The end of management

I come with good news. If I’m correct about the future of the world economy, the Era of Management is beginning to close, and will wind down over the next few decades. I’ve spent a lot of time thinking about these issues, and I’ve come to a few conclusions:

  1. The quality gap between the products of managed work and unmanaged work has reversed, with unmanaged work being superior by an increasing– at this point, impossible to ignore– amount. For one notable example, open-source software is now superior to gold-plated commercial tools. Creativity and motivation matter more than uniformity and control. This was not always the case, but it has become true and this trend is accelerating.
  2. This change is intrinsic and permanent. It is unnatural for people to manage or be managed, and the end of the managerial era is a return to a more natural motivational framework.
  3. Approaches to business that once seemed radical, such as Valve‘s open allocation policy, will soon enough be established as the only reasonable option. Starting with top technical companies, an with the trend later moving into a wide variety of industries, firms will discard traditional management in favor of intrinsic motivation as a means of getting the best quality of work from their people.

What’s going on? I believe that there’s a simple explanation for all of this.

“We will kill them with math”

Consider payoff curves for two model tasks, each as a function of the performance of the person completing it.

Performance | A Payoff | B Payoff |
-----------------------------------

5 (Superb)  |      150 |      500 |
4 (Great)   |      148 |      300 |
3 (Good)    |      145 |      120 |
2 (Fair)    |      135 |       40 |
1 (Poor)    |      100 |       10 |
0 (Awful)   |       50 |        0 |
-----------------------------------

What might this model? Task A represents easy work for which an average (“fair”) player can achieve 90 percent of the highest potential output:135 points out of a possible 150. An employee achieving only 50 percent of that maximum is clearly failing, and will probably be replaced, and there won’t be much variation between the people who make the cut. Task B represents difficult work for which there’s much more upside, but for which the probability of success is low. Average performers contribute very little, while the difference between “good” and “superb” is large. Task B’s curve might be more applicable to high-yield R&D work, in which a person would be considered highly successful if she had success in even 30 percent of the projects she set out to do, but it increasingly applies to disciplines like computer programming, where insight, taste, and vision are worth far more than commodity code. What matters, mathematically, is that Task A’s input-output relationship flattens as performance improves, while Task B’s accelerates. Task A’s curve is concave and Task B’s is convex. For Task A, the difference in return between an excellent and an average performer is minimal, but for Task B, it’s immense.

Does excellence matter? At most jobs, the answer has traditionally been “no”. At least, it has mattered far less than uniformity, reliability, and cost reduction. The concave behavior of Task A is more appropriate to most jobs than a convex one, and that’s largely by design. The problem with creative excellence is that it’s intermittent. Creativity can’t be managed into existence, while reliable mediocrity can be. As much as we might want managers to “nurture creativity”, the fact is that they work for companies, not subordinate employees, and their job is largely to limit risk. If we expect managers to do anything different, we’re being unreasonable. For Task A, performance-middling behaviors like micromanagement are highly appropriate, because bringing the slackers into line provides much more benefit than is lost by irritating high performers, and most industrial work that humans have performed, over our history, has been more like A than B. Getting the work done has mattered more than doing it well.

One of the interesting differences between concave and convex work is the relationship between expectancy (average performance) and variance. For traditional concave work, there’s a lot of variation at the low-performing end of the curve, but very little among high performers. To consider variance uniformly bad, therefore, will not be detrimental, the upside of variation being so minimal. Managerial activities that reduce variance are generally beneficial under such a regime. Even if high performers are constrained, this is offset by the improved productivity of the slackers. For convex work, the opposite is true. In a convex world, variation and expectancy are positively correlated. It turns out to be much easier, for a manager, to control variance than it is to improve expectancy. For this reason, almost everything in the discipline of “management” that has formed over the past hundred years has been focused on risk reduction. In a concave world, that worked. Reducing variance, while it might regress individual performances into mediocrity, would nonetheless bring the aggregate team performance up to a level where no one could reliably do better with comparable inputs. For most of industrial humanity’s history, that was enough.

Variance reduction falls flat in the convex world. Managerial pressures that bring individual performance to the middle don’t guarantee that a company has an “average” number of high-performing people, but make it likely that the firm has zero such people, and the result of such mediocrity is an end to innovation. In the short term, this damage is invisible, but in the long term, it renders the company unable to compete. Its prominence and market share will be snapped up in small pieces by smaller, more agile, companies until nothing is left for it but dominance over low-margin “commodity” work. Contrary to the typical depiction of large corporate behemoths being sunk wholesale by a startup “<X> killer”, what actually tends to happen is a gradual erosion of that company’s dominance as new entrants compete against it for something more important, in the long run, than market share: talent. Talent is naturally attracted to convex, risk-friendly work environments.

For a digression into applied mathematics– specifically, optimization– I would like to point out that since maximizing a concave function (such as bulk productivity) is equivalent to minimizing a convex one, we can think of management in the concave world as somewhat akin to a convex optimization problem. This is more of a metaphor than a true isomorphism, with one being abstract mathematics and the other rooted in human psychology, but I think the metaphor’s quite useful. I’ll gloss over a lot of detail and just say this: convex optimizations (again, akin to management of concave work) are easier. A convex minimization problem is like finding the bottom of a bowl (follow gravity, or the gradient). However, if the problem is non-convex, the surface might be more convoluted, with local valleys, and one might end up in a suboptimal place (local minimum) from which no incremental improvement is possible. The first category of problem can be solved using an algorithm called gradient descent: start somewhere, and iterate by stepping in the direction that, locally, appears best. The second category of problem can’t be solved  by simple gradient descent. One can fall into a local optimum from which some sort of non-local insight (I’ll return to this, later) is required if one wants to improve.

Concave and convex work are, in kind, also sociologically different. When the work is concave, the optimization problem is (loosely speaking) convex, and the one stable equilibrium (or local optimum) is, roughly speaking, “fairness”. On average, you’ll get more if you focus your efforts on improving low performers (who will improve more quickly) than by making the best even better. A policy that often works is to standardize performance: figure out how many widgets people can produce, and develop a strategy for bringing as many people as possible to that level (and firing the few who can’t make it). Slackers are intimidated into acceptable mediocrity, incorrigible incompetents are fired, and the bulk of workers get exactly the amount of support they need to reliably hit their widget quota. It’s a “one-size-fits-all” approach that, while imperfect, has worked well for a wide variety of industrial work.

Management of convex work is, as it were, a distinctly non-convex optimization problem. It’s sociologically much more complicated, because while the concave world has a “fairness” equilibrium, convex work has multiple equilibria that are usually “unfair”. You end up with winners and losers, and the winners need to be paired with the best projects, roles and mentors, although one might argue that the winners “don’t need them” from a fairness perspective. For convex work, you don’t manage to the middle. The stars who get more support and better opportunities will improve faster, and the schlubs’ mediocrity (whether a result of inability or poor political position) will persist. The best strategy, for a managed company, would be to figure out who has “star” potential and invest heavily in them from the start, but the measurements involved (especially because people have such strong incentives to game them) are effectively impossible for most people to make, both for intrinsic and political reasons.

For convex work, excellence and creativity matter, and they can’t be forced into existence by giving orders. Additionally, the value produced in convex work is almost impossible to measure on a piece-rate basis. Achievements in concave work tend to be separable: one can determine exactly how much was accomplished in each hour, day, and week, so it’s easy to see when people are slacking off. Work that is separable by time is usually also separable by person: visible low performers can be removed, because the group’s performance is strictly additive of individual productivity. For convex work, this is nearly impossible. A person can seem nonproductive while generating ideas that lead to the next breakthrough– the archetypical “overnight success” that takes years– and a colleague who might not be publishing notable papers may still contribute to the group in an important, but invisible, way.

If your tools are traditional management tactics, then convex work is intractable, and management is often counterproductive. I think the best metaphor that I can come up with for managers and executives is “trading boredom”. There are many traders out there who could turn a profit if they stuck to what they knew well, but get bored with “grinding” and start to depart from their domains of competence, adding noise and room for mistakes, and burning up their winnings in the process. Poker players have the same problem: the game gets so boring (at 2000-3000 hours per year) that they start taking unwise risks. The 40-hour work week is so ingrained in modern people that there’s often a powerful guilt people face of feeling useless when there is no work for them to do (even if they achieve enough within 10 of those hours to “earn their keep”) and this often leads to counterproductive effort. This, I believe, explains 90 percent of managerial activity: messing with something that already works well, because watching the gauges gets boring. Whenever an executive comes up with a hare-brained HR policy that the company doesn’t need, trading boredom, and the need to still feel useful when there is no appropriate work to do, is the cause.

At concave work, this managerial “trading boredom” is a hassle that veteran workers, who have been doing the job for decades, learn to ignore. They already know how to do their jobs better than their bosses do, so they show enough compliance to keep management off their backs, but change little about what they’re actually doing unless there’s a legitimate reason for the change. They keep on working, and the function of the team or factory remains intact. For convex work, on the other hand, managerial meddling is utterly destabilizing. The pointless meetings and disruptions inflicted by overmanagement take an enormous toll. In a convex world where small differences in performance lead to large discrepancies in returns, spending 2 hours each week in pointless meetings isn’t going to reduce output by a mere 5 percent, as one might expect from a linear model (2 hours lost out of 40). It’s probably closer to 25 percent.

The corporate hierarchy: an analytical perspective.

The optimization metaphor above, I believe, explains certain functional reasons for the typical three-tiered corporate hierarchy, with executives, managers, and workers. The workers are just “inputs”– machines made of meat, with varying degrees of reliability and quality, and for which there exist well-studied psychological strategies for reducing variance in performance in order to impose as much uniformity as possible. A manager‘s job is to focus on a small region over which the optimization problem is convex (which implies that the work is concave) and perform the above-mentioned gradient descent, or to iterate step-wise toward a local optimum. The strategy is given to the manager from above, and his job is to drive execution error as close to zero as possible. As variance will, all else being equal, contribute to execution error, variance must be limited as well. The job of an executive is to have the non-local insight and knowledge required to find a global optimum rather than being stuck at a local one. Executives ask non-local “vision” questions like, “Should we make toothpaste or video games?” Managers figure out what it will take to get a group of people to produce 2 percent more toothpaste.

This hierarchy is becoming obsolete. Machines are now outperforming us at the mechanical work that defined the bottom of the traditional, three-tier hierarchy. They are far more reliable and uniform than we could ever hope to be, and they excel at menial, concave work. We can’t hope to compete with them on this; we’ll need to let them have this one. So the bottom of the three tiers is being replaced outright. In addition, specialization has created a world where there is no place for mediocrity, and, therefore, in which the individual “worker” is now responsible for finding a direction of development (a non-local, executive objective) and planning her own path to excellence (a managerial task). The most effective people have figured this out by now and become “self-executive”, which means that they take responsibility for their own advancement, and prioritize it over stated job objectives. As far as they’re concerned, their real job is to become excellent at something, and they will focus on their career rather than their immediate job responsibilities, which they perform only because it helps their career to do so. As far as self-executive people are concerned, their employers are just along for the ride– funding them, and capturing some the byproducts they generate along the way, while they work mostly on their real job: becoming really good at something, and advancing their career.

Self-executive employees are a nightmare for traditional managers. They favor their career growth over their at-moment responsibilities, have no respect for the transient managerial authority that might be used to compel them to depart from their interests, yet tend at the same time to be visibly highly competent, which means that firing them is a political mess. They’re the easiest to fire from an HR “cover your ass” perspective (they won’t sue if you fire them, because they’ll quickly get an external promotion) but the damage to morale in losing them is substantial. In concave work, a team could lose its most productive member with minimal disruption; at convex work, such a loss is crippling. Managers who want to peaceably remove such people have to make it look like something the group wanted, and so they create divisions between the self-executive and colleagues– perhaps by setting unrealistic deadlines and then citing the self-executive person’s extracurricular education as a cause for slippage– but these campaigns are disastrous for group performance in the long run.

From a corporate perspective, a self-executive employee is the opposite of a “team player” and possibly even a sociopath, but I prefer to call the self-executive attitude adaptive. What point is there in being a “team player” when that “team” will be a different set of people in 36 months, and where one can be discarded from the team at any time, often unilaterally by a non-productive player who’s not even a real part of it? None that I see. The “team player” ethic is for chumps who haven’t figured it out yet. Additionally, because the working world is increasingly convex, self-executive people are increasingly good (if chaotic good, to use a role-playing analogy) for society. They sometimes annoy their bosses, but they become extremely competent in the process and, in the long term, they will advance the world far more than anyone can do by following orders. Self-executives tend to “steal an education” from their bosses and companies, but twenty years later, they’re building superior companies.

Self-executive employees want to take risks. They want to tackle hard problems, so they get better at what they do. While managers want to reduce variance, almost obsessively, self-executives want to increase it. Also relevant is the fact that managerial fictions about intrinsic “A”, “B”, and “C” players don’t exist. Stack-ranking– the annual “low performer” witch hunt that companies engage in to scare their middling crowd– doesn’t actually do much good in personnel selection. (It excels at intimidation, which is performance-middling and thus reduces variance, but the desirability of this effect is rapidly declining.) What does exist, and seems to be intrinsic, is that there are low- and high-variance people. Low-variance workers can kick out an acceptable performance under almost any circumstances– long hours, poor health, boring work, difficult or even aggressive clients and managers. They’re reliable, not especially creative, and tend to do well at the war of attrition known as the “corporate ladder”. They make lousy executives, but are most likely to be selected for those sorts of roles. High-variance people, on the other hand, are much more creative, and tend to be self-executive, but are much less reliable in the context of managed work. Their level of output is very high if measured over a long enough timeframe, but impossible to read at the level of a single day, or even a quarter. This distinction of variance, much more than the A- and B-player junk science, seems to be intrinsic or, at the least, very slow to change for specific individuals. Unfortunately, traditional managers and high-variance individuals are natural enemies. Low-variance people tend to be selected for management positions, are easiest to manage, and (most importantly) are less likely to make their bosses insecure.

What is changing

Why is work moving from concavity to convexity in output? There are a few answers, all tightly connected. The first of these is that concave work tends to have a defined maximum value: there’s one right way to perform the task. If we can define a target, we can structure the task as a computation, and it can be automated. Machines win, no contest, at reliability as well as cost-reduction. They’re ideal workers. They never complain, work 168-hour weeks, and don’t have hidden career objectives that they place at a higher priority than what they’re asked to do. As we get better at programming machines to perform the concave work, it leaves us with the convex stuff.

Second, the technological economy enhances potential individual productivity. The best programmers deliver tens of millions of dollars per year in business value, while the worst should probably not be employed at all. The capacity to have multiplier effects across a company, rather than the additive impact of a mere workhorse, is no longer the domain of managers only. The best software architects and engineers are also multipliers, because their contributions become infrastructural in nature. I don’t think that this potential for multiplicative impact is limited to software, either. As software becomes more capable of eliminating menial tasks from peoples’ days, there’s more time available for the high-yield, high-risk endeavors at which machines do poorly. What this enables is the potential for rapid growth.

When studying finance, one often learns that high rates of growth (8% per year) in a portfolio are “unsustainable”, because anything that grows so fast will eventually “outgrow” the entire world economy, which grows at only 3 to 5 percent, as if that latter rate were an immutable maximum. This might also apply to the 10-15% per year salary growth that young people expect in their careers– also unsustainable. Wall Street (in terms of compensation) has been called “a bubble” for this reason: even average bankers experience this kind of exponential compensation growth well into middle age, and it seems that this is unreasonable, because even small-scale economies or subsectors “can’t” grow that fast, so how can a person? Can someone actually increase the business value of his knowledge and capability by 15% per year, for 40 years? It seems that there “must be” some limiting factor. I no longer believe this to be necessarily true at our current scale. (There are physical, information-theoretic upper limits to economic prosperity, but we’re so far from those that we can ignore them in the context of our natural lifespans.) Certainly, rapid growth becomes harder to maintain at scale; that is empirically true. But who says that world economic growth can’t some day reach 10% (or 50%) per year and continue at such a rate until we reach a physical maximum (far past a “post-scarcity” level at which we stop caring)? Before 1750, growth at a rate higher than 0.5% per year would have been considered impossible: 0.1 to 0.2 percent, in agrarian times, was typical. If we view our entire history in stages– evolutionary, early human, agricultural, industrial– we observe that growth rates improve at each stage. It’s faster-than-exponential. I don’t believe in a single point of nearly-infinite growth– a “Singularity”– but I think that human development is more likely than not to accelerate for the foreseeable future. In the technological era, rapid improvements are increasingly possible. Whether this will result in rapid (30% per year) macroscopic economic growth I am not qualified to say, and I don’t think anyone has the long-term answer on that one, but we are certainly in a time when local improvements on that order are commonplace. Many startups consider user growth of 10% per month to be slow.

Rapid growth and process improvements require investment into convex work, which often lacks a short-term payoff but often provides an immense upside. It’s this kind of thinking that companies need if they wish to grow at technological rather than industrial rates, and traditional variance-reduction management is at odds with that. That said, traditional management is quite a strong force in corporate America. Most companies cannot even imagine how they would run their affairs without it. For sure, the managerial and executive elites won’t go gently into that good night. The private-sector career politicians who’ve spent decades mastering this inefficient, archaic, and often stupid system are not going to give up the position they’ve worked so hard to acquire. The macroscopic economic, social, and cultural benefits to a less-managed work world are extreme, but also irrelevant to the current masters, who have a personal desire to keep their dominance over other humans. The people in charge of the current system would rather reign in hell than serve in heaven. So what will give?

There won’t be an “extinction event” for managerial dinosaurs and the numerous corporations that have adopted their mentality, so much as an inability to compete. First, consider the superior quality of open-source software over commercial alternatives for an expanding set of software. That’s indicative. Open-source projects grow organically because people value them and willingly contribute, with no managers (in the industrial-era sense) needed. Commercial products die unless their owners continue to throw money at them (and sometimes even then). Open-source contributors are intrinsically motivated to be invested in the quality of their software. They’re often users of the product, and they can also improve their careers by gaining visibility in the wider software world. They have real, technological-era, self-executive motivations for wanting to do good work. For a contrast, most commercial software products are completed at a standard of “just good enough” to appease a boss and remain in good standing. It’s software written for managers, but from a product-quality standpoint, bosses themselves rarely matter. Users do. The quality gap between non-managed work and managed work is becoming so severe that the value of managed work is (albeit slowly) declining, out-competed by superior alternatives. This is bringing us to a state where “radical” cultures such as Valve’s purportedly manager-free open allocation policy become the only acceptable option. I would be shocked, in 30 years, if open allocation weren’t the norm at leading technology companies.

The truth is that managed work and variance reduction, which made the Industrial Revolution possible, are capable of producing growth at industrial (1 to 5 percent per year) rates, but not at technological rates (and a venture-funded startup must grow at technological rates or it will die). Compared to the baseline agrarian growth rate (0.05 to 0.3% per year) of antiquity, the industrial rate was rapid. Traditional management still works just fine, if your job is to turn $1.00 into $1.03 in twelve months. If you’re already rich and looking to generate some income from your massive supply of capital, this might continue to work for you indefinitely. If you’re poor, or looking to compete in the most exciting industries, and you need to unlock the energies that turn $1.00 into $2.00, you need something different.

Does this mean that there will no longer be no role for managers? It depends on how “manager” is defined. Leadership, communication, and mentorship skills will always be in high demand. In fact, the increasing complexity of technology will put education at a premium, and the few people who can lead groups of self-executive workers are becoming immensely valuable. Although the most talented workers will evolve into self-executive free agents, they will need some way of learning what efforts are worth their time, and they’ll be learning this from other people. Some aspects of “management” will always be important, but to the extent that management lives on, it will have to be about genuine leadership rather than authority.

Fossil fools

What has a one-way ticket to the tarpit (and almost no one will miss it) is the contemporary institution of corporate management: the Bill Lumbergh, who uses authority by executive endowment to compensate for his complete lack of leadership skills.

Leaders are chosen by a group that decides to be led, whereas corporate managers are puppet governors selected by external forces (or “from above”) as a means of exerting control. They don’t have to have any leadership skill, because the people being led have no choice. They’re hand-picked by their bosses: higher-level managers and executives. Leadership often requires handling trade-offs of peoples’ interests in a fair way, but that’s impossible for a corporate manager to do. Executives will never select a manager who would support the workers’ interests at an equal level to their own. Managers play a variety of roles, but their main one is to be a buffer between two groups of people (executives and workers) who would otherwise be at opposition because, even if for no other reason, they get dramatically different proportions of the reward. Managers legitimize executives by creating the impression that the separation between the company’s real members and its workers is a continuous spectrum (and thereby support the company’s efforts to mislead people regarding their true chances of upward mobility) rather than a discrete chasm, but they also form, because of their own increasingly divergent interests, a weak link that is increasingly problematic.

The corporate structure is effectively feudal. Just as medieval kings never cared how the dukes and earls treated their peasants, as long as tributes were paid, managers generally have unilateral power over the managed (as long as they don’t get the company sued). Managers are trusted to execute the corporate interest. It seems like this should create a weak link, giving managers the power to force workers to suit the manager’s career goals rather than the corporate objective. Perhaps surprisingly, though, in a concave world this doesn’t cause a major problem for the company. Managerial and corporate interests, at concave work, are aligned for reasons of sociological coincidence.

Managers have high social status and status is positively autocorrelated in time (that is, high status tends to reinforce itself) so a manager will “drift” into higher position as the group evolves, so long as nothing embarrasses him. Workers have to prove themselves in order to stand above the masses, but managers can coast and acquire seniority. In other words, a manager’s career is optimized not when he maximizes group productivity (which may be impossible to measure) but when he minimizes risk of embarrassment. A subordinate who breaks rules, no matter how trivial, embarrasses the manager– even if he’s highly productive. It’s better, from a manager’s career perspective, to have ten thoroughly average reports than nine good ones and one visible problem employee. Great employees make themselves look good, while bad ones are taken to reflect on the manager who failed to keep them in line. The consequence of this is that managers are encouraged toward risk-reduction. In a concave world, this is exactly what the company needs. So what happens in a convex world?

The convex world is different. If a company “gets” convexity (which is rare) it will begin to make allowances for individual contributors to allocate time to high-variance, high-reward activities which are often self-directed. This gives workers the opportunity to achieve visible high performance, and it’s good for the (expected) corporate profit, but managers lose out, because the worker who hits a home run will get most of the credit, not the manager. They find their subordinates increasingly interested in “side projects” and extra-hierarchical pursuits that “distract” them from their assigned work. There’s a conflict of interest that emerges between what the worker perceives as managerial mediocrity and the quest for the larger-scale excellence that can exist in convex pursuits. Because self-executive workers think non-locally (extra-hierarchical collaboration, self-directed career advancement) the appearance is that they’re jumping rank.

In the concave world, managers were the tactical muscle of the company. They drove the workers toward the local optimum in the neighborhood that the globally-oriented executives chose. In the convex world, managers are pesky middlemen. If they operate according to self-interest (and it’s unreasonable to expect otherwise of anyone) then their best bet is to use their authority to coerce their reports to prioritize the manager’s own career goals, which have now diverged from the larger objective. In other words, they become extortionists. That’s not a business that will live for much longer.

What seems clear is that middle management will decline in power and importance over the next 50 years. Increasingly convex work landscapes will decrease the use for it, and people will have less desire to fill such positions (which, in concave work, are coveted). What’s less clear is what will replace it. If this corporate middle class disappears within the current framework, what’s left is a two-tier system with workers and executives. That’s a problem. Two-class societies are extremely unstable, so I don’t think that arrangement will thrive. What’s more likely, in my (perhaps overly optimistic) opinion is that the functions of workers, managers, and executives will all blend together as individuals becomes increasingly self-executive. In many ways, this is a desirable outcome. However, it dramatically changes the styles of business that people will be able to form, making companies fairer and more creative, but also more chaotic and probably smaller. If the result of this is a macroscopic increase in creativity, progress, and individual freedom over one’s work, then a truly technological era might begin.

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26 thoughts on “The end of management

  1. The quality gap between the products of managed work and unmanaged work has reversed, with unmanaged work being superior by an increasing– at this point, impossible to ignore– amount.

    That is the most ridiculous assertion I have ever encountered.

    It is not management that must end, it is bad management. The current management doctrine came of age at least one industrial revolution ago. Why hasn’t the doctrine been updated already? Could it be that it benefits those who have power? Do you think the powers-that-be are willing to sacrifice their position to please the Goddess of Quality?

    For one notable example, open-source software is now superior to gold-plated commercial tools.

    Microsoft never shipped great software and they made it to the top. Why? Has it occurred to you that the world is not as meritocratic as you wish it would be? That is the engineer’s fallacy: that the highest-quality product will win. The world does not work that way, partly because lobbyists have more power and influence than engineers. And salesmanship often decides which product wins, not quality per se.

    Creativity and motivation matter more than uniformity and control. This was not always the case, but it has become true and this trend is accelerating.

    Proof by assertion? That which happens to work in the special and unique ecosystem that is Silicon Valley may not work in other industries. To assume that it can is not only naive, it is extremely pretentious. This post is titled “the end of management”, not “the end of management in the software industry”.

    It is unnatural for people to manage or be managed

    That is ridiculously childish.

    Obedience does not imply submission / surrender. To accomplish greater things, a “creative” über-engineer (of the sort you idolize) will have to be managed. The problem is not being managed, the problem is being managed by a moron that is commanded by someone who lacks vision.

    I think it is fair to say that Apple is the prime example: someone with the charisma and vision of Steve Jobs can polarize his troops and guide them towards great victory. What can 10,000 engineers do without any guidance? Isn’t guidance a form of management? Perhaps, the best form of management? To accomplish great things, people must know what the goal is.

    Does excellence matter? At most jobs, the answer has traditionally been “no”. At least, it has mattered far less than uniformity, reliability, and cost reduction.

    Sorry, but I tend to think that reliability is a form of excellence.

    Respectfully, but do you have any actual engineering experience? People who design bridges, airplanes, avionics systems, medical equipment, analog / digital chips tend to value reliability a great deal. Of course, if you’re doing something like Android apps, you don’t have to know what engineering is: if you make a mistake, no one dies.

    I find it amusing that the rovers sent to Mars by NASA / JPL used Intel 286 (or 386) microprocessors, even though Pentium microprocessors were available. You see, the old ones were radiation hardened, and people knew they were reliable. Innovation is great, but it should be confined to applications where lives are not at stake. Creativity is wonderful too, but good engineering is even better. Why do you care about productivity if you don’t care about reliability? I would be willing to pay a premium for reliability. The thought of having life-support systems that were designed by “creative”, “rebellious”, “innovative” pseudo-über-techies is horrifying. May I never end up in the emergency room…

    I generally enjoy reading this blog, but there’s “deliciously thought-provoking” (like that post on the 3-ladder taxonomy) and there’s “jump the shark quasi-insanity” (like this post).

    You have some interesting and original ideas, but you seem to lack self-control and self-censorship. You tend to follow this script: start exposing an idea, perform well, get to the point where greatness seems to be within reach, and then you ruin it all because you had to inject your wishful thinking and ideological biases into it. Personally, I think you would be a better writer if you could be more detached, if you could write coldly and impersonally, like a man from Mars who has just landed on Earth and is attempting to study human beings and human institutions the way a botanist would study flowers: in a detached manner. The more emotionally invested you are, the more difficult it is.

    • Hi Rod,

      You make some really good points, and I think we’re talking past each other on the topic of “management”. It is absolutely true that people will need leadership, mentorship, and to use your word, guidance. There are a lot of team-building and administrative tasks that can’t easily be divided or left to emergent behavior.

      You said that the problem isn’t management but “bad management”. The problem, as I see it, is structural. Not all kings were bad, but many were, and this was enough of a problem that we moved away from hereditary, autocratic monarchies. Likewise, not all managers are bad, but many are. In many companies, managers have the unilateral ability to either (a) fire someone, or (b) ruin that person’s reputation (through globally-visible performance reviews) so badly as to have the same effect. That creates a monstrous single-point-of-failure, and it’s abused all over the place, so much that it’s unremarkable. In a large number of companies, managers prioritize their own career objectives over the needs of their reports and the good of the company. That’s becoming increasingly pathological as work changes from a concave to a convex variety.

      It’s not that everything we call “management” is going to disappear. It’s that middlemen who exploit their SPOF-ness to force others into total subordination to their own career objectives are going to be too toxic for organizations to afford, while that behavior is not currently something companies care much about.

      On reliability, I should have clarified what I meant. Reliability in systems is a form of excellence: you’re absolutely right, and there’s no disagreement there. My objection is to the bullshit reliability, based more on appearances than anything meaningful, that determines who succeeds in the corporate world. Machines are capable of reliability and designing systems to be maximally reliable is a form of excellence. Being in the office before your manager gets in, and not leaving until he’s gone, is not a form of excellence. That’s just a bunch of mindless sacrifice geared toward archaic social protocols.

      Companies should generally not be bet on human reliability, ever, if it can be avoided, because machines are just so much better at being reliable. This means that the skills selected in the typical corporate-ladder war of attrition are no longer as important in the technological era.

      • It is interesting to note that I disagreed with virtually everything in your blog post and, yet, agreed with virtually everything in your comment. I am all for robustness, and SPOF scares me (for obvious reasons).

        Having said that, are you acquainted with Venkat’s Gervais Principle? It is a caricature of reality, of course, but if it is a reasonable faithful one, then it explains why (middle) managers do what they do.

        Quoting Buckminster Fuller:

        You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.

        If the existing reality is so pathological, why hasn’t a new model emerged to replace it? There are some companies where managers are “coordinators” rather than “slave drivers”. But once such companies grow to a certain size, they seem to end up sclerotic, dysfunctional, and pathological.

        • I think it’s really only just starting to be possible for a company to have a majority of employees on the “creative” side. The vast majority of work is still along the lines of data entry where the best performers have maybe 50% better performance, but Github is a good example in the software world-they have highly nontraditional management, and achieved a valuation of roughly 7.5 million dollars per employee.

          WL Gore & Associates is an example of a company that essentially has open allocation and nontraditional management. They’re constantly rated as one of the best places to work for, are highly profitable, and have ~9,000 employees.

        • I think my flame-war-esque title and failure to flesh out a good definition of “management” may have biased you (and probably a lot of other potential readers) against the post.

          It’s not managers I have a problem with, so much as “management” as traditionally defined. Many managers are victims of the system, because they’re often not allowed to execute the interests of their reports, or because they’re forced to do unethical things (like give bad reviews to a certain percentage of people because of a stack-ranking policy).

          I think that a bit part of the problem is that “management” becomes a separate caste with its own special interests but all of the vote. There are a lot of important functions that can be called “management”, but most companies let the manager distinction turn into an in-the-club/out-of-the-club distinction.

          Regarding pathology and sclerotic mediocrity, what I think is changing is that companies can afford it less if they want to be at the forefront (especially in the competition for talent). A manager is someone who has the authority to force a person to prioritize other interests, and this was traditionally used to put them to the manager’s own career interests, but those aligned well with the firm’s, because the concave input-output relationship meant their variance-reductive tendencies were beneficial. Now, they’re at odds; the manager’s career interests are not the same as the company’s. That potential for abuse and SPOF-ness was always there, but there was a time when it didn’t matter. For commodity workers on concave tasks, firing a few unfairly doesn’t hurt the company at all; they’ll find others.

          I tend to think that an open allocation company can scale, if there’s a concerted effort to preserve the culture. What I think happens is that companies tend to lose their culture based on the demands of executives and managers it wants to hire from without. When you’re trying to hire executives who are used to single-trigger firing autonomy and total dedication from their subordinates, an executive role at an OA company is not attractive to them, it’s tempting to sell off a little bit of employee autonomy. That seems to be what happened to Google. No one set out with the explicit desire to lose the culture; it was sold in small pieces to transplant executives, one at a time.

          If you’re going to make open allocation work, you have to be ready to accept that it will be very hard to hire external managers or executives, which raises the question: does one really need managerial and executive castes and all this hierarchy? If the answer is “yes”, than open allocation can’t scale, but I tend to think the answer is “no”.

          • “If you’re going to make open allocation work, you have to be ready to accept that it will be very hard to hire external managers or executives”
            Of course, that is only a short term problem. It will get easier as open allocation become more common

        • Rod,

          I totally agree on the Gervais Principle reference. Regarding your question on where the new model is, perhaps it’s the Valve self-selection model that Michael mentions.

          As far as growth leads to pathology, I would tend to agree, but I have hope for the future. I’ve always looked at company growth as the evil cousin of the network effect — dysfunction grows as the square of headcount.

          The counter-agent to this may be something like the Netflix high performance culture (http://www.slideshare.net/reed2001/culture-1798664). E.g. look for what Michael calls “self-executives” such that the average talent density grows faster than the complexity of the business (see pages 44-58 in the culture deck). It’s not infinitely scalable, but for the seven years I was there, the company evolved into what I’ve thought of as the world’s biggest startup.

    • For this article, I’m talking more about the corporate institution than the set of tasks or the people who do them. There are a lot of important jobs that companies file under “management”, and those will still be important, but I think the military-inspired hierarchical model where people dedicate themselves wholly to a commanding officer is, in business, a dinosaur.

      In the traditional corporate world, almost everyone’s job is “make your boss happy”. That leads to risk-aversion and mediocrity. It was acceptable 50 years ago, but now, I don’t think it works well for the most exciting businesses. However, the changeover to a newer model will probably be slow, human nature being what it is.

  2. Of course, all of this mainly just applies to right side of the bell curve people. It’s a solution for the cognitively gifted who can self manage.

    “They sometimes annoy their bosses, but they become extremely competent in the process and, in the long term, they will advance the world far more than anyone can do by following orders.”

    It depends on what you do. This is exactely one of the changes that happened in the investment banking world. People cared more about themselves then thier firms or clients. They expected to bounce around every 36 months. And the talent level went way up. Unforunately this just meant you have lots of people really talented at ripping people off and pursuing short term gains. It was a part of the entire financial crisis.

    In a lot of industries this leads to excellent politicing and dishonesty more then it leads to higher work output.

    • I think this is a simplistic assessment, because investment banks optimized for two dimensions of talent in two separate categories of work. They developed the quant track to get really smart people, and the analyst program (with the notorious 120+ hour weeks) to get really competitive and vicious people.

      The quants actually have made finance stabler and saner. The people who brought us the 2008 cockup were not, for the most part, quants but business-side sleaze who abused the models.

      For example, no quant worth his salt actually believes that 6-sigma events (in distributions that are clearly fat-tailed, i.e. not normal) are actually 1 in 1-billion; that’s just something that scummy business-side bullshitters/rainmakers say to schmooze with clients.

      The people responsible for sliminess on Wall Street aren’t $500,000-per-year quants coming up with new pricing models. They’re the $10-million-per-year masters of the universe, and entering the latter category has much more to do with how much moral sacrifice you’re willing to make than with talent.

      • Dude, I was on the quant track. No, it did not make finance stabler. We invented most of the derivatives the blew things up. And there are lots of dirty quants, I know em. if they weren’t dirty they would not be in investment banking, they’d be out doing real work. My best friend from high school a genius and infinitely more skilled quant then I, laid out the whole life plan to me when we were still both in the business trying to get me to buy on board.

        1) Work in an IB for 5-10 years, however long it takes to build a client network,

        2) Start a hedge fund an solicit those clients.

        3) Take a huge punt on something. It doesn’t matter what it is. Dress it all up in fuzzy math, we’re good at that thing.

        4) If it hits profit big. If it sinks its other peoples money.

        What, you thought high math ability and being a nerd made you a saint? Being an asshole ain’t just for the jocks dude.

        The models are fundamentally broken. It’s just a big zero sum game that you add complication too. If you believe different you’ve bought into the lie. The only way to create wealth is to actually create it.

        We should not exist. Our product was fundamentally useless. That’s the upside, uselessness. The downside is what we got.

        • Of course there are dirty quants. There are also fraudulent scientists, sick doctors, crooked lawyers and perverted priests. No profession is free of assholes and scumbags. A large percentage (probably 20-30 percent in the highest-status jobs) of people are absolutely shitty no matter where you are.

          I don’t think that quants, as a group, are worse than these supposedly world-changing startup folks, for one example. In fact, I think VC-istan is worse in some ways. Bad hedge funds lose rich people’s money, but bad startups and crooked VCs fuck up people’s careers and reputations. Taking degenerate risk with $5 million of a billionaire’s assets because of “2-and-20″ is wrong, but bait-and-switch hiring, irresponsible firing, and flat-out lying about a company’s prospects to motivate some of society’s smartest and hardest-working people to sacrifice their career-building years for a lame idea is a lot worse in my opinion. The most evil people I’ve encountered in my work life were not in finance.

          Whether models are “broken” is another discussion. Every model contains false assumptions. Linear regression? Almost nothing’s actually globally linear. Brownian motion of stock prices? Doesn’t account for black-swan “jumps”. Neural nets? Great nonparametric tools, but impossible to audit. Most of the quants I know understand the limitations of the models. This doesn’t stop “rainmaking” jackasses from abusing them to win others’ confidence, but you don’t need mathematicians to have con artists. The con artists just use the language of quants because people at large are beginning to realize the importance of data and the mathematical tools necessary to exploit it.

          Sure, there have been many quants who’ve facilitated greedy bastards’ elaborate scams, and some of those even knowing exactly what they were doing, but financial fraud is old as dirt and can’t be blamed on the quants.

          • Before I go into my usual criticism mode I want to state I agree with most of what you say.

            Everyone lost in the financial crisis. Not just rich dudes in a hedge fund. Anyone with a 401k took a hit. Lots of people lost their jobs, their homes, etc. Even people not in finance at all. Also, you can’t replace the resources that went to build tract houses in the desert. And there are lots of other bubbles out there still that are gonna hurt. I could go on and on here.

            Even when its just rich dudes losing money its still a net loss to society. Many of these quants are smart dudes, they could be working on real problems. They mostly get into finance for the money though. Then they aren’t working on real problems. That’s a net loss to society.

            “Most of the quants I know understand the limitations of the models.”

            Then they should quit and try to do something with their lives. Nobody on wall street is making anything. A derivative is a zero sum piece of garbage. All of the crap about reduced risk/volatility is propaganda garbage. When I realized this I got out, I didn’t just keep cashing checks because its the path of least resistance. Some other dude is getting really rich off your scam model and your only getting kinda rich. Who cares, your still a scumbag living off your cut of the scam. Letting other people rob on your behalf while your an accomplice is wrong.

            “but financial fraud is old as dirt and can’t be blamed on the quants.”

            Certainly they deserve some of the blame. Your assertion that quants are somehow a “good” part of finance if only the evil salesmen didn’t twist their work is wrong. The work itself is bad. The models don’t create wealth. All of them, in one way or another, just move it around in fairly useless ways while retaining a big cut for themselves. Without the salesmen the quants wouldn’t have jobs because their jobs aren’t creating wealth. They need the salesmen, they turn their shit into gold.

            As for VC-istan or any other industry I’m sure there is a lot of shit all over the place. At least in some industries despite all the shit something real gets produced. I’m not sure that’s true in finance. The only useful stuff in finance is the same shit from 100 years ago and it could be done with an infinitely smaller finance sector (and wouldn’t require a whole lot of quants).

            • Where I think we agree strongly is that quantitative finance isn’t the best use of the top mathematical and scientific talent. I don’t feel as negatively about derivatives as you do– obviously, some of that stuff is just degenerate risk-taking, but I don’t personally feel that I have enough insight to know which products are legitimate risk transfers (such as when airlines buy oil futures to hedge against their intrinsic risk) and which are not– but it’s pretty appalling that there are a lot of really smart people whose only real option is to work for banks.

              Basic research has been cut to the bone and halfway through it, academia’s melting down, and what remains of industrial science is both competitive and specialized, so you can’t get a job unless you’re already established in the corresponding specialty, and you had better hope that this specialty stays fundable for the next 40 years. The result is that generalists and people who chose the wrong specialty are getting screwed.

              Wall Street saw an opportunity: society throwing its smartest people under the bus in a major way, lots of available talent on the market. The quant industry (or something similar, like writing ad exchanges for startups) is flush with cash and willing to take on a smart generalist, and it’s the only real option for a lot of smart people who failed to pick the right specialty.

              Everything nasty that can be said about the quant industry is (a) probably true of substantial parts of it, and yet, (b) equally true of the corporate private sector in general, including startups. This is where I think we disagree, because I don’t see the quant world as being any worse than anything else corporate (in fact, it’s better). Ninety percent of corporate work is bullshit, zero-sum positioning, socially negative, scammy, et cetera. No disagreement there, because our society is run by a bunch of fucking crooks. For one example, does advertising make product discovery more efficient, or is it a zero-sum waste of resources? Mostly, the latter. What about the fact that, instead of designing innovative new drugs, pharma companies pursue copycats and analogs, giving us 27 slightly different statins? I’d be surprised if more than 2-4 percent of contemporary corporate work, at the managerial-professional level or above, actually does anything useful for the world.

              You know where I see quant finance doing good? It keeps the top talent employed doing work that is, if nothing else, intellectually stimulating. It kicks out (or at least, assists and funds) some neat open source projects, and it keeps these top technical minds from atrophying in the way that they would if they took the MBA -> McKinsey -> corporate executive route. If quant finance disappeared, a lot of the smart people who are currently quants would NOT be going into socially-positive research efforts, because there are no jobs there. They would be taking shittier, lower-paid corporate jobs making even less use of their abilities, and after 10 years, their brains would be atrophied outright.

              • “but I don’t personally feel that I have enough insight to know which products are legitimate risk transfers”

                Sure, its not your industry. I’ve got less bile for someone simply admitting their own ignorance. I’ve been in the industry though and I have drawn my own conclusions.

                The example you give about oil futures is a really old contract that doesn’t require quants at all. All the “good” financial products are all really simple and old. A rule of thumb is if it requires a math PhD its probably a scam.

                I agree that its the easy way out for a lot of people. As I said in another post (here or elsewhere I can’t remember) lots of people take jobs in finance out of fear (fear of an uncertain future, fear of getting a dead end corporate job, fear of not being able to attract a mate or provide a certain standard of living for a family). However, let’s be real about what they fear. They fear not being super stars. All these people could get normal jobs and make a normal salary. You might not be able to get a nice apartment in an expensive city. You might not be able to send your kids to private school. That’s a risk you take. However, morality requires sacrifices sometimes. It’s not just a thing you do when its convienient and you don’t have to give up too much.

                I agree various changes in societal structure make the choice starker and harder. We get judged by our actions though. You and I aren’t going to change society, we can only live in it. How will you live in it? What choices will you make?

                I had a guy living in one of my spare rooms who was doing basic research for a uni. He was living on $40k/year. Does that suck? Yes. Was he at least doing something he wanted and contributing to the world? Yes. We can curse the world for making that the choice but we only get to make the choice, we don’t get to change the world.

                At the end of the day you just have to choose. Nobody said the choices would be easy. I understand compromise, I’ve had to do it sometimes myself because of sick family members, but I’ve made my fair share of sacrifices too.

              • If you want to understand more of what went wrong in the world of finance, read Yves Smith’s blog. There’s a fair amount there that goes over my head, but a lot of it is legible and it really shines a bright light in some dark places.

                Also, read about the gaussian copula function and how it was (mis)used. I’m not a quant, but I know GIGO – garbage in, garbage out. If a correlation based risk model uses only data from a period of continuous growth, that model is broken at best and fraudulent at worst.

                I do not have an opinion of who is ultimately at fault here. I don’t know if the quants screwed up and did not warn of the limitations of their models, or if their managers screwed up by failing to listen to the warnings. But the net result was that these models were used quite intentionally and quite specifically to hide risk.

  3. I don’t know if you meant it this way, but this reads like an idealist’s response to Venkat’s Gervais Principle.

    I found the explanation of the Type A and Type B work to be useful, but I have to mention that the the concave/convex dichotomy is intuitively backwards. I guess I think of the shape of the curve from above, rather than from below. Maybe that’s just me.

    I will say that I have seen some of this in the working world, but it’s extremely rare outside of software. I work for an engineering firm (real, actual engineering of actual matter, not software) that operates this way and encourages self-executive behavior. But this firm is both small and elite – I’m not aware of another one like us in the entire industry. I am very fortunate.

    I have got to complain, though, about one of the things you said.
    Can someone actually increase the business value of his knowledge and capability by 15% per year, for 40 years? It seems that there “must be” some limiting factor. I no longer believe this to be necessarily true at our current scale. (There are physical, information-theoretic upper limits to economic prosperity, but we’re so far from those that we can ignore them in the context of our natural lifespans.)

    Unless I am badly misinterpreting you, the thing you are saying is entirely counterfactual and at odds with reality. The fact is that we are, currently, pushing up hard against the planetary carrying capacity. In order to feed, clothe and (in the west) entertain our billions, we are doing grave and likely permanent damage to the ecological systems that make the Earth a friendly and comfortable place to live. Climate change, of course, but also loss of soil, freshwater depletion, eutrophication of waterways, and species loss. We cannot possibly replace these functions technologically – we are still very much dependent on mother gaia for our sustenance, and anyone who tells you otherwise is ignorant of engineering, ecology or (most likely) both.

    You appear to be making the standard error, of believing that technology or “innovation” are the basis of prosperity. They are not. Technology enables access to and application of resources, which facilitates prosperity. But technology is merely an enabler – the basis of prosperity is still natural resources and available energy flows.

    • If we view work as a loss-minimization problem, then what I’ve called concave work becomes _convex_, and we have something that is in some ways analogous to a convex optimization– the “fairness” equilibrium at the bottom of the surface. If we view it as a value-maximization problem, then my convex/concave terminology makes sense.

      On the issue of resources and economic growth… I actually think fast economic growth is possible, although the form of most of this will be much of the world becoming less poor. We won’t see 8%/year growth in the U.S. for a long time.

      Fossil fuels are a major issue, and so is global warming. These are huge problems not to be underestimated. The 21st may be a painful century. These problems might cause short-term (but severe) declines in quality of life, but I don’t think they will prevent humanity from having a long-term upward direction. We will make our way to better energy sources (nuclear and green) over time.

      The problem is that the market is failing to account for externalities of resource depletion and (until recently, with carbon-offset markets) pollution. People gripe about gas prices in the U.S. but the truth is that they’ve historically been too _low_, leading to over-reliance on a fuel source that is very bad for our future. We’re getting better at managing markets like this, and green energies seem to be progressing, and we have a president who (while conservative, by my standard) gets it. Don’t get me wrong: the suburban way of life, as it presently exists, is quite likely fucked. We’ll probably also have a decade or two where meat is so expensive that a lot of people become vegetarian for financial reasons. But I don’t see “peak oil” as a civilization-killer. At worst, I see it an American-dominance-killer and a generation-long setback. It is scary, though, because no one really knows for sure.

    • Personally, I interpreted

      (There are physical, information-theoretic upper limits to economic prosperity, but we’re so far from those that we can ignore them in the context of our natural lifespans.)

      with a transhumanist outlook. Assuming we manage to upload ourselves into the Matrix, our material needs are likely to drop dramatically. (I assume that the energy actually required to run a human mind is much, much less than what our current wetware consumes. Also electricity is a much more efficient carrier of energy than food). Now it will no doubt cause other significant problems, like, who gets to be root, privacy, and anything that could turn this potential heaven into hell.

      My point is, used well, technology still have a few orders of magnitude of growth to offer us.

  4. Peak oil will not kill civilization.

    Peak oil + peak natural gas (watch for the fracking bubble to burst in the next few years) + topsoil loss + fisheries collapse + eutrophication + freshwater constraints (the American breadbasket is irrigated with ancient water from the Ogallala aquifer, which is not replentishing) + climate change induced storms + climate change induced drought + climate change induced shifting of the seasons (which makes it really hard to farm, even if you have soil and water and predictable rain)… All that together might well kill technological civilization. It’s certainly not inevitable, but if we continue to make the same kinds of stupid choices we’ve made for the last 40 years, for another 40 years, it’s a real possibility.

    But that’s not my point. My point is that peak oil* will kill economic growth, because economic growth is a function of net surplus energy, and that is in decline.

    * “peak oil” is really just the most commonly understood manifestation of a general trend in all fossil energy sources, which is a decline in availability, quality, and most importantly, energy return ratio.

    It takes energy to build the equipment and drive the activities necessary to extract energy and make it available in a useful form. If it takes 1 unit of energy to extract 100 units of energy, then your energy return ratio is 100:1. This means that if you extract/harvest 100 units of energy total, you have 99 units to actually use for everything else you do in society, other than procure more energy. That’s your net energy surplus.

    Net energy surplus defines the upper bound of a society’s material prosperity, because everything that humans like to do – largely in the general categories of moving mass through space, and maintaining unnatural thermal gradients – requires it. The efficiency with which you use that energy matters, of course, but at a given general level of efficiency, if your society’s net surplus energy drops significantly, the standard of living will suffer.

    (The issue of efficiency is a whole other conversation. To be brief, efficiency is great, and is a valuable strategy but it is subject to the law of diminishing returns. Becoming more efficient could make it possible to maintain a stable technological civilization in the face of energy decline, but it will not open the door to endless growth.)

    The shocking and non-obvious thing about the relationship between energy return ratio and net surplus energy, is how quickly your surplus energy declines as your ERR drops below about 10:1. Consider this graph.

    The X axis is your ERR. (The author calls it ERoEI – Energy Return on Energy Invested, but it’s the same idea.) The Y axis is your total energy throughput. The blue portion represents your net energy surplus, while the red part is the energy that must get plowed back into the energy production process in order to procure the energy in the first place.

    As you can see, a decline from ERR of 50:1 to 20:1 has minimal impact, but the decline from 10:1 to 2:1 takes you to a place where you have almost NO surplus net energy available. At low ERRs, you are in a red queen’s race just to maintain your society. Remember that that both your non-energy infrastructure maintenance, and ALL of your other activities, from education of the young to vacations, retirement, and Christmas toys, has to come out of the blue portion.

    I don’t necessary agree with all the ERR figures listed in the graph, but they are approximately right. I don’t think that the threshold for maintaining civilization is as high as the graph shows, but I agree that there is a limit below which technological civilization canot persist – I’d estimate that 5:1 is about the threshold.

    The upshot is that our historical energy sources have had ERRs of well above 20, often as high as 100 or better. That is the basis on which the prosperity of the last hundred years was built.

    However, those sources are largely tapped out and new sources (including deepwater oil, fracked gas, oil sands, and other intensive extraction techniques) have a much lower ERR. Some of the sources we are pursuing (corn ethanol in particular) have ERRs that are approximately 1, which is to say that they are useless as a source of surplus energy.

    At this point, we as a society have a choice. We can pursue renewable technologies, which have an ERR lower than we are used to (and thus are considered “too expensive”) but one that is stable over time. If we do this, we can have a sustainable steady-state economy that maintains high technology at a ERR of about 10.

    Or we can continue to pursue a lifestyle and economy based on perpetual growth, which requires ERRs that are much higher. In that case, we continue to chase new fossil energy sources right down the depletion curve. We hide this decline from ourselves by accepting, for example, more destructive extractions processes – increasingly externalizing the costs in order to maintain the illusion of profit and net social benefit. If we insist on continuing to lie to ourselves and pursue this path, we will most likely stop when we are down around an ERR of 2, at which point our infrastructure and civilization is falling apart because we no longer have the surplus energy (i.e. real wealth) to pay for maintenance, much less expansion.

    That is why the illusion of the possibility of perpetual growth is so dangerous. And that’s why I’m calling out your post: you are falling into the same mental trap that afflicts our economists and policymakers, who mistakenly believe that technology creates wealth. It does not. Technology facilitates access to surplus energy. Surplus energy is wealth.

    (Note that this framework extends to pre-tech civilizations as well. In a low tech civilization, the ERR that matters is the ERR of agriculture. But the principal is the same: if you can consistently produce a surplus, you can be rich. If not, not. And if you destroy your means of production in an effort to maintain the illusion of excessive wealth, you are good and screwed.)

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