Episode Transcript
Speaker 1 00:00:08 Hi everyone. This week I'm gonna give you a preview of the keynote I'm gonna be giving at our conference next week, which is about organizational ingenuity. And I know that's a new phrase, which you're gonna hear a lot more about it from us. But what we've basically discovered is that the combination of ai, the economic uncertainty and inflation we're dealing with right now, the constrained labor market, the need for more skills, the constant pressure to improve productivity, and the challenges we have with employees, stress have created an entire new model of talent. And I'm not gonna give you the whole keynote in the podcast, but let me give you a couple things to think about. As most of you know, the current economy we live in is shifting from the information economy to what I call the intelligence economy. And if you look at economic data on GDP per hour worked, it is starting to skyrocket.
Speaker 1 00:01:04 And going back to the 18 hundreds and the 17 hundreds, it was almost flat for most of the 14 hundreds, 15 hundreds, 16 hundreds, 17 hundreds. The mid 18 hundreds that started to go up in the turn of the century, it started to peak, move up a little bit more when we had the invention of automated farming. And then when the automobile was invented in the twenties, it went up more. And then around the 1950s and 1960s, it shot up thanks to the computer at the time, it was the mainframe computer, the mini computer, the personal computer, the mobile phone. And it went up significantly. In fact, the GDP per hour worked, grew. It took 150 years to double it, then took about 30 years to double again. And we believe it's going to double again in 10 to 15 years thanks to ai. And so it's an, it's an asymptotic vertical curve that's moving up, and you're all experiencing it every day.
Speaker 1 00:01:57 Just go to chat g p t and ask a question. Chances are that the answer you're getting is something that would've taken you 15 minutes or a half an hour or an hour to find, and now you're getting it in a few seconds. It's not always a hundred percent correct, but your time has been saved. And so what's essentially happening in this post-industrial age is these two conflicting things. The number of workers it flat to declining because of the birth rate and because of the retirement of the baby boomers in most countries, and certainly in the developed countries, yet the power or human augmentation of each individual is skyrocketing. So we're all becoming, in a sense, superpowered. You remember when Superman suddenly realized he could lift a car if you ever watched Superman? I mean, I did. He didn't know what to do with it.
Speaker 1 00:02:43 I mean, he was break. He actually broke things <laugh> early in the comic book series, and later realized he had to harness his power for good. And that's all, that's the whole story of Superman. And that's really the story of ai and technology is for all of the powerful bad things that could happen, incredibly large number of good things are happening. And we're already seeing that. And what we're gonna be introducing next week at the conference is our new HR AI offering, which we're gonna call the h Josh person HR co-pilot that you're gonna see live there. We're gonna be talking about the three models of ai, and we're gonna put together some discussion, which I'm gonna share with you next week on what I call organizational ingenuity on how to take advantage of these SUPERPOWERED workers that we have in our companies. And you know, it's just like when digital transformation started in the early two thousands, we didn't really know what it meant.
Speaker 1 00:03:36 We originally thought it meant digitizing the current way we work, which is what it was. And then later it became changing the way we work and evolving our work practices around digital, and then later changing everything around digital, the workflow, the processes, the interactions we have with the customers and so forth so that the human centered part of work was accelerated in value. The same thing's gonna happen again, but what's gonna hold us back, regardless of how much AI you give somebody, is your ability to be ingenious at the organizational level. Because what has happened during the last economic cycle is most companies were over hiring and they ended up with inefficiencies in the way they get things done. I just got off the phone with one of the executives at at Meta, and we talked about the hiring and the layoffs they've been through.
Speaker 1 00:04:25 We talked about this in the banking research. We just finished the CPG research, we just finished. The industrial management model is you hire people to grow. And unfortunately, most managers and leaders still work that way. How much headcount do we need? Let's staff this thing up. Let's reward managers with more people so that they can have more span of control and obviously make more money and have more power and influence. And we'll grow the company through the process of hiring and training and engaging more people. It's all well and good, and obviously we need human beings to run our companies. If you're a retailer or a hospital or a manufacturer or a product company, you need people to do the work. But if you injected AI into all of those jobs effectively, by the way, we don't know exactly what effectively means yet. Well, maybe you wouldn't need so many people.
Speaker 1 00:05:15 And I believe we're entering a period of time where bigger companies with more people will actually be at a disadvantage over smaller companies with a more ingenious organizational design. Now, this is not a new idea. I mean, the whole Agile manifesto brought this to software, the Mythical Man month, you know, Holocracy, I mean, there've been maybe hundreds of ideas on how to make organizations more efficient through flattening the organization, empowering people, getting rid of too many managers, giving people T mobility, which by the way, we're doing a big study on all of those things that that we've been working on, and you guys know a lot about. We've been out there, but it's different now because the level of knowledge and information that individuals will have and do have is orders of magnitude different. And it's not just that they're able to get information faster, it's bigger than that, they're able to assimilate more information faster.
Speaker 1 00:06:12 I've been playing around with our co-pilot, and what's been interesting to me is when you guys get a chance to see it, is when you ask it a question, it doesn't just read the relevant piece of research and tell you what was in that report. It reads all of the research in all of the reports and all of the podcasts and all of the articles and all of the courses we built, and gives you the best answer across all of them. So what AI is going to do for individuals is not just make it faster and easier for them to do the job they're in now, but to take advantage of cross domain information that they may never have even have known to ask for. So if I'm a customer service agent and I get a call from somebody that's completely off base from the domain that I'm responsible for, instead of transferring the call to another agent, I'm probably gonna be able to answer that question, or at least I'll know enough to direct that person to probably solve the problem themselves, or perhaps maybe solve it 75% of the way and then transfer to a another specialist.
Speaker 1 00:07:10 So we all become super generalists in a way, and superhuman specialists through ai. Now, I don't think I know all the implications of this yet. I doubt anybody can quite figure it out yet, but we do know that what we are going to be running into is the bureaucratic process of slowdown. So if you end up working in a company where there's too many people, regardless of how smart everybody is, less work gets done. And this was the focus of the People Analytics article I just wrote last week. In many cases, the knee jerk reaction to a talent problem is to train somebody or hire somebody. But actually that might not be the solution. And there's a fascinating example we just discovered at Panasonic. We interviewed one of the HR leaders at Panasonic. I won't get into the details of who and where, but they're, they manufacture batteries, obviously, they're growing like crazy.
Speaker 1 00:07:58 You can imagine what the battery business is like. And the HR team was getting beaten up by the manufacturing line. We need more people, we need more people, we need to staff these shifts. We're getting, you know, we want to improve the quality, we wanna improve the productivity, we wanna improve the output. And of course, the knee jerk reaction is, great, we'll get you more people. Let us go out there and try to figure out where we can find them. But this particular person did what we call a systemic analysis. I, I like that word. It's sort of brings together this idea of, of stitching the pieces together. And she looked at productivity and output and product quality over time based on staffing levels and counter to intuition. The more people they were adding, the slower it was getting. And the managers didn't really even know this.
Speaker 1 00:08:41 I don't think they understood it, or they were watching it, and perhaps the data wasn't clear to them. And she went back to them and she said, you know, the last 20 people you asked us to hire, we shouldn't have hired them. And so we're gonna move the line staff from 50 to 60 people down to 30. Because actually, if you look at the data, you're getting more work done and certainly in a much more productive manner with fewer people. And she said the first time she showed them that data, they had absolutely no interest in looking at it. They didn't want to talk to her. But once she showed the correlation between the different pieces and the actual validated production data, as a result, they became convinced too. And so this very strategic issue of creating organizational ingenuity and organization design is now possible because of the data we have.
Speaker 1 00:09:25 And I think when we're all super powered AI powered professionals, we're gonna have to look at this very, very carefully because you know, I have noticed in our company, we have approximately 40 people at the moment. We're growing at a rate that I never would've imagined because we happen to be very good at information systems. And actually now, hopefully will become very good at ai. I think this is true in sales, I think this is through in customer service. I think this is true in engineering. I think this is true in manufacturing. I think this is true in consulting. And so the big theme that we're gonna be talking about at the conference around the ideas of irresistible and my book is that all of these irresistible work practices are really opportunities to design your organization around super powered individuals who will have access to more information than ever before.
Speaker 1 00:10:16 Now, one of the unfortunate things that's happening in the middle of the AI revolution in the early days of this is there's a lot of noise in the system. There's hundreds of tools, there's hundreds of startups, there's VC firms making ridiculous predictions about this, that, and the other thing. I mean, what do they know? There's people who are AI experts going in the New York Times and telling us the world is gonna come to an end. Sam Altman's flying around the world scaring everybody. I'm really not sure why he's doing this. So it's a very confusing time. What you're gonna read about in the paper we're putting out next week is that what this technology really is, it's, it's a way to interconnect information and gain access to it in a much more productive and useful fashion than ever before. The information might be words, if it's a character sentence, the information might be images, the information might be data, the information might be sound.
Speaker 1 00:11:10 There's many, many applications of what we now are seem to be calling generative ai. But the ultimate outcome of this is you have to, as a manager and HR person, you need to become familiar with this technology and understand how it's gonna affect your organizations. Now, along the lines of this concept of irresistible organization design, let me share with you what we've learned through the org design research we did and the new course in the J B A on org design. It turns out that the actual design of the structure isn't as important as the design of the accountability, who reports to who? And whether you're set up this way or that way in the span of control, tho those are, you know, kind of interesting artifacts to think about. But the big issue is who's gonna be responsible for what and how are you gonna break the work down into clear lines of accountability?
Speaker 1 00:12:00 And then what are you going to do to measure and monitor and improve that accountability and get feedback on that accountability? And how are you gonna work together as a team? It turns out that in all of the projects I've been involved in, in my 40 some odd years of work, in almost every case I can think of where things went really well, the organization design had nothing to do with the success. There were cross-functional teams, there were senior people and junior people together, but there was a very, very clear mission and a very clear delineation of who's responsible for what. And in most of the most successful projects and companies that I worked in, we had very little bureaucracy. Every time there was something like a quarterly business review or a board meeting or a management review or any type of an inspection process, it slowed us down because the team itself didn't feel that it was adding value.
Speaker 1 00:12:54 The managers needed to kind of put their stamp on things. But you know, we as a team were very clear on what we needed to do, and we always respected each other and worked together as peers regardless of who was at what level. And we were honest with each other about things that were off track. And so while we're all becoming superhuman powered individuals through our tools, we're gonna go back to some of the basics of org, design of culture, of teamwork, of accountability. Does this mean we need more OKRs? Does this mean we need performance management? No, I don't think we need more of that. I think we need some of that. There have been many, many people who've kind of believed that these goal management systems are a way to run a large organization. I, I don't know if that's really true. I, I know that's a part of it and I know that many companies have found them to be highly successful when they're in large organizations.
Speaker 1 00:13:51 Generally speaking though, most of the high performing organizations I talk with are very good at talent mobility. They're very good at advanced skills and development of people. They're very good at talking to each other about problems and psychological safety. And they're very good at cross functional, cross domain, cross level collaboration and teamwork. And that's how the army works. That's how the military works. That's how most mission critical organizations work. And so the theme for next week is gonna be all about that and all about AI and about this idea that it will be your organizational ingenuity that will carry you forward into the next decade. The speed of getting information and the quality of information will be a commodity. You'll have to get good information and you'll have to get good at leaning up the information you have because it'll become very, very visible, very, very fast once the AI systems are all turned on.
Speaker 1 00:14:44 And we're finding that, by the way, in our company, now that we've turned on our AI and we're all looking across all the research, we're realizing we've got some metadata issues that we've gotta clean up. So we're doing that, but that will become commodity like value. And now the differentiation of your company is going to be your leadership, your structure, your accountability, your empowerment, and your skills. Let me finally conclude and just mention the pacesetter research. This week we launched the, the Gwi study of consumer package goods following the research we just did on healthcare and the research we just did on consumer banking. They're all interesting stories, very, very, you know, comprehensive in-depth discussions of those industries. But what we basically found is something very, very similar in the CPG industry is the others. Their problem, by the way, is a little different. The problem in CPG is that they're getting intermediated by retailers who are building white label products.
Speaker 1 00:15:36 And so they need to become customer intimate and they have to start thinking about their consumers as customers, not consumers. And they need to go direct to consumers, to customers directly and get customer data, customer information, customer marketing, et cetera, as opposed to assuming that the retail and distributors are gonna do that for them. So there's all sorts of skills there, but basically what we learned in all of these pacesetter studies is that the, the skills that are needed for high performing companies have to do with organizational agility. They have to do with change management, they have to do with bringing people together and creating alignment and, and making people feel comfortable with change. And that includes talent mobility and talent marketplaces and de development and cross domain opportunities and experiences, but also cutting edge skills. If you choose to wait and not adopt AI or not adopt data management, or perhaps in the case of cpg, not adopt direct to customer data systems, you're gonna fall behind.
Speaker 1 00:16:36 Advanced skills are now the currency of all the pace setters. And what we found in the banking industry, believe it or not, is that hiring advanced skills isn't enough. Because we basically published a study this week that said that virtually all of the tech people that joined the banking industry in the last year, or maybe it was last two years left, almost all of them, the inflow and the outflows almost identical. And that's because in the case of banks and other companies too, sometimes there are so many legacy systems that the advanced skilled people don't wanna work there. So you have to not only attract those people and pay them, but you need to give them a reason to come to your company and develop salary boosting skills. Because if they come to your company with these great skills and they don't find good work going on there to use those skills, they're gonna look back and say, wow, that that job just reduced my marketability in the market.
Speaker 1 00:17:27 So it isn't a matter of just identifying what skills you have, this is a problem of understanding the trending salary, boosting important skills, which by the way are in our gwi research. And then building a whole organizational ingenuity around attracting, retaining and enhancing those skills so you can stay ahead. Final little story on that, we're not a very big company, but when we started getting involved in our own AI project, which was, you know, really a couple of months ago, I knew it was gonna be hard, but we came up the learning curve very, very fast. And I would say that for us, it gave us the opportunity to think about our business completely differently. When you start using our co-pilot, you're gonna see that the research we've been doing for 22 or 23 years is even more meaningful when it's all brought together in a single, um, neural network than it was as individual studies.
Speaker 1 00:18:21 And I think you're gonna find the same thing in your company is that when you adopt a technology like direct to consumer marketing in the case of CPG or ai, in the case of maybe banking or another skill that's needed in healthcare, you think about your company differently because you suddenly see things and opportunities you just didn't even see before. So this isn't just kind of like bringing those skills in because you want to have more people that are smarter and better at their jobs. This is opening your eyes to business opportunities that you didn't even see before. And that's, that's another part of this whole idea of organizational ingenuity. Okay, I know this was a little bit of a mysterious podcast because I don't want to give you the whole speech, but I'm gonna be giving this story in great detail at the Resistible conference next week.
Speaker 1 00:19:07 And let me just say to you, relative to AI and all the things going on in the market right now, this is all gonna be good stuff. Lean in. We're build building a course in the JBA that'll be coming out over the summer or early fall. Um, really advanced course on ai, all sorts of cool stuff. And uh, we will have a lot to talk about when we come back from LA next week. Those of you that are coming, I'm looking forward to seeing you there. We're gonna have a fantastic time and have a great week. Bye everybody.
