Category: culture

  • What LEGO Can Teach Us about Autonomy and Engagement

    What LEGO Can Teach Us about Autonomy and Engagement

    Last time, I built the connection between distributed autonomy (or lack thereof) and engagement (or lack thereof). Admittedly, I drew from different sources, and one could question some claims or connections I made.

    So how is it, really? Do we really feel more engaged when we have more control over the work we do?

    I have the privilege of running the course on progressive organizations in all sorts of settings, from MBA programs, through postgraduate studies, to professional training. As a part of the course, I designed a little experiment to run with all those different crowds. Over the years and across contexts, it keeps telling the same story.

    What Can LEGO Teach Us About Autonomy?

    The experiment is fairly simple. I get a group of people to build a relatively simple LEGO set. Twice.

    The Managed Build

    The first run is well-organized. We pick one team member as a manager, who starts by assigning tasks to the rest of the team. A typical team member’s job would be to:

    • Be responsible for a specific type or color of pieces.
    • Build a particular part of the model.
    • Etc.

    Over the years, I experimented with how much freedom a group’s manager has in organizing work. It doesn’t seem to matter. What’s important here is that the whole work organization is designed by—and, to a degree, enforced by—a single person.

    page from build instructions for lego catamaran model

    Then they get to build a catamaran. With instructions. Displayed on a screen. With me controlling the pace. Actually, it’s they who control the pace. I “flip” the page once the last team is ready.

    Eventually, all the teams build perfect catamarans. Up to specs. There are some subtle challenges in the process, but that goes beyond the context of autonomy versus engagement.

    lego model of catamaran

    The Self-Organized Build

    The second run is different. There aren’t managers anymore. There is no task assignment pre-building. The whole instruction is: “Self-organize.”

    There is no instruction either. The only thing a group gets is the picture of a hydroplane they’re building.

    lego model of hydroplane

    People have all the freedom to organize their work. Sometimes they do plan. Much more often, they don’t. A creative and messy process commences. Inevitably, it’s all louder and more chaotic than the first run. On average, it’s a bit longer, too.

    Eventually, I get my hydroplanes. Some of them perfect. Others not so. However, I’m yet to receive one that differs from the picture in anything other than minor details.

    The Lesson

    While there are many facets to this experiment, the big lesson is about engagement. After each run, I ask everyone individually to assess their engagement during the task on a scale from 1 to 5:

    1. Very low
    2. Rather low
    3. Neither low nor high
    4. Rather high
    5. Very high

    The underlying hypothesis is, of course, that the second run, the one where people have more autonomy, yields better engagement.

    Across all the teams that have ever participated in the exercise, the current running averages are:

    • 3.24 for the managed build
    • 3.94 for the self-organized build

    There wasn’t a single experiment in which teams were less engaged in the second run (though in one case the results were close—0.14 difference).

    In other words, I’m yet to see a group of people who would be less engaged in a creative LEGO build when they were given more autonomy.

    Some Experiment Caveats

    One important aspect of the experiment design is that the models are relatively simple, while I organize people in groups of 4 or 5. As a result, there are too many hands for the task. It is so by design. It’s an environment where it’s relatively easy for people to disconnect, should they choose to.

    Also, it’s LEGO. For some people, it will be inherently engaging no matter what. They tend to take an active part in the first run, disregarding their assigned role.

    Those two aspects of the game create an environment in which people use the full scale when assessing their engagement. I’ve only had one group that hasn’t used 1s at all. Possibly too many AFOLs in the room.

    The pace of flipping the instruction pages in the managed build tends to be a minor source of frustration for faster teams. Again, that’s by design. It’s just another dimension of limited autonomy. After all, with real work, we have all sorts of interdependencies.

    A side note: Interestingly, it’s not always the same team that is the slowest throughout the whole run. It’s a classic case of a shifting bottleneck.

    Distributed Autonomy Is a Crucial Prerequisite for Engagement

    My working hypothesis is that the main reason behind appalling engagement levels is limited autonomy. The theory suggests as much.

    global employee engagement 2009-2024
    Source: Gallup’s State of the Global Workplace

    The LEGO experiment is a neat way to confirm that in practice. With a simple change of giving people more autonomy, the declared engagement goes up by more than 20%.

    The observable behaviors are different, too. The managed build generates way less energy, fewer discussions in teams, less movement across the room. If you saw randomized silent movies (no audio) from the respective experiment runs, it would be obvious which is which.

    Distributed autonomy—being able to decide how we work—is an absolutely crucial aspect of our workplaces. And a prerequisite for high motivation and engagement.


    This is part of a short series of essays on autonomy and how it relates to other aspects of the modern workplace. Published so far:


    I’m writing these posts by hand. Like an animal.
    https://okhuman.com/NbZHoQ

  • Limited Autonomy Is the Main Reason for Low Engagement Levels

    Limited Autonomy Is the Main Reason for Low Engagement Levels

    I like the following quote from Gallup’s State of the Workplace. It’s from the 2023 report, but it didn’t lose any relevance.

    After dropping in 2020 during the pandemic, employee engagement is on the rise again, reaching a record-high 23%.

    Yup, it reached a record high in 2022, stayed there in 2023, and dropped again in 2024.

    global employee engagement 2009-2024
    Source: Gallup’s State of the Global Workplace

    We had COVID-related uncertainty to blame for the drop last time. This time it’s AI-related uncertainty. Here’s a thing, though. We discuss marginal changes. A per cent here, a per cent there.

    The big lesson remains the same. Engagement levels in the modern workplace are appalling.

    If it were a football team (a soccer team for my American readers), it would be as if 2 players tried to win, 7 just moved around without much engagement, and 2 more tried to score an own goal. If you’d rather take a basketball metaphor, you get one baller who tries to win, 3 who fake defense, and one who keeps turning the ball over to the other team.

    The only hope of actually winning is that the other team is about as disengaged as yours.

    These are realities we have lived with in the past decade. Before that, it was even worse.

    Autonomy, Mastery, Purpose

    So why is the engagement so low? I like Dan Pink’s answer. In his classic book Drive (and no less classic TED talk: The puzzle of motivation), he points 3 prerequisites for high motivation.

    • Autonomy. The ability to decide about important aspects of the work we’re doing.
    • Mastery. Being able to work according to our own aspirational quality standards and get better at what we do.
    • Purpose. Having a shared goal with a broader team or group, we collaborate with.

    Remove either, and you remove the conditions for engagement. Since we have a motivation gap, at least one part of the trio must be the culprit.

    Purpose tends to be relatively individual for companies. You can probably instantly think of organizations that are purposeless (take any that have “increasing value for shareholders” painted all over the place) as well as those that are purposeful.

    Mastery is trickier. However, in the context of knowledge work, I see a one-way correlation between autonomy and mastery. If you can make all relevant decisions about how you work, you very likely can work according to the aspirational standards you set for yourself. If you have autonomy, you can have mastery, too. The vice versa is not necessarily true.

    So yes, when I have to explain Gallup’s results, I blame autonomy, or rather, lack thereof.

    Hierarchy Discourages Autonomy Distribution

    In a modern corporation, we perceive hierarchy as the only possible organizational paradigm. Hierarchy here is understood as a decision-making power distribution structure. The higher up you are in a hierarchy, the more (and more important) decisions you can make.

    Sadly, that very structure discourages us from distributing autonomy to lower levels. If I hypothetically allowed my team to make the decisions assigned to me, inevitably, I’ll face a situation where someone makes a decision I disagree with. Then I face two choices, both bad.

    I can stick with the decision that goes against my experience, intuition, and better judgment. However, since it was mine to make, I’ll be responsible for its outcomes. If my experience, intuition, and judgment were any good, I would pay the consequences of a mistake, even though I knew it was a wrong call in the first place. Psychologically, it’s a tall order.

    The other option is to change the decision. In one swift move, I fix the decision and show my team that they didn’t have any autonomy in the first place. They could “make” decisions only as long as these were decisions I would have made anyway. If that sounds like a kick in the teeth, it’s because it is.

    Hierarchy discourages managers from distributing autonomy. Add to that how prevalent this organizational model is, and we have an answer to why engagement in the modern workplace sucks big time.

    The Writing Is On the Wall

    No matter which vantage point we choose, we see the same picture.

    • We cheer appalling engagement levels only because they’re slightly better than they were.
    • We listen to Dan Pink’s rants with awe, then go back to the same old solutions that never worked.
    • We applaud stories of bold leaders who challenged the status quo with stunning results, and rationalize them, saying, “It would have never worked in my company.”

    I’m curious, how well your current “solutions” work? If we believe Gallup data, there isn’t much to brag about. On the one side, we have unquestioned dogma, which we have followed for more than a century. On the other, we have science. In such cases, I tend to pick team science.

    This is Dan Pink again:

    “This is one of the most robust findings in social science, and also one of the most ignored.”

    “There is a mismatch between what science knows and what business does.”

    The writing is all over the wall. And it will only get more pronounced as we surrender parts of our autonomy to AI agents. Let’s not expect fundamental changes in our motivation levels.

    Unless we start treating the autonomy gap seriously, that is.


    This is part of a short series of essays on autonomy and how it relates to other aspects of the modern workplace. Published so far:


    This post has been human-created: 웃https://okhuman.com/g8lX5w

  • Radical Candor Is an Unreliable Feedback Model

    Radical Candor Is an Unreliable Feedback Model

    Sharing good-quality feedback is one of those never-ending topics that we simply can’t get right, no matter how hard we try. We’d try things, exchange best practices, and… have the same discussion again, 2 years down the line.

    I remember rolling my eyes at a trainer two decades back when they tried to teach us the feedback sandwich. In the early 2010s, Nonviolent Communication (NVC) was all over the place. Then there was a range of methods inspired by active listening. Finally, Radical Candor has arrived as a new take. A wave of fresh air was that it didn’t focus so much on the form, but more on what’s behind.

    I wish I could refer to a single method, tell you “do this,” and call it a day. In fact, when challenged to share what is a better option, I don’t have a universal answer. Not much, at least, that goes beyond “it depends on the context.”

    contextual feedback

    If there’s something that I found (almost) universally applicable, it is to share any feedback in a just-in-time manner. The shorter the feedback loop, the better.

    Yet, of course, there is a caveat to that as well. Both parties need to have mental capabilities to be there. Sometimes, especially when hard things happen, we aren’t in a state when this is true, and we’d better defer a feedback session to a later point.

    Also, it doesn’t say a thing about the form.

    Radical Candor

    Kim Scott’s Radical Candor is continuously one of the most frequent references when we discuss feedback. Its radicalness stems from the fact that it abandons being nice as a desired behavior and advises direct confrontation.

    radical candor, obnoxious agression, ruinous empathy, manipulative insicerity

    In short, as a person delivering feedback, we want to be in a place where we personally care about the other person and we challenge them directly. No beating around the bush, sweet words, or avoiding hard truths.

    Caring personally is the key, as it builds this shared platform where we can exchange even harsh observations and they will be received openly. After all, the other person cares.

    The other part—challenging directly—is more straightforward. We want to get the message through, leaving little space for misinterpretation, especially when feedback is critical.

    Do We Personally Care?

    Out of the two dimensions, the directness of a challenge is the easier one to manage. We can pre-prepare feedback so that it goes straight to where we want it to land. This way, we avoid ruinous empathy territory.

    The caring part, though? How do we figure out whether we care enough that our message will be radical candor and not obnoxious aggression? How do we know that we are here and not there?

    radical candor which quadrant we are in

    I’m tempted to say that we should know the answer instantly. After all, it’s our care. Who’s there to understand it better than ourselves? I’m teasing you, though.

    Figuring it out in front of the mirror will often be difficult. More so in environments where care is not a critical part of organizational culture, and thus, does not come up easily.

    Then, it’s not just about whether we care or not. It’s as much about whether we are able to show it.

    A simple advice would be to show as much care as we reasonably can. We bring that dot up as much as we can, and things should be good, right? Oh, if only it were that simple.

    Feedback: Radical Candor or Obnoxious Aggression

    Some time ago, I was talking to one of our developers, who was complaining about another person. The other person had asked questions/challenging the developer about relatively sensitive matters.

    Then, it struck me.

    “OK, I remember myself making exactly the same remarks and asking exactly the same questions. Does it mean that I have offended you, too?” I asked, upon realizing that at least in one case, my behavior was a carbon copy of the other person’s.

    From the response, I learned that I was OK. The other person was not. Why? “Because you care and [the other person] does not.”

    In other words, I was in a safe space of radical candor, and the other person was way down in the obnoxious aggression territory. Except we were precisely in the same spot (same behaviors, same remarks).

    The whole situation was all about how the said developer interpreted specific situations and how much goodwill and leeway they gave me and the other person.

    Where Are the Lines?

    The story clearly shows that we can’t fix the lines in place in the Radical Candor model. It’s not a simple chart with four quadrants, where we necessarily want to aim for the upper right corner.

    radical candor ordered domains

    The borders between the domains in the model will move. They will be blurry at times. And, by no means, will they be straight lines. If we tried to sketch a model for an actual person, it would look way messier.

    radical candor messy domains

    There will be areas where we’re more open to a direct confrontation, and those that are way more sensitive.

    Take me as an example. I tend to consider myself a person who’s open to critique (and I’ve done some radical experiments on myself on that account).

    I’m fine if you question my skills, judgment, or the outcomes of my actions. Not that it’s easy, but I’m fine. But question my care? That’s a vulnerable place for me, and you’d better be less direct if that’s what you’re about to do.

    To make things worse, the picture will be different depending on who is on the other side. For a person I deeply trust and respect, the green area will dominate the chart. For another, where neither trust nor respect is there, the green space may be just in a tiny upper right corner.

    And if that wasn’t enough, it changes over time. We have better days and worse days. We have all other stuff to deal with, stress, personal issues, and all those things conspire to mess with the Radical Candor clean chart even more.

    “Fuck off” Coming From a Place of Love

    During my first weeks at Lunar Lugic, one of the youngest developers at the company told me, in front of a big group, that “I acted like a dick.” It was his reflex response to something I did, which I can’t even remember now. Nor can he.

    The next day, he came to the office with a cardboard box to pack his things, ready to be fired for offending the newly hired CEO. Little did he know that:

    • I was grateful for his timely remark
    • I appreciated his courage
    • I couldn’t care less about the form

    Even if none of the common advice would suggest that, for me, it was indeed a quality bit of feedback. And the developer? He stayed with us for more than a decade. And he definitely didn’t need that cardboard box.

    His challenge was direct and blunt. Did he care about me personally, though? No. Did it change anything for me? No, not really. For me, the remark has still landed well in the radical candor territory.

    As a metaphor, I have some people in my life whom I can tell to fuck off. Or vice versa. And that “fuck off” would come from a place of love. The form, while harsh, is something that bothers neither me nor them. After the shots have been fired, we will laugh and hug.

    I bet you have such people in your life, too. Those who have seen the best and the worst of you and decided to stick with you, nevertheless. People you trust and who trust you. You respect them, and they return the favor.

    Send the same “fuck off” to a random colleague and you’re neck-deep in obnoxious aggression, no safety guardrails whatsoever. Although, in this case, it should instead be called obnoxious violence. No amount of personal care can fix this.

    Radical Candor Is an Unreliable Feedback Frame

    As a theoretical model, Radical Candor is neat. I really like a cross-section of personal care and direct challenge as a navigation tool in communication.

    However, it creates an illusion of precision while pushing us more toward unfiltered, well, candor. This combination is harmful more frequently than just occasionally.

    We can figure out (roughly, at least) where our message is on the diagram. The big problem is that we’re mostly clueless about where the lines are.

    radical candor where is the line

    In fact, we have good insight into the borders between the domains only after we have established a pretty good relationship. Which is precisely when we need the least awareness about the exact line position.

    In a typical case, we’d be shooting in the dark. Even if we understand the form and the content of feedback we share, it may lead us to a very different place than we expect. Many of the reasons why are beyond our sphere of control.

    Feedback Instruction Manual

    I’d be reluctant to adopt Radical Candor as my go-to feedback frame. However, if someone comes to me and says that’s what they expect, I’m happy to oblige.

    That’s a good trick, by the way. As a person who wants to receive more feedback (don’t we all?), tell people how to do it in your case.

    For example, I prefer criticism to praise. The latter sure feels good, but it does little in helping me improve. I’d rather feel awful for a while and get better afterwards than the reverse.

    I appreciate challenges. Which doesn’t mean that I’m quick to admit I was wrong. I need time to rethink my position. So, if you want such an outcome, give me that time.

    And I could go on. But this is my instruction manual. I don’t expect it to work for anyone else automatically.

    The same is true when you are on the sharing end. Be explicit about your intentions. I routinely start or finish (or start and finish) giving feedback with the following remark:

    The first rule of feedback applies: Do whatever the hell you want with it.

    Save for some edge cases, I never have any explicit expectations for a change. When I share, it’s just this—sharing.

    Being explicit about your intent will do way more than following any fancy model.


    This post has been inspired by the conversation with Lynoure Braakman on Bluesky. Thank you, Lynoure, for the insightful remarks and the inspiration.

  • Fundamental Flaw of Hustle Culture

    Fundamental Flaw of Hustle Culture

    It’s all over the news. AI companies force their engineers to permanent crunch mode. Expectation for working long hours is like a badge of honor in Lovable job ads. Google defined a 60-hour work week (at the office) as a productivity sweet spot.

    But in the spirit of one-upmanship, everyone was beaten by Scott Wu, Cognition CEO. He announced 6-day work at the office, 80-hour weeks as the new norm.

    We don’t believe in work-life balance—building the future of software engineering is a mission we all care so deeply about that we couldn’t possibly separate the two”
    Scott Wu, Cognition CEO

    You see? All it takes to suck twice as many hours from every engineer is to stop believing in work-life balance. Voila!

    Why All the Hustle?

    The visible reasons for all that hustle are obvious. Everyone understands that, at the end of the day, there will only be a very few winners of the AI race.

    They will get rich. Everyone else will go bust.

    To make things worse, the bubble has been pumped to its limits. If you want to get a prediction that AGI is just around the corner, there’s no shortage of optimists.

    However, notably, after GPT-5’s lackluster premiere, Sam Altman mentioned that AGI is not a very useful term. Whoa! That’s new! One would wonder what might have triggered such a twist in the official messaging.

    Anyway, seemingly, the rest of the AI crowd is yet to catch up. The extreme hustle culture they install in their companies clearly suggests that they believe AGI is around the corner.

    Otherwise, how would we explain 60/70/80-hour workweeks?

    I mean, these are smart people. They do realize such work is not sustainable, right? Right?

    Cynicism

    OK, I’m not naive. There’s a ton of cynicism behind the hustle culture. The top leaders do it because everyone else does it, too. So they can get away with it. And people fall for this trap.

    Given all the hype, it’s easy to promise mountains of gold to everyone. If. You. Hustle. Just. A. Little. Bit. More.

    People will rationalize it by asking themselves a question: Am I fine coping with that toil for a couple of years and then walk away with $10M?

    Seems like an acceptable tradeoff, doesn’t it? CEOs of AI companies prey on that.

    However, I believe that they know the correct question should be: Am I fine shortening my life for 1-2 years because of the toil when someone dangles $10M in front of me?

    The answers to these questions might be different. But if you expect prominent AI figures suggesting such an alternative vantage point, well, don’t hold your breath.

    They will cynically exploit the opportunity even if it improves their odds of succeeding only marginally. After all, everyone else is doing the same.

    The Cost of Extreme Hustle Culture

    What’s fascinating is that it’s a herd behavior. No one seems to stop and validate whether hustle culture even works. Not even companies historically known to be data-driven, like Google.

    It’s as if a simple linear approximation was all they could conceive: twice as many hours, twice as much work done.

    Any team lead with even meager experience would disagree. It’s kinda obvious that the last hour of continuous work would be less productive than the first, when we’ve been well-rested.

    So, how about adding a few more hours each day? And then replacing one rest day with another workday?

    If you need to spell it out for you, here it is. It means more mistakes, more rework, more context switching tax. And even more toil. Which generates rework of the rework. A vicious cycle.

    At some point, and rather quickly, each additional hour has diminishing returns. Then, at some point, each additional hour has a negative return, i.e., it decreases the total output delivered.

    If you wonder why Henry Ford introduced a 5-day, 40-hour workweek in 1926, while keeping a 6-day pay, it’s not because he was an altruist. He wanted better overall productivity. And, surprise, surprise, he got what he wanted.

    Economics of Crunch Mode

    Sure, a factory floor in 1926 is an entirely different environment from an engineering office a century later. Yet Ford’s was hardly the only such experiment.

    Across many examples, it’s extremely hard to find any argument that supports the hustle culture.

    “We have omitted from this list countless other studies that have shown [dcreased productivity] across the board in a great number of fields. Furthermore, although they may exist, we have not been able to find any studies showing that extended overtime (i.e., more than 50 hours of work per week for months on end) yielded higher total output in any field.”

    Note, it’s about total output, not output per hour.

    Now, when dozens of research papers from different contexts tell the same thing, I tend to listen. So when it comes to the most recent trend for crunch mode in AI startups, there are two potential explanations.

    1. Extreme hustle culture and extended crunch don’t work. Thus, AI startups are harming themselves.
    2. AI startups are so completely different that they operate under a different set of rules.

    Because they surely employ human beings similar to you and me.

    At a risk of oversimplifying matters, these companies do software engineering. A fancy and cutting-edge flavor, I give them that, but software engineering nonetheless. They are not that different.

    Well, put two and two together.

    Data-Driven? Data-Driven My Arse

    If either of them, celebrity CEOs, had actually looked at the data, they might have realized that they’re harming their businesses.

    Of course, they’re harming their people, too. Yet I wouldn’t expect enough empathy or reflection from Sam Altmans of this world to make it a viable point in a discussion.

    If they want cutting-edge and speed, they’d be better off going against the tide and sticking to healthy work conditions. Ultimately, these companies have no shortage of investment money, and if AGI is, indeed, just months ahead, they could burn through some of those dollars by hiring more.

    Even more so, given that raising funds for these startups is easier than ever. These days, you don’t even need to tell what you’re working on, let alone release anything, to get billions. That is, given that you properly market your idea as AI.

    That is true, of course, only unless AGI is not even remotely close and the AI startups CEOs know it all along (but won’t say, as then it would be harder to attract investors’ dollars).

    Extended Crunch Mode Story

    There are industries known for crunch mode (I’m looking at you, game dev), and there’s no shortage of stories about how extended hustle was behind well-known disasters.

    I had a chance to listen to a creative director from CD Projekt RED speaking about their engineering culture just weeks before the launch of Cyberpunk 2077. During Q&A, inevitably, he was asked whether they would release on an announced date (which had already been moved a couple of times).

    “There’s no other option,” was his answer.

    We know how it ended. “Buggy as hell” was the reviewers’ consensus. The game was pulled from sale on PlayStation. And shareholders filed a class action lawsuit over the share price drop. A hell of a launch party, if you ask me.

    CD Projekt RED has extended crunch mode to thank for all that fun stuff. In an interesting twist, after they dropped the hustle and started working in a more sustainable way, they were able to recover from the initial disaster.

    Unsustainability of Hustle Culture

    The camel’s back is already broken, but I’ll add one more straw anyway.

    People will burn out working under such a regime. Some of them will last months, some quarters, some may even last years. But break they will.

    Again, I don’t expect empathy from the celebrity CEOs, but the consideration of their bottom lines is what they’re paid for, isn’t it? So, what’s the cost of replacing an expert engineer specialized in AI? Given the outrageous poaching offers we see, it’s absurdly high.

    And I don’t even mention all the time lost before a company manages to hire a replacement. Yes, precisely the time that seems to be precious enough to make CEOs force their engineering teams to toil for 6 days and 80 hours a week.

    It. Is. Not. Sustainable.

    Never has been. Never will be.


    If similar topics are interesting, I cover anything related to early-stage product development (and, inevitably, AI) on the Pre-Pre-Seed Substack.

  • Care Matters, or How To Distribute Autonomy and Not Break Things in the Process

    Care Matters, or How To Distribute Autonomy and Not Break Things in the Process

    At Lunar Logic, we have no formal managers, and anyone can make any decision. This introduction is typically enough to pique people’s curiosity (or, rather, trigger their disbelief).

    One of the most interesting aspects of such an organizational culture is the salary system.

    Since we all can decide about salaries—ours and our colleagues—it naturally follows that we know the whole payroll. Oh my, can that trigger a flame war.

    Transparent Salaries

    I wrote about our experiments with open salaries at Lunar in the past. At least one of those posts got hot on Hacker News—my “beloved” place for respectful discussions.

    As you may guess, not all remarks were supportive.

    Comments about transparent salaries from Hacker News

    My favorite, though?

    IT WILL FAIL. Salaries are not open for a reason. It is against human nature.

    No. Can’t do. Because it is “against human nature.” Sorry, Lunar, I guess. You’re doomed.

    On a more serious note, many comments mentioned that transparent salaries may/will piss people off.

    The thing they missed was that transparency and autonomy must always move together. You can’t just pin the payroll to a wall near a water cooler. It will, indeed, trigger only frustration.

    By the same token, you can’t let people decide about salaries if they don’t know who earns what. What kind of decisions would you end up with?

    So, whatever the system, it has to enable salary transparency and give people influence over who earns what.

    Cautionary Tale

    Several years back, I had an opportunity to consult for a company that was doing open salaries. Their problem? Selfishness.

    In their system, everyone could periodically decide on their raise (within limits). However, each time after the round of raises, the company went into the red. All the profits they were making—and more—went to increased salaries.

    The following months were spent recovering from the situation and regaining profitability, only to repeat the cycle again next time.

    Their education efforts had only a marginal effect. Some were convinced, but seeing how colleagues aimed for the maximum possible raise, people yielded to the trend.

    The cycle has perpetuated.

    So what did go wrong? After all, they followed the rulebook. They merged autonomy with transparency. And not only with salaries. The company’s profit and loss statements were transparent, too.

    It’s just people didn’t care.

    Care

    Over the years, when I spoke about distributed autonomy, I struggled to nail down one aspect of it. When we get people involved in decision-making, we want them to feel the responsibility for the outcomes of their decisions.

    The problem is that we have a diverse interpretation of the word. I once was on the sidelines of a discussion about responsibility versus accountability. People were arguing about which one was intrinsic and which was extrinsic.

    As the only non-native English speaker in the room, I checked the dictionary definitions. Funny thing, both sides were wrong.

    Still, I’d rather go with how people understand the term (living language) rather than with dictionary definitions.

    So, what I mean when I refer to being responsible for the outcomes of one’s decisions is this intrinsic feeling.

    I can’t make someone feel responsible/accountable for the outcomes of their call. At most, I can express my expectations and trigger appropriate consequences.

    To dodge the semantic discussion altogether, I picked the word agency instead.

    The only problem is that it translates awfully to my native Polish. Frustrated, I started a chat with my friend, and he was like, “Isn’t the thing you describe just care?”

    He nailed it.

    Care strongly suggests intrinsic motivation, and “caring for decision’s outcomes” is a perfect frame.

    How Do You Get People to Care?

    The story of the company with self-set salaries—and many comments in the Hacker News thread—shows a lack of care for their organizations.

    “As far as I get my fat raise, I don’t care if the company goes under.”

    So, how do you change such perspectives?

    Care, not unlike trust, is a two-way relationship. If one side doesn’t care for the other, it shouldn’t expect anything else in return. And similarly to trust, one builds care in small steps.

    Imagine what would happen if Amazon adopted open salaries for its warehouse workers. Would you expect them to have any restraint? I didn’t think so. But then, all Amazon shows these people is how it doesn’t give a damn about them.

    And that can’t be changed in one quick move, with Jeff Bezos giving a pep talk about making Amazon “Earth’s best employer” (yup, he did that).

    First, it’s the facts, not words, that count. Second, it would be a hell of a leap for any company, let alone a behemoth employing way more than a million people.

    As I’m writing this, I realize that taking care of people’s well-being is a prerequisite for them to care about the company. And that, in turn, is required in order to distribute autonomy.

    The Role of Care

    The trigger to write this post was a conversation earlier today. We’re organizing a company off-site, and I was asked for my take on paying for something from the company’s pocket.

    Unsurprisingly, the frame of the question was, “Can we spend 250 EUR on something?”

    Now, a little bit of context may help here. Last year was brutal for us business-wise. Many people make some concessions to keep us afloat. Given all that, my personal take was that if I had 250 EUR to spend, I’d rather spend it differently.

    But that wasn’t my answer.

    My answer was:

    • Everybody knows our P&L
    • Everybody knows the invoices we issued last month
    • Everybody knows the costs we have to cover this month
    • Everybody knows the broader context, including people’s concessions
    • We have autonomy
    • Go ahead, make your decision

    In the end, we’re doing a potluck-style collection.

    Sure, it was just a 250 EUR decision. That’s a canonical case of a decision that can not sink a company. But the end of that story is exactly the reason why I’m not worried about putting in the hands of our people decisions that are worth a hundredfold or thousandfold.

    We’ve never gone under because we’ve given ourselves too many selfish raises. Even if we could. The answer to why it is so lies in how we deal with those small-scale things.

    After all, care is as much a prerequisite for distributed autonomy as alignment is.


    This is the third part of a short series of essays on autonomy and alignment. Published so far:

  • The Role of Alignment

    The Role of Alignment

    In the first part of this series, I focused on why autonomy in a workplace is a critical ingredient if we want to stay relevant. Not only is it a response to the nature of everyday work, with the increasing significance of remote work and the rise of AI, but it is also an emergent outcome of the large-scale evolution of the economy.

    However, if there is a universal warning that should be attached to the advice suggesting decentralizing control, it should be the following.

    It’s never as simple as “give people more autonomy.” The way people act in a decentralized system depends on a broader culture, which one should consider before giving everyone more power.

    Purpose

    One common theme in the discourse on organizational culture is purpose. A shared theme that people and teams aspire to change into reality.

    By the way, when considering joining any company, I recommend asking about their purpose. In fact, I’d ask different people this very question and see whether their answers are aligned.

    “Making more money” is not a purpose. It’s a tactic. Ditto “increasing value for shareholders.” If you want to send a man to the moon, that’s a great purpose. But it doesn’t have to be that big. I’m a fan of honest aspirations like “creating a healthy workplace that sustains a few dozen employees and their loved ones,” too.

    Aside from its strategic role, or impact on motivation, purpose has a role in the discussion about autonomy. It is the force that encourages alignment of all the efforts happening in an organization.

    Misalignment

    Imagine a company guided by the “making more money” aspiration. People would naturally see different, sometimes contradicting, ways of generating revenues. They’d be pulling in different directions.

    Using a physical metaphor, we could consider a circle as the whole organization and arrows within as different individuals pursuing different goals.

    Low autonomy and low alignment impact on organizational momentum

    All those forces combined would create some momentum. The company would be slowly moving wherever the push is strongest.

    What would happen if we gave people more autonomy in such a setup? It is the equivalent of giving every individual more influence over the whole company. Each force vector would become stronger.

    High autonomy and low alignment impact on organizational momentum

    Now, everyone has better leverage, but the combined effect on the organizational momentum is marginal. The reason is obvious. It’s all the contradicting priorities. People try to push in different directions.

    Alignment

    In contrast, we can start in exactly the same situation. However, instead of pursuing the agenda of distributed autonomy, we’ll begin with an attempt to sync up everyone’s efforts.

    Low autonomy and low alignment impact on organizational momentum

    It would mean getting more arrows to point in a similar direction. I don’t expect a perfect alignment. Every individual has their own goals, which would never be matched perfectly with an organization’s goals. But we can get closer.

    The basic tool we have is the purpose. Once it’s clear to everyone what that is, two things will happen. Some people will adopt it and adjust their actions to help achieve it. It’s as if they redirected their vector more toward the desired direction.

    Others will figure that they’d rather keep pushing where they have before. For them, it would be clear they wouldn’t get much support. The odds are they’ll leave soon. If our HR does even a half-decent job, whoever comes in their place would be better aligned with the purpose.

    One way or the other, we’d get more people rowing in (roughly) the same direction.

    Low autonomy and high alignment impact on organizational momentum

    That itself changes the organizational momentum significantly. Not only did we remove the opposing force, but we also added a supporting one.

    If we follow up with increasing autonomy in this setup now, we will maximize the gains.

    High autonomy and high alignment impact on organizational momentum

    Again, everyone has bigger leverage, but thanks to synchronized efforts, the impact is so much more significant.

    Alignment First

    One could argue that we can achieve the same outcome independently of the order of changes. After all, if we refocused everyone’s efforts after increasing autonomy, the end game would look the same.

    In theory, yes. In practice, achieving alignment in such a manner is much less likely and more difficult.

    Each vector is a representation of somebody’s drive. The stronger it is, the harder it is to redirect it significantly. Think of the arrows as if they had weight proportional to the force they represent. With bigger weights, it simply requires more effort to align the vectors.

    Realignment cost with high and low autonomy

    In some cases, alignment will be impossible altogether. We extend our individual expectations to the whole organization. It’s like saying, “I want to pursue this agenda, and thus, I want my company to enable that.” While we would rarely, if ever, express it with these exact words, that’s a prevalent theme in conversations happening around job changes (exit and job interviews alike).

    Bigger arrows tend to break before we can realign them to a significantly different direction.

    Alignment versus Autonomy

    There’s a fantastic depiction of the relationship between autonomy and alignment proposed by Stephen Bungay in The Art of Action.

    He plots a two-dimensional plane with our culprits defining the axes.

    Stephen Bungay's autonomy and alignment dimensions

    In an environment with low autonomy and alignment, we won’t see much action. People will neither feel empowered, nor they would have a sense of clarity. You can expect a lot of confusion and minimal tangible outcomes.

    If we stick to low autonomy but increase alignment, we will have clarity about the goals. However, the actions will still be carefully managed and controlled. It would be a typical micromanagement environment. Not the most inspiring workplace in my book.

    On the opposite end, there’s a low-alignment, high-autonomy environment. There will be a lot going on in such an organization. The problem is that much of that effort will be misdirected. Some of it may be actively counterproductive.

    Finally, we have our most desired quadrant with high alignment and autonomy. That’s where we have clarity about the goals, and people act without waiting for permission. Their actions, thus, will be both targeted and effective.

    Interestingly enough, Stephen Bungay doesn’t stop by showing what we should expect in each type of environment. He also suggests the best path from the bottom left to the upper right corner.

    Unsurprisingly, this path leads through increasing alignment first and only then distributing more autonomy.

    Stephen Bungay's autonomy and alignment dimensions

    I can personally attest it’s a good way, as we did the opposite at Lunar. The price we paid for neglecting alignment was steep. There was a load of interpersonal conflicts, which became a borderline tribal war, and 20% of the company left in the aftermath. Show me a leader who’d willingly drive their company there.

    Big Picture

    If there were only one big-picture suggestion, I’d couple with my strong encouragement to make distributed autonomy a central piece of organizational culture, it would be about alignment.

    Decentralizing control means everyone gets more power over a company and everything it does. That may only get us promising results if everyone rows (roughly) in a similar direction.

    We won’t get that unless we explicitly work on alignment. Or are extremely lucky.

    I tend not to rely on the latter.


    This is the second part of a short series of essays on autonomy and alignment. Published so far:

  • Pivotal Role of Distributed Autonomy

    Pivotal Role of Distributed Autonomy

    I’m a massive fan of distributed autonomy. I believe that, in principle, giving people more autonomy at work is the largest organizational challenge the modern workplace faces.

    Yes, the news of the day is either remote/hybrid work or the impact of AI on everyday jobs. Reinventing the organizational structures of a 21st-century corporation doesn’t belong to a broad discourse.

    From both perspectives, however, distributed autonomy plays a pivotal role.

    Autonomy in Remote Work

    With remote work, the dependency is straightforward. Much of the work has moved from the office—where it could be physically supervised by a manager—to homes, where supervision is significantly limited.

    The manager’s control is limited to the outcomes but not the actions that lead to them. For example, I can observe whether my engineers deliver features or add code to the codebase, but I don’t see when, how, and how much time they spend on activities that lead to “new features.”

    Sure, some organizations would turn to digital tools to control employees’ activities. Guess what. It doesn’t work. Well, it does, but not the way they intend. Here’s what this kind of monitoring does to people:

    • It reduces job satisfaction.
    • It increases stress.
    • It reduces productivity.
    • It increases counterproductive work behaviors.

    One hell of a slam dunk, really.

    It’s not only the lack of control, though. It’s also the availability of help. For the vast majority of organizations, remote work creates additional communication barriers.

    My leader no longer sits at the next desk. I can’t see whether it’s a good moment to interrupt them. Sure, I can drop them a DM on Slack, but they may not answer instantly. So, whenever I face one of those micro-decisions that I might have naturally delegated to my leader in the past, I may call a shot myself. It feels more convenient.

    What has just happened here was me grabbing a little bit more authority. I might have had it all the time, but I didn’t use it because it was easier to ask the leader. Now, the path of least resistance is making decisions myself.

    Multiply that by everyone in an organization, and suddenly, we have more distributed autonomy.

    The choice is between embracing and strengthening the change or resisting it. In the latter case, well, we tax ourselves on every single front, from productivity to employees’ mental health. Not really a choice, is it?

    Autonomy and AI

    The emergence of AI creates another shift in the nature of work. We get a relatively powerful co-pilot that can help us with many tasks that would be difficult or arduous in the past.

    Back then, we might have turned to the experts for help. Or drop the task altogether if it was non-essential.

    The experts would give us a suggestion, and we’d accept it as the decision. If we abandoned the task, there would be no decision to make whatsoever.

    But now, with our AI co-pilot, we have new capabilities at our fingertips. Yet it wouldn’t make any decision for us. Again, the path of least resistance is to grab some of that power, make a call, and move on.

    As an example, it’s often a challenge to dig up a relevant source to link in my writing. I often remember a research paper or article covering a useful reference. But its topic or author’s name? Beats me.

    Googling it was always a struggle, so I either turned to a human expert friend or gave up.

    But now? LLMs are pretty decent in digging up relevant options. Still, the work of reviewing suggested sources and choosing a valuable one is on me. I now face a decision that I earlier deferred to an expert or dodged entirely.

    More autonomy again.

    Adhocracy

    The changes coming from different directions align with a broader evolution of the nature of work. Julian Birkinshaw, in his book Fast/Forward, provides a neat big picture.

    Over the past century or so, the world has evolved from the industrial, through the information, to the post-information era. Each step changes the rules of the game.

    A hundred years ago, scaling was the biggest challenge, and the effective use of resources was advantageous. Thus, bureaucracy was a winning strategy.

    In the second half of the 20th century, we saw the increasing value of information, and its accessibility and effective use gave us an edge. Thus, meritocracy was gaining ground.

    Now, information is ubiquitous. In fact, with the help of LLMs, we can easily generate as much of it as we want. The world becomes less about who knows what. It’s about who can act upon (incomplete) data in a fast and effective manner. Thus, ad-hoc action gives an advantage.

    Coexistence of bureaucracy, meritocracy, and adhocracy over time.

    Birkinshaw coins the term adhocracy to describe this new mode of operation.

    A side note: one important part of the model is that all three modes of operation coexist. However, an organization will defer to the default mode whenever it faces uncertainty. We can’t expect a bureaucratic, hierarchical behemoth to act in an adhocratic way routinely.

    The coexistence of all modes will naturally create tension. The decision can’t be made at the same time made by:

    • a manager with the most positional power
    • an expert with the best data and most expertise
    • a line professional involved in the task hands-on

    If we want to embrace adhocracy, which Birkinshaw argues is a prerequisite for organizational survival, we necessarily must move authority down the hierarchy.

    We need to distribute more autonomy. Again.

    Common Part

    It’s not a surprise. When you go through the stories of companies successfully embracing non-orthodox management models, autonomy would be one shared part of all.

    Be it a turnaround story in David Marquet’s, unsurprisingly titled, Turn the Ship Around, or Michael Abrashoff’s It’s Your Ship, pushing autonomy down the hierarchy was crucial.

    And the fact that the military context would pop up so frequently in this discussion shouldn’t be a surprise. Decentralizing control was a pivotal part of the revolution of the 19th-century Prussian army. Its victory streak forced other armies to follow suit.

    Yes, the corporate world, despite all its inspirations from the military lingo, takes its sweet time to adopt the truly important inventions. And yes, our views of the military tend to be rooted more in Hollywood movies than in the actual realities of these gargantuan organizations.

    I often mention that we’d see more distributed autonomy in late 19th-century armies of the West than in many 21st-century corporations.

    We’ll arrive at the same conclusion if we stick to management theory. Take Holacracy, Sociocracy, Teal, or whatever generates the most buzz these days. The cornerstone of each of those will be autonomy. It may go into how we design roles (Holacracy), get to the principle list (self-government in Teal), or define the decision-making process (consent in Sociocracy). But it’s always there.

    When you think of it, it’s only natural. For hundreds of thousands of years, homo sapiens lived in small tribes of hunter-gatherers that were egalitarian and had very little to no hierarchy.

    Even when our species started evolving into bigger societies, adopting a strong hierarchy wasn’t given and was only one of the possible ways of coordination.

    I’d speculate that we are genetically predisposed to autonomy.

    Reinventing Autonomy

    Wherever we look, we seem to be reinventing the role of distributed autonomy. It’s critical to succeed on a battlefield. Staying relevant in business increasingly requires its presence. It sneaks along with the changes in the nature of work. We know it’s a prerequisite for engagement and motivation.

    Nothing should be easier than embracing the change and giving people more power.

    Sadly, it’s not the case. Power is a privilege. And as with every privilege, those in power will not give up easily. The good old bureaucracy will fight back.

    More importantly still, even if we have the means to overcome the resistance, the challenge is not as easy as “Let’s just give people more autonomy.”

    We need to take care of other things before we embark on this journey. But that’s the topic for another post.


    This is the first part of a short series of essays on autonomy and alignment. The following part(s) will be published on the blog and linked here during the next weeks.

  • Wholeness Is a Lie

    Wholeness Is a Lie

    Over the past decade, the idea of wholeness—to bring the whole self to work—got quite some traction. The sources are many. It rides on the wave of increasing acceptance of individualism. It appears to align with diversity, which has become a major topic across HR departments.

    Last but not least, it’s one of the pillars of Teal Organizations. Teal might be far from a household name that Fredrick Laloux, who coined the term, envisioned a dozen years back. However, it successfully grabbed the wider attention of many forward-looking companies (for better or worse).

    Why Wholeness?

    Laloux’s argument for wholeness is straightforward. He juxtaposes the old-school bringing our professional, ego-driven, masculine, rational selves to work with getting access to emotional, intuitive, and even spiritual resources. The latter, he argues, is not a simple upgrade. It’s a whole different game.

    This is not mathematical, but it is only 1/16 (of us) that’s showing up. When that is the case, we also show up with 1/16 of our energy, of our passion, of our creativity.

    Frederic Laloux

    One could easily envision the yields we’d gain if only we could access 10x as much creativity pool as we can now.

    Then, for many of us, it’s only a humanistic reaction. We might think of ourselves as tolerant, welcoming, inclusive people (I know I do), and accepting others’ whole selves seems like a natural consequence of that view.

    I didn’t need much more convincing to get on board and push the wholeness agenda at Lunar Logic.

    Truly Whole Selves

    Fast forward several years, and I was trying to understand what went wrong. I was looking at a workplace equivalent of a tribal war.

    People hurt each other. In extreme cases, they even refused to work together as a team.

    While it didn’t happen out of the blue, and circumstances added a lot to the mess, none of that would have occurred without years of fostering wholeness.

    You see, no matter how we don’t like that thought, our whole selves are not all roses. We carry our dark passengers within us. We view the world around us through the lens of our biases and our prejudices. We can’t leave that dark guy at home. It doesn’t work this way.

    If we let him out, we act out. That’s when we start hurting others. The worst part, we don’t even notice.

    The Case in Point

    A few years back, environmental activists from Extinction Rebellion stopped commuter trains to London by climbing on top of them. It made the news back then, including the social media wave of comments.

    It was interesting to see how people I knew sided with either the protesters or the commuters. Interesting enough to watch the footage of the events.

    If you’ve just watched the video, you might have had more sympathy and understanding for either side of the conflict.

    Make an experiment. Pretend you know nothing about environmental activists and their agenda. Pretend you don’t understand the anger of the crowd. Rewatch the video.

    What do you see?

    See the man on top of the train trying to kick a person climbing the train in the head. Notice the crowd pulling the man down on the platform and kicking him. At its most basic level, what you see is people physically hurting others.

    These are people who bring their whole selves to the scene.

    Intentions Matter

    – But Pawel, clearly, we can’t ignore actors’ intentions before judging their actions!
    – Fine, be my guest.

    The protesters’ agenda is clear. They aim to raise awareness of the ecological crisis that humankind is engineering for itself. The commuters? They want to sustain themselves and their loved ones. For some, the delay may just be an annoyance, but for others, it may trigger serious financial consequences.

    Their intentions are clear and pure.

    I bet no one came to the platform with the intention to hurt another human being physically. Not a single person.

    And yet, here we are. We want it or not, wholeness includes our dark passengers. What follows is that, when unbounded, it brings harm. Probably, more harm than good.

    Bounded Wholeness

    So, what was the grand finale of our tribal war? We lost 20% of the people who mentioned the situation as the primary trigger for their decisions to move on.

    We found an expert to help us organize rules and norms around non-discrimination and inclusion. A big part was learning what is and is not safe for work.

    It seems a hell lot of things are not safe for work. In other words, if we want to be inclusive and non-discriminatory, we must limit ourselves.

    It’s anything but wholeness.

    Well, you could call it bounded wholeness. However, it’s akin to bounded freedom, which essentially is not true freedom.

    – But Pawel, freedom is limited, too. You can’t do anything. Your freedom ends when you start violating someone else’s freedom.
    – Sure, the lines are blurry at best. But if you want to avoid people hurting others, they need to constrain their wholeness a lot. And I mean, a lot.

    Respect as Guidance

    Before the whole thing happened at Lunar, I believed it would be enough to follow a simple rule of thumb. Something that would tell us to respect one another.

    Make sure people give more consideration to others than they demand for themselves. It is more inconsiderate to prevent people from exercising their rights because you are offended by them than it is for them to do whatever it is what offends you. That said, it is inconsiderate not to weigh the impact of one’s actions on others, so we expect people to use sensible judgment and not doing obviously offensive things.

    Ray Dalio

    Or, as my favorite conference puts it in their code of conduct: “Don’t be a jerk, be excellent to each other.”

    The harsh lesson, though, is that it leaves too much space for interpretation. The closer we are to someone, the easier it is to empathize with them. As a result, the generic guidance will work for folks within our ingroup but not necessarily for those outside of it.

    The more different the outgroup from my circle, the harder it is to give them “more consideration” than I expect for myself. It’s even worse when we consider groups polarized against each other. Think modern politics.

    Suddenly, almost everything may theoretically offend someone.

    Clear Boundaries

    That’s why we need very clear boundaries. When my behavior is within those boundaries, I shall feel safe. Even if someone feels hurt, I am free to ignore it, and the other person has to get over it.

    However, when I violate the boundaries, the opposite is true. The other person has every right to expect me to stop doing whatever I’m doing, no matter whether or not I think it should be OK.

    As a team or an organization, we can negotiate these boundaries. We can bring them as far as we collectively agree upon. However, with a diverse team, we will necessarily constrain acceptable behaviors quite heavily.

    It’s not ideal. We still agree that some more sensitive individuals may feel hurt every now and then. That’s the price we pay for “unfreezing” everyone else.

    Otherwise, we’d be petrified that something we do may hypothetically harm somebody.

    Conclusion

    Wholeness, sold to us as “let’s freely bring more of ourselves to a professional context,” is a lie. As appealing as it sounds, it overlooks a critical part. While focusing on the upside, it entirely ignores the risks.

    I know it’s a hard pill to swallow, but in this case, the potential downside is more significant than the gains we get.

    If we reverse engineer the whole process and start with building a (relatively) safe work environment, we won’t end up with wholeness. At least not the kind we were sold in the first place.

    If I’ve succeeded in getting you interested, here’s a video that covers the topic in more depth. A fair warning, though. There might be triggering content inside.

  • Why Wouldn’t an Intern Fire a CEO?

    Why Wouldn’t an Intern Fire a CEO?

    The question seems completely wrong. Obviously, because they can’t. An intern could not possibly let go of a CEO.

    But what if they could? Would they? And if not, why?

    Right now, you may be thinking, “But Pawel, what do you mean by imagining an intern could fire a CEO? It’s a completely abstract problem.”

    It is not. In fact, at Lunar it is possible.

    Radical Autonomy

    I wrote about our radical way of distributing autonomy many times before. In short, anyone can make any decision (in a structured way). So why don’t people abuse that power?

    Why don’t I need to worry that an intern would launch a letting go process for me?

    And yes, they totally can.

    While this decision is somewhat more complicated than the vast majority of others, anyone has the authority to start this process. Including people who joined us yesterday.

    The Dynamic of the Organizational Culture

    Whenever we join a new group, we tend to be more withdrawn than whatever is our norm. That’s one of the basic social dynamics.

    First, we observe and learn. Subconsciously (or consciously), we look for patterns to understand the group’s norms. What’s acceptable? What’s not acceptable? What’s rewarded? What’s punished?

    We orient ourselves in a new environment.

    That’s precisely what happens in an organization when a new person joins. Even when rules as written say something, we observe whether it’s really so. After all, if rules contradict the norms, it’s the latter which prevails.

    No one will fire the big guns before they learn to navigate a new environment well.

    Peer Pressure as Safety Mechanism

    OK, but the same intern will still not fire a CEO 6 months later when they already learned the norms. Why?

    In a system based on distributed autonomy (again, anyone can make any decision; that’s the ultimate distribution), we have very different power dynamics.

    We don’t have a person in power entitled to make the call, that entitlement being the ultimate get out of jail free card. After all, there’s no one else to make that decision.

    In this case, anyone can act. But then, such a decision will be judged, challenged, commented on. If it’s controversial, let alone outrageous, people will be very vocal when opposing it.

    Through that, we introduced peer pressure as a safety mechanism that basically prevents the most extravagant decisions from being made.

    Reputation as Currency

    What follows is that whoever volunteers to make any decision makes a bet. A bet of their reputation. If the decision goes well, the bet is won.

    The more obvious the decision, the smaller the bet.

    After all, if everyone thinks something is a good idea, it’s unlikely that they’ll complain, even if it goes sideways.

    It’s a different beast altogether when the call is controversial. If I go against a big group, I better end up right, or my reputation as a decision-maker gets slashed.

    Before anyone’s ready to make such a bet, they must accumulate some of that reputation. Which means they will have been around long enough that we no longer talk about an intern firing a CEO.

    In fact, when someone is around that long, and they still want to fire me, well, they probably have some damn good arguments.

    By the way, if you’re interested, the most radical proposal coming from a fresh hire we’ve ever discussed was changing the salary system. Admittedly, a serious call, yet it didn’t even reach a stage where it was an actual proposed decision. The person gave up way sooner after receiving peer feedback.

  • Levels of Slack Time

    Levels of Slack Time

    I learned the meaning of slack time years back in the context of Kanban. Once we start managing workflow for effectiveness, we necessarily create these moments when we want to stop the work. Otherwise, we’d overload the bottleneck.

    When we design the slack time in the system, the natural question is, what’s next? How do we use it?

    The Use of Slack Time

    My first natural, although with the benefit of hindsight simple, answer was to optimize the teamwork.

    There’s always a colleague who would appreciate help. There’s always a stage of the process that no one loves (code review, anyone?). There’s always an improvement task that just never makes it the top priority (like paying technical debt back).

    Then, there’s a whole another context. Individual. Slack time creates a perfect opportunity to invest in oneself. Catch up with what’s new with technology (with the AI race, it seems like there’s something to catch up with almost every week). Learn something outside of the immediate context of the project. Sharpen one’s saw.

    But then, when we start considering the value of slack time in a more generic context, we realize that it goes way beyond the team level.

    Think of a fire station. Their whole system is designed around slack time. We don’t try to optimize the work for fire brigades for utilization. It would mean that we want firefighters fighting fires all the time.

    Thus, we’d either have an excess of fires or firefighters moonlighting as arsonists.

    Cross-Team Slack

    We can then abstract away the idea of slack time and consider how it applies in different contexts.

    The most basic context would be individual. Slack time helps me to get better.

    Going just a bit further, we have the team level. Slack time helps the team to become more effective. We achieve that either by coordinating around the ongoing tasks (short-term help) or working on improving the long-term performance (continuous improvements, paying technical debt back, etc.).

    So far, it’s all the basics. But what if we take another step into a broader context?

    Then we end up in cross-team/cross-project land. We start considering coordination problems. We look at interdependencies. We analyze an entirely different layer of work design.

    As much as we have a bottleneck within a development team (let’s say it’s testing), we will have one if we consider a cross-team initiative (let’s say it’s passing the security acceptance).

    Once we understand this high-level picture, we can use slack time to help the entire initiative become more effective. It’s likely that one team being able to deliver more features or deliver them more predictably will not move the needle of the whole product by a millimeter.

    The actual bottleneck may be in the design, or release, or even grand product-related decisions.

    That’s where cross-team slack time can be redirected. It would mean we’re asking the question: what’s the best way to help when I see the big picture?

    Organizational Improvements

    Can we go further up, though? Once we consider individual, team, and cross-team levels, is there more?

    But of course, there is.

    Once we strip the context from the product/project work, we look at the bare bones of any company—its organizational design. And there’s always plenty to do around these parts.

    At this level, we wouldn’t ask questions about improving my project/product. We’d look for ways to make the whole company improve.

    Think of any novel initiatives. Of course, “novel” is in the context of this company; I don’t expect us to routinely do world-changing stuff. Starting a self-help group. Running a new product experiment. Looking for fellow folks to challenge existing management paradigms. Opportunities are almost endless here.

    The more extravagant you become with the ideas, however, the less likely you’d be allowed to implement them. And here comes our culprit.

    Role of Autonomy

    We established different levels of slack time:

    • Individual
    • Team level
    • Cross-team
    • Organizational

    The further down that list you go, the bigger the potential impact of the changes. But most people wouldn’t even consider going beyond the team level. Why?

    Simplest answer? They don’t have enough autonomy.

    The degree to which we can impact our organization depends on our sphere of influence. And that is strongly correlated with how distributed autonomy is in any organization.

    It’s not binary, of course. It’s not that I can or cannot make a decision in a cross-team context. Sometimes, even when I can’t call the shots, I can influence the decision-maker.

    But if I don’t have autonomy on a team level, I shouldn’t expect to have influence on a cross-team level. Thus, we can use the autonomy distribution as our measuring stick.

    Limited Autonomy, Limited Impact

    Whenever I teach that stuff during workshops and university courses, I ask people a series of questions to assess how much their organizations distribute autonomy.

    The questions are separated into groups, roughly referring to the three levels mentioned above: team, cross-team, and organization. The outcome is the same every single time.

    We see a lot of autonomy on a team level. Teams can freely decide about many things. I think we have Agile to thank for that.

    But then, it breaks. Once we get to cross-team, the perceived autonomy goes from “significant” to “barely there.” And it won’t be a surprise that when we touch the organizational level, it’s non-existent.

    In such an environment, we shouldn’t expect to get that much out of slack time.

    So, the next step after introducing slack time to our systems is to get more autonomy in it as well.