on a team panel analytics over at FedEx. 00:02:37.526 --> 00:02:42.406 So I think most often it's a team of a third of a person working on people analytics. 00:02:42.445 --> 00:02:43.146 You're not wrong. 00:02:43.146 --> 00:02:45.693 Fedex is like a monster of a company. 00:02:45.693 --> 00:02:51.181 Most people don't realize that they have like 600,000 employees, and so 50 people is just a drop in the bucket there. 00:02:51.743 --> 00:02:53.167 Wow, wow, that's awesome. 00:02:53.167 --> 00:03:02.364 Well, quite an impressive background and I know that that shaped a lot of your perspectives on talent analytics, so super excited to dive in a little bit deeper. 00:03:02.364 --> 00:03:03.948 You alluded to it already, cole. 00:03:03.948 --> 00:03:06.693 So Lightcast puts out a lot of research. 00:03:06.693 --> 00:03:08.125 You have a lot of great data. 00:03:08.125 --> 00:03:25.348 One of the things we're excited to talk about is Lightcast really recently made some waves with its workforce risk outlook report, and so we've heard the phrase rising storm quite a bit, and it really finds that hey boy, a lot of these labor shortages are putting many companies in the Fortune 1000 at risk. 00:03:25.348 --> 00:03:34.568 So, before we really dive into it, maybe you could share a high-level genesis of Lightcast's new workforce risk outlook. 00:03:35.311 --> 00:03:43.248 Yeah, well, there's kind of a pre-story to the risk report that I think really shapes why this is relevant. 00:03:43.248 --> 00:04:02.752 And so and it starts with a colleague of mine his name's Ron Hetrick, I think a few years ago had written a research report called the Demographic Drought, and it started, for one of the first times, one of the few firms that started talking about you know what's going to happen to the labor force when baby boomers start retiring. 00:04:02.752 --> 00:04:07.140 And then, a few years after that, they published the Rising Storm. 00:04:07.140 --> 00:04:13.084 So this was last year and the Rising Storm just blew up, and so it was a continuation of the demographic drought research. 00:04:13.084 --> 00:04:19.747 But it's really difficult to summarize the Rising Storm because there was so much really good information in there. 00:04:19.747 --> 00:04:34.105 But talking about rising trends like AI, the baby boomer retirements, the population of college educated versus non-college educated, and how that's changing over time, immigration impacts just a variety of impacts on the workforce. 00:04:34.105 --> 00:04:47.605 And it got such a positive reception last year when they published that Everybody kept asking the question what does that mean for my organization, kept asking the question what does that mean for my

organization? 00:04:47.625 --> 00:04:57.653 And so that was the genesis of the workforce risk report, where we went through and we scored all of the Fortune 1000 companies on exactly how is this going to impact your organization over the next five to 10 years. 00:04:57.653 --> 00:05:03.228 And so it was broken down into four different categories of how their risk was qualified. 00:05:03.228 --> 00:05:06.935 The first category was the industry risk. 00:05:06.935 --> 00:05:10.187 So what's going on in your particular industry? 00:05:10.187 --> 00:05:19.403 Because everyone in the industry kind of suffers from the same problems and so some industries are more risky than others in terms of what they're going to lose. 00:05:19.403 --> 00:05:23.432 So think of the top three most risky industries are hospitality. 00:05:23.432 --> 00:05:29.105 The top three most risky industries are hospitality, their construction and I believe it's healthcare as well. 00:05:29.105 --> 00:05:30.487 And then you go into the market supply. 00:05:30.487 --> 00:05:32.872 So where does your company actually operate? 00:05:32.872 --> 00:05:38.699 So just because your industry is risky doesn't mean where you operate necessarily is or is not risky. 00:05:38.699 --> 00:05:45.553 And so we analyzed every organization where their top five locations that people were employed at their organization. 00:05:45.553 --> 00:05:54.610 And then the next was looking at the occupations within that organization, so looking at the top 10 occupations that a company employs. 00:05:54.610 --> 00:06:10.016 And so again, if you're a big healthcare organization, obviously we're looking at nurses and doctors and nurses, aides and all the top 10 occupations at a particular employer and saying what is the risk associated with them for their ability to staff over the next five to 10 years. 00:06:10.658 --> 00:06:18.264 And then the last and this is kind of a flip in terms of what you see in most organizations is the AI skills gap. 00:06:18.264 --> 00:06:23.062 And in this case a lot of people are like, oh, is AI going to take my job, is it going to automate what I do? 00:06:23.062 --> 00:06:41.351 But we actually see this in terms of optionality for employers, because if you have a shortage of people who are doing a particular job and AI can help augment those people to you know, one person doing the job of two people, that's actually a positive thing if you know you have workforce shortages. 00:06:41.351 --> 00:06:54.927 So the AI skills gap some jobs are more akin to have automation impacts than others and, frankly, if your organization AI is not going to impact you at all, that actually probably really increases your risk. 00:06:54.927 --> 00:07:09.204 And so that's a little bit of the background about the Workforce Risk Report, but it has been a fascinating piece of research and many, many organizations have had their eyes opened to what's coming in the next few years. 00:07:09.264 --> 00:07:16.432 Because I think if you had to kind of distill down what the findings of the report are, is the future is not going to be like the past. 00:07:16.432 --> 00:07:21.911 We've never seen anything like this in the history of the workforce in the world. 00:07:21.911 --> 00:07:24.750 And so, you know, birth rates are decreasing. 00:07:24.750 --> 00:07:28.129 The bigger generations in the past, like the baby boomers, are retiring. 00:07:28.129 --> 00:07:34.872 They're being replaced by smaller generations and there might just not be enough people to do all the jobs, like there always has been. 00:07:35.240 --> 00:07:44.149 Another example is think about college education, and so in the 2008 crisis, you know many people had less children, right? 00:07:44.149 --> 00:07:44.774 Well? 00:07:44.774 --> 00:07:45.175 Guess what? 00:07:45.175 --> 00:07:50.629 Those folks are turning 18 in the next two to three years, right? 00:07:50.629 --> 00:07:51.411 Well? 00:07:51.411 --> 00:07:53.682 That means college enrollments are about to plummet. 00:07:53.682 --> 00:08:02.471 What is that going to do to the future of higher education, and how many people are going to graduate from programs or going to the skilled trades over the next few years? 00:08:02.471 --> 00:08:11.548 There's just going to be less human beings that are able to come in and replace people who are retiring, not to mention all the impacts that are going on right now with immigration and all of that. 00:08:11.548 --> 00:08:14.805 But I'll pause there because I have been talking for a while. 00:08:14.805 --> 00:08:18.000 But it's some really fascinating research, wow. 00:08:18.021 --> 00:08:19.463 Yeah, a lot there to unpack. 00:08:20.184 --> 00:08:26.295 I love the simplicity of the risk index and the four major categories that you outline. 00:08:26.779 --> 00:08:36.947 I'm assuming, as is the case with most simple but powerful frameworks, it took a while to kind of distill it into those four, but it's kind of like peeling an onion. 00:08:36.947 --> 00:08:45.385 I think If you're doing great and have low risk in all four of those, then it's an easy answer, and if you're doing horribly in all four, then it's an easy answer. 00:08:45.385 --> 00:08:57.682 But you probably see some pretty interesting combinations where, say, an industry isn't particularly high risk, maybe it's actually very low risk, but due to the pragmatics of where the business is located, it's actually a high risk business. 00:08:57.682 --> 00:09:13.326 Or, conversely, you could have a company that hires occupations that aren't particularly competitive and they have a good position in the marketplace, but maybe the opportunity for AI to disrupt that industry is lower than any other industry. 00:09:13.326 --> 00:09:18.488 So I think there's just probably a lot of permutations that you see, and it allows for a lot of fascinating conversations. 00:09:18.488 --> 00:09:23.269 I'm assuming you looked at a lot more than just those four

before you landed on those four big buckets. 00:09:23.269 --> 00:09:23.591 Cool. 00:09:24.139 --> 00:09:27.129 Yeah, we looked at a variety of different characteristics. 00:09:27.129 --> 00:09:38.610 Some of this is just limited to the amount of data that's available, and I'll say one of the things that we've seen is you'll see different publications and they will focus on just one component of this. 00:09:38.610 --> 00:10:33.408 So they'll say, here are the following industries with the following risk, or here are the following companies that are going to be impacted by AI, and we thought it's like, and everybody's coming to the same kind of conclusions, but they're not looking at this data holistically, and so we thought we're really the only company on earth that can combine all four of these characteristics and what I'll call like hyper trends into one and then give every organization and say your organization, here's where you have to worry, and because we publish it out there for everyone to see, you can also worry in comparison to your competitors too, and so one of the things that we put out there is a graph of every company in a particular industry by the risk score and the revenue, and so you can see not only where you stack up, but where do all your competitors stack up as well, and who's potentially going to come eat your lunch over the next few years, because they may be at less risk than you. 00:10:33.408 --> 00:10:42.688 But another component is and I think, even the companies that have a lower relative risk score, that's in relationship to what they are today. 00:10:42.688 --> 00:10:58.501 So, basically, even if your score which every company score is above one, if your score, the scores are on one to five, one being less risky and five being more risky, if you're above one, which everyone is, that means you're at more risk than you are today. 00:10:59.023 --> 00:11:04.053 Right, and so literally every organization is at more risk over the next year. 00:11:04.053 --> 00:11:17.466 So that means that every organization is going to have to do something and some organizations are at more risk than others, and that can create competitive situations where some organizations can see one company's loss as another company's gain. 00:11:17.466 --> 00:11:31.413 But I would say the most important thing is for organizations to look deeply into their score, try to understand it and to take proactive steps to mitigate this, because the people who act quicker will be the winners. 00:11:31.413 --> 00:11:40.409 The other thing, and I'll say here too, is we scored the Fortune 1000, but we have this data on virtually every large organization much beyond the Fortune 1000. 00:11:40.409 --> 00:11:49.562 So there's a link you can actually click in the report that can say hey, I don't see my organization here, and Lightcast will actually reach out to you and show your organization's data as well. 00:11:50.043 --> 00:11:55.057 Wow, okay, every time you respond it's like a spider web. 00:11:55.057 --> 00:11:59.789 I have like six more questions I want to ask, but we'll try to keep it focused here. 00:11:59.789 --> 00:12:02.221 I really want to ask you some more about the sausage making. 00:12:02.221 --> 00:12:03.304 That goes into that score. 00:12:03.304 --> 00:12:14.615 But maybe we'll do that offline and keep it a little higher level for our audience and maybe on that point we could unpack some of these big risk factors or trends that you kind of called out. 00:12:14.615 --> 00:12:17.168 So AI, obviously that's a huge one. 00:12:17.168 --> 00:12:23.047 I do think it's interesting what you said about it being sort of the converse of what we typically think about when we think about AI. 00:12:23.047 --> 00:12:24.946 Ai is replacing jobs. 00:12:24.946 --> 00:12:31.402 That's bad for employees, obviously, arguably anyway, or at least it's a risk on indicator for people. 00:12:31.442 --> 00:12:35.993 I'll ask you this question have you seen any single job that has been replaced by AI yet? 00:12:35.993 --> 00:12:40.402 I know that's somewhat of a rhetorical question, but the answer is it hasn't what it has done. 00:12:40.402 --> 00:12:48.326 And this is we actually had a separate piece of research called the speed of skill change, and this is kind of AI agnostic. 00:12:48.326 --> 00:12:55.948 One of the things that we found is one in four jobs has seen 75% of their skills change in the last three years. 00:12:55.948 --> 00:13:12.846 Right, and so if we're trying to create kind of a skills-based future or skills-based hiring, you have to realize that and that's not just because of AI Every job is changing, but likely they're being augmented by AI or AI is becoming a part of the job rather than AI replacing the job. 00:13:12.865 --> 00:13:21.923 Because I'm actually working on some research right now to find is there any mythical job that has been replaced by AI thus far, and I'll let you know just from what I've found so far. 00:13:21.923 --> 00:13:22.663 I can't find any. 00:13:22.663 --> 00:13:23.426 Right. 00:13:23.426 --> 00:13:33.530 I've seen these major companies that have published things that have said, oh, we're laying off people because of AI, but it's not because they said the AI has automated their job. 00:13:33.530 --> 00:13:37.529 I think it's just they wanted to give a boogeyman excuse for why they're doing layoffs. 00:13:37.971 --> 00:13:38.653 Yeah, that's fair. 00:13:38.653 --> 00:13:41.208 I guess my gentle pushback would be I'm not sure it works like that. 00:13:41.208 --> 00:13:57.967 I mean, you would be closer to it than I am, but you could imagine AI slowly replacing certain skill sets in a job and then, as the company has its normal labor cycles where they lay off people and hire new people, you could argue that the person whose job got replaced when they got laid off and they didn't hire somebody. 00:13:57.967 --> 00:13:59.105 That would be an example of that. 00:13:59.105

--> 00:14:04.610 But sure it's not exactly like oh, we brought in chat GPD and then we fired 10 people. 00:14:04.932 --> 00:14:09.241 So I think yeah, so you're getting it, Marty, yeah, so maybe we can. 00:14:09.503 --> 00:14:17.351 There's plenty to talk about with AI, but maybe we could put a pin in that for a minute and focus on demographics and immigration, which I think are closely related. 00:14:17.351 --> 00:14:18.765 But you could tell me if you disagree. 00:14:18.765 --> 00:14:20.365 You covered the boomer thing. 00:14:20.365 --> 00:14:33.203 That always struck me as like the most obvious cliff that our economy, not just labor markets but the housing market, education, all the things you point out, I mean we could have seen this cliff coming 30 years ago. 00:14:33.203 --> 00:14:41.147 The baby boomers, as the name indicates, the biggest generation we've seen, perhaps, I think, ever in the history of the country. 00:14:41.147 --> 00:14:46.469 And then the millennials that after them, their children sometimes called the echo boom generation. 00:14:46.469 --> 00:14:52.092 So yeah, a sizable generation, but much smaller, maybe even half the size, you'd have to tell me. 00:14:52.092 --> 00:14:55.308 So we're just facing some harsh realities, it seems. 00:14:55.308 --> 00:15:04.200 What do you say to a TA executive or C-suite person who's seeing this trend and panicking, Like, what can we do about these demographic shifts? 00:15:04.200 --> 00:15:06.291 And then maybe, if you have thoughts on immigration, we'd love to hear. 00:15:07.615 --> 00:15:13.908 There are industries that have more like trades workers that aren't using knowledge worker skills. 00:15:13.908 --> 00:15:19.004 That's where the shortage is occurring, and so you have to think about it in terms of. 00:15:19.004 --> 00:15:20.429 I love the concept of. 00:15:20.429 --> 00:15:27.279 Demographics are destiny and, like you said, we could have known 30 years ago about this looming problem of baby boomer retirements. 00:15:27.279 --> 00:15:37.327 Actually, just as a point of fact, the millennial generation is just as bigger or slightly bigger than the baby boomer generation in terms of the workforce availability. 00:15:37.327 --> 00:15:40.811 However, they're actually not the ones entering the workforce anymore. 00:15:40.811 --> 00:15:51.365 It's Gen Z, and Gen Z is much, much smaller than the baby boomers generation that is retiring right now. 00:15:51.385 --> 00:16:01.341 Over the next few years, and every time a baby boomer retires, let's say they had a 30% chance of and again, I don't have these exact numbers in front of me, but let's say this is directionally correct, ha ha ha ha, since that's my podcast name. 00:16:01.341 --> 00:16:33.746 So I would say, let's say they have a 30% chance of being a college educated knowledge worker and a 70% chance of being some kind of worker that is, you know, in a doing physical labor or in a trade profession, or maybe a business, a small business owner, it could be, it could be a variety of things, right, but they're replaced by a Gen Z-er who's going into the workforce and, and that Gen Z-er is has, like, let's say, a 70% chance of being a college-educated person who's looking for a knowledge work job. 00:16:33.746 --> 00:16:47.364 And so you see, immediately there's an imbalance between the types of people that are available for jobs and the types of jobs that are available, and this is where the skill shortages come into play. 00:16:47.364 --> 00:16:51.947 Now what has happened, and this is where immigration comes into the picture to play. 00:16:51.947 --> 00:16:56.875 Now what has happened and this is where immigration comes into the picture and given. 00:16:56.895 --> 00:17:10.182 You know, from a politics standpoint, I have no idea where things are going to go over the next few years in terms of immigration policy, but let's just say, for over the last few years, the number of immigrants, those are the ones that are more likely to fill those low-skill, medium-skill, trade-skill jobs, that gap. 00:17:10.182 --> 00:17:13.455 But the gap's only going to get worse over the next few years. 00:17:13.455 --> 00:17:28.707 If we felt like there has been pain in the labor market for there being a divergence between people with a college degree and people without a college degree, that problem is only going to get exacerbated as more baby boomers retire and more Gen Z enters the workforce. 00:17:29.615 --> 00:17:29.976 Interesting. 00:17:29.976 --> 00:17:35.148 Let me just restate a few of those points just because I want to make sure I'm understanding but also the audience gets it. 00:17:35.148 --> 00:17:53.380 So you introduced this concept of workforce availability and you made the point that baby boomers, while they're much bigger in terms of raw numbers than millennials, millennials are actually the same size in terms of the percentage or the number of millennials who are workforce ready or available for the workforce. 00:17:53.380 --> 00:17:55.746 Is this just another way of saying? 00:17:55.746 --> 00:18:04.665 I mean, there's a lot of forces that probably went into that, but obviously one of the big moments that happened during the boomers generation was that women entered the workforce in a big way. 00:18:04.665 --> 00:18:06.157 So that's one factor. 00:18:06.157 --> 00:18:10.695 But when they started, much fewer women in general work than probably millennial women. 00:18:10.695 --> 00:18:13.298 Is that one way of understanding it? 00:18:13.838 --> 00:18:18.137 Oh yeah, you've definitely read through the Rising Storm report, because that is in one of the later chapters. 00:18:18.137 --> 00:18:19.099 So well done, marty. 00:18:19.099 --> 00:18:21.224 That is absolutely at play. 00:18:21.224 --> 00:18:36.704 So there's a difference between the amount of human beings that are alive in a particular generation and the amount of workers that are still working in that generation,

and so that's where the gap that you've identified exists, and there's a variety of reasons for that. 00:18:36.704 --> 00:18:40.884 The percentage of females working is definitely one of them. 00:18:40.884 --> 00:18:42.126 Immigration is another one. 00:18:42.126 --> 00:18:45.627 The amount of college educated versus non-college educated is another. 00:18:45.627 --> 00:18:56.268 But yeah, there's a variety of impacts there, but the largest workforce that is working right now is actually the millennial generation, because of their labor force participation rate Got it. 00:18:56.509 --> 00:18:57.711 Okay, that's helpful. 00:18:57.711 --> 00:19:07.755 And then I guess the big lesson on the other point not to simplify it too much is if you've got kids, you should encourage them to go into the trades and maybe not become knowledge workers. 00:19:07.755 --> 00:19:09.880 Is that a fair top line? 00:19:10.121 --> 00:19:11.042 finding yeah line finding. 00:19:11.042 --> 00:19:18.165 One of my running jokes is if you are worried about being AI, automating your job, become a plumber. 00:19:18.165 --> 00:19:21.845 That's the last thing that AI is going to automate. 00:19:21.845 --> 00:19:38.321 Again, I say that sort of tongue-in-cheek, but there's a seed of truth within it, which is, if you're an enterprising, younger person today, if you're an entrepreneur you know, enterprising, you know, younger person today and you're looking as I want to go, I want to skate where the puck is not going right. 00:19:38.321 --> 00:19:46.240 Everybody's going this direction and I want to kind of, you know, go against the grain but also be successful If you go into a trade profession right now. 00:19:46.921 --> 00:19:50.308 Yeah, my colleague, I mentioned him earlier Ron Hedrick. 00:19:50.449 --> 00:19:58.878 He gives a few kind of anecdotal stories on this that are based in the research that you know something like you know when somebody goes, they turn 18. 00:19:59.361 --> 00:20:25.007 And if they decided to go into a trade profession versus going to a four-year college degree and becoming an accountant, and so they go into a four-year degree, they take out $200,000 in debt and then they get a $50,000 a year job as an accountant, or they can go and become a trade professional, which usually takes less than two years, may not even have to take out student loans, but if they do, it's a very manageable amount of money. 00:20:25.007 --> 00:20:36.604 They graduate and they start in an $80,000 a year profession at 20 years old, right, and so they have a headstart on their peer, they have less debt and they're making more money. 00:20:36.604 --> 00:20:53.163 And they're also more likely, if you go fast forward a few more years into the future, to actually own their business and then contract out other people who are doing that type of trade skill right, and so it can actually be a quite lucrative opportunity if you choose to go into the right fields. 00:20:53.855 --> 00:20:54.916 Yeah, I think that's great. 00:20:54.916 --> 00:20:57.563 So, like you know, let's try and unpack that a little bit more. 00:20:57.563 --> 00:21:00.548 Or, you know, maybe just dive a bit deeper into the skills piece. 00:21:00.548 --> 00:21:02.215 You know, first let's say we love Ron. 00:21:02.215 --> 00:21:18.271 We've had him on the podcast too and, like you know, I tell you like maybe it was two years ago when we had him on and it was pretty scary because he said hey, it's about to cost $50 for you to go out and buy a cheeseburger Because we're not going to be able to find people that can be able to do the work. 00:21:18.271 --> 00:21:28.607 And I would say over the last two years you read the news I think the cost of going out to eat has probably gone up quite a bit. 00:21:28.607 --> 00:21:30.434 And so we love Ron, and he always warned us it's not going to be pretty. 00:21:31.878 --> 00:21:36.585 Are there tr truffled on this cheeseburger or something? 00:21:36.585 --> 00:21:36.786 What? 00:21:37.207 --> 00:21:39.713 yeah, ron is fantastic and he has this expression. 00:21:39.713 --> 00:21:45.045 He says he likes to bludgeon people with data, and so he, he is just so. 00:21:45.045 --> 00:21:47.316 Uh, I mean, everything he said is is fact. 00:21:47.316 --> 00:21:48.359 He says is factual. 00:21:48.359 --> 00:21:49.825 It's just he's. 00:21:49.825 --> 00:21:55.804 You know, he tries to kind of gen people up when he's talking about it, so I try to be a little bit more measured. 00:21:55.804 --> 00:21:59.141 But yeah, absolutely Everything he says is factual in nature. 00:21:59.461 --> 00:22:00.805 Oh yeah, Very much on the nose. 00:22:00.805 --> 00:22:02.137 Well, you know on that, I guess. 00:22:02.137 --> 00:22:03.260 So, all right, well, you know. 00:22:03.260 --> 00:22:06.377 Talking about knowledge workers, you know, but I want to unpack a little bit more nuance to it. 00:22:06.377 --> 00:22:25.336 So in Lightcast's report, I think one of the more eye-popping stats was that is it 85 million is the number of jobs that is probably going to go unfilled over the next five years, so by 2030, just due to skills matches. 00:22:25.336 --> 00:22:36.660 I think I'm stating that I'm remembering that stat, right, but maybe can we unpack that a little bit more then, right, Because on one hand, we're saying, hey, knowledge workers, hey, that's a dab, we don't have to worry about it. 00:22:36.660 --> 00:22:39.019 I'm taking a leap there. 00:22:39.019 --> 00:22:44.226 But let's unpack that a little bit more, Because in five years, hey, $85 million, that's a lot of job. 00:22:45.016 --> 00:22:45.900 It is a lot of job. 00:22:45.900 --> 00:22:49.580 Well, and one thing you have to be aware of is so that's over a five-year period. 00:22:49.580 --> 00:22:56.692 So if you've divided it by five, that's about 17 million jobs a year, and given that it's only going to get worse. 00:22:56.692 --> 00:23:05.459 So I would actually say, if you looked at

it on a trend, it's probably less jobs next year in terms of the gap, but getting more and more and more over the next five years per year. 00:23:05.459 --> 00:23:10.505 Right, and so if you think about it, there's already a huge skills gap, as it is Like. 00:23:10.505 --> 00:23:25.705 You'll see these, you know, when the the the jolts report comes out and you'll see the number of jobs that have been created and every month, and you'll see that there's this huge gap between the number of jobs that are available and the number of people that have have gotten a job in the last month. 00:23:25.705 --> 00:23:26.936 And you'll say how is that possible? 00:23:26.936 --> 00:23:42.714 And everybody I talk to you know who is unemployed, can't find a job right now, and one of the reasons why that occurs is because of this skills gap that we keep mentioning those jobs that are available out there they're tradespeople, they're nurses, they're hospitality, they're waiters and waitresses. 00:23:42.714 --> 00:23:50.400 There are a lot of the service industry, people that you know Ron talks about all the time and the jobs that people want. 00:23:50.400 --> 00:23:58.365 You know, maybe they want a coding job or an accounting job or any other kind of knowledge worker job that they're looking to land back on their feet. 00:23:58.365 --> 00:24:08.836 In reality, over the last few years those type of roles have been contracting and so that is the tale of two labor markets that we talked about in our speed of skill change report. 00:24:08.876 --> 00:24:17.703 The $85 million number it's a huge number and again I mentioned earlier in the conversation, we've never seen anything like this. 00:24:17.703 --> 00:24:19.424 This has never happened before in history. 00:24:19.424 --> 00:24:21.165 We're not prepared for it. 00:24:21.165 --> 00:24:21.445 Now. 00:24:21.445 --> 00:24:26.490 It's not to say that the future is exactly going to be linear like the past. 00:24:26.851 --> 00:24:38.627 So there could be a chance that you know, if AI comes in and it does more automation and augmentation that I mentioned earlier, maybe that $85 million goes down to $65 million or something like that over the next few years. 00:24:38.627 --> 00:24:40.201 That is entirely possible. 00:24:40.201 --> 00:24:46.907 And again, I mentioned earlier why the workforce risk is so relevant is for organizations to be proactive. 00:24:46.907 --> 00:25:17.289 If they are more proactive, perhaps the eye-popping stat of 85 million jobs, maybe that number will be lower because they've done a good job of combining skills, combining roles, creating the right pipelines of talent for the organization, recruiting people proactively and doing all the right things that can help mitigate these risks is not necessarily a foregone conclusion, but if you project the current trends that we see right now with the gaps that are coming in the future, that's what you can expect. 00:25:17.755 --> 00:25:18.396 So that's great. 00:25:18.396 --> 00:25:20.682 So I'm going to push on this one a little bit. 00:25:20.682 --> 00:25:22.714 So I'm going to ask two questions, cole. 00:25:22.714 --> 00:25:27.032 So where do you see, or where are we seeing, the biggest skills mismatches? 00:25:27.032 --> 00:25:33.645 And then maybe the right follow-up is how can companies start addressing these skills gaps? 00:25:33.645 --> 00:25:44.269 On maybe a more practical level, let's dive into some examples of where smarter CEOs are really cultivating their workforce for the future, or where they're trying to help close that gap. 00:25:44.849 --> 00:25:45.109 Yeah. 00:25:45.109 --> 00:25:49.537 So I'll use an example from the retail industry Again. 00:25:49.537 --> 00:26:00.356 I know you guys don't have it in front of you, but if you look at the retail, we plotted all of the organizations again by the risk and by the revenue In the top right-hand corner. 00:26:00.356 --> 00:26:12.410 So this would be very high revenue but also very high risk is Walmart, all right, and if you look in the top left-hand corner, which is very high revenue but lower relative risk, is Amazon. 00:26:12.410 --> 00:26:13.875 Why is that the case? 00:26:13.875 --> 00:26:19.087 You could look at it in a variety of ways, but largely Amazon has structured. 00:26:19.087 --> 00:26:21.883 They're virtually in the exact same business as Walmart. 00:26:21.883 --> 00:26:29.256 They're trying to get people, you know whether it be groceries or you know grills, or you know workout equipment or whatever it may be. 00:26:29.256 --> 00:26:33.247 They're just trying to be the universal kind of commerce and e-commerce providers. 00:26:33.247 --> 00:26:39.221 But Walmart has a lot more brick and mortar stores, which means from. 00:26:39.342 --> 00:26:43.701 If you remember the four different components of the risk score, one of them is market risk. 00:26:43.701 --> 00:26:50.142 They are very much geographically beholden to the markets in which they operate because they have brick and mortar stores. 00:26:50.142 --> 00:27:06.096 There's a reason why, you know, when Amazon was experimenting with creating stores a few years ago, they literally had no workers in those stores and it was self-checkout and you could find an item, you could scan it and then you would leave the store without ever interacting with the human being. 00:27:06.096 --> 00:27:18.596 Everything else that they do, for the most part outside of their distribution footprint, is e-commerce, which means that they can locate those workers in the tech hubs where there is an abundance of talent. 00:27:18.596 --> 00:27:23.917 So, from a market risk standpoint, that's really the huge difference between a Walmart and an Amazon. 00:27:23.917 --> 00:27:33.880 They have virtually the same revenue, virtually the same number of employees, but because of the market risk, walmart is at a much higher risk, even though they're in the same industry as Amazon. 00:27:33.880 -->

00:27:34.762 Does that make sense? 00:27:35.586 --> 00:27:39.721 Yeah, no, I mean, it definitely makes sense and I guess I'd say so, you know. 00:27:39.721 --> 00:27:44.981 Let's say, if you're a Walmart, then what are we doing in the next five years to combat that? 00:27:44.981 --> 00:27:51.403 You know, because I think you know Walmart certainly built its brand on like brick and mortar stores and like it's a very different model than Amazon. 00:27:51.403 --> 00:27:54.347 So if you're at Walmart, I'm sure they're listening too. 00:27:54.347 --> 00:27:55.328 What's next? 00:27:57.135 --> 00:27:57.777 What do you do to fix that? 00:27:57.777 --> 00:28:04.884 Well, I think you're actually again, a lot of these trends are already underway and you're seeing this, and so I'm just going off the things I've seen in the news. 00:28:04.884 --> 00:28:06.520 What has Walmart done recently? 00:28:06.520 --> 00:28:09.604 They've increased their pay for all of their store workers. 00:28:09.604 --> 00:28:15.521 Right, because what Walmart realizes in a particular market geography, it's a zero-sum game for talent. 00:28:15.521 --> 00:28:24.596 So if you are paying, you know I don't know their exact numbers, but let's say it's $17 an hour and your competitors in fast food are paying $12 an hour you can take their talent. 00:28:24.596 --> 00:28:25.459 Right. 00:28:25.459 --> 00:28:31.890 The same thing is and I think I saw this that they're paying something like store managers like $600,000 a year. 00:28:31.890 --> 00:28:40.067 Now, I can imagine only a few years ago that was not the number that they were paying because they know they need to be proactive when it comes to getting the talent of the future. 00:28:40.615 --> 00:28:52.702 Another thing that, again, I've just seen publicized is Walmart has been closing down a lot of underperforming stores and really, really investing in the Walmartcom or I think that's what they call it Walmartcom platform. 00:28:52.702 --> 00:28:59.979 Right, it's because they know that one of the ways of de-risking their future is becoming more e-commerce centric and less brick and mortar centric. 00:28:59.979 --> 00:29:01.487 So those would be again. 00:29:01.487 --> 00:29:06.916 Just, I mean, I don't have any inside knowledge on Walmart versus Amazon, but those would be some things that I've just seen from the sidelines. 00:29:07.317 --> 00:29:22.454 That Walmart is doing proactive and they're probably one of the things that you'll see that we've noted in our report is and this is why we included revenue in addition to risk. 00:29:22.454 --> 00:29:23.880 The more revenue you have is also the more potential you have to lose. 00:29:23.880 --> 00:29:37.888 But you also have somewhat of a moat for the ability to invest proactively compared to your peers who maybe have less revenue than you, and so Walmart and Amazon have somewhat of the luxury is that they can make those proactive investments because they have a little bit more cushion

to deal with these situations. 00:29:37.888 --> 00:29:43.179 It's when you're in the lower right-hand quadrant, which is a low-revenue company but high-risk. 00:29:43.179 --> 00:29:51.050 Those companies are at a real competitive disadvantage because they may not be able to afford to be proactive, even if it's existential to them. 00:29:51.785 --> 00:29:53.251 Yeah, fascinating. 00:29:53.251 --> 00:29:57.913 Well, certainly, with deep pockets you can sort of plug the holes in the boat a lot better. 00:29:57.913 --> 00:30:05.953 But in terms of long term, I guess we'll see what the real strategy is for mitigating risk, because I mean, fighting a wage war only goes so far. 00:30:05.953 --> 00:30:11.257 I would say Okay, so maybe we could just zoom out, because I think you said something earlier that was interesting to me. 00:30:11.257 --> 00:30:20.671 You call sort of the historical precedent of the labor market linear and that we can't necessarily look to the past anymore as a model for the future. 00:30:20.671 --> 00:30:26.895 I think that probably makes intuitive sense to folks, but I think we should just spend a moment on that, because I think we see this. 00:30:27.016 --> 00:30:44.209 I mean, I'm not an avid consumer of labor market statistics, but certainly most people who check on CNN or whatever their favorite news outlet will see numbers get reported and oftentimes there's a mismatch, I think, between like wow, the economy did better than we thought, but why is it so hard to find a job if you're a knowledge worker? 00:30:44.209 --> 00:30:54.166 And I think those are early indicators of that change or maybe that shift that you're talking about, it used to be that we could get a very high level top line number. 00:30:54.166 --> 00:30:58.057 That said great, the economy is good, it should be easy to find a job. 00:30:58.057 --> 00:31:01.525 Level top line number that said great, the economy is good, it should be easy to find a job. 00:31:01.525 --> 00:31:13.056 The current moment seems much more complex than that, and so if you take someone that is maybe a software developer who just graduated, thinking I'm going to easily get a job, and they find out that actually competition is quite stiff in knowledge work, they have a choice. 00:31:13.297 --> 00:31:18.515 Perhaps you could go back to the drawing board and invest in a trade. 00:31:18.515 --> 00:31:22.753 That might be a good idea, but I don't know how many people will do that. 00:31:22.753 --> 00:31:28.653 Which brings us to how do we take the knowledge workers we have currently and give them the skills of the future? 00:31:28.653 --> 00:31:34.432 And I know that's a big question, but I think it's a big question that's on the mind of pretty much all CEOs. 00:31:34.432 --> 00:31:41.711 Your report is telling them you guys are in trouble, all the top companies have high risk. 00:31:41.711 --> 00:31:44.298 How do you even begin to address that issue? 00:31:44.984 --> 00:31:55.567 Yeah, well,

I'll say, is one of the ways that we try to address it at Lightcast is we want to give people the information to make the decisions for themselves, because there is no universal prescription. 00:31:55.567 --> 00:32:06.392 Every company, every human being, every you know junior career person or maybe somebody who is at the tail end of their career, who maybe just got laid off, has to address the situation differently. 00:32:06.392 --> 00:32:20.494 So it's really hard to give a one size fits all answer to that question and, frankly, I don't have all the answers because, again, we've never been here before right, and so I would say again, the rewards are going to come to the people who experiment, who are proactive, who act early. 00:32:20.494 --> 00:32:37.491 And so, as I look at this and I say, you know, for the software engineer example that you mentioned, who is graduating and maybe there's not as many jobs out there is, you know I'm not an economist, but I took Economics 101 and what they talked about in there was supply versus demand. 00:32:37.491 --> 00:32:56.205 Right, what's happened is there has increasingly been more and more supply of software engineering graduates over the last few years, and what's also going on is kind of a mega trend in the tech industry of less and less demand for those same software engineers and at a certain point you see an inflection point. 00:32:56.205 --> 00:33:02.719 We haven't ever seen that inflection point before in the last few decades, and so people just aren't accustomed to it. 00:33:02.719 --> 00:33:07.978 Right, and so they, because this is just pure supply and demand at play. 00:33:07.978 --> 00:33:10.307 And you could fast forward into the future. 00:33:10.307 --> 00:33:22.493 And let's say, if everybody started going into skilled and trade and service sector professional jobs and stopped getting software engineering degrees, you would see the supply and demand swing in the other direction. 00:33:23.215 --> 00:33:31.132 And so again, I would always just say skate to where the puck is going or where the puck isn't going, depending on what is more advantageous for your career. 00:33:31.132 --> 00:33:38.444 I'll say as a side note, I'm looking into some research right now and it's very hard to triangulate some of these things. 00:33:38.444 --> 00:33:50.952 But I'm actually trying to find if we can see are there people who've gotten college degrees that are currently pivoting into roles like trades professions, and how are they faring in that process? 00:33:50.952 --> 00:33:52.310 Is this even happening? 00:33:52.310 --> 00:33:55.193 And if so, how are the people faring that are doing that? 00:33:55.193 --> 00:33:59.496 I guess I'll report back to you in like a year once I figure out what's going on there. 00:33:59.496 --> 00:34:09.851 But the key is, I mean, we're trying just as much as the next group to figure out how to navigate this, and I might even put the question on to you what do you think we should do, marty, or what do you think we should do Graham? 00:34:11.025 --> 00:34:12.793 I mean, I think that's probably a loaded question. 00:34:32.105 --> 00:34:36.152 I think we've always said and we probably talked about this with Ron there's probably a bit of a stigma attached to trades in the US, I think for the longest time. 00:34:36.193 --> 00:34:48.137 So many of us were growing up and it was hey, it wasn't about are you going to go something with computers, and I think you know, because of that, that's probably been a bit of a stigma to investing or taking that you know path of trades and so I think you know part of the, you know part of the challenge. 00:34:48.137 --> 00:35:05.076 You know one of the exciting things that we're, you know, probably see with you know people like Lightcast and some of the reporting is, you know what you're saying is boy, you know we're, you know we're past the tipping point where you want to go to become a software engineer because you know they're throwing jobs out like it's, you know, like they're free. 00:35:05.076 --> 00:35:24.297 We're now at a point where, boy, like you know, your toilet gets clogged or like a pipe bursts, like you know, that's the most lucrative job that you can have because there's no one else within a 15-mile radius that's going to be able to come in and fix your plumbing or rewire electricity on your house when fuses blow right. 00:35:24.396 --> 00:35:28.936 Yeah, you better get on YouTube and try to figure it out right. 00:35:29.545 --> 00:35:42.896 It's kind of like the foundation is kind of we've been building to use a horrible metaphor, I'm sure we're kind of neglecting the foundation of the house, where we're putting windows in up top and we don't need 100 different windows. 00:35:42.896 --> 00:35:49.797 We still need a strong foundation, and that's the piece that is kind of the tipping point seems to be, or the pendulum is swinging the other way. 00:35:49.797 --> 00:35:51.550 Does that make sense? 00:35:51.965 --> 00:36:41.878 I love that metaphor and let me build on it for a second, Something you said a second ago, because we were doing some research for some investors the other day and we were talking about how a lot of the narrative around like what is a good job and the stigma that you mentioned about some of the trades being negative jobs that was based on a post-industrial revolution baby boomer narrative that goes on in this workforce, and what we are needing right now is a new forward-looking narrative for the current generations to go forward by saying here's what the future of work is, here's what your opportunities look like and here's a compelling vision about how you can have a good career and a good life in that world and as a society. 00:36:41.918 --> 00:36:55.811 I think the research that Lightcast is trying to do is to help drive the ability to formulate that narrative, Because, frankly, a lot of what the narrative that exists right now is just malware

that's still hanging around long after it served its purpose. 00:36:55.811 --> 00:36:59.659 It meant it did a great job at the time it was formulated. 00:36:59.659 --> 00:37:10.275 It has just outlived its use and we need a new one, and so I think this research is our ability and attempt at trying to formulate what's that narrative of the future. 00:37:11.025 --> 00:37:12.469 Well, I think that's super interesting, right? 00:37:12.469 --> 00:37:16.927 And so let's tie this back to this Walmart versus Amazon example. 00:37:16.927 --> 00:37:19.813 I'm curious if we can unpack that a little bit more, right? 00:37:19.813 --> 00:37:23.630 So, like there's also been this narrative about, you know, the war for talent, right? 00:37:23.630 --> 00:37:30.969 And I think you know we're also saying is like, hey, walmart and Amazon is, you know, they're two big competitors, they're going on very different paths, you know. 00:37:30.969 --> 00:37:45.135 But at the end of the day, like you know, moving forward, like you know, there's going to have to be a bit more collaboration across all organizations to address a pretty large, growing problem about what jobs are going to be available and what, you know, where people are going to go work. 00:37:45.135 --> 00:37:53.289 So, you know, I think it's not just about changing, you know, the narrative on trades, but I think there's going to need to be a lot more collaboration between organizations. 00:37:53.289 --> 00:37:56.333 You know, not just, you know, changing the narrative about trades. 00:37:56.333 --> 00:37:57.615 Does that make sense, cole? 00:37:58.016 --> 00:38:11.007 It makes perfect sense and I would say this is why we focus so much on creating a skills-based future and skills-based hiring and even enabling, through our products, the ability to upskill and reskill employees. 00:38:11.007 --> 00:38:31.568 And I love this concept of competition versus kind of how can we all be in this together is I would not be surprised if you start to see the types of joint ventures in the future between entire industries about how are we going to reskill our current workers or upskill our current workers for the skills that are needed in the future. 00:38:31.568 --> 00:38:35.717 And so that you know, the rising tide lifts all boats in that industry. 00:38:35.717 --> 00:38:44.054 I think that that would be one mechanism for creating kind of a joint future where everybody benefits and thrives together. 00:38:44.054 --> 00:38:54.492 I'll say, on more of the competitive component, I put this out to my colleagues the other day internally as somewhat of a provocative statement, but I think you could also see it happen. 00:38:55.545 --> 00:39:16.829 Imagine in the next few years, if automation doesn't automate enough of, like fast food for instance, that I could see restaurants giving people signing bonuses and putting them under like three-year contract deals like an NFL player, but for somebody who works in fast food because from a competitive dynamic, if, like, at a certain point. 00:39:16.829 --> 00:39:30.864 You literally just have a human being problem and there's not enough human beings, and so if you have a human being that works for you, you better lock them down, and one of the ways that we have as a vehicle for doing that in the United States is through contracts. 00:39:30.864 --> 00:39:57.668 We have never seen in the history of fast food putting people under contracts, and I think you're going to start to see more experimental employment arrangements because of what's come in the future and again, so it's a fascinating time to be alive, but you're right hitting the nail on the head in terms of there's collective options for how we do this together, but there's also competitive options for how organizations navigate this in the future. 00:39:58.431 --> 00:40:02.559 I think it's fascinating, Cole, what you're saying about this idea of needing a new narrative. 00:40:02.844 --> 00:40:12.617 Because we all see trends, reports and we can come up with cool names like a risk index or whatever it may be, and people can kind of lose sight of what's driving it and what's important. 00:40:13.204 --> 00:40:28.333 But you're calling out, if I'm understanding you, you're calling out that I'm not sure this is overstating it to say that the American dream is fundamentally broken from the dream that was put forth when the baby boomers were coming of age. 00:40:28.333 --> 00:40:45.003 And if you worked hard and you had some talent and you have a little bit of luck perhaps, and you went to college, you were guaranteed to have a very solid upper middle class life, if not a better one. 00:40:45.003 --> 00:40:59.367 And it's no coincidence that I think millennials and Gen Z are the first generations in a long time where the standard of living, earning potential, however you want to look at it, is probably going to be lower than the previous generation. 00:40:59.367 --> 00:41:10.518 And I think that's probably just another way of pointing out that, yes, this dream that we've had and that we've sold, to the extent that it was true previously, it's certainly not true anymore for most people and we're in desperate need of a bigger narrative. 00:41:10.518 --> 00:41:16.067 And the narrative transcends individual businesses, which is why you're calling for collective action, I think. 00:41:17.849 --> 00:41:24.786 So I did not say the American dream is dead and it depends on how you define the American dream Right. 00:41:25.045 --> 00:41:28.036 And the version that I outlined yeah, the version that I thought you would have. 00:41:28.585 --> 00:41:30.753 I think there's a part of the part. 00:41:30.873 --> 00:41:37.070 The one qualifier would make in terms of the narrative you put forward on what the American dream is, is the part about going to college. 00:41:37.070 --> 00:41:49.266 Because for a long, long time, even right now, you know, a majority of people don't go to college right,

or don't have a college degree or haven't completed a four-year degree or something like that. 00:41:49.266 --> 00:41:55.413 They may still have two years in a community college, like if you add all the different types of college together, it is a majority. 00:41:55.413 --> 00:42:11.512 But if you just use, you know, let's say, a traditional four-year college degree when you turn 18 years old, that is not a majority of the population, and so you could never have said at any point in time that you know the American dream was only dependent on going to college and having a better life. 00:42:11.572 --> 00:42:15.695 I think the qualifier I would make is there's lots of good lives to be had out there. 00:42:16.157 --> 00:42:20.550 You just have to be willing to go for the skills that it's going to take to be successful in the future. 00:42:21.351 --> 00:42:26.193 And you know I can't comment on, you know, whether or not people are going to make more or less than their parents. 00:42:26.193 --> 00:42:35.432 I think that's on a person by person basis and, frankly, that's outside of the scope of the research that we've done, and so I would just be, you know, giving my own opinions and conjecture at that point. 00:42:35.432 --> 00:42:50.333 But to say the American dream is dead, I would just say the American dream is being modified before our eyes and it's important to have the facts about that and then be able to be proactive so that you can choose the career and the skills that you need to be successful in the future. 00:42:50.333 --> 00:43:13.016 I mean, there is a stark message that's being communicated, and this data is again things that we've never faced in the history of, you know, since the industrial revolution, right, but it doesn't mean that there's not positive futures out there to be had for, you know, the individuals who understand what's going on and take the right steps and next actions. 00:43:13.538 --> 00:43:16.110 Yeah, I think that's a much softer landing for us Colvin. 00:43:16.110 --> 00:43:16.713 The American dream is dead. 00:43:16.713 --> 00:43:18.505 So I think that's a much softer landing for us, cole, than the American dream is dead. 00:43:18.505 --> 00:43:22.757 So I think that's a great place for us to put a put a pin in today's episode. 00:43:22.757 --> 00:43:31.077 So I'll leave it with a probably hopefully the easiest question of all, and you know I'd say you know where can people learn a little bit more about you and Lightcast? 00:43:32.565 --> 00:43:39.751 Yeah, this ended up being a little bit more intensive a conversation than I was expecting, but I've enjoyed it be a little bit more intensive a conversation than I was expecting, but I've enjoyed it. 00:43:39.751 --> 00:43:52.101 So, yeah, you can find me, cole Knapper, on LinkedIn and, you know, obviously, look into Lightcast, look into the workforce risk, look into the demographic, drought, the rising storm, the speed of skill change All of those are out there and free and available to anyone. 00:43:52.101 --> 00:43:57.849 You know, look into these things, because this, again, this information is knowable. 00:43:57.849 --> 00:43:59.072 And also you, you know, check out directionally correct. 00:43:59.072 --> 00:44:01.965 It's a, it's a lot more funny than this conversation we've just been having. 00:44:01.965 --> 00:44:09.110 So, yeah, let's do it, and the american dream is not dead on directionally correct love it all right. 00:44:09.489 --> 00:44:22.369 well, thanks, cole, it's been a great, uh great episode, great conversation and, um, yeah, hey, like you know, sometimes we like asking hard questions, like but like, hey, we're, we're super excited about the future too and we'll link everything from Lightcast in the show notes per usual. 00:44:22.369 --> 00:44:23.431 So thanks for joining. 00:44:23.652 --> 00:44:24.375 Thank you for having me. 00:44:24.925 --> 00:44:26.612 All right, thanks for tuning in. 00:44:26.612 --> 00:44:33.074 As always, head on over to changestateio or shoot us a note on all the social media. 00:44:33.074 --> 00:44:36.367 We'd love to hear from you and we'll check you guys next week.