Joe Fuller: Welcome to the Managing the Future of Work podcast from Harvard Business School. I’m your host, Harvard Business School Professor and Visiting Fellow at the American Enterprise Institute, Joe Fuller. We’re please to present Part 2 of my interview with Cal Newport, Georgetown professor of computer science, author, and contributing writer to The New Yorker magazine. In this section of our comprehensive conversation, we’ll talk about how to define and measure productivity—and Cal’s concept of “slow productivity.” We’ll also discuss social skills, leadership, virtual reality, quiet quitting, and scientific management’s long struggle to come to grips with knowledge workers. Cal, you mentioned that you’ve got a new book in the works. Tell us a little bit about this and this concept of slow productivity, how to think about productivity differently.

Cal Newport: Well, we don’t have great definitions of what productivity should even mean when we’re talking about people who work at a computer screen and use their mind to actually think. I mean this is one of the big counterarguments people often have at first when I talk about these types of topics. They’ll just say, “Wait a second, it’s dollars and cents. If this way we’re working is not productive, why wouldn’t we just immediately evolve toward ways that are more productive? We would just see, okay, less email, less distraction, now we’re more productive. Why would we not just naturally evolve there quickly?” And I think the answer is, we don’t have the metrics. We can’t look at average man minutes per Model T produced, which was a key number that helped Henry Ford justify the big investments into the continuous-motion assembly line. We don’t have that in knowledge work. And so this was an issue that became clear, as I was writing about people’s frustration with work during the pandemic, is that there was a generic discomfort with the notion of productivity, because they didn’t know what it meant. People were interpreting it as a sort of psychological pressure, just I guess be more busy. There was industrial notions of what productivity meant. And so I started this project in the pandemic of, let’s come up with a definition. What is an actual aspirational definition for what productivity should mean for someone who uses their brain to make a living—a definition that’s not only going to produce really good work but create a work environment that’s sustainable and meaningful and something that people actually enjoy doing. That’s where this notion of slow productivity emerged. It’s still a work in progress. But the three principles that seem to undergird it right now are: 1) doing fewer things at a time. The human brain is really bad at having a large task list. That’s not the way we’re wired; 2) It stresses us out working at a natural pace. So the industrial notion of, there are set hours that we should be at peak intensity for those full hours and just do that day after day. Actually for elite-level knowledge work, you want more variation that’s more sustainable and natural; and then finally, 3) obsess over quality. The focus should be on the quality of what you produce and less on some sort of generic notion of presence or performative busyness. So I’m trying to actually build a notion of productivity that you could build a company around or build your freelancer business around or build your start-up around, and not only be very successful but have employees who are happy.

Fuller: Yeah, I’d suggest that, actually, we see a mirror image in performance management systems in white-collar environments to the type of useless data and complexity and intrusiveness that you describe in work processes more generally. If you go into a large company, you’ll find a proliferation of key performance indicators, use of a “balanced scorecard”—a very famous tool developed by a colleague of mine here at Harvard Business School that has become so complicated, that you are trying to measure so many things, that nothing really counts. No genuine type of focus is being imposed by the performance management system. And in fact, since it’s impossible for any human being to accomplish 18 things in a period, it doesn’t serve the purpose of lending focus and discipline on somebody’s subordinates, because they always have the completely legitimate position to say, “I couldn’t possibly accomplish all these things that you put in my priorities for the year. So I’m not accountable for any of the things I didn’t accomplish.”

Newport: And we have no idea, and that’s the key. We have failed to this point to have a quantitative, reasonable, generally applicable notion of productivity. And so we have to shift probably toward something that’s more qualitative. I mean slow productivity is in some sense more qualitative. It’s more of a mindset about what work should be than it is a matrix that you fill out and it leads to a number. In the book I talk about, go back and look at the histories of some of the greatest scientists in history. I really get into the details, starting with Copernicus going forward. On the day-to-day scale, they often seem disastrously unproductive by our modern standards. Months will go by where they’re not even working on their core project, but they also changed the world. I mean, it’s a really hard thing to try to nail down—what do we mean by productive—once we really step away from the de-skilled industrial paradigm of, you’re here during certain hours, performing actions that usefully apply energy to a process that generates value. We want to see you in action. We care about how many hours you’re in action. Once you leave that framework, things get a lot more complicated.

Fuller: And interesting, also, perhaps to apply this to our conversation about higher ed, that what we measure in higher ed are things like hours in seats and attendance and doing rote assignments, as opposed to the development of demonstrated competence. And so often, even the way we fund higher ed in the United States or K–12 is much more like a penal sentence. Time served, we think, bestows a capability to you on, you’ve learned something in a way that allows you to build on that skill going forward.

Newport: Yeah, I mean you could almost imagine by the way, the tenure system for professors, there’s actually some interesting value in that. It’s demonstrated competency. Were you able to demonstrate a high level of competency? That’s basically all that matters. Now that’s very high stakes, and that can be quite scary and anxiety producing, but there is a sort of nice, I guess, simplicity to that. We talk to the people who know whatever field it is, and we ask them, “Does this stuff matter?” The letters are private, and it’s just looked at by a committee, and that decision is made, and there’s no bluffing around it. They don’t know how quick you answered emails. You can’t be the guy who’s always on every Zoom meeting. There’s no performativity that’s going to help here. Here’s the paper. I read it, the proof was great. A lot of people cited it. There is a simplicity to that that I like, and I wonder if that can be more generally extrapolated.

Fuller: Cal, one thing we haven’t talked about, which is increasingly evident in the labor market, is the importance of what are variously called “social skills,” “professional skills,” “power skills,” and in the classic literature called “soft skills,” which is a term I’ve always been uncomfortable with because soft implies easy. But how do you think about both the development of social skills—the theory of the mind, the ability to deal with strangers or unfamiliar situations, even spontaneous written and oral communications—how do you think about the development of that and the measurement of that in terms of valuing productivity and how work should evolve in the future?

Newport: Well, I mean first, I’ll say we need to be very worried about the state of those skills right now. This is an argument I made in my book, Digital Minimalism, that the ubiquitous use of social media technologies on smartphones among young people can have an incredible stunting impact on their ability to actually develop reasonable competency at these types of social skills—that comfort with talking to people and different types of social situations, one-on-one, trying to understand someone else’s situation, theory of mind. I mean, not to get too specific about it, but one of the numbers you see from demographers is that current youth, for example, spend a lot less time even in their teenage years navigating, let’s say, parties. And this is something I remember from my misspent youth, is that attending a high school party is a masterclass in theory of mind. You’re trying to figure out, okay, where do I fit into this social hierarchy? Am I kind of cool enough to be here or not? Am I skating on the edge? How is that person looking at me? Who do I need to ... I think I need to start a conversation over here. I mean it’s a masterclass in simulating other minds and building empathetic connections, as well as I suppose a class in how to open a beer bottle without an opener. But I think there’s social skills that are happening there. So I’m very worried about that. I’m very worried about the loss of those skills. On the flip side, yeah, it’s very difficult. How do you evaluate something like that? I mean, I think you know it when you see it. This often gets ossified into the notion of leadership. This is someone that people like to work for and be around. These teams do better. And again, I think this is a skill that’s harder to assess. The more I think we’re in a setting of just haphazardness and email and Slack, so that might be one factor of it. But I think it’s a really pressing issue, is how do you figure out this person is a master of being around and interacting with people, because that really should be emphasized. It’s like we see in universities. There’s a lot of weird professors at universities. But the people who are reasonable, they’re the ones who end up being pulled into more and more things and moving up various administrative tracks, because it’s such a valued commodity. Oh, you can talk to a normal human being like a human being. Here, why don’t you be a dean?

Fuller: Well, certainly, it’s an area of research for us here at our Harvard Project on Workforce, which is an inner-school project about, can we understand how not just to measure social skills but to develop them, because in so many instances, a lot of social skills really are an extension of learning and growing as a young child. And just as we see growing disparity in the type of non-routine cognitive work that is highly rewarded in the U.S. is associated with certain socioeconomic backgrounds and lived experiences as you mature, it may be even more true in social skills. And that’s very, very bracing, because as more routine work is automated away, ipso facto, the importance of social skills in work grows simply because the residual that’s associated with hard skills is shrunk by work-displacing technology. Speaking of technology, how do you think about technology like virtual reality, which may be a vehicle, for example, for helping people develop better social skills, but also might change the nature of interactions in work to being more real-time, less asynchronous, store-and-forward email type interactions? Are you hopeful about technologies like that becoming something other than yet another device that compounds the problems that you’ve described so wonderfully in your research?

Newport: Well, I’ve thought a lot about it. I’ve done some writing about it. I’ve talked to a bunch of people in this industry. And where I land now, I think, is the most popular storyline surrounding these technologies in the workplace, which is social interaction. We can create virtual meetings, where people from all around the world can get together and see each other and see their faces, and it’s going to be a new way of meeting. I think in some sense that’s a red herring. I don’t think that’s actually the trend that is going to dominate out of these technological developments. I wrote an article last year about the company that, at the time, had the number one productivity apps. The number one app in the productivity category on the Oculus store was called “Immersed.” And what they figured out was, don’t try to offer a virtual reality social experience, because it’s a pain to put on the helmet and to log into the room. It’s much easier just to log in to Zoom. So people weren’t doing it. They instead said, “How do we figure out how to make the virtual environment a more productive place for you to work on your own, because then you’re going to have this on all the time. And then we can add the social feature. You already have your helmet on, and then we’ll jump over.” And so what their software focused on—and I think this is the tip of the spear—what their software focused on was screens. We can give you, in a virtual world, multiple large high-resolution monitors. And I have the software, I’ve tested it, you can read the monitors just fine, they’re high resolution. And their early adopters were software developers who like to have complex monitor setups. My code is here, my compiler is over here, my whatever. They use two or three monitors. Here, they could have five. And I set up one of these rooms in a virtual world, and I was on a mountaintop with a fire pit, and I had five monitors, three in front of me, one above me, one over here. And you could really use all these monitors. That’s the tip of the spear. So it made these workers more productive. Five monitors makes me more productive than what I have in the real world. And I think they’re onto something with that—that virtual reality is going to make its inroad in the work into making the work you normally do more productive, not socializing, not sociality. Where that’s going to lead, though, as my big contention, is it’s going to lead us right out of the world of VR and into the world of augmented reality. There’s no reason to be on top of the mountain top with the fire pit; I want the monitors. And as augmented and mixed-reality technology advances, I think that’s going to eat the world, because why do I need to buy a computer? Why do I need to buy a laptop? Why do I need to buy a phone? Why do I need to buy a big screen TV if the one piece of high-end AR goggles I own can create all of those screens whenever I need them, where I need them? I think that is going to be the huge revolution that comes out of this, is a world that actually, from your perspective, looks a lot like the world today. There’s a computer screen here, I have a phone I’m working on, there’s a TV over here. It’s just that those things don’t actually exist in the real world. And so it’s not going to be a massive change for our day-to--day experience at work. I mean, we’ll have better screens and more of them. But it’s going to be a hugely disruptive force for the economy as a whole, because basically it’s going to eat up the entire personal consumer electronics industry. We don’t need a Samsung and a Sony and an Apple producing high-end physical electronic devices. We need one company producing the glasses. Everything else takes place in server farms and software. So I think this is this end-of-reality moment, where a non-trivial amount of the things in our space are actually not actually there. That’s where this is all heading. And I think it’s going to be hugely disruptive for the world and probably less disruptive to our day-to-day experience than we expect.

Fuller: Well, once again, a great illustration of how what we ought to be doing is thinking back from the type of experience we want people to have—in social settings, in the workplace—to maximize both their productivity and their happiness, toward what technologies can enable that, as opposed to ladling another technology into the existing system and hoping it somehow helps cut through the proliferation of technologies that’s causing so much loss of productivity and, arguably in many social settings, unhappiness. Cal, we’re in the fall of 2022, and now out of the pandemic elements of Covid, time of Covid, and maybe in the afterglow of what a lot of people described variously as the Great Resignation. And something we’re hearing about now more from executives and commentators is this concept of “quiet quitting.” What do you make of that? And do you think that it’s more real or imagined?

Newport: Well, it’s a timely question. I just recently spent a long week going deep on this topic for a writing project I was working on in the future, which means I spent more time watching TikTok videos of people complaining about their workloads than probably is healthy for any one individual to do. And I’ll say, I came away with this thinking, quiet quitting has two separate phenomenons captured under the same term. There’s a social media phenomenon, and then there’s a cultural phenomenon. The social media phenomenon, I could really care less about. It’s just becoming the online world of virality, quiet quitting now in the fall of 2022 has just become a pile-on of shallow criticality. The cultural phenomenon I think is much more straightforward. I think all quiet quitting is an expression of is what we’ve been talking about throughout this conversation, which is this exhaustion with this specific way that knowledge work is unfolding. It is a signal—one of many—just like we talked about, the push for work should be more remote or we should have a four-day work week—just like the Great Resignation was the prior signal that was again getting at the same point at quiet quitting, which is this way we work today—where it’s haphazard and ad hoc, we have more on our plate than our mind can handle, our context is switching back and forth, reward is ambiguous, work is hard to pin down. It’s just a flurry of digital frenzy. We’re fed up with that. We know this isn’t productive, we know it’s not useful. There’s a bit of artificial performativity to our work. All of these different things are signals of that same underlying issue. That’s what I think is important about quiet quitting, is not the details, but that it’s just one of many different pointers back to the same fundamental issue: We’re not really good at knowledge work yet. The way we do knowledge work isn’t working yet. We haven’t had whatever the knowledge work equivalent is of our Henry Ford moment, when people figured out, “Oh, here’s how you actually run factories.” We haven’t had that yet. We shouldn’t be surprised that we haven’t. It’s still a relatively young industry, at least at scale. It really hasn’t been that long. That’s what I take away from that. Let’s forget the details of the kid on TikTok and specifically what they’re saying, and let’s get to the heart of the matter, which is the way we’re working isn’t yet working. We have to keep looking for new ideas.

Fuller: So it’s just a further manifestation of the various trends we’ve been speaking about. And it is interesting to think about, well, office work has existed for a long time. Office work in this context is, in the 21st-century context, certainly the post-2010 context, is so radically different than any of the things that preceded it, that understanding it is using the old tools and the old logic, and managing using the old process is going to be an exercise in futility.

Newport: And not to interject, but I think that this timeline it’s really important. I think these dates really matter. The scale of this time really matters, is that if you look at the evolution of knowledge work, you get a widespread knowledge industry maybe emerging in the mid-20th century. This is when Peter Drucker coined the term, “knowledge work” was in a book in the early 1950s. But early knowledge work was quite administrative. A lot of the original innovation knowledge work came out of the industrial context, because the very first, let’s think about large office tower-type settings, came out of the consolidation of very large industrial corporations. It’s no surprise that Peter Drucker made his name in invented management theory studying General Motors. And the very first big offices were front offices for very large industrial concerns. So early knowledge work was quite industrialized—filing cabinets and clerks moving information around. Then in the ’70s and ’80s, we had the rise of what I talked about as a lead or more demanding cognitive work, more creative cognitive work. That began to emerge, more service-oriented knowledge work. And you have a big inflection point in the mid-’90s. That’s where we get the front-office deployment of network computers. And I think that is the age we’re in. It started in the mid-’90s, digitally connected, non-routine knowledge work. So that’s only less than 30 years old. And I’ve done this before in my writing. I’ve looked at other major intersections of technology and commerce. Twenty-five years is not that long. I mean, there’s a famous case study out of Stanford, for example, about the adoption of electric dynamos in factories. And we have this technology emerge, electrical grids and electrical motors. And it took something like 50 years before factories actually began deploying those electrical motors in a way that made a lot of sense, which was basically put a small motor at every piece of equipment. They would ignore them, or they would replace their large steam engine with a giant electric motor that was still hooked up to all of the inefficient leather belts and axles. It took 50 years even just to figure out, now that we have electric motors, how do we put them into a factory? So yeah, we’ve had 25 years since we’ve said, “Here’s computers and networks and non-routine knowledge work. How do we make this work?” That’s not a lot of time. And it’s why I’m baffled when people say, “I think the way we’re working works. This is fine, this is efficient, it’s technology. We know what’s going on.” I was like, “That’s ahistorical. That’s arrogant and ahistorical.” Never have we been able to figure out new seismic shifts in economic sectors this quickly before. Of course, we don’t know what we’re doing yet. And I always emphasize that point. It’s only been 25 years.

Fuller: I do have a confession to make, Cal, which is that here at the Harvard Business School in the early days of the school, the school’s evolution was strongly influenced by Frederick Winslow Taylor and the notion of scientific management. So we may be more responsible for the propagation of that type of hide-bound regressive thinking about management than I would care to admit, not only as a faculty member here but as the child of faculty members on this campus.

Newport: Taylor wrote a monograph about scientific management in the office environment when he was trying to—whenever, the end of his career—push his ideas into the office environment. And it’s very insightful and unintentionally hilarious, because it’s obsessing over, for example, the perfect placement of the light on the desk so that you have enough illumination to read the form you’re filling out, but not too much illumination so that it glares. What’s the perfect distribution of envelopes? And I think it’s a really useful monograph. If you ever could ever get your hands on a copy of it, it’s a really useful monograph, because it makes as clear as anything else the reality that Peter Drucker then picked up on in the ’50s that, “Oh, that is not going to work here.” But on the other hand, I think that was the start of our issues, because Drucker then said, “Stop with all of this Taylor stuff. You can’t assembly line writing ad campaigns. Knowledge workers are creative. Let them do their own thing.” And at the core of my thinking is that we took that too far. It’s smart, like Drucker was trying to say, to allow the execution of work be left autonomous to the creative skilled knowledge worker. But we went too far, and we allowed the organization of work to also be left in the control of the individual knowledge worker. And that’s where we ended up where we are. So we went too far away from Taylor. We need a little bit of that thinking on how we organize work, but not too much of that thinking. So when it comes to me actually writing my computer code or coming up with my academic papers, leave me alone. But when it comes to how many people can ask me to be on a committee, maybe we need an organizational answer to that question. So I think that Taylor-Drucker tension is the tension that explains everything we’ve seen in the last 70 years in this economic sector.

Fuller: Well, their common denominator, of course, is what drives productivity. And so one of the great things about being at our business school is my office is roughly 200 meters away from the biggest best business library in the world. So my guess is we have that monograph, I’m going to find out. But Taylor was obsessed with creating work processes that maximize productivity. There’s his famous example of the iron loader at the railroad, who increased his productivity by 250 percent, his earnings by 80 percent simply, as Taylor said, by doing exactly what he was told and nothing else. And that was in the service of productivity, not in terms of regimentation. Regimentation, productivity in that industrial setting were, in his view and his understanding, the same. So if we can start with that common denominator—what allows someone to be productive and stay productive because they’re happy and not being abused by the intrusion of others, by a hugely complicated performance management system, or whatever else might be causing them to lose focus and lose that capacity to put their skills to work against highest best use—we can get a solution.

Newport: And just to briefly hammer on that point, because I think it’s so critical. And it’s often where I’m often most misunderstood, where people sometimes will in a casual reading of my thinking think that I’m somehow wanting to bring back Taylorism and the knowledge work. And it’s way more subtle than that. And I think you hit it exactly right in the way you summarized it. But I’ll just hit it one more time. Drucker was exactly right, that you can’t de-skill the actual work that most knowledge workers do. If you read his original writings on knowledge work, what you see him arguing is that usually the person doing the work is often more skilled than the manager at that thing they’re doing. This was very different than industrial manufacturing, where de-skilling made all the sense in the world. You’re bringing the experts, you figure out the best way to do it, and then you disseminate those step-by-step instructions to the employees. Drucker was making this point, that doesn’t work for an ad executive or a researcher in an industrial design engineering lab or something like this. And we take that for granted today. But if you go back and read him in context, in the 1950s, that was actually really revolutionary. That was a very important point he was making. But where we get it wrong is thinking that the organization of work, how we identify task, assign task, collaborate about task, and review task getting done, that actually is served by more structure. And it’s this almost paradox—but not really, once you untangle it—is if I am a computer programmer, you cannot give me a step-by-step flow chart for writing a good algorithm. You have to just depend on my skills to make that happen. On the other hand, having a step-by-step organizational system like Scrum makes it much easier for me to do that work and my life much happier. And in that, you’re really getting at that distinction, which I appreciate, because I think that is the key distinction that we’re getting wrong is autonomy is critical, but it’s critical in the right place. And you put in the wrong place, it actually makes people more constrained and less happy.

Fuller: Well, Cal Newport, it’s been absolutely great to get a chance to discuss these issues with you, and we’re really looking forward to seeing what more comes out of your deep work on your own behalf.

Newport: Well, I appreciate the chance to talk about it. This is why I was excited about this show, is that I don’t always get to geek out to this degree of technicality on work issues when I’m on a general public-facing podcast. So it’s been a pleasure for me.

Fuller: Well, I’ll take that as a high compliment to get a chance to geek out with you, Cal. Thanks again.

We hope you enjoy the Managing the Future of Work podcast. If you haven’t already, please subscribe and rate the show wherever you get your podcasts. You can find out more about the Managing the Future of Work Project at our website hbs.edu/managingthefutureofwork. While you’re there, sign up for our newsletter.