Posts Tagged ‘corporations’
“Something is happening here / But you don’t know what it is / Do you, Mister Jones?”*…
Further to the post of Septmeber 15: on trying to understand what might lie on the other side of a transformation driven by AI (and related technologies). Microsoft’s Deputy CTO, Sam Schillace, suggests that organizations are about to change completely…
… Here’s a nerdy TL;DR if you want it: I think AI will enable a switch from what is essentially circuit switching today, in all kinds of organizations, to something that will look and feel a lot more like packet switching. This will happen partially because it can now (AI is to this problem what fast processors were to distributed networking protocols), and because networks are almost always more powerful, flexible, and scalable. This idea is going to feel super uncomfortable and be rejected by business leaders, employers and academics in much the same way that network engineers rejected the idea of packet-switched networks…
… In 1965, making a long-distance phone call in America was a feat of engineering coordination. A call from New York to Los Angeles required a dedicated copper path, physically reserved, for the duration of the conversation, and AT&T had to employ armies of switching engineers to manage this. The Bell System was one of the great technical achievements of the twentieth century, and the people who built it were not fools. They worked ferociously for what they were optimizing for: guaranteed, high-quality, reliable connections between two points.
It seemed fine – expensive, but that’s what everyone was used to. If you are my age, you remember when long-distance was even a thing, and those calls cost more and were precious. I still get a tiny bit nervous talking to my parents 3000 miles away in Michigan, that was so deeply ingrained. Part of me still can’t believe that phone calls all cost the same.
Then a small group of researchers, largely funded by ARPA, mostly working in universities, proposed something that sounded to the Bell engineers like a joke. Instead of reserving a dedicated path, you would break messages into small pieces, label each piece with a destination, and release them into the network to find their own way. Different pieces of the same message might travel completely different routes. They might arrive out of order. There was no guarantee that any particular piece would arrive at all. A phone call, under this scheme, would be like mailing a letter by tearing it into a hundred pieces and dropping each one in a different mailbox, hoping they’d all show up. (Kind of like training a giant AI model on lots of small fragments of language (tokens) and hoping that somehow intelligence would emerge from putting them back together randomly – which largely worked).
The Bell engineers had a name for this general idea: chaos. They had a specific critique too, which was that you couldn’t make any guarantees about quality of service. Voice needs low, consistent latency: you can’t have some syllables arriving seconds after others. And of course, data needs reliability: a corrupted file is useless. The engineers were right about all of this. Packet switching, in its early forms, was genuinely worse at the things circuit switching was designed to do.
It also, within a few decades, made the Bell System irrelevant. The internet didn’t improve on the telephone network; it made the telephone network a minor application running on top of something much larger. Today your phone calls travel as packets (which is why they all cost the same – there’s no such thing as a “long circuit” now), just like everything else. The Bell engineers optimized for the wrong thing. I love that this also has a flavor of “worse is better”. The Bell engineers were optimizing for “correct, complete, but complex and rigid” and the internet is more “simple and recoverable beats correct and complex”.
What actually happened was a philosophical shift about where intelligence should live. Circuit switching is a centralized control philosophy. Someone, somewhere, reserves the path before any message travels it. The network takes responsibility for delivery. The endpoints are dumb; they just send and receive. All the complexity, all the guarantee-making, lives in the infrastructure itself. This works, and it scales up to a point, and then it hits a wall, because the central system has to know everything about every connection, and that knowledge becomes impossible to manage as the network grows. (Sound familiar? This is how we build companies these days. We’ll come back to that idea)
Packet switching inverts this entirely. The network is dumb and the endpoints are smart. A router doesn’t understand the content of the packets it handles – it reads a destination address and forwards the packet one hop closer. The intelligence about what the message means, whether it arrived correctly, what to do if it didn’t – all of that lives at the edges, in the devices doing the communicating. The protocol defines what the endpoints must do. The network just moves bits.
You have seen this argument before, in a different domain. Central planning versus markets is the same disagreement. The Soviet planning apparatus tried to do for an economy what circuit switching does for a telephone network: reserve resources, guarantee outcomes, manage the whole system from the center. It failed not because the planners were stupid but because the information required to run a complex system centrally exceeds what any center can hold (it also failed because many of them were corrupt, and centralized systems are vulnerable to this, since there’s no way to build in mechanisms to correct, outcompete or otherwise reverse that corruption).
Prices, in a market, are packets. They carry information about supply and demand from the edges without anyone at the center having to understand or coordinate it. Markets are chaotic, wasteful, frequently unfair, and they consistently outperform central planning at scale for the same reason the internet outperformed the Bell System. The network always wins, eventually, because the network is where the information actually lives.
Let’s think about companies now. Companies love to do re-orgs. Or at least, they have to do them. They’re a lot of work, just like it was a lot of work to organize and change the old Bell network, and for the same reasons. Companies have to deal with the pain of organizational overhead, because to a large extent, they try to do central planning – circuit switching.
A manager, in an org chart, is a leased line. From an organizational perspective, they’re like a circuit between strategy and execution, reserved whether or not signal is flowing. The org chart is the circuit map. It tells you the paths that exist, which means it also tells you the paths that don’t. If you need to get information or work from point A to point B and there’s no line between them on the chart, you have a problem – you need to go up to a common node and back down, or you need to get someone to lay a new line. When a company needs to change how it behaves, it rewires the circuit map, which we call a reorg.
Why do we do this? This is not because companies are stupid or because the people running them lack imagination (hopefully). It’s because circuit-switched organizations are the only kind that could be managed without the infrastructure that packet-switched organizations require (which isn’t unlike what happened with the internet – we needed cheap processors to be able to build routers that could handle packets fast enough. Before we had that, we had no choice but to set up dedicated circuits).
If you can’t do the things an organization needs – observing and judging work, finding capabilities, holding people accountable – without the overhead of a fixed org chart, well, you just have to have it.
The cost of this solution is enormous and mostly invisible because it’s so normalized…
[Schillace expands on this idea…]
… When packet switching was proposed, the experts who objected most loudly were the most qualified people in the room. They were “right” in an engineering sense, but wrong in the systems sense. And they did what most people do, asking a “why not” question (against the old design and constraints) instead of a “what if” one: what if the new processors could enable a new network design?
Most people looking at AI are making the same mistake, and I predict we will see a lot of this from the orthodox “business advisor” community. I hear this from engineers and leaders already, and it sounds just like the Bell folks: You can’t guarantee accountability in a decentralized system. You can’t audit a network that routes around hierarchy. Regulators will never accept this. Sophisticated investors will raise concerns about governance.
All of these objections will be correct in the short term and beside the point in the long term. They are right from some kind of local engineering perspective but wrong from an emergent systems perspective. The question is not whether packet-switched organizations perform better on the metrics that circuit-switched organizations were built for. They won’t, at least at first, just like packet-switched networks didn’t at first. The question is whether the new architecture unlocks things the old one couldn’t do at all. And I think it will – I think we will get levels of scale, creativity and responsiveness by using these new tools to push intelligence to the edge of all kinds of organizations – not just businesses but political, social, educational and creative ones…
…There is a useful heuristic here, which is that disruptive ideas tend to produce a room that’s roughly split in half. Usually something like half the people think the idea is obviously correct (the folks asking “what if”), and half think it’s obviously wrong (the “why not” crowd). I’ve written about this kind of bifurcation before – this is the sign of something that is genuinely disruptive, and the split is between people who are rejecting it because it feels threatening, and people who have internalized the new world view and are beginning to extrapolate it…
[Schillace considers earlier, unsuccessful attempts at “packet-switched organizations,” concluding that “AI is [the] missing piece – cheap enough intelligence to put “everywhere” and enable a bunch of these ideas for real. It’s the equivalent of those cheap processors [that enabled packet switching] finally showing up, except it’s a much more complete stack arriving all at once” and that the next few years will consist in discovering the new protocols that will allow “packet-switched organizations” to succeed…]
… The Bell engineers who resisted packet switching were not, in the end, wrong about what they said. Voice quality did suffer in early VoIP, packets did get dropped a lot, and for a while, quality was worse. But they were wrong about what would matter in ten years, and catastrophically wrong about what would be possible in thirty.
Email was not a better telegram, the web was not a better encyclopedia, and streaming was not a better cable network. Each of these looks, in retrospect, like an obvious evolution, but none of them were conceivable from inside the circuit-switched world (I remember the freak out about how video was going to break even the highly scalable new internet. It wasn’t even thinkable in the circuit switched world). They required the new infrastructure before anyone could imagine what to build on it.
The organizational equivalent is similarly hard to see in advance. It is likely that packet-switched, AI-native organizations will not just do existing organizational things more efficiently, but that they will do things that are not currently possible. There might be organizations that form around specific problems and dissolve when the problem is solved, rather than persisting as structures in search of purpose, or expertise that routes to where it is needed rather than being allocated by headcount. We might have large groups with a degree of strategic flexibility and sophistication that have never existed together – we might get political or creative movements in radically different shapes because of that. We are definitely going to see an evolution in the creation, management and use of institutional memory. Training will probably look very different, as will job descriptions.
And almost certainly: we will get things we cannot name yet. Nobody in 1975 could have described Google, or Facebook, or VOIP, or even Google Docs.
The phone company’s engineers built something extraordinary. The Bell System was a genuine engineering achievement, and the people who designed it were some of the best technical minds of their era. They lost anyway. Networks are more robust, once the infrastructure to support them exists, and the right protocols to create and maintain them are adopted.
My bet is that the organizations of the future, the ones that compete and thrive, will make use of AI to build networks the same way the internet made use of those cheap processors and new protocols to build huge scale and new capabilities.
This will feel controversial, and might even be worse at first, but networks always win. The age of centrally planned organizations is coming to an end…
Eminently worth reading in full. Chaos that scales: “The Network Always Beats the Castle,” via @timoreilly.bsky.social.
See also: Benedict Evans‘ “AI, tools and transformation“:
… With every new technology, we start by using it for the work we already have, and we just do that more and faster. But then, over time, you make entirely new things. We will use AI to automate broad classes of stuff inside existing workflows and existing companies (although, as I’ve outlined above, that will be enormously more trouble and work than just giving everybody a model). But with every previous platform shift, the stuff that actually mattered was the stuff that wasn’t even possible before and that no-one even imagined…
And by way of keeping all of this in perspective, see Henry Farrell‘s “Machine god metaphors eat your brain” and Max Read‘s “Between 5 and 14 thoughts about AI and the discourse cycle.”
(Image above: source)
* Bob Dylan, “Ballad of a Thin Man” (from Highway 61 Revisited, 1965)
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As we try to peer over the horizon, we might send carefully-calculated birthday greetings to a man whose work has helped propel the advances we’re pondering: James Hardy Wilkinson; he was born on this date in 1919. A mathematician, he is best known for his pioneering work in numerical analysis and numerical linear algebra, especially in the context of high-speed digital computing. In 1970 he won the ACM Turing Award.
“Humanity is actually much more cooperative and empathic than given credit for”*…
We looked earlier at the shrinking away of public companies in the U.S., both as a product of consolidation (of operations and of ownership) and of the (potentially dangerous) growth, in their stead, of private equity. University of Michigan professor Jerry Davis has a more optimistic take…
Public corporations have been dominant institutions in the American economy since the dawn of the 20th century. Whether due to their greater efficiency or power, listed corporations spread across nearly all industries. “Capitalism” in America was synonymous with “corporate capitalism,” and the number of exchange-listed companies grew with the size of the economy.
Yet since the late 1990s, the number of listed corporations has dropped by half in the US, underwritten by new technologies that lower the cost of assembling an enterprise. Meanwhile, neglected alternatives to the public corporation both old (e.g., mutuals, cooperatives) and new (e.g., open source, platform coops) have proven surprisingly durable. Given the manifest pathologies of shareholder capitalism, the combination of these two trends may suggest pathways out of our current dilemma…
[David explains how both consolidation among listed companies and the rise of private equity have contributed to this drop, but then raises a third, more general explanation…]
A more encompassing interpretation is that information and communication technologies (ICTs) have drastically changed the basic economic calculus of what an enterprise looks like and how it might be funded. In the US context, this has meant that companies prefer “buy” to “make,” as transaction cost enthusiasts might describe it. I coined the term Nikefication to describe the process of vertical dis-integration that reconfigured American industry during the 1990s and 2000s and the options it opens for alternative forms of enterprise, described in detail in previous books…
The vertical dis-integration of the American economy was driven by Wall Street and enabled by ICTs. Ironically, the result is that the capital requirements to create and scale a business can be much lower, reducing the rationale to go public in the first place. Indeed, IPO prospectuses routinely convey that the point of the IPO is not to raise capital, but to create a market for the company’s shares to enable VCs and employees to cash out – which is not the most persuasive pitch to potential buyers, and perhaps helps account for the disastrous post-IPO performance of most new listings.
The asset-lite model means fewer public companies, but it also suggests new possibilities for non-corporate forms that may be more human-scale and democratic. Nike’s profit-driven, asset- and employee-lite model is not the only option enabled by new technologies.
By “noncorporate” I mean forms of economic organization that are not owned by outside shareholders, although they may be legally organized as a corporation. These include mutuals (where consumers or members are also the owners); cooperatives (where workers, producers, or consumers are the owners); municipal enterprises (where citizens or governments own the enterprise); nonprofits; and open source projects. These forms are far more prevalent than one might expect, and in some cases they dominate their industry (e.g., property insurance, server software).
Noncorporate forms of enterprise have proven surprisingly resilient in the US. The Fortune 500 list for 2022 includes at least a dozen mutual insurance companies, including State Farm (#44), New York Life (#71), and Nationwide (#83). The single largest shareholder of over 350 of the 1000 largest American corporations is Vanguard—also a mutual. Land o’ Lakes (#213) is an agricultural cooperative owned by its producer-members, as are Ocean Spray and Blue Diamond. Ace Hardware is a retail cooperative in which local stores can be attuned to local needs and tastes yet gain the economies of scale of a large-scale brand. Jessica Gordon Nembhard’s brilliant book Collective Courage documents that cooperative forms thrived in African-American communities for generations – often overlooked by those who find data about the economy solely through online databases. And the US is home to nearly 5000 credit unions, which by law are not-for-profits, owned by their members.
Stanford Law professor Ron Gilson once quipped that if shareholders didn’t exist, they would have to be invented. That’s not quite true: plenty of American enterprises do quite well without shareholders. Indeed, civilization itself might be better without them. As I have written elsewhere, “nearly every major societal pathology in the West today – certainly in the USA – is caused or exacerbated by profit-oriented corporations,” including the opioid epidemic, the obesity crisis, the return of nicotine addiction among the young, democracy-undermining social media, and a climate catastrophe underwritten by the fossil fuel industry. Shareholder capitalism may be a suicide pact. Conversely, cooperatives are inherently democratic and accountable…
Institutional alternatives to public corporations are well-established in the US, and in some cases they lead their industry, such as mutuals in finance and insurance. But cooperatives have historically been thin on the ground here compared to Europe. According to the Democracy At Work Initiative, there were 612 worker cooperatives in 2021 –a 30% increase over 2019, but still a tiny number.
Perhaps the digital revolution has finally created the conditions for cooperatives to thrive. Research from the pre-digital era suggests that one of the factors limiting cooperatives is, for want of a better term, the transaction costs of democracy. A lot of workers’ time spent in meetings to engage in dialogue, debate, and polling is a price that corporate dictatorships don’t have to bear. But newer tools have dramatically reduced the transaction costs of democracy: the same smartphones that enable pervasive corporate surveillance also allow worker voice at scale on a continuous basis.
It is not just transaction costs that have declined: the required assets to start a business are also much cheaper now to own or rent. Capital equipment such as Computer Numerical Control tools, powered by software, gets better and cheaper much the same way other software-powered tools do. (Compare the price of a color laser printer in 1990 to one today.) This is also true of the software required to run an enterprise. It is possible to buy a knockoff version of the enterprise software underlying the Uber app for under $10,000 – and the Drivers Coop in New York is creating a version to “franchise” the locavore driver-owned coop alternative to Uber. The ICTs that dis-integrated the corporate economy have opened space for noncorporate alternatives that might be more democratic and human-scaled.
There are reasons for optimism here. Platform cooperatives merge the benefits of coops with accessible technology, and have been especially effective in industries in which the required new capital investment is low (home cleaning, home health aides, transit). Trebor Scholz’s new book Own This! provides details on the opportunities here. Municipally- or cooperative-owned fabrication facilities can enable enterprises with limited capital to launch and thrive. If the required investment to start a business is low, then the range of alternative institutions, including coops, is correspondingly larger.
The technologies exist to create low-cost alternatives to public corporations. Maybe we are not stuck with the legacy of 20th century corporate capitalism after all…
An optimistic (and aspirational) take on what might follow the economic reign of the public company: “Is This the End of Corporate Capitalism?” from @vanishingcorp via @iftf.
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As we ponder proprietorship, we might recall that, on this date in 1933 the hospitality industry got a boost as Congress ratified the 21st Amendment to the U.S. Constitution– repealing the 18th Amendment, which had prohibited the manufacture, transportation, and sale of alcohol. Prohibition had gone into effect in 1920 in an effort to reduce crime and improve public health, but it had backfired: despite massive public investment in enforcement, there was a sharp rise in organized crime (c.f.: bootleggers like Al Capone stepping in to supply black market booze) and the emergence of a “scofflaw” attitude on the part of a public that wanted its alcohol.
“A suburb is an attempt to get out of reach of the city without having the city be out of reach”*…
In mid-twentieth century, in contrast to the noisy and diverse city, the suburbs were seen as spacious, segregated, and quiet— a much more promising state of affairs to corporations bent on expansion. American cities had been spreading out into metropolitan areas since the 19th century; but for most of that time city centers remained the hub of economic and social life. As Luise A. Mozingo explains, that began to change after World War II; residents and businesses alike began to leave…
… As a number of scholars have emphasized, the iconic suburbs of white, middle-class, nuclear families were a well-known part of this story but by no means all of it. Added to prewar suburban expansion, the rapid restructuring of postwar metropolitan areas formed a complexity of patches, spokes, and swaths of separated, specialized, and low-density land uses in the peripheral zones around older city centers, including industry, retail centers, ethnic enclaves, and working-class neighborhoods. This rapid decentralization created the conditions that were conducive to the invention of specialized suburban management facilities by large corporations.
To many privileged Americans of the 1950s and 1960s, the center city appeared to be in a state of inexorable decline. The proliferating automobile inundated the center city’s gridded 19th-century street pattern, and “congestion” seemed intractable and highly detrimental to economic activity. Increasing numbers of people of color walked the streets. Vacancies and abandoned properties were on the rise as tenants relocated to the suburbs and owners could find no replacements. New construction in the city center required homage to an ensconced and layered system of political patronage. Even then, wedging in new skyscrapers that could accommodate large corporate staffs in a single building proved difficult in blocks divided into multiple parcels of land and built out with varied buildings, including many used for industry. To redress these perceived shortcomings, the urban renewal process acquired property, removed tenants, destroyed buildings, and reparceled land in order to insert freeways, offer large lots for corporate offices, supply parking, and confine the poor to mass public housing. In the process, it took apart what remained of the vitality of the old urban core and added to the inventory of open urban lots and dysfunctional neighborhoods. The center city was noisy, diverse, crowded, unpredictable, inflexible, expensive, old, and messy — a dubious state of affairs for postwar capitalists bent on expansion.
In contrast, the suburbs seemed to warrant a sense of forward-looking optimism. At the city’s edge, an effective alliance of well-financed real estate investors, large property owners, local governments, federal loan guarantors, and utopian planners opened property for speedy development. Building along federal- and state-funded road systems that brought these large tracts of land into the economy of metropolitan regions, this alliance conceived of low-density, auto-accessed landscapes of highly specified uses with plenty of parking, and wrote these forms into stringent zoning and building regulations. Once built, these suburban expansion zones were deliberately resistant to change, with the end of producing both social stasis and secure real estate values.
The suburbs as a whole may have been diverse, but the process of building their component parts created insidious racial and class divisions. While the separation of different classes and races of home dwellers is the best-understood part of this spatial process, all kinds of workers were categorically set apart in discrete landscapes as well — corporate executives from factory labor, retail clerks from typists, electronics researchers from accountants. Hence the suburbs were predictable, spacious, segregated, specialized, quiet, new, and easily traversed — a much more promising state of affairs to corporations bent on expansion.
…
My book “Pastoral Capitalism” describes how pioneering projects established the essential landscape patterns of the corporate campus, corporate estate, and office park and how, from those few early projects, other corporations followed suit in great numbers. These landscape types became embedded in the expectations of the corporate class and could, at a glance, embody both the reality and prospect of capitalist power. Hence, the development forms have remained remarkably consistent for six decades. By the end of the 20th century, the suburbs, not the central business district, contained the majority of office space in the United States. This was a new and potent force in the process of suburban expansion…
More at “The Birth of the Pastoral Corporation.”
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As we ponder the prominence of the periphery, we might send altitudinous birthday greetings to Louis Sullivan; he was born on this date in 1856. An architect, he was hugely influential in the Chicago School, a mentor to Frank Lloyd Wright, and an inspiration to the Chicago group of architects who have come to be known as the Prairie School. He is considered by many to have been the “father of modernism” in architecture (the phrase “form follows function” is attributed to him) and (as he pioneered the steel high-rise) “the father of the skyscraper.”
Indeed, in Sullivan’s honor, this date is National Skyscraper Day.
“Bureaucracy defends the status quo long past the time when the quo has lost its status”*…
… which is one of the reasons that they’re hard to update. Kevin Baker describes a 1998 visit to the IRS Atlanta Service Center and ponders its lessons…
… the first thing you’d notice would be the wires. They ran everywhere, and the building obviously hadn’t been constructed with them in mind. As you walked down a corridor, passing carts full of paper returns and rows of “tingle tables,” you would tread over those wires on a raised metal gangway. Each work area had an off-ramp, where both the wires and people would disembark…
… The desks were covered with dot matrix paper, cartons of files, and Sperry terminals glowing a dull monochromatic glow. These computers were linked to a mainframe in another room. Magnetic tapes from that mainframe, and from mainframes all over the country, would be airlifted to National Airport in Washington DC. From there, they’d be put on trucks to a West Virginia town of about 14,000 people called Martinsburg. There, they’d be loaded into a machine, the first version of which was known colloquially—and not entirely affectionately—as the “Martinsburg Monster.” This computer amounted to something like a national nerve center for the IRS. On it programs called the Individual Master File and the Business Master File processed the country’s tax records. These programs also organized much of the work. If there were a problem at Martinsburg, work across the IRS’s offices spanning the continent could and frequently did shut down.
Despite decades of attempts to kill it, The IRS’s Individual Master File, an almost sixty-year old accumulation of government Assembly Language, lives on. Part of this strange persistence can be pegged squarely on Congress’s well-documented history of starving the IRS for funding. But another part of it is that the Individual Master File has become so completely entangled in the life of the agency that modernizing it resembles delicate surgery more than a straightforward software upgrade. Job descriptions, work processes, collective bargaining agreements, administrative law, and technical infrastructure all coalesce together and interface with it, so that a seemingly technical task requires considerable sociological, historical, legal, and political knowledge.
In 2023, as it was in the 1980s, the IRS is a cyborg bureaucracy, an entangled mass of law, hardware, software, and clerical labor. It was among the first government agencies to embrace automatic data processing and large-scale digital computing. And it used these technologies to organize work, to make decisions, and to understand itself. In important ways, the lines between the digital shadow of the agency—its artificial bureaucracy—and its physical presence became difficult if not impossible to disentangle….
Baker is launching a new Substack, devoted to exploring precisely this kind tangle– and what it might portend…
This series, called Artificial Bureaucracy, is a long-term project looking at the history of government computing in the fifty-year period between 1945-1995. I think this is a timely subject. In the past several years, promoters and critics of artificial intelligence alike have talked up the possibility that decision-making and even governance itself may soon be handed over to sophisticated AI systems. What draws together both the dreams of boosters and the nightmares of critics is a deterministic orientation towards the future of technology, a conception of technology as autonomous and somehow beyond the possibility of control.
These visions mostly ignore the fact that the computerization of governance is a project at least seventy years in the making, and that project has never been determined, in the first instance or the last, primarily by “technological” factors. Like everything in government, the hardware and software systems that make up its artificial bureaucracy were and are subject to negotiation, conflict, administrative inertia, and the individual agency of its users.
Looking at government computing can also tell us something about AI. The historian of computing, Michael Mahoney has argued that studying the history of software is the process of learning how groups of people came to put their worlds in a machine. If this is right—and I think it is—our conceptions of “artificial intelligence” have an unwarranted individualistic bias; the proper way to understand machine intelligence isn’t by analogy to individual human knowledge and decision-making, but to methods of bureaucratic knowledge and action. If it is about anything, the story of AI is the story of bureaucracy. And if the future of governance is AI, then it makes sense to know something about its past…
Is bureaucracy the future of AI? Check it out the first post in Artificial Bureaucracy, from @kevinbaker@mastodon.social.
* Laurence J. Peter
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As we size up systems, we might recall that it was on this date in 1935 that President Franklin D. Roosevelt signed the Social Security Act. A key component of Roosevelt’s New Deal domestic program, the Act created both the Social Security program and insurance against unemployment.
“People in any organization are always attached to the obsolete – the things that should have worked but did not, the things that once were productive and no longer are”*…
Ed Zitron argues that America has too many managers, and managers misbehaving at that…
In a 2016 Harvard Business Review analysis, two writers calculated the annual cost of excess corporate bureaucracy as about $3 trillion, with an average of one manager per every 4.7 workers. Their story mentioned several case studies—a successful GE plant with 300 technicians and a single supervisor, a Swedish bank with 12,000 workers and three levels of hierarchy—that showed that reducing the number of managers usually led to more productivity and profit. And yet, at the time of the story, 17.6 percent of the U.S. workforce (and 30 percent of the workforce’s compensation) was made up of managers and administrators—an alarming statistic that shows how bloated America’s management ranks had become.
The United States, more than anywhere else in the world, is addicted to the concept of management. As I’ve written before, management has become a title rather than a discipline. We have a glut of people in management who were never evaluated on their ability to manage before being promoted to their role. We have built corporate America around the idea that if you work hard enough, one day you might become a manager, someone who makes rather than takes orders. While this is not the only form of management, based on the response to my previous article and my newsletters on the subject, this appears to be how many white-collar employees feel. Across disparate industries, an overwhelming portion of management personnel is focused more on taking credit and placing blame rather than actually managing people, with dire consequences.
This type of “hall monitor” management, as a practice, is extremely difficult to execute remotely, and thus the coming shift toward permanent all- or part-remote work will lead to a dramatic rethinking of corporate structure. Many office workers—particularly those in industries that rely on the skill or creativity of day-to-day employees—are entering a new world where bureaucracy will be reduced not because executives have magically become empathetic during the pandemic, but because slowing down progress is bad business. In my eyes, that looks like a world in which the power dynamics of the office are inverted. With large swaths of people working from home some or all of the time, managers will be assessed not on their ability to intimidate other people into doing things, but on their ability to provide their workers with the tools they need to measurably succeed at their job.
In order to survive, managers, in other words, will need to start proving that they actually do something. What makes this shift all the more complicated is that many 21st-century, white-collar employees don’t necessarily need a hands-on manager to make sure they get their work done…
The pandemic has laid bare that corporate America disrespects entry-level workers. At many large companies, the early years of your career are a proving ground with little mentorship and training. Too many companies hand out enormous sums to poach people trained elsewhere, while ignoring the way that the best sports teams tend to develop stars—by taking young, energetic people and investing in their future (“trust the process,” etc.). This goes beyond investing in education and courses; it involves taking rising stars in your profession and working to make them as good as your top performer.
In a mostly remote world, a strong manager is someone who gets the best out of the people they’re managing, and sees the forest from the trees—directing workers in a way that’s informed by both experience and respect. Unfortunately, the traditional worker-to-manager pipeline often sets people up for inefficiency and failure. It’s the equivalent of taking a pitcher in their prime and making them a coach—being good at one thing doesn’t mean you can make other people good at the same thing. This is known as the Peter principle, a management concept developed by Laurence J. Peter in the late ’60s that posits that a person who’s good at their job in a hierarchical organization will invariably be promoted to a position that requires different skills, until they’re eventually promoted to something they can’t do, at which point they’ve reached their “maximum incompetence.” Consistent evidence shows that the principle is real: A study of sales workers at 214 firms by the National Bureau of Economic Research found that firms prioritize current job performance in promotion decisions over whether the person can actually do the job for which they’re being considered. In doing so, they’re placing higher value on offering the incentive of promotion to get more out of their workers, at the cost of potentially injecting bad management into their organization.
What I’m talking about here is a fundamental shift in how we view talent in the workplace. Usually, when someone is good at their job, they are given a soft remit to mentor people, but rarely is that formalized into something that is mutually beneficial. A lack of focus on fostering talent is counterintuitive, and likely based on a level of fear that one could train one’s own replacement, or that a business could foster its own competition. This is a problem that could be solved by paying people more money for being better at their job. Growing talent is also a more sustainable form of business—one that harkens back to the days of apprenticeships—where you’re fostering and locking up talent so that it doesn’t go elsewhere, and doesn’t cost you time and money to have to recruit it (or onboard it, which costs, on average, more than $4,000 a person). Philosophically, it changes organizations from a defensive position (having to recruit to keep up) to an offensive position (building an organization from within), and also greatly expands an organization’s ability to scale affordably…
The problem is that modern American capitalism has equated “getting the most out of someone” with “getting the most hours out of them,” rather than getting the most value out of them. “Success,” as I’ve discussed before, is worryingly disconnected from actually succeeding in business.
Reducing bureaucracy is also a net positive for the labor market, especially for young people. Entry-level corporate work is extremely competitive and painful, a years-long process in which you’re finding your footing in an industry and an organization. If we can change the lens through which we view those new to the workforce—as the potential hotshots of the future, rather than people who have to prove themselves—we’ll have stronger organizations that waste less money. We should be trying to distill and export the talents of our best performers, and give them what they need to keep doing great things for our companies while also making their colleagues better too.
All of this seems inevitable, to me, because a remote future naturally reconfigures the scaffolding of how work is done and how workers are organized. The internet makes the world a much smaller place, which means that simple things such as keeping people on task don’t justify an entire position—but mentorship and coaching that can get the best out of each worker do.
Hopefully we can move beyond management as a means of control, and toward a culture that appreciates a manager who fosters and grows the greatness in others.
The pandemic has exposed a fundamental weakness in the system: “Say Goodbye to Your Manager,” from @edzitron.
* Peter Drucker
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As we reorganize, we might recall that it was on this date that Henri Giffard made the first first powered and controlled flight of an airship, traveling 27 km from Paris to Élancourt in his “Giffard dirigible.”
Airships were the first aircraft capable of controlled powered flight, and were most commonly used before the 1940s, largely floated with (highly-flammable) hydrogen gas. Their use decreased as their capabilities were surpassed by those of airplanes- and then plummeted after a series of high-profile accidents, including the 1930 crash and burning of the British R101 in France, the 1933 and 1935 storm-related crashes of the twin airborne aircraft carrier U.S. Navy helium-filled rigids, the USS Akron and USS Macon respectively, and– most famously– the 1937 burning of the German hydrogen-filled Hindenburg.
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