Episode Transcript
[00:00:00] All right, I got a couple things for you guys this week. I spent the week in New York, had a lot of incredibly fascinating meetings I want to tell you about briefly. The first is a big article that just came out in Business Insider about the Microsoft copilot. Why Microsoft's been overselling it, some security issues.
[00:00:18] You got to read it. I think basically what's going on is we're finding out something that I think I've mentioned many times, which is these are specialized Systems and one AI platform that does everything from building PowerPoints to doing business analysis to doing employee self service to doing marketing is kind of a bit much. It's not really the right idea. And Microsoft, in their efforts to really work over and kind of lead this market has probably over positioned the copilot and it is not deep enough in all these different domains. You can read that article yourself. But the story there is you're not going to get one agent that's going to do everything you want in your company. Maybe never. I know everybody wants that. Everybody keeps asking me which one should I use. I mean, I'd like you to use Galileo, to be honest. But Galileo is only for hr. We're going to have multiple systems that are specialized in different areas that are optimized by vendors that have a corpus and a knowledge set in that industry. And I don't think there's going to be one agent that does everything. There's going to be one from SAP called Juul. There's going to be a workday assistant. There's going to be a bunch of stuff from Salesforce, the LinkedIn hiring assistant. You're going to see end to end systems like Paradox, Galileo for all this HR and leadership stuff. And there'll be a bunch for legal and there'll be a bunch for other areas. But read the article because I think it's very educational and I think Microsoft's not going away. Microsoft's going to keep working at this and they'll find the core winning use cases for the copilot. I just think they're a little bit spread thin at the moment. Okay, that's number one. Number two, I want to make a comment on the Doge Department of Government Efficiency. I wrote an article on this last week. You know, I won't get into my own political opinions here, but the federal government is an institutional organization. It has hierarchies, it has history, it has job levels, it has pay bans, it has job responsibilities, it has extremely important missions and and clients that it serves. Obviously the military Is, you know, life or death. Social Security, the Health and Human Services, immigration. You can throw rocks at this stuff all you want and get upset that your taxes are too high. But if you think you're going to re engineer it by two really smart tech guys slashing and burning budgets, it's not going to be that easy. Those of you that have done this in your own companies, what you probably remember, and I've seen this in a lot of the places where I've worked, that generally what happens when you have money that seems to be wasted, you try to cut it, but that the institution fights back. Because every project or initiative that you want to cut has a stakeholder or an owner or a sponsor. So usually what these organizations do is they cut the people first and then they decide what goes and what stays. Now the problem with the government is because we're all living on a lot of these benefits, that is really going to be hard. So I'm fascinated by this. I mean, I think it's a really wonderful idea and it has to be done. We can't just keep piling initiative on top of initiative on top of initiative. And of course Congress doesn't get involved in the details of how all these things get rolled out. That gets done by the agencies. But I don't think it's going to be a quick project and I don't think Elon and the other guy are going to get through it very quickly. But that's kind of the way it goes.
[00:03:55] All right, number three, I want to talk about expertise and job design. You know, the one thing that's interesting to me about AI and all these specialized agents is what they are doing is they are automating work tasks or activities that we do by hand. Things that we now think are very high value things become not very high value things. You know, writing emails, writing articles, editing, doing data analysis. It's much, much faster to do that stuff in AI if you know how to use it. And then if you buy an off the shelf system like a paradox or a LinkedIn hiring assistant, you know, then it does this, you know, in a very structured way and saves you time. And that, you know, by the way, is a little bit of the problem with the copilot is it's, it's very unstructured. Well, in order for that to be useful, you know, somebody in the company or individuals are going to have to figure out which of these activities they automate. But we didn't write down what all the activities are because we just did them. We didn't architect them. Well, in the last couple of months, last couple of weeks really, we have found through the big reset, a bunch of companies that did do that, they did write down every task or activity that a given job does. Two industries. One is construction. In construction, if you're trying to build a big building or a dam or a airport, or a bridge or whatever it may be, you have to know every piece of metal, every air conditioning part, every wire, every switch, every light, every construction, concrete pour, weld, et cetera. That stuff has to be figured out. And you have to know who's going to do each step. And the project management team actually does detail out step by step, who's going to do what. Sometimes they can delegate large sub assemblies to subcontractors, but somebody in that subcontractor is doing it also. So there is an industry that we can learn from and that is construction on how to decompose our jobs. Because in construction, if a weld, if we have a bunch of welders, we used to have this at the refinery where I worked that are specialized in pipe welding. And they're very expensive people, they make a lot of money, they are very highly trained and it's kind of dangerous work. And all of a sudden you stop welding because you buy your pipe pre welded by the manufacturer. Suppose that becomes part of the service from the people that sell you the pipe. Well then those guys need to be retrained. It's pretty obvious. But if you've got this kind of peanut butter approach to smushing all these jobs together and one of these things gets automated or disappears, we don't know what jobs go away and who becomes more efficient and who doesn't. And maybe we don't become more efficient because of course people find things to do to fill their time. So we're going to work on this. But I want to really get you to think about it. Because as I was talking to people about it and I talked to a vendor that I work with a lot, I realized that in a lot of the functional areas of business, the activities are the same. In B2B marketing, where I spent a lot of my career, there's basically the same 50 things that everybody does. You do customer segmentation, you do industry segmentation, you define your buying job title, you write content to differentiate your product. You come up with positioning statements for salespeople to position against the market or against competition. You do lead generation through events, lead generation through emails, lead generation through downloads of white papers. You go to conferences, you build Your own user conference, which has a whole bunch of steps with it. Anyway, there's like 50 of these things. And if you've done B2B marketing, you've done the same 50 things everywhere you've gone. And some companies do 23 of them, some companies do 26 of them, some of them do different ones. And the reason they do different ones is because the person who's running marketing may not know or have experience in some of these other areas.
[00:08:06] And every now and then new things come up, like affiliate marketing is new and there's other things that have been created, you know, innovations, but they're more or less the same. That's unfortunately lost on those of us who run our companies because we don't really structure these jobs quite so finely grained like we do in construction. We don't have a list of tasks that we run around on a project. Well, some people do, actually, but a lot of them don't in marketing like you would in construction. So if we come along and say we're going to automate this, this, this and this, we got to figure out who's doing this, this and this because. Because it's not always clear and how are we going to take advantage of this new tool. So this is a really valuable exercise. I don't think it takes months, by the way, to do this. I think this can be done in a week or less. But to go through these functional areas where we have AI, by the way, HR is definitely one of them. If you look at Galileo and when we publish the hundred use cases for Galileo, you're going to go through those hundred use cases and you're going to, oh, we got to do this one, this one, this one and this one. And you know, Joe's doing part of that one and Sally's doing this one and Sue's doing this one, you're going to go out there and you're going to do this. And that's what's going on. And I talked to the investment bank I met with about this, I talked with several other clients in the L and D space about it this week. And I think because of the focus of AI on automating, these activities, I don't want to call them tasks, I call them activities, that there will be a lot of this engineering going on. And we're going to start putting our engineering discipline into white collar work. Okay, third thing, expertise.
[00:09:41] Now, this is a big topic and it's been going on for hundreds of years. And many people have looked at how experts are Developed why some people are experts at one thing and other things, the full stack versus the vertical, T shaped expert, et cetera. Well, it turns out when you look at HR which the primary place where I spend my time, the deep domain experts are badly needed, but they're not that useful if they're not cross trained.
[00:10:12] And we know this from Systemic HR. In Systemic HR, we identified more than 400 job titles in HR, each of which are different jobs. And we know there are at least 96 complex capabilities which we know and we assess in our capability assessment. So if you had a person or a job that clustered together these 96 things in these 400 job titles, you're going to have a very complicated HR department. It's going to be really hard to manage. And the reason that isn't a good idea and we don't want specialist, specialist, specialist, specialist is that in our particular domain these things are all very interconnected. In marketing, if you're doing lead gen and you're doing an email campaign, all you need to know is that you got a certain number of leads and then they'll be handed off to the next person in the cycle. In hr, if you're working on pay, you got to look at tenure, you got to look at skills, you've got to look at span of control, you've got to look at the competitive job market, you've got to look at cultural issues in the organization. Are we a high payer or a low paying kind of company? You got to look at our benefits. I mean that's just one thing. You could pick any one domain of expertise in HR and I will guarantee I can show you 10 other things that are either affected by it or that impact your decisions that are probably more than 10. So when you say who's an expert in HR? I think we need to change the idea from an expert to being a consultant or a domain expert. Because as we talked about with the investment bank that I met at a really great meeting with this wonderful company, know New York, the greatest HR people that I've met in my career are very rounded professionals. They know a lot of things. They've been through layoffs, they've been through recruiting, they've been through learning and development, they've been through leadership. They understand issues of dei, they understand issues of employee experience, they understand why people are productive, they understand onboarding, they understand enough about technology to understand what it doesn't do versus what it could do. And they know this from experience. They don't. They haven't just read about it, but they've done it. And that is where we're trying to go with systemic hr.
[00:12:36] And Kathy and I are very excited that systemic HR has taken hold like a wildfire. When we first started this research more than two years ago, probably more like almost five years ago, and I came to this conclusion that we were organizing our HR departments like 1980s IT departments. And we went into it and did a lot of research and talked to a lot of companies and thought about it for a while. We basically concluded that HR is an integrated system. It is a system of services, expertise, consulting, advice and content and transactional services. And some of them are packaged into products and offerings. Some of them are simply available as self service transactional systems. But some of them are very handcrafted based on the problem and the nature of the group that you're working with, as you know. And we have to merge this all together. I would imagine it is the same way when you actually look at it, but I'm not as familiar with it these days.
[00:13:40] So the word expert in HR to me means a full stack expert. And when we got into this with this company we were meeting with in New York, we all came to the same conclusion that we're not going to just move people around from place to place just to give them a rounded experience so they would feel like they're having a more enriching career. We're going to give them enough depth so that they really understand the domain they're in and then move them around strategically from place to place to see the interconnectivity of these things. I mean, a good example of this is the relationship between recruiting and learning.
[00:14:20] You would imagine they have no relationship whatsoever. One is about finding people and sourcing people and interviewing people and qualifying people and getting them to take jobs. And the other one's about training people, educating people, understanding their skills and so forth. Well, they're actually very related. What recruiters do is they assess people's capabilities and skills. That's what really good recruiters do. They just know how to do it through a different form than an L and D person. Well, what L and D people do is they look at performance gaps in groups of people and they try to figure out, oh, well, there's Joe over there who's really good at this, and there's Sam who's not very good at it. So let me find the difference between Joe's skills and Sam's skills. And now that shows me what kind of a training program we need to build. That sounds A little bit like what happens during a recruiting process too, when we need to hire a new person and we're not sure who that new person is. So my point is that we need to come to grips with the fact that the word expertise is a very meaningful word in hr. And when you want to do an HR transformation or a downsizing or restructuring or whatever you call the change that you're going through, you're going to have to deal with this issue, especially with AI, because AI is going to create a whole bunch of questions and discussions about who does what. What do the instructional designers do when the AI builds the course for you in 60 seconds? Are they performance consultants now? Are they graphics people? Are they editors? Do we promote them into a higher level job or do we promote them into lower level job? I mean, this is going to happen a lot. It's going to happen in a lot of these responsibilities. So, you know, the word expertise is going to come up over and over and over again as we go through this transition into AI. Okay, one more, you know, quick thing because I got a couple more minutes here. Session that I did Wednesday morning was with our friends at SANA on the future of L and D. And we had the same exact experience there that I had at LinkedIn. And I just want to share it with you. L and D, which is a $320 billion industry, very large, very complex, not all of it's in hr, by the way. A lot of it's not in hr, is about to be disrupted in a significant way, and it's long overdue. Because what's been happening to L and D is we really haven't had that many new paradigms or technologies for about seven or eight years. The last major innovation in corporate L and D, other than VR, which is a little bit of a niche area, was the lxp, the Learning Experience platform. And the Learning Experience platform, as innovative as it seemed, was really a band aid on top of the LMS, which is 25 years old. So we didn't, other than video authoring and YouTube and things like that, we didn't really have big transformational innovation available to L and D professionals. So all of the skills projects, the talent intelligence work, the advanced global workforce planning data that we're getting, job architecture stuff, kind of didn't involve L and D that much. And I know a lot of L and D people, and I think a lot of them were left out in these transformation cool things. And they were just running their training departments, doing the best they could, trying to make the experience modern and useful and basically valuable. Along comes AI and all of a sudden we wipe out a massive percentage of the number of things L and D people do. And so I've been talking to L and D people about this now, and we're going to produce a big piece of research in Q1 or Q2 that they'll explain this. Essentially, what's about to happen is the L and D team is going to rise up and become very, very important. So for those of you that are in L and D, or in leadership Development or any of those titles, you are going to play a massive role in the management of knowledge and information and education and skills in the next year. And that is what we talked about in New York. And we will tell you much more about this ahead because this is a big core area for us as a research organization, but also as an education organization ourselves. Okay. I know a lot of you like me keeping this to 20 minutes, so I'm going to stop there. Look forward to catching up with you guys over the next couple of days, and we'll talk again next week. Bye for now.
