Episode Transcript
[00:00:06] I'd like to give you a broader context now that we're six months into the year on the Super Worker organization. And this is highlights of some material I presented at our conference two weeks ago. So I want to go through five big ideas that fit together. The first is generally thinking about business. That even though we treat humanity, human capital and payroll as an expense, we have to consider the fact that without people, we don't have a company. And I don't mean that in a sort of flippant way. I mean people make the company, people make the products. People are the ones who innovate, people are the ones who deliver services. People are the ones that take care of customers and patients and do creative things like marketing and sales and engineering. And so fundamentally, regardless of how much technology you may create or integrate or build or buy, people will be the ones that will create value on top of it. Because technology is a commodity. Everybody can get it, you can buy it, but it's how you use it and what you do with it that matters. And I do not buy this narrative that agents are going to be like people. Agents are technology. We will manage them like we manage other data systems. And you can, you know, kind of personify the word manage and then personify the word train. But you're not really training them, you're really loading them with content and then adjusting the content to create the right kind of experience as an intelligent agent. So I do not particularly think it's helpful to think of agents in a human way, because we ride on top of them, we use them, we create them, we add value and decide how to use them. They are not peers of us. Okay, so that's number one. We can debate that one as much as you'd like. But by the way, I don't believe that AGI is worth discussing. These things are going to get smarter and smarter and smarter. They're going to have more and more and more content and data and intelligence within them, but they're never going to be human. They're never going to have the cellular genetic learning and adaptation of us as animals. They are not animals. They are machines. Again, open to debate, but that's number one. Number two, companies today are designed around the business models and organizational models that were created around the technologies that we had. So in the agrarian days of, you know, slaves and animals doing work and people doing work, we had, you know, organizations that were very people centric. And the humans, the people picked the cotton or harvested or planted the crops or drove the cows and the sheep and we managed them as more or less flat organizations with certain skills and capabilities. So if you're good at, you know, planting but not harvesting, then you would be in the planting group and if you're in the harvesting group, you'd be in the harvesting group and so forth. Along comes industrial technologies and robots, and rather machines, not robots, factories. And then we had management and labor and we had a very, very different model where the management made the decisions and the labor implemented the decisions. Ended up with labor unions, we ended up with job descriptions and job titles and job levels, hourly wages, then we ended up with unions. But the idea in that model was there are a bunch of people that make decisions and then there are a bunch of other people who execute on those decisions. And those are not the same people, they're different people. And if you were lucky enough to be in the management class, you were part of the decision making part of the company, and otherwise you were part of the doing part of the company. When I went to work for IBM, for example, I mean, excuse me, for Exxon in the early 80s, late 70s, my job title was engineer, but I didn't do any engineering because all the engineering had already been done. I pretty much copied things out of a book and just implemented project management tasks and engineering management tasks that frankly anybody could have done. You didn't need an engineering degree. So this second model has been around a long time. Then in the last 15 or 20 years we've had information based companies and we flattened things a lot. We created cross functional teams, we created agile work practices. Managers who were hands on doers, not just managers. Ideas like Holacracy, ideas like flat organizations. A lot of this came out of software, but it didn't all come out of software. There was chemical companies that did this, there were hospitals that did this. And we ended up with a model of a company where you had much longer, broader spans of control, much more empowerment. There were still managers, but the managers weren't making all the decisions. The managers were maybe doing resource allocation, but the people were making the decisions. And we really focused a lot on empowering people and training people to make better decisions on the front line, because that's where all the action is anyway. And that meant hiring and training and investing in people more significantly. And companies became much more productive because they had more scale, more innovation, more good ideas. And along came the pandemic. We sent everybody home, kind of disrupted that whole thing because we didn't have the face to face experience we did before. And then AI hit the market. And now we're in a world where we go to the fourth stage of empowerment where you're not just a worker in a field, you're not just a laborer in a plant, you're not just an empowered software engineer or an empowered salesperson. You're a super worker because you have access to data, information, tools, systems that are so intelligent that you know as much as the CEO. Maybe you know more than the CEO because you're in a part of the company that's more important than he or she may realize. And he or she may realize that they're thinking about everything and you're thinking about some more important, you know, kind of focus things. And these agents, which become smarter and more multifunctional, cross the functional domains of the original company strategy. In the case of hr, there are agents being developed that do everything from sourcing, recruiting, selecting, assessing, onboarding, training, and then they'll do performance management, and then they'll do career development, and then they'll do coaching, and then they'll do assessment, and then they'll do leadership development. On and on and on. So, so all of these siloed silver center of excellence kinds of functions we had in hr, but also in sales and marketing and customer and product are all going to get agentified. I mean, if you think about a product company or a company like ours that sells things, there's a straight line from finding a lead, identifying a prospect, getting to know that prospect, communicating what our value is, understanding the needs of that prospect, presenting a solution, creating a proposal, closing a deal, implementing the solution, monitoring the person or team or company's success or failure with the solution, solving their customer service issues, getting them to renew, getting them to upgrade, getting them to buy more. That is one big process. We have it in about five functional areas. We have a marketing department, we have a sales department, we have a contracts department, we have a product engineering department, a customer support department, a customer service department, and maybe even a customer consulting department, all of which are operating separately around a customer. Well, they all ought to be one department, to be honest. And that's what an agent can do. And there's many, many examples of these cross functional business things that we can do which create much more empowered people. So that's number two, is that with AI, everybody has much more authority and data and information and power. That's the idea of a super worker. The people that were doing routine work, they don't disappear from the planet. They get new jobs, they find new work. The people that used to take Care of the horses before the cars came, then took care of the cars and then they became taxi drivers or Uber drivers or who knows, you know, where, where people go from roll to roll. But you know, we're not going to be eliminating the need for these humans. There's going to be many, many new things needed to manage and maintain and update these agents. So, and those are higher level jobs. So the arc here is upward, upward in pay, upward in value, upward in interesting jobs, upward in career opportunities, and upward in productivity in terms of revenue or profit or growth per human. You know, a super worker company may not have to keep hiring people to grow, but they're going to grow a lot because they can sell and implement and design and serve customers in a more, much more scalable way. But that's not the whole story. Number three, something else has changed. The pace, the timing. When I got out of College in the 70s, GE was really big, Corning was really big, Procter and Gamble was really big. I graduated from Cornell, Boeing, these big companies were doing a lot of hiring up there and I ended up going to work for Exxon. And these were companies that had, you know, 20, 30 years already of experience and they were unstoppable. No one could get in their way because they had dominant control over their markets through their channels of distribution, their customer sets, their brand and their just intellectual property. That of course has completely changed because of the Internet, because information is so transparent and so easy to move around.
[00:09:05] So now things change very fast. A new technology is invented, a new version of ChatGPT comes out, a new methodology for gene splicing comes out, a new science of engineering material science comes out and within minutes it's published somewhere. It might even be open sourced where people openly share the technology behind it or the code and other people can get it. So all of those, you know, traditional barriers to entry or moats vanish if you're an innovative company. So the third part of a super worker company, and this comes from our pacesetter research, is that now you have to not only be good at level one and level two that I talked about earlier, but, but you've got to be good at change. And identifying new technologies. We found in the pacesetter research, which is studies we've done for three years on eight different industries, hundreds and hundreds of companies, billions of employees, using data from Eightfold that the high performing companies have more advanced skills in every domain, whatever they do business in, and they change faster. They have skills in change, they have skills in change management skills in Workshop design and org design. Some of these geeky HR things that nobody likes talking about are actually hard skills. And so they are adaptable or what we call dynamic companies. And they have skills in that. So that's number three. So being a super worker company is not a one time A to B shift. It's a change in the way you run the company and the way the company adapts and changes. Because super worker jobs are going to be changing constantly. The AI itself is changing, the data within it is changing, and of course the jobs are changing. So in a super worker company, you have people making decisions with technology support, but also continuous evolution of those jobs and continuous evolution of the skills and the training and development of the people in those jobs. And that leads to number four. Number four is mobility. I talked about this a lot. Over the years it's become very clear and very predominant that if you're not good at moving people around from role to role, function to function, location to location, you are not going to be a good company, period.
[00:11:21] Now, you know, many things get in the way of moving people around. Hoarding by managers fear a lack of cultural support for internal mobility. By the way, you know, when you change jobs inside a company, it's very risky because if you fail, you have no way out, you can't go back. So you have to have a support structure for people moving around inside the company. You have to be willing to train them. Managers have to be a part of this. We have to reward people for cross functional careers or T shaped careers, or M shaped careers, as Josh Newman talked about last week. And we have to have flattened organizations, we have to find a way to pay people that move around a lot. But you look at these high performing companies like Netflix or whoever, your favorite, you know, Amazon, they move people around a lot. And people become very savvy about the organization, the customers, the products, the technologies because of that. So that's number four. It's part of super worker. And then there's number five, which is leadership and culture, which is, you know, kind of a big, often tired topic that gets, you know, overly discussed in many, many organizations. But it is the most important of all. We have a big client that's in the middle of a culture transformation and they call it time for tension. In other words, are you willing to have a difficult conversation with your individuals or people or managers about change? Are you willing to push back? Are you willing to speak up? Are you willing to challenge authority? Are you willing to discuss mistakes? As we used to say in our learning Culture, research. Are you willing to challenge authority or bring a customer issue forward and champion it in the company? Do leaders invest in the development of people? Do they spend money on development and mobility and external relationships and partners? Does your company have a culture around a mission or a purpose? Whatever it is that makes your company successful? Are you all focused on that? Are you clear on what that is? Do you communicate that well? Super worker companies have to be really well focused because things happen so fast you don't have time to blather along in a year or two and fumble and not know what you're doing. Look at what's happening to Apple because of their lagging acceptance of AI. I mean, it's really hurting them to not have an AI. I don't know why that happened or how that happened. I'm sure Tim Cook's involved. But you know, you look at companies that are faltering or failing, you know, I think it's very funny that as soon as Elon Musk left Tesla, the company stopped performing. That's a cultural issue, that that company seems dependent on one human being that's not good for the long run. He may live another 30 or 40 years or maybe longer, but you know that he, he can't do everything.
[00:14:05] So you know, those are those leadership issues that we debate endlessly have to facilitate this movement to super worker status. And when you look at, take for example Netflix, which is one exam, or Amazon, or you know, whatever company you in, your industry is really kind of rocketing ahead. And I can use our company as an example too. We are willing to reinvent ourselves. We are really willing to take risks, we are willing to try new.
[00:14:30] We're willing to go through one way doors because we see the inevitability of making changes and the need to have degrees of freedom and not get locked into some old model that's very frankly brittle and possibly could be disrupted by someone else or another change in the market. Those are leadership issues, cultural issues. And that also means moving people into and out of leadership. It means diversity in leadership and diversity in thought. I hate bringing the word up, but it's not going to go away. I'm sorry. To the US administration, diversity is a good thing and we're going to keep talking about it. And more and more and more we find that companies that are going through AI transformations, one of the big software companies I've been talking to the last couple of months is very clearly aware that they have a dysfunctional organization in some respects and they want to bring people together and reorganize and implement various AI solutions. But they're such an old culture of their original founding principles that the founding members, the people that have been there a long time, are afraid of making changes because they've been there so long. So their pioneering, innovative beginnings are holding them back. You look at what happened to Apple over the years, what's happened to intel over the years, what's happened to Boeing over the years. You gotta break stuff down and rebuild it a lot to make a company successful. And that's hard on the founders, it's hard on the leaders, it's hard on the people that have been around for a long time. But it's good for the company, it's good for the employees, it's good for the stakeholders, it's good for the customers. So those are the five things about super worker companies. And the reason I think this is such a. Maybe I'm overselling this, but the reason I think it's so profound is the pace of change and the transparency of information are disrupting everything we've ever done. When I got involved in HR25, 30 years ago, I read books, I talked to experts, I visited many companies, was very respectful of the history of all of these business practices that people had invented and pioneered and studied. I now realize, and I did a bit at the time, that none of that matters that much except in a historic, with a historic perspective. Because things are changing so fast. You have to invent in your company what's going to work for you. And this is another thing that's changed. I think we're going to move back to a world of companies building their own systems because AI systems are easy to program and develop on. We outsourced a lot of technology for many years to the cloud vendors and other vendors. We did a lot of copying of business practices at GE or other companies that we emulated. And that always, you know, there's always a need for best practice, sharing, reading business reports and case studies and things of other companies. But. But I think the secret to super worker organizations is, is invention, internal invention, and creating your own definitions of talent density and skills density and culture that are relevant to you. Every company in some sense is almost like an individual human. It has its own DNA and its own history and its own value proposition. And you need to take care of it. I can't tell you how to run your company except by giving you examples of others that I've talked to that might be similar to you or have gone through similar situations. And it gets back to this big topic of what we call falling in love with the problem, not the solution. AI is not a solution to be emulated for its own sake. It is a solution to solving a problem. And so, you know, if you think AI transformation is the way you define your company's transformation, think about these five super worker issues and I guarantee you you will be successful. Number one, people over technology.
[00:18:03] Number two, deep levels of technical skills and not fear of being afraid of getting involved into new technology. Number three, focus on capabilities in general and capabilities of change and redesign and reorganization. Number four, talent mobility, internal reinvention, career reinvention, whatever you may call it. And number five, management and leadership culture that is adaptable and fearless, but forgiving to deal with these changes. And if you do that stuff, you're going to find technology as your friend, you're going to find AI as your friend, and you're going to adapt your company quite well to this new environment we're in. As complex and disruptive as it feels. Now, I'm going to be working on this much, much more with many more case studies and probably write a book on it. I've decided I think it's time to write one more book, but we'll stay tuned on that and we're happy to talk to you about what this means in HR and hiring and recruiting and learning and development. I mean, we see disruption all over HR. The L& D function is going to be completely changed, as you know, we've talked about that. We have a great research study on that. Talent acquisition is going to shift to a growth function, not a recruiting function. Talent management is going to become talent density. Many things are changing in HR that we like to put words on them so you understand them. And I think the super worker concept is definitely the right way to think about AI and business transformation over the next couple of years. Thank you, Sa.
