Episode Transcript
[00:00:00] Good morning, everyone. It's Labor Day weekend here in the United States and lots and lots of things going on in the labor market. But I want to talk about some new data that came out from the Bureau of Labor Statistics and correlate this to all the work we're doing in HR around AI. I think most of you are pretty aware that the existential change going on in the population is, is the lower birth rate. Nobody really knows why this is happening, but all the research that's been done on this tends to show that it's getting worse, not better. In other words, developed economies, us, uk, Germany, France, most of the European countries are all having children at the rate below replacement. And that means that the overall size of the workforce is shrinking. And of course, there's also a major trend toward people getting married later and having children later in life. So the entry level workforce is probably going to keep getting tighter. Now, universities and schools and colleges are freaking out about this. Well, they're freaking out about a lot of things. And I'm going to publish a podcast in the next couple weeks from Taylor Stockton, who's the Chief Innovation Officer for the Department of Labor. And you'll hear what the US Federal government's trying to do, which is a lot to try to address this issue. But the major issue for us as employers is operating in a world where there's just fewer people to hire. Now, I'm not saying we're going to run out of employees, but if you look at the data that just came out this last week from the Bureau of Labor Statistics, they believe that the rate of growth of the job market over the next 10 years from 2023 to 2033 is going to be only 3%, a little over 3%. It was 13% for the last 10 years. So for those of us living in the United States, that's a massive, massive change. Now, they don't explain why that is. They don't explain if that's economic or otherwise, but that doesn't really matter. If you just think about that number, then on the counter side, consider the fact that the Trump administration believes, and I don't believe this, but they do that, that they can increase GDP in the US by 3% per year. You end up with a diverging, a set of diverging curves where GDP goes up much faster, much faster than the number of workers, which means, of course, that we need more automation and productivity. And in the middle of that, of course, is AI. Now, last week there was quite a controversial report from MIT. I talked about it that showed that 95% of business users don't believe they're getting a return on investment from AI. I don't give that report a lot of credibility because it's always true of enterprise products that it takes a while to see the roi. But what it tells you is that it takes time, as you all know, for a company to gain the benefits of a new technology.
[00:03:09] So if we're going to be forced to increase productivity by 25, 30, 35, 40%, which, by the way, that's where the numbers work out. If that GDP number happens, then we're going to do a lot of reengineering over the next decade. And this is going to happen over the next decade. This isn't going to happen in one year. If I think back to the Internet in 1998, 1999, when we didn't know what to call it, believe it or not, we weren't even sure what to call it. The world we live in today, 25 years later, 27 years later, is very different from what we had imagined originally. We originally, of course, imagined, you know, things just being online to view and consume, not to have all of these interactive experiences we have on our phones and our headphones and all the other things that we're now interacting with. The same thing's true with AI. AI will permeate our entire lives. It'll be in our eyeglasses, it'll be in our headphones, it'll be in our devices, in our clothes, et cetera. So for the next decade, there's going to be just enormous amounts of innovation and creativity and, you know, going to the next couple of weeks of HR tech conferences. I'm going to be keynoting several of them. We're going to talk a lot about this. And what I generally find when I talk to most of you is excitement, confusion and fear. Yes, we see the potential. Yes, we love using Galileo or ChatGPT or the copilot, but we're not sure exactly where to apply it in the broader business context and how to get to this productivity improvement that we want. So we're going to be forced by our CFO to, to reduce headcount, to get to where we want to be. And that puts us in the middle as people that design the organization and the structure and the job architecture and all that stuff in trying to make this all happen. Now, luckily enough for all of you guys listening, we've been having a lot of conversations with companies about this, and I'm going to talk about this a lot in the keynote speeches I'm giving. But let me give you a little preview of what we've discovered historically. The way we've deployed people, humans, employees, workers and companies is around business processes. You know, you have a product or a service or some sort of an offering. Maybe you're an insurance company, maybe you're a software company, maybe you're a manufacturer or you run a retail chain and you have a process that you're, you know, you've developed to sell to consumers or customers. They're buying it, you're making a profit on it, and it turns into a business process. There's the delivery of the product, the support of the product, the sales, the marketing, the collection of money, the supply chain, all that stuff. In the ERP systems, Oracle, SAP Workday, et cetera, 25, 30 year old designs were developed to stitch those things together into an integrated financial system. ERP systems are primarily financial systems. And then what we did as organizations, as we said, in order to manufacture all these cars or parts, we would build manufacturing plants, we would have automation and then we would hire people in the middle to do the tasks or activities, I like to call them activities, not tasks that would fill in the gaps in these business processes. And in the early days of the economy there was no automation. So the humans did all of the work. And then as we got more automation, the humans did less and more and more of the people work was managing the machines, not managing the process. So if you go into a manufacturing plant, there aren't that many people screwing things together and bolting, you know, equipment, but there's a lot of people managing the process or the systems. I spent some time at the Tesla plant in San Jose and I've been to a few other manufacturing plants. So you know that. And so the workers or work or employees were deployed to manage these automated systems and then also do the tasks that the automated systems didn't do. And the companies that didn't have a lot of automation had more workers doing those tasks or activities. And the companies that, you know, a better automated system had fewer people doing that stuff. You read the book about Apple and how Apple automated its systems in China, which is a fascinating book, or you read, you know, books about the origins of the auto industry and you realize that in decade after decade, industry after industry, the companies that figure out how to automate things, well, not just in general, well, rocket ahead of their competitors. The reason they do is they can deliver their solution faster, cheaper and usually with higher quality because they have scale and data integrated into their companies. So automation or technology enablement is a critical business competitive advantage. And I'm not the first one to say this, but companies that know how to deploy technology well outperform. They don't just have fewer people, in fact, they oftentimes have more people because they grow faster. Google has a lot of people, Amazon has a lot of people, IBM has a lot of people. And they're also incredibly well automated companies. And they invest in technology. And what we learned in all of our pacesetter research and all of our industry research, and we've now done eight or nine in depth industry studies on this, all of which is available in Galileo by the way, is that companies, including banks, that automate things well and continuously refresh and update and rearchitect their automation, are pacesetters. But they're not just great at technology and automation, they're also great at organization, design and change. Because as you automate, as you add more technology, as you integrate more things into data systems and so forth, you have to move people around and change people's jobs. And if you're not good at that, then the automation systems stagnate and they don't progress. And the reason they don't progress is because people will resist them. When I was at IBM in the 80s, we had an organization that was very resistant to open systems. I mean, the company spent at least a decade in an existential crisis about the fact that the world wasn't going to buy IBM mainframes anymore. And they refused to admit it or even see it. And so IBM was late to the market in open networking software and systems, in open computing systems and open database systems. All of the things that IBM did on mainframes came to market in other forms long before IBM understood that their mainframe business was going away. So there was a lot of organizational culture and change, fragility or rigidity in IBM. And that's why IBM as a stock went nowhere for, I don't know, two decades. So all of you guys in business roles, which I think most of you are, are sitting in companies that are about to go through a massive amount of this automation and redesign. And you gotta be ready for it. And the reason things like the MIT study come out and including our super worker research is because it takes time, it is hard, it is not easy. And I, you know, really admire companies like Amazon and Google and, you know, and Microsoft to some degree too, who have learned how to reinvent themselves, not just once, but on a continuous basis. Because when I first learned about Change management. When I first got into hr, I thought the word change management seemed sort of silly. I don't know how you manage change because change is sort of a fluid thing. But we have to think about our companies as constantly changing things. We need change agility, not just change management. Change management is the old fashioned idea that we're going to make a change and then stop and then we're going to wait and do another change later. This is constant change, especially now because AI is changing so fast that the type of automation we can do changes almost every month. I mean, you're going to all have drones, we're going to have vision devices, we're going to have devices that understand voice, we're going to have devices that can talk and interpret language, we're going to have devices that can create graphics. I mean, we already have this stuff, right? So this economic trend of productivity is very much going to fall on us as HR leaders, business leaders, CEOs, CFOs, CIOs, figuring out how to reorganize our companies to take advantage of it. Okay, so what have we learned so far about this task automation activity automation streamlining process. Let me mention a couple things. First of all, you have to read our research report on the Super Worker because we, I think pretty, pretty accurately predicted the four stages of automation that we're going through. And I won't repeat them here, but you really should look at that. Come to the conferences I'm going through and we'll sort of step you through it. And what you see is that there is individual automation of individuals where we each decide how to do our own jobs better. But that actually is not really where this is going. That's actually a small piece. And this is why Microsoft's copilot strategy, you know, has yet to evolve. Where it's going to go is that the real benefit of automation is the process automation, not the individual work task automation. I mean, in our company, I know what I do all day and I'm quite automated in my work because I'm an engineer and I just kind of like to play with tools. I know what our publishing team does, I know what our marketing team does, I know what our sales team does. I can't expect every one of the 40 or 45 people in our company to figure out how to automate their work on their own. They're too busy doing other things to do that. We need to do it for them. And then we need to look at the things that can be stitched together to make the processes work better. And so what we've been discovering in these meetings is general confusion about the situation. And the answer is not that difficult to understand. But let me just explain it here and we'll be talking much more about this in the next couple of months. First is you need to make sure everybody in the company is comfortable with AI. What is it? What can IT do? What are the tools we have deployed or will deploy inside of our companies? How do I create a prompt if that's appropriate? Why does the system not always give me the right answer? How do I make sure the content in the system is trusted and all that? Those are things that are going on in companies pretty quickly. And what we're basically finding is that most organizations are hiring young people out of college or from other companies that are already very comfortable with it. 60, 65% of the new employees at KPMG believe AI is their future. They're not worried about it at all, they're just ready to use it. So you know that's going to happen relatively quickly. The second piece is finding big use cases. Now that doesn't mean waiting for everything to bubble up from the bottom because sometimes the big use cases come from the top. Not always, but sometimes they do. The CEO, the cfo, the head of the business may be aware of big problems that can be solved company wide that individuals are not aware of in their own functional areas or their own group. Allianz built an integrated claims agent. We've talked to companies building digital twins. We're actually building digital twins inside of our company. We'll talk more about that later. I was talking to ServiceNow about automation, automating the sales management process. I mean, there's very strategic things that will come down from the top and then there's teams in your group and your company that are going to just come together and do things. I know in recruiting there's a tremendous need to stitch pieces together and to make it more integrated. And there's vendors working on that. I know in L and D, which is going to be massive, we're going to have integrated dynamic content systems that are going to revolutionize the way employees learn. And that's a huge area for us and a very critical area in this whole, this whole issue. And then, you know, every company's got their own stuff, so that has to come from the top. So we end up with this governance process where there's an AI, AI steering committee or, or a panel. I don't, I wouldn't call it aizar, but really A group of people that decide where to invest, the major investments, and then individuals automate as best they can and learn how to share with each other. I think it's pretty analogous to 1981 when the IBM PC was launched. Most of you are a lot younger than me. Basically what happened then was everybody was running their own mainframe. Sounds silly to say it now, but we had mainframe computers in the basement run by professional IT people before that and all we had was dumb screens. All of a sudden we all had our own computers. We all had to learn how to use DOS and Windows and Excel and Word and all the other things that came along. And we didn't wait for somebody to teach us how to do all that. Eventually we got a lot of IT systems integrated. Not in the early days. So there's going to be both. There's going to be individual productivity and there's going to be system wide governance around it. Now the thing that I think is the most interesting to me in HR is every part of the talent system is going to change. And if you look at all of our systemic HR research and the work that we're doing right now on super worker, super manager and talent density, you're going to have to rethink the talent management process. You know, I don't know how many times I've written about talent management. You know, maybe 50 times. Talent management grew out of senior level succession. In the early days of the word talent management, it was only for the top talent. There were the workers who were not talent and then there were the leaders who were talent. So we had this bifurcated set of systems where we'd have sort of succession and leadership development and all sorts of senior level stuff for the top people. And then everybody else got treated as a worker. And what happened in the late 90s and early 2000s is we all became talent because we had a, you know, shortage. And we deployed talent management to everybody. So we had onboarding for everybody, performance management for everybody, check in career development, leadership development, skills assessment, all that stuff for everybody. And then we ran into issues with pay, pay equity, various forms of performance based Pay, goal setting, OKRs, flatter organizations. All that stuff came from this idea that everybody's talented. Well, we're already there, everybody is now talent, but we're now operating in a highly empowered form. So you know, from my perspective, this has been a continuum now for 25, 30 years where the individuals, all the individuals in your company are high value talent, every single one. Especially if this labor market stuff continues because we're just going to have fewer people, we're going to have more revenue per person, more customer service per person, more innovation per person, et cetera. So the new world of talent management is what we call talent density. How trained, skilled, aligned and productive is every single person. Every person is now a pyramid of talent. How can we make this person better at their job? How can we make this small team more productive? How can we teach everybody more about what they need to know? How can we get created a level of enablement for everyone? And by the way, that changes learning and training and skilling. We can't rely on these old fashioned training strategies anymore because they don't scale like this. If you have a company of superworkers, every employee now has their own personal learning journey and their own needs and their own interests. We need personalized learning for everyone. That's why Galileo Learn is so huge as a dynamic AI enabling system. We just did a project in the Middle east with an airline to help them reinvent their L and D strategy and they are totally rethinking the whole thing now around individual learning. And that isn't just about L and D. This is about your company. This is about being the high productivity company you want to be. You have to focus on every single point of density. You know, I'm a mechanical engineer. So early in my life I learned about mechanics and stress and strain and fluid mechanics and all sorts of things like that. In a machine, if one part of the machine is weak, the machine breaks. I mean, every single part of the machine has to work correctly. If you have a part in your car that's poorly designed and it fails, you're not going to be happy. The whole car isn't going to work correctly. And that's the way it works now in our companies. Talent density means every part of the company has to be dense or highly engaged and highly trained and highly skilled. And of course there will be turnover, there will be people that don't fit, there will be people in the wrong job, there will be people that don't get along. So you know, this issue of employee engagement is also going to have to change into a high degree of cultural alignment. You know, I going a little bit off on multiple directions here, but let me just talk about that. Employee engagement is also a very dated idea. Engagement was the dated idea going back to the industrial age where if we keep people happy with, you know, Carl Young or whatever, you know, engagement survey, you know, you like, if we keep them happy, the company will work well, well I mean that's, it's much more than that. Now is everybody aware of what they need to do? Do they know what they're accountable for? Do they have skills? Do they have access to the skills? Do they have access to information?
[00:20:50] Do they know who to talk to? Are they empowered? Are they held accountable? Are they in the right job? You know, young, that's is what young people want. They are not expecting you to give them a 30 year career in one company. They want to know right now, this year, what am I capable of doing that can help me contribute and me get ahead in my life and my career.
[00:21:10] So talent density is very, very different way of thinking about talent management. Now obviously if you're a big gigantic company like l' Oreal or Exxon or Microsoft, it's much more complex. But we've seen a lot of this and a lot of this comes down to individual empowerment and individual skills and individual energy, levels of energy and passion, but also simplifying the job architecture. So people don't wait to be told what to do, don't wait to be promoted, don't expect things that are not necessarily going to happen to them.
[00:21:45] And you know, if you sort of rethink your talent strategy along these lines and we will help you do this, Julia and Nahal are working on a, a whole body of research on super managers and talent density. You will rethink how your company operates and you'll end up being like Google, like Amazon, like one of these high performing companies. And it doesn't matter if you're an industrial company, if you're a healthcare company. By the way, I think one of the toughest industries of all the industries we've ever worked with is healthcare. It is the number one industry increasing in job roles during the next 10 years because we're all getting older and there's lots of science and things we need to do about health. And every healthcare worker in a hospital, in a network of hospitals, is an empowered worker. Every single person, the person that pushes you around in the wheelchair, the person that takes care of your food, the person that's your nurse, your doctor, your diagnostician, the person scheduling your appointments, they're all part of your healthcare experience. And every single one of them has to be highly trained and skilled and aligned. And I think healthcare, great healthcare organizations are really good at this. So you don't have to be a high tech company like Amazon to do this. In fact, I think, you know, many of these other industries are more benefited from this approach than others. So all of These things are collecting together as imperatives for you as a business person or an HR person in this new world of AI powered organizations. I'm not going to predict where we're going to be in 10 years. There are going to be new Amazons, there are going to be new companies that rethink their businesses in a significant way and there's a lot of creativity going on. Luckily, the AI isn't as sophisticated as it will be in the future, so it's not going to wipe everybody out yet. I'm reading a very, very detailed book on superintelligence and the more I read it, the less impressed I am with the word itself. AI is not super intelligent. It is not equivalent to humans in its perspective and judgment and wisdom. It isn't even close, but it's really good at a lot of things. So let's not try to overextend what it can do and let's take advantage of what it is able to do today and you'll find enormous benefits. You know, we have more than, I don't know, 4,000, 5,000 people using Galileo. Some of them are individuals, some of them are consultants, some of them are large organizations. And everybody we talk to is doing different things with it. I mean, there's a lot of common use cases, but there's, you know, we have 350, 400 pre developed prompts in Galileo for HR, but there's probably a thousand or more use cases out there. And that's an example of how pragmatically useful AI is already right now, right this minute. So you, as a professional or an ambitious business person, you have to keep up on this and you have to play with it. And this governance process will help because if you have a steering committee and a process of bubbling up good ideas, you can share the knowledge, the automation capabilities with people who don't have time to figure it out on their own. Not everybody wants to do it on their own. So I'm sort of struck with this BLS data and saying to myself, this is our future, this is the next decade mapped out for us very clearly. Now, if you're a vendor, your product better fit into this new world. That's a big challenge in and of itself. If you have a big business on a transactional platform, you're going to have to rethink it. If you're a consultant, you have massive opportunities here to help companies. By the way, I think one of the most valuable tools for consultants is Galileo. If you're a consultant working in a large consulting firm or within a company or on your own. We've almost designed Galileo perfectly for you because it has all of our tools and case studies and examples and vendor information in it. And I guarantee you, you'll be a much, much better consultant if you use it. So check out what we've done here. And if you're an executive, this is a really fascinating time because culture matters, skills matters, focus matters, technology matters. You're going to really be tested because what's going to happen fairly soon is we're going to see some companies in every industry figure this out faster than others. And they're going to do things and you're going to read about them in Fortune magazine and you're going to say to yourself, smokes, how come we didn't think of that? You can wait if you want, but we're not going to be waiting for vendors like we did in the past, because these are systems you use internally. And then from the standpoint of the labor market, if the birth rate stays low, if we end up with this slowly growing labor market, we are going to be forced as organizations to do this. It isn't just because our shareholders are asking us to make more money or we want our stock price to go up or we want to pay a dividend or the CFOs got targets. It's also a necessity that for in order for us to fulfill on the mission we have in our company, whatever it may be, we have to figure out how to do more with the people that we have. And it's good for the people. By the way, you know, the final thing I'll just say at the end of all this is despite the fears and fear mongering coming out of some places, this is going to be good for the workforce because people are going to have new job opportunities, they're going to be more empowered. We're going to have to pay people more money because there will be fewer of them around. We will have to give people more skills. And as long as you're willing to work hard and learn in your career, which basically has always been the key to success, we're all going to have more interesting, more fascinating, more rewarding careers in the future.
[00:27:31] So that was a lot for Labor Day, but I figured I ought to try to sort of take it up a level. Come to HR Tech. Come to unleash, Come to success. Connect. I will be at all three of those. We'll be at Workday Rising and there's other events around the world. Check out Galileo. Check out Galileo learn. Have a great holiday weekend for those of you in the US and we'll talk again next week. Bye for now.
