Episode Transcript
[00:00:06] Hey, everyone. Today I'm speaking to you from Las Vegas. I've been all over the planet the last couple of weeks, and there were two big events I attended this week. One was the unleashed conference, which is an HR tech conference. And then I spent a day at the Servicenow massive Knowledge conference of 22,000 people. 22,000 people. By the way, the keynote could only support 8000 people, so 14,000 of the 22,000 people were in breakout rooms. And in both cases, of course, everybody everywhere is talking about AI. So let me tell you a little bit about what's going on from my perspective, and I'm sure you all have lots of things that you've been working on as well.
[00:00:54] So the first is that we this week produced and launched a piece of research we've been working on for probably six months on what we call enterprise talent intelligence. And what this is about is the expansion of sourcing and recruiting talent intelligence.
[00:01:12] The expansion of sourcing and recruiting talent intelligence to many other enterprise applications.
[00:01:23] For those of you that are familiar for those of you that are not familiar with talent intelligence in general, this is a technology that amasses many billions of employee profiles from many, many public data sources, including LinkedIn and many others, and analyzes individuals roles, skills, capabilities, potential career paths. And we can use that information for sourcing workforce planning, location planning, skills assessment, competitive assessment, leadership assessment, organization design, and many, many other things. And what the white paper, the research report is about is how this technology that started in recruiting is now an enterprise class technology for many, many other things. And so along those lines, not only are there lots of HR tech vendors with talent intelligence in their taglines, but there's a lot of data providers as well that are feeding this market and new jobs, new careers, new opportunities in HR for you or people in your company to do talent intelligence, which is a very important strategic function. And we've now worked with Chevron, Starbucks, Procter and Gamble, Coca Cola, lots and lots of companies that have implemented these systems, because we're very sort of involved in this and doing workshops to help companies understand their talent intelligence strategy. And it is really adding a lot of value.
[00:03:09] One of the companies I just finished meeting with at the conference, consumer goods company, has basically built domain specific capability academies in the major functional areas of their company, co owned by the business leaders and HR that are being fueled by skills data from their talent intelligence strategy, and they're continuing to advance it. And what talent intelligence does is it gives you the talent management information that you kind of always wanted from your talent management system, but you never had, who is ready for a new role, who can be moved in from this role to this role, who has the potential to do more leadership than we thought, who is overpaid, who is underpaid? I mean, all of these decisions that we thought we were going to make, be able to make in the talent management system, by the way, and also how do we assess somebody's performance? These platforms are going to give us maybe orders of magnitude better information for making those decisions and let us build much more adaptable organizations. So read that white paper and talk to us about it. But it is a big shakeup call, because this is technology that does not exist in workday, in Oracle, in SAP, yet they are working on it. They are interested in it. They are acquiring companies. To some degree, the higher score application by work day is a piece of that.
[00:04:37] But the big vendors are Eightfold. Gloat, fuel 50 to some degree. Newer companies like retrain, Skyhive, and many others that you can read about in the article. And it's important to think about it and learn about it, because I think it's technology that's going to upend, disrupt, and possibly replace a lot of the HCM technology that we've invested in for the last two decades. Now, the second, of course, topic is Genai and all the chatbots and HR related generative AI solutions.
[00:05:18] And I just finished a panel with Amy Coleman from Microsoft and some other people.
[00:05:25] This is also going mainstream to a large degree. It's definitely not mature yet, but it's getting there. For those of you that have used Galileo, you know how powerful a domain specific, well trained, safe AI chatbot can be. We are going to be announcing some new things next, the week after next at our conference. I think you're going to find very cool in the world of Galileo and companies. We did a workshop at the conference this week for about 50 companies going through basically the basics of what this technology is and how it works and what is a hallucination and what is drift and how do we protect people from seeing the wrong data and how do we manage the technology and what are some of the platforms we can use. This is going to be a massive undertaking in HR with huge ROI. It isn't just making you productive at writing articles or, you know, maybe editing a performance appraisal or writing a job description. Those are all somewhat commodity like features that we're all going to have access to. It's much more than that. You're going to be able to build a corpus of knowledge for your company, for new hires, for managers, for general HR questions. Train the bot as Microsoft does and is working on with the copilot, as Walmart has done with their own technology, as we've done with Galileo. And you're going to be able to manage that corpus and that system, and it will answer the questions from employees for you. It's going to make business partners more productive. It's going to make call center agents more productive. We're going to probably not need as many people in the call center and we can look at the intelligence about what kind of questions people are asking. We can tune it, we can train it. So there's going to be a lot of new exciting jobs in HR, building the content for these things, cleaning up the messes that we have, improving these things, training them and so forth.
[00:07:29] Now, the reason I mention it is that ServiceNow made a big deal about this with what they call now assist. They're trying to get everybody to buy it. I think now assist is going to probably turn out to be very, very powerful and to some degree competitive with Microsoft, although they also announced an integration between the two. Now, assist comes from the history of case management and IT service management. And so they're going to be doing HR stuff.
[00:07:54] Our product, Galileo, fits into this space for those of you that understand what we're doing, and then there are probably going to be a lot of homegrown systems that you're going to build. The other aspect to this that we talked about at one of the meetings I went to was learning. I honestly believe, and I've said this to many of you before, there is a trillion dollar business out there which will not be captured by one company, but we will be addressing it. Of legacy content, legacy websites, sharepoint portals, training programs, videos, articles, compliance documentation, process documentation, onboarding documentation, you know what I'm talking about. All these things and artifacts that we create to run our HR departments, to train people, to give people tips, to give them guides on how to do things, are sitting around in our companies collecting dust, overlapping with each other. We're not sure who's responsible for which one. We have tried various forms of knowledge management, wikis and so forth. Doesn't really work that well because the old stuff still stays there. Well, with Genaid, you can unlock that stuff and give employees access to that knowledge, that consent, that corpus, the way they want it, the way an individual employee wants it. I don't want to take a course on this process. I just want to know what step six, because I got stuck here. I don't want to take a course on safety. I want to know what to do about this frayed wire in my customers system that I just implemented. I don't want to take a course on how to lead and manage people. I want to know what should I do when this employee comes storming in my office because they're mad about their pay.
[00:09:38] These are thousands and thousands of interactions that we deal with every day. We try to build training or support materials, or we try to train and enable business partners and generalists to support managers and employees in these areas. We're going to spend the next decade cleaning that stuff up because now we have an access tool that makes it available. I mean, even if you do clean up your portal, your sharepoint portal today, people have to find the information. It's hard to search. They don't know where to search. They're not sure what is what to search for. That's a massive business. And if you're an l and D and you're building content and you have an lms with compliance content in it and courses from all the third party vendors out there, you're, I'm sure, undoubtedly scratching your head and thinking, well, why do we have so much of this and how come it all overlaps and who's using what? And by the way, I know, I don't really know what the utilization is of all these things. AI is going to give you all of that. That's this massive, massive information management solutions we're going to have in HR, and we're not going to do this overnight. This isn't going to be like you buy a tool and turn it on. It all works, but it's going to give us the capability to improve access to the relevant, timely, important information in ways we could never do before. And I guarantee you this is going to work because we have done it in Galileo. I mean, we have loaded 50,000 or more of our research assets in there. And it is really smart. I mean, it is getting smarter all the time. And my experience, and Bill and I have talked about this a lot is you don't want these things to be horizontal. You want them to be vertical. In other words, you want a specialized bot that's highly trained on benefits and rewards and flexibility and those kinds of things. Another one that might be trained on compensation systems and compensation analysis, another one that might be changed on other things. And those will communicate with each other through an orchestration system. So it won't look like you have to log into multiple things. Because when you create a database or a corpus that's very broad and wide, the system actually doesn't get smarter, it actually gets dumber.
[00:11:54] And then, of course, if you pollute it with bad information or old information, you've kind of messed up the recipe for your soup. I was using this as an example. You know, when you're creating soup and you're following the recipe and you precisely put all the ingredients in and you're tasting along the way, and it's getting better and better and better, and it's just right. And then you say it needs a little more red pepper. And while you're putting the red pepper in, the top falls off the red pepper, and a little blob of it falls in there. And then you taste the soup and you're like, oh, my God, it's too hot. What did I do? You can't untrain it. You can't pull the red pepper out. You can add sugar and try to counteract it. But now you have sweet and sour soup that wasn't really what you were trying to create, and it actually doesn't taste that good. And honestly, I actually think that's the way Genai works.
[00:12:48] These broad, generalizable systems like chia chi, VT and Gemini are pretty good at a lot of things. But when you get into narrow, very specific topics about medicine or business practices or financial analysis or HR like we have, they're just kind of generalists. They're sort of like average intelligence. Well, the deepest intelligence comes when the soup is perfectly made with just the right recipe. And so, you know, one of the domain expertise areas in HR we're going to have to learn is how do we build the soup with the right recipe and not add sort of the wrong kinds of things into it so we don't make it taste the way it's supposed to taste. And those of you that are working with us, and we encourage you to work with us, we'll show you what this means by demonstrating to you how this works in Galileo. And we're going to do more education, by the way, after the big success we had this week with this AI course we did for four or 5 hours, we're going to be doing much more of that. And also, there's an AI course in the JVA in our academy that's very, very well regarded. So I think you should check that out, too.
[00:13:58] The third thing I want to talk about is this somewhat ridiculous but interesting article that came out in Business Insider about workday.
[00:14:08] They called it something like the most hated software on the planet. Well, I mean, it's sort of entertaining to read it. And I'm sure the people at workday are very unhappy, but it's really not correct.
[00:14:22] And here's, you know, my justification for being bullish on workday. Workday is a very, very complex system. They have bitten off thousands and thousands of transactions and business processes that you've asked them for and tried to implement them in a system that has security, scalability, all of the global compliance data processes they need. And it's hard.
[00:14:55] The reason there's a lot of menus, the reason it's hard to use is because a lot of decisions have to be made at a product level in the beginning of the launch of a new offering, like the new learning system and the new recruiting system that later you decide were mistakes and you want to do them differently, but you've already made those decisions and they're coded into the software. So despite the complaints that this particular article points out from people about the recruiting tool and so forth in workday, they know about all this stuff. They have a lot of product managers there and they're going to work on it. And if you look at the ratings of Workday in g two crowd or any of the other software rating systems, I don't know how accurate they are, but there's a lot of ratings there. Workday is rated about four out of five. SAP successfactors is rated 4.1 out of five. Salesforce is rated about 4.1 or 4.2 out of five. The only HR system that's significantly higher is Highbob, which is a very unique, highly creative, almost instagram like system that we happen to use. But Hibob can't handle a global bank with 300,000 employees doing business in 35 countries.
[00:16:06] So I think there is some truth to the fact that workday does tend to sell the system as powering rock stars and that it's going to make you famous and it's going to make you more powerful. And nobody got fired for buying workday, et cetera. And I don't think that's necessarily the best marketing anymore. I think workday is becoming much more pragmatic now. I think under Carl, the company knows that they have to work with partners, they have to iterate, they have to have more third party solutions embedded into the system. They just acquired higher score, which is a fantastic technology. I talked to Athena Karp a lot this week, so, you know, don't read that article and say, yikes, you know, why should we consider workday because they're all this way? I mean, there's things about success factors that are hard to use. There's things about Oracle that are hard to use. There's things at ceridian that are hard to use. There's things about UKG that are hard to use. There's probably things about lattice that are hard to use. All of them. And when you're building HR software for small companies, there's slightly less functionality you have to build. And the newer vendors, many of the newer HCM vendors have started with employee experiences. First, building front ends for managers, workers, teams like 15, five, for example, lattices like that, culture amp, it's like that. And then they built in more HR functionality later. And they're missing a lot of HR functionality because they didn't design it as an HR operating system, they designed it as a management system for the workers or the employees or the teams. So, you know, depending on which side of this you're on, they're all struggling with the same issue. The reason I mention this in this particular podcast is the real answer to this, which has yet to be developed. But somebody's going to do it is to put a generative AI system on top. If you think about what you do in a core HR system, if you're a payroll manager, if you're a recruiter, if you're an l and D manager, if you're an employee, if you're a personal line manager, executive, whatever, you ask the system questions, you try to get information out of it, and then you ask it or tell it or transact with it to do something. Update my vacation balance, update my skills, update my education, etcetera.
[00:18:36] That all can be done in a conversational way. Now, we don't have the experience to do that yet, and it's not going to be as easy as it sounds. But ServiceNow is working on this, and I think workday is as well. But I think ServiceNow is ahead. ServiceNow has built and is building a series of transactions, generic transactions that they know people do. I update my vacation balance, I ask for leave, etcetera. And they've mapped all those out. And because they have open interfaces to lots of different HCM systems, they are going to map those transactions or use cases to various HR systems. So those of you that are willing to pay for ServiceNow, it's a very expensive product, by the way. They're not, you know, they're not trying to do this for free. They're in some sense more expensive than the core HR system itself. But you can or will at some point in time be able to abstract away the complexities of workday, Oracle, SAP, whatever into this system.
[00:19:45] SAP is doing this with Juul. SAP has a product that they are demonstrating that does this and they're putting a lot of serious energy into it. And I talked to Aaron Green who runs marketly for them and I'm convinced they're, you know, in some sense ahead of workday on this. Workday has vision of the same thing. I'm sure they're going to get to it and, you know, I know they're working on it and all the vendors are really going to be forced to do this. This is, you know, you know, from the use of your phone, from the use of your chat on your computer and the other devices that were beginning to take around with us that this is the way we're going to interact with technology.
[00:20:19] At some point we're not going to have web browsers anymore. We're going to have voice oriented or touch oriented systems. I'm not sure that web will ever completely go away, but it's going to diminish. That's where this is going to have to go.
[00:20:33] I think in terms of the frustrations people have with workday, there's a little bit of overselling that goes on with workday, of course. But you can't argue with the fact that 4000 companies use workday recruiting. Some similar. Thousands of companies use workday learning. Ten to 15 thousands of companies use HCM. Many thousands are using workday financials.
[00:20:57] They've successfully helped these companies do a lot of things. Now the sophisticated workday users build stuff on top of it. At Google they built a whole system on top of it. At Amazon they built a lot of stuff on top of it. But every company that says, you know, we don't like workday, we're going to build our own fails. It's very hard to do this.
[00:21:18] This is a complex, domain specific space.
[00:21:24] The way we manage people is very different in different companies. So one workflow won't work for everybody. So you have to make it very customizable. You have global issues in different countries, you have to localize the functionality. So if you're a tech person and you're saying, oh, we'll just build a system, replace it, it takes a while. ADP has a next gen ATCM system that is highly flexible, very, very different architecture from workday. I'm a big fan of it, but it's taken them a long time to get into the point where a lot of companies are using it. It's just reaching that point now that they have 20 or 30 large companies using it.
[00:22:01] I just want to give workday the benefit of the doubt here and say, I think that article could have been written about almost anything in enterprise software. And maybe the reason they wrote about workday is because workday does have such a pristine brand and is so highly regarded by so many people. And by the way, workday is still growing at 20 or 25% per year. So as difficult to use as you may think it is, companies are finding that it's still better than other things. So, you know, I just want to make a few comments on that.
[00:22:35] Okay, last thing really quick. We are ten days, 15 days away from irresistible. It's sold out. If you want to come sign up, sign up and we might be able to get you in on the waiting list. You know, every couple of people don't show up at the end. We have a spectacular cast of people coming. I just can't tell you how fantastic it's going to be. We're going to be doing a major announcement around Galileo there. You're going to see a whole bunch of cool stuff coming from us. You know, we are really an advisory, research and education company, but we're turning into a product company because of this technology.
[00:23:13] We're going to explain to you and talk about the history of how we built this and how it can teach you how to use AI in your company. And we're going to have some really exceptional learnings there from some of the people that are coming. We're giving away two awards to two world class companies that you're going to be really excited about. So those of you that are coming, we're really excited about the event. And if you're not coming, stay tuned. We'll certainly put out all sorts of information about what happened.
[00:23:42] It is a busy time. One final thing I'll say about AI, as I talked about last week, relative to employee experience, we are in the first year of a revolution. I think if you were living in the industrial revolution when Thomas Edison invented electricity and somebody invented an electric motor, and you were sitting around saying to yourself, how are we going to use this? That's kind of where we are with AI. We can't predict what AI is going to do five years from now, but if you're not experimenting with it, playing with it, learning about what it is and how it works and its strengths and its weaknesses and its limitations and its architecture, you are going to be left aside afraid of it. And that is maybe the biggest risk you have, is this is not intimidating technology. You dont have to be a computer scientist to use it. You dont have to be a computer scientist to learn how to do great prompting. You should be doing your own playing around and experimenting with it. Work with your IT department as much as you can. Because there is no question in my mind this is maybe one of the most revolutionary technologies I've seen in my career, especially in the areas that we work, where we have all sorts of vague data issues and human issues and content issues that we have to deal with in HR that vastly need this type of technology. So that's my kind of closing comments there. Have a great week, and we'll catch up again next week.
