Episode Transcript
[00:00:00] Okay, I have an interesting podcast I want you guys to think about, and that is in the throes of layoffs, Oracle and others. I'm beginning to think that the way we do layoffs could be much better managed by an AI agent. And here's the story. I wrote an article on this. So, you know, back in the 70s and, you know, 60s and 70s, when I was young, layoffs were a fairly big group, grandiose, episodic experience, and they didn't happen all the time. They happened three, four, five years apart in big companies during restructuring.
[00:00:35] And during that period of time, employees were much more loyal to their employers. We didn't have the Internet, we didn't have all these job search tools. And so, you know, you had this strong bond between worker and employer. So there was an implicit agreement on both sides that you were going to stick it out. And if you did do a layoff, it was a big deal.
[00:00:57] I worked at IBM when Lou Gerstner came in and very much remember the discovery that he had that IBM was broken in many ways and fundamentally restructured the company and laid off about a hundred thousand people. Jack Welch did this Neutron Jack at ge. And you know, many companies have gone through this in the past, but over the last 50 years, 50 years since then, two things have happened. Employees are much more unshackled from employers because it's easier to find a job, and there's much more contract work available. And young people want to be influencers. They don't even want to work for a company or they want to start their own company.
[00:01:37] And the regulatory and legal environment has also created more of an independent workforce with 401s, the reduction in the number of unions, and lots and lots of ownership messages that you should own your own career, you should own your own retirement, et cetera. And in exchange for that process or change, companies have moved to a much more regular redeployment or layoff process. Now, I don't mean every company's laying off people all the time, but there is a lot of it going on in a much more regular way. And if you, you know, if you're a historian of business like me, you've learned that there is no company ever created that didn't have problems where they had the wrong people in the wrong jobs. There's products that fail, there's market initiatives that fail, there's competition that stomps all over you in certain areas or geographies that you're just not suited for, et cetera. And so when that Happens. Wall street loves the story. Oh, we're going to get rid of a bunch of people.
[00:02:42] So what companies are now very anxiously doing is dynamically laying off groups of people for all sorts of reasons. And sometimes you don't even know the reason. They just do it. And then they make up an answer, they make up a reason, and they say it's because of AI. Most of the actual stories show that these layoffs are more like business problems than they are AI initiatives. Nobody seemed to be able to prove that yet, but I've certainly seen it anecdotally. So we're. So we're now in this world where the employees are a little bit more expecting this. I'm not saying they like it, nobody likes it. I've been laid off. It's no fun at all. But it happens more regularly. Wall street accepts it and kind of enjoys the stories and thinks it's positive. So the CEOs and the CHROs are looking for opportunities to restructure, flatten the organization, increase productivity, increase revenue per employee all the time. And then part of that is just creating a more accountable company where people feel a little more energy at work. Most big companies that I've worked in go through periods of time when things are kind of stagnant and you need new leadership or new people, or you need to sort of shake things up to get people to re energize themselves and maybe do something different or behave differently. I mean, I used to, you know, laugh all the time at IBM when I was there in the 80s when it was a great company that every year we reorganized the sales organization and a bunch of people changed jobs. And I used to ask my boss, I was pretty naive, why are we going through all these reorgs? And he said, because it's good for you. Because it's good for you to keep you on your toes. And he kind of laughed, and that was the end of that conversation.
[00:04:21] So given that the problem we have is that those of us in HR cannot possibly deal with these decisions quick enough. If somebody comes to you and says, this product is failing, we want to get rid of all the people associated with it. Well, it's not as simple as just looking at the org chart and lopping off an entire leaf and saying adios to all of you guys. Because some of the people in that business unit are very critical staff, skilled people that are needed in other places. Some are high performers, some are low performers, some are, you know, domain experts that might be needed somewhere else. There's all sorts of Strategic decisions that could be made when you're not in a hurry to redeploy people. And, you know, what do you offer people for a package? Should everybody get the same package? No. I mean, there's all sorts of math and algorithms you could make about how the package should be structured by different locations, geographies, costs of living, tenure, et cetera. Well, nobody has a lot of time to do that when a layoff comes along. I've been involved in a few of these, and there's all sorts of personal opinions and political reasons why this person gets laid off and not that person. I mean, I actually worked in a company where we asked the managers to come up with the individuals that they wanted to let go and then bubble that back up. That takes a long time. And there's all sorts of politics in that, in that process, obviously. So what if you had an agent that knew what everybody was doing, knew their job title, knew their level, knew their skills of the job, they knew what skills were needed, and they knew this person's skills reasonably well. And they also knew from performance ratings or business metrics what their level of performance is, either at an individual level or at a group level. And we got lots of data on that. We've got data on revenue per employee, We've got data on a number of lines of code written, time to market, whatever measures you want to use. If you had that data and you went to the AI and you used a tool like Galileo that knows a lot about hr, and you said, we would like to redeploy the technical staff working on Product X because we're going to discontinue it, and we want to redeploy them to the following three areas where the company's growing. Please assess the people that are the most valuable that we want to redeploy, and what kind of new jobs should they have. Then assess the people that are retrainable and what kind of job they could have, and then look at the rest and. And make a decision on whether we could redeploy them in other roles or whether we should offer them a package. I know the AI can do that. I know it because I've done it. We actually built a scenario here, a training scenario that we did for a bunch of customers at Unleash, where we actually created a simulated company. It was only an hour, but we could have spent a day on it. And we told Galileo about this company, and we explained how the company was organized, and we asked it a bunch of these questions. And not only Did Galileo make those kinds of decisions for us? But if we had wanted to, we could have also said to the AI, what is the best change management approach to doing this? How should we communicate it? Can you create customized emails? What are the courses and development programs that the internally redeployed people should have? And you know, every company, you could spend a lot of time building this talent redeployment or talent mobility agent.
[00:07:47] And by the way, Gloat has done this and they're working on it. They just announced it this week, but you could do it yourself also.
[00:07:54] And all of a sudden, the next time somebody says we need to lop off a bunch of people over there in that group, you could run the agent on it. The agent could give you some very intelligent answers as to what to do. So my point in sort of making a slightly inflammatory headline is that getting redeployed or laid off by an AI might be great, because if you don't have an AI, it's going to be a pretty coarsely grained decision making process and you might just get fired because nobody has the time to even assess whether you're appropriate for another role or another opportunity. And from a business standpoint, these cyclical layoff things, even though Wall street loves them, eventually do damage the brand of a company. There's a lot of companies that have been through this very regularly. Meta does this a lot. I know Oracle does it a lot. I know a lot of people at Oracle that have been laid off and over time the brand is damaged. There's a funny story I had a long, long time ago. I was talking with the head of HR of a defense and aerospace company in la. And there used to be a very big industry in Southern California. It's probably still there. Hughes Aircraft and Lockheed and all sorts of defense contractors used to be down there. And they would always be hiring engineers when there was a big federal contract and then laying them off as soon as the contract ended. So there were lots and lots of engineers in Southern California jumping around from place to place all the time. And one of the chros I met in one of the companies down there said to me, we now have this situation where we've hired and fired the same people so many times that they refuse to come work for us anymore. So we can't do it anymore. So as much as this feels like a positive trend in making companies more dynamic, and by the way, we've written an entire study on what the dynamic organization is, it's actually very hard to do because if you don't have something like this. I mean, you can have a talent marketplace, but that's a very slow way to redeploy people. Like you can say to people, all the people. I mean, this happens all the time in Oracle where they say your job's being eliminated. You have 90 days to find a new job inside the company, otherwise you're gone. Well, you know, as soon as that happens, the hiring managers get very, very picky about who they talk to. And you know, maybe some of the people can find roles, but a lot of them can't because the hiring managers may not even have the headcount to rehire them. So this AI agent approach is huge. And I would say this kind of an agent is a super agent because the talent redeployment or the talent mobility agent is going to have to talk to the pay agent about what the different levels of pay are. It's probably going to need to talk to the agent about DEI and other factors that fall into this. And then it's going to have to talk to the L and D agent about the skills adjacency of this job versus that job and what kind of training is needed and what kind of coaching the managers are going to need for these redeployments. I mean, this is a little bit early days, but I guarantee you this is going to happen. And the reason I know that is that if I think back about the 50 years of research, I've done years, about 50 years of research. I haven't been doing research for 50 years. This is a, an inevitable long term trend of what I call decoupling the employee from the employer.
[00:11:17] And if the agent can do a better and better job of making sure that the company has the right people in the right jobs and that individuals are given intelligent opportunities to reinvent themselves as the company evolves or the company changes or disappears, it's good for everybody. Anyway, think about it and we'll be talking about it a lot in their upcoming research on the future of hr. And we'll be talking about it at our conference. And any of you that have stories about this, just reach out to me. I'd love to interview you. Thanks a lot.
