Episode Transcript
Speaker 1 00:00:07 Hi everyone. I'm gonna be outta town this weekend. So I wanna start the podcast a little bit early and give you some things to think about here. First of all, I had a very interesting conversation with Scott Galloway, who's a very renowned professor at NYU Stern and well known in the business community about remote work. And the interesting thing about the conversation is, even though Scott and I are about the same age, we have very different perspectives on remote work. Scott's position is that young people have to be in the office to get ahead, they have to physically be present with their peers to learn, to understand the workplace, to understand personal dynamics, to become leaders, et cetera. And I completely agree with him. Where we differed a lot was he grew up in the northeast, in New York City working for an investment bank where you had to work 80 hours a week to get ahead.
Speaker 1 00:01:06 And during the first five or 10 years of his career, he was very, very active and very, very successful, which he believes launched himself into the career that he's in today, which is quite an interesting career he has. My situation was really quite different. I spent really 20 years, 15 to 20 years of my career in mid-level jobs, doing things I loved. I loved being an engineer. I loved working in sales. I loved working in customer service and customer support. I loved doing product marketing. I loved doing product management. I loved doing corporate marketing. And I had eight or 10 really interesting assignments in technology companies, including some very fast growing companies as well as 10 years at IBM before I became an entrepreneur, before I became successful in the current definition of success, which really didn't happen to me until I was in my forties, mid forties.
Speaker 1 00:02:00 So the difference I would say in our perspective is Scott's perspective is the sooner you lean in and strap yourself in for a rocket ship career, the better. In my case, it took later and it worked out fine for me because I learned a lot of things early in my career. And that means that if you work from home and you choose to work from home, which many people do, by the way, I think I shared the research that I found that shows that from Gallup, that the people who work three to four days in the office have the happiest work lives much happier than the people that work five days in the office. That you just do have to lean in and show up every now and then because that is important to get to know people and learn how to work together. So that was a really interesting conversation.
Speaker 1 00:02:44 Let me add on the topic of remote work that this week Amazon workers are planning a walkout because they're unhappy with management's mandate getting all white collar workers back in the office, which Elon Musk has made a big stink about this too. I've done a lot of research on this and I've talked to a lot of companies and that is not necessary and probably not a good idea. Second thing that happened this week is we finished the big AI white paper we're going to be introducing at our conference. Irresistible has about 40 or 50 seats left if you'd like to come. It will fill up, go to irresistible 2020 three.com to register. And we have just an incredible lineup of activity and speakers and fun and games and things on the USC campus and visits to different corporate offices and things going on there. But one of the things that is discussed in that paper is the three generations of ai, the first generation being the Boltons, which I consider a generative ai, basically to be a Bolton to existing product.
Speaker 1 00:03:46 So if you're a vendor and you add generative ai, I consider that Generation zero or integration of existing systems of AI into your platform. The second is using machine learning and various forms of AI in your system. And that is typically what transaction systems do like Workday or Oracle or sap, although they're all changing. And then the third is what I call second generation systems that are built on AI first and become transactional systems later. And that sounds odd, but I had a really interesting conversation with Asha Tosh Gar yesterday from Eightfold, and I've talked to the folks that seek out and a few others that are AI first companies. And what they've basically discovered is that when you build an AI centric system first, that can deal with very complex heterogeneous data sources, finding in a sense signal from noise with many, many complex data amounts.
Speaker 1 00:04:42 You can then store data in a transactional form from that. And we TA had a long conversation with Success Factors last week about their architecture, and they are moving to an AI centric architecture. They are moving to a second generation architecture. They see the need for that in the HX M success factors platform. Workday is doing a lot of work on machine learning and their platform as well. They are using it to simplify workflow processes, make better recommendations of Workday, make Workday easier to use. They haven't experimented with an entire large language model for an entire corporate's HR data set yet, but they are playing around and they have a lot of machine learning engineers working on things. And so it'll take some time to shake out what the traditional E R P types of technologies do in the world of ai. But as an engineer, myself and a data person, I do believe that the ROI and the value add of an AI centric system is going to be in order of magnitude greater than that of a transactional system.
Speaker 1 00:05:40 Transactional systems are never gonna go away. You gotta pay people and you gotta store data and you gotta keep records on things. And I mean, that's not a bad business to be in, but to suddenly pretend that your transactional system is an intelligent system isn't really fair. And that's the reason we're putting out this, this big white paper. So you'll get that at the conference, and we will also be previewing our our AI there and talking with quite a few leaders in the AI industry there, including some faculty from usc, some folks from Microsoft and some other companies. But that's another kind of latest thing that happened this week. The third thing I want to mention is the job market and economic data that's been coming out. It's pretty clear from the economic data, despite all the shenanigans going on in Washington, that the job market's very healthy.
Speaker 1 00:06:31 And yes, there have been layoffs, but most of the layoffs have been companies that radically overhired and just weren't managing themselves well. And my perspective on that is you're gonna hear about in systemic HR is you should never be hiring willy nilly, even in the best of times to compete with your market competitors because you end up creating a bureaucracy. And that's what happened to a lot of these tech companies that overhired. But generally speaking, even though there's a little bit of a layoff scenario going on in some companies, most companies are doing pretty well, and we're now coming to the grips with the new demographic reality that the number of people to hire in the world is probably going to flatten or decrease. In fact, some really striking data came out about China that I think China has been lying about their birth rate and the growth of their population.
Speaker 1 00:07:27 And some of the data I'm gonna share with you at the conference might convince you that the Chinese economy is not nearly as strong as people think it is, just for demographic reasons at all. The reason that's relevant to you in HR is this issue of always being able to hire the person you need when you need them, is the way we've been brought up, right? I mean, that's the way companies operate. We hire people into the company all the time as we grow and we get rid of the people we don't need or the people that aren't performing well or the people we don't like, or whatever excuse we have. And capital is more important than labor. And so the labor is a little bit more of a replaceable part in the, uh, expense side of the, of the ledger. That's just not gonna be true anymore.
Speaker 1 00:08:15 We, we aren't going to have the workforce availability in the future that we've had in the past. And this has been happening slowly and slowly and slowly, more and more and more. And as I've thought a lot about my keynote at the conference and what I'm going to contrast over the last several decades, both that I've been doing this work and prior to that, the most existential change that we're going through is the shortage of labor. Now, coupled with that is technology. And there's no question in my mind, and I'm sure you're all coming to the same conclusion, that AI or this intelligent technology that we now are beginning to get our hands on is transformative in many, many ways. The productivity increases, the amount of automation we can put into jobs, including white collar jobs, and the sort of creative unleash of generative AI is gonna change the amount of work every individual person can do.
Speaker 1 00:09:12 And if you wanna be a profitable company competing against others that are using ai, you're gonna have to do the same thing. So you thought digital transformation was tough for the last 20 years. This one's gonna be even bigger. I don't think it's gonna be as hard because we've gotten familiar with this idea of transformation, but it's going to be significantly important and in some sense, a mandate. And that leads me to the third thing I want to talk about, which is the pacesetter research. And I've talked about this in the past, but I've had a lot of time to socialize it with many companies. We're going to be introducing a big new study next week on the consumer package goods industry. C B G industry is massive. These are companies like Nestle, Mars, Unilever, Clorox, general Mills, these are companies you do business with all the time.
Speaker 1 00:10:05 Coca-Cola every day. The historical way those companies worked is they either developed through research or they acquired brands that had particular products, consumer products that were well known or well established in their market segment. And their company was basically a big distribution company. And so what they would do is there would be a fair amount of r and d in developing something new, and there would be this massive distribution network of truck drivers, store shelves, retailers, online activities all around the world to get that stuff to the market so that we would buy it and consume it. And so the vast majority of their infrastructure and skills and investment was in that supply chain and distribution process. Now, two things have changed, and you'll read about this in the report if you're a member, but I think it's relevant to every company. Number one, consumers became very, very discriminating.
Speaker 1 00:11:07 Right now, I'm very worried about food and even skincare products and even sunscreen when I go for a bike ride that doesn't have healthy things in it, I'm in my, you know, later years. I don't want to get any sicker that I may already be from all this stuff. So I'm very careful about what I buy, and I get a lot of those signals from my kids who are even more worried about it than I am. I can go online and I can find information, and I can find products from all over the world that are the healthiest ones in the world if I choose to, so I don't have to buy it just because it's in the company's shelf. And then of course, the second factor is that the retailers are getting smarter and smarter and smarter, and they've built w White label brands to intermediate or disintermediate CPG companies from reaching you.
Speaker 1 00:11:58 If I go to Whole Foods where I happen to go shopping fairly regularly, the 360 brand, which is a selected Amazon brand, disintermediates lots and lots of other companies. So the CPG companies have to get smarter about data and markets, and they have to get closer to their customers. That isn't something they were really good at. They were reasonably good at r and d, but most of their business was scale. And this goes back to the big discussion I had in the last podcast about the industrial scale model of business. These companies, just like everybody else, have to become consumer, customer, intimate companies. They can't think about the consumer as one giant market anymore. They have to think about all the micro markets of consumers, and they have to build products and marketing campaigns and eventually forms of distribution to meet them directly. They can't assume that Walmart or Target or whoever they're going through is gonna distribute their products effectively for them.
Speaker 1 00:12:59 I distinctly remember when I was at Sybase 15 or 20 years ago, and we were selling a lot of data warehouse software to consumer companies. Their real strategy was to get products on the shelf so that you could buy it and you could find it. Well, even though that remains an important part of their businesses now, they have to be very smart about data location, a sentiment, competitors. And you'll see in the report how different the skills are amongst these companies. And the pacesetter CPG companies, just like the pacesetter healthcare companies, the Pacesetter banks, the pace setters in the other industries that we're studies are really good at identifying these critical new skills. And they don't just talk about them, they lean in and they use them. And here's the thing about advanced skills. Talking about advanced skills. We can talk about it till you're blue in the face, but until you actually have somebody using them, you don't know the implications of them.
Speaker 1 00:14:00 Every company I've ever worked at in my entire career, there have been a few people kicking around. Sometimes they're kind of over in the corner that are just hacking away at something that's really different. And sometimes we don't respect them or pay attention to what they're doing. But lo and behold, those people tend to discover things in your company that are transformational if you're listening and paying attention. And that's what advanced skills mean. Advanced skills doesn't mean waiting for everybody else to do something, and then you do it too. It means trying new things in technology, in consumer, in the business processes, in whatever it is you're working on in your functional area, including HR, by the way, and learning from those new ideas. And in the world of hr, we don't do enough of that, although we're starting to do more and more and more of it.
Speaker 1 00:14:51 We've had quite a few senior level discussions with HR leaders as we prepare for the conference. And in addition to the pacesetter issues on the business side, there's the pacesetter issues in HR because the more we discuss systemic HR with people, the more we see people nodding their head and saying, absolutely, absolutely, absolutely, we need to do this. And then they look around at the team and the ability to change within the HR department and they say, well, we need to do this ourselves. And that is a cultural strength that we're gonna talk about in the conference. And we're gonna really highlight, and we're gonna give you some information. We're gonna highlight two award winners. We're gonna give away two awards for two very interesting companies at the conference that I think you're gonna learn a lot from on how to operate at scale without necessarily hiring more people, how to transform the company through HR and how to build a full stack end-to-end systemic HR operation.
Speaker 1 00:15:51 So that's a lot of new stuff that we'll be talking about in the next couple weeks too. The final thing I'll touch on as we wrap up the podcast for the weekend, given that it's a little bit early here is a piece of research. We're just finishing with ams, Alexander Mann, who we're working with on all sorts of things in recruiting. And it has to do with the time to hire. And if you look at time to hire data, it's a metric that a lot of recruiting firms and recruiting organizations look at. It's been extending little more and more and more year by year. The average time to hire in the benchmarks we're gonna publish is in the 45 to 50 days. That's almost two months, and it's lower for some jobs and higher for others. Why is it so long? Why does it take so long to hire people?
Speaker 1 00:16:40 Well, one is of course the unemployment rate is very low. So people can look around and be very discriminating on the jobs they take. But the ultimate reason is the process of hiring in most companies is kind of a bureaucratic mess. We've got this candidate pool development process to bring in candidates. We have the sourcing process of matching a candidate to an opportunity. Then we have the process of interviewing and screening, which goes on for weeks and weeks and weeks. Then we have the process of generating a job offer and negotiating a set of benefits or pay that the individual will be willing to take. And then there's the process of getting the person to come join us. 45 to 50 days or two months is actually pretty fast, but it is a long time. So the question that you ask yourself is, given that it takes that long and is expensive, and in some cases it's not gonna work out, you know, at some percentage of the people you hire are not gonna be a good fit for just random reasons, things you missed.
Speaker 1 00:17:44 Why do we spend so much time on hiring? Well, first of all, there are companies like AMS that are very good at simplifying this process so you can be more strategic about it. I have found over the years that it is better to slow down your hiring in many cases, to make sure you're hiring the right person and that you're carefully designing the work for that person that really justifies bringing that person into the company. I know there are a lot of companies that hire retail, frontline high volume workers, and they have to hire all the time. That's a little bit different. That's a different situation. Those time to hire situations can be very short. But for the more high value, difficult skill oriented jobs, it is okay to slow down. So if you can bring in a company like AMS to help you and you can accelerate that process, you can have a huge impact on the agility of your company.
Speaker 1 00:18:41 Because if it's taking you 60 days to hire somebody and you're doing a reasonably good job at it, think about what's happening during that 60 day period in terms of how your company's changing. There's a basically a big lag. There's a two month lag between everything you want to do. And when you get started doing it, and by the way, as you know, when somebody starts in your company, they don't become productive the first day. It takes probably 60 to 90 days before they really know what's going on, maybe even longer. So this extended time to hire issue is, is really quite an interesting problem we have. It's not gonna get any better the way the job market is working now. And you can use companies like Amms to help you develop a much more scalable process or you can do it yourself. And of all the things we've learned in the Gwi research and in the pacesetter research, in the area of recruiting, you really need a systemic approach.
Speaker 1 00:19:34 You need to look at internal candidates. You need to look at the job very carefully and the skills that are needed, you need to source in different locations. You have to be much more intelligent about diverse hiring, non-biased hiring and removing the factors that are irrelevant to the job and the candidate qualifications. And let me conclude with one more thing. One of the things we're gonna talk about at the conference is the new laws that are being passed on ai. Keith son Ling's gonna be there, who's a great guy. He's the chairman of the E E O C, commissioner of the E O C. There was a largest passed in New York that says that if you're using any AI tools for hiring, you have to prove to the state of New York that they're unbiased. And the interesting thing about that law is it's actually sounds like a good idea, but it's also the beginning of a little bit of chaos.
Speaker 1 00:20:28 And Keith's gonna talk about this because even before that law was passed, there are E E O C regulations about fair hiring practices. So whether you use AI or a recruiter or you're just randomly picking people up, up off the street to join your company, if you discriminate hiring, you can be sued. And I actually was sued by somebody who thought there was discrimination in our hiring process. There wasn't. We settled with her, but it was really a misunderstanding. And that law already exists. So all these new AI discussions were having about legal ramifications of AI may not be as important as you think. And we're gonna talk that over with Keith cuz he has some very interesting perspectives on what we're gonna do about pay equity, what we're gonna do about diverse hiring, what we're gonna do about E E O C mandates and so forth.
Speaker 1 00:21:19 So anyway, those are things to think about for the next week. As I said, I'm gonna be out of town this weekend, so I won't be doing a podcast on Saturday, but I hope to hear from you and you've got a couple more weeks to come to our conference. As I said, it will be full. We've already got quite a fascinating group of people coming, so it's gonna be a fantastic event. June 20th through 22nd at the USC campus in Los Angeles, go to irresistible 2023, you're going to see a preview of our new AI system for research, which I think you'll find cool. You're gonna see a preview of the new Josh Bur Academy, and you're gonna get a chance to meet lots of amazing people, some of the most incredible HR and business leaders in the world. Thank you.
