People's Republic of Walmart

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* Book: Leigh Phillips and Michal Rozworski. The People's Republic of Walmart: How the World's Biggest Corporations are Laying the Foundation for Socialism. Verso (Jacobin), .

URL = ebook


From the publisher:

Since the demise of the USSR, the mantle of the largest planned economies in the world has been taken up by the likes of Walmart, Amazon and other multinational corporations

For the left and the right, major multinational companies are held up as the ultimate expressions of free-market capitalism. Their remarkable success appears to vindicate the old idea that modern society is too complex to be subjected to a plan. And yet, as Leigh Phillips and Michal Rozworski argue, much of the economy of the West is centrally planned at present. Not only is planning on vast scales possible, we already have it and it works. The real question is whether planning can be democratic. Can it be transformed to work for us?

An engaging, polemical romp through economic theory, computational complexity, and the history of planning, The People’s Republic of Walmart revives the conversation about how society can extend democratic decision-making to all economic matters. With the advances in information technology in recent decades and the emergence of globe-straddling collective enterprises, democratic planning in the interest of all humanity is more important and closer to attainment than ever before."


"Phillips and his co-author, Canadian labour organiser Michal Rozworski, have outdone themselves with this volume.

The two are addressing themselves to the socialist calculation debate, which raged through Austrian economic circles a century ago, with market-focused economists like Ludwig von Mises arguing that it was technically impossible to calculate an efficient allocation of goods in a large, industrial society, and that markets alone -- as a kind of distributed calculation engine -- could solve the problem of getting goods to the people who could make best use of them.

Von Mises won the argument in the 1920s, but a funny thing happened on the way to the 2020s: we are now surrounded by companies and organisations that within the same order of magnitude as the Soviet economy at its apex, which undertake breathtakingly efficient allocations of goods and resources, and all without markets, running as command economies.

You've heard of these comparable-to-the-Soviet-Union command economies: Amazon. Walmart. The Pentagon. There are many more. Each one is an existence-proof of the idea that markets are not needed for mass-scale allocation. What's more, the counterexamples, like Sears -- which implemented internal markets at the insistence of an ideology-blinded libertarian CEO -- show that markets are much worse at allocating resources than the computational command economies used in other enterprises.

The upshot of this is that to the extent that the Soviet Union was crippled by inefficient allocation, that is no longer the problem it once was. It's that we can imagine something as efficient and convenient as Walmart or Amazon without CEOs, shareholders or exploited workers, bringing all the bounties of late-stage capitalism without its pathologies.

The upshot is that fully automated luxury communism isn't just science fiction: it's a going concern with real evidence on the ground.

Market purists argue that we must tolerate all the evils of markets -- exploitation, inequality, the endangering of our biosphere -- because markets are the only conceivable force that can accomplish efficient allocation in our highly technical world. Deep greens take them at their word and say, fine, let's get rid of technology and return to a kind of agrarian feudalism.

Both of them are buying into Thatcher's maxim that "there is no alternative." But Phillips and Rozworksi are proposing an alternative: bright green, high-tech societies where markets are useful tools for solving the odd problem, but where allocation is primarily accomplished by the preferred means of Jeff Bezos and Sam Walton, but to the benefit of the many, not the few." (


The Left and Big Data

James Meadway:

"The case for democratic planning has recently been restated by Leigh Philips and Michal Rozworski in their very readable The People’s Republic of Walmart. Their argument hinges on the presence of ‘islands of planning’ in a sea of market competition in the form of the vast operations of corporations. The possibilities of using the technologies and organisation mobilised by the likes of Walmart for more obviously human ends than is the animating thread of their book – just as was observing the prodigious efforts of capitalist states planning production for total war for earlier generations of socialists.

In particular, fast computers and cheap digital sensors open up the prospect of continuous, real-time planning of the economy in ways that have never been feasible before. The ‘socialist calculation problem’ of old – that society was too complex to plan everything – appears solved. Yet this may not be an entirely desirable solution. In the World Review of Political Economy, Bibin Yang and Xiaoyan Li have recently proposed the implementation of a planned economy using real-time Big Data to allow immediate adjustments to plans, creating a hybrid ‘market-based, plan-driven’ system. Like Philips and Rozworksi, they suggest that major corporations – particularly the platform companies like Alibaba and Amazon – already operate on such a model. All that is needed, they suggest, is for the state to replicate such functions and expand its sphere of planning. Jack Ma, founder of Alibaba, has suggested that his company is a stepping stone to a planned economy: ‘with access to all kinds of data, we may be able to find the invisible hand of the market.’

There are two important points here. The first is that ‘finding the invisible hand’, whilst a striking metaphor, is very much in line with conventional economics thinking on the relationship between planning and the market. The ‘ideal’, welfare-maximising distribution of societies’ resources, as selected by a perfectly benevolent planner, is identical to the ‘ideal’, welfare-maximising distribution of societies’ resources as selected by an entirely free market, in the standard proof of the desirability of a market society. The presence of Big Data turns this hypothetical social planner into a real possibility, overcoming the standard free market criticism of planning, exemplified in the work of Von Hayek – that the information needed to perform the task, in any reasonably complex society, is too great to be performed. We have not stepped outside the boundaries that neoclassical economics usually establishes for the problems it seeks to address.

Second, if we do look beyond those boundaries, we are back in the world of a state-capital fusion. ‘All kinds of data’ has deep implications: it could include, for instance, social credit scoring, as applied in China (and of which the recently-departed Dominic Cummings was something of an enthusiast). It is not obvious that this should be acceptable. Francis Spufford’s semi-fictional account of the development of Soviet planning, Red Plenty, makes exactly this point: that even with faster computers and more data, the demands of a (presumed) benevolent planner might well be rejected by those expected to follow its edicts. (In the book, changes in the prices of food, intended to produce a fairer distribution according to the plan, provoke riots.) We would have to exhibit a very high degree of trust in the planner to simply allow for its diktat to set the course of our lives.

Arguably, via the mass data-collection empires of Big Tech, we do display that sort of trust, happily handing over to them unimaginable volumes of information about ourselves and our relationships. We might read this as a challenge to Graeber’s vision of reciprocity: that a version of free exchange – even a gift relationship – can be established with an entirely faceless bureaucracy subject to no obvious legal or democratic or even, if we are not careful, human restraints. The latter point is particularly important with AI that can teach itself and devise new rules for us, as is already occurring. We are implicitly offering our consent to a process that is running ahead of us – and one which, under Covid-19, has accelerated markedly.

There are two profound side-effects to the presence of mass data that the Left has not yet got its collective head around. The first is the gradual disappearance of consumer-facing markets from our lives. Facebook is, as it says on the homepage, ‘Free, and it always will be.’ No exchange of money takes place between the Facebook consumer and the Facebook company, as in a more conventional market operation. Instead, Facebook monetises the data it gathers and sells it elsewhere. But this is a challenge to how we conventionally think about capitalism, and certainly how we conventionally try to register its activities. Constructing GDP becomes harder when there is less being obviously traded, and the location of where ‘value’ is realised becomes harder to pin down. This is a process of capital-led decommodification, at least for its end-products; but the corollary recommodification of data is also still poorly understood. Katharine Pistor has recently explored some of the implications. In ‘Rule by Data: The End of Markets?’, she speculates persuasively that the data will likely displace markets and law as the dominant organising principle of human societies. We are already seeing the displacement of markets; law is further down the line. This process runs counter to the neoclassical expectation that the improvement of markets would lessen the dependence on law and reduce the role of firms in the economy. In fact, Pistor suggests, we have seen the reduction of transactions costs to bare minima via digitisation, but, alongside and as a direct consequence of this, the massive growth of ‘corporate behemoths’ in the form of the data giants. Law is being bent towards their will, directly in the sense that they are very powerful lobbyists for specific legal structures, and indirectly (and ultimately more consequential) in that their actions create new structures enjoying a form of legality in advance of any formal lawmaking.

There are three sets of responses to this. One is to attempt to reassert market rule, as with the various anti-trust efforts against Big Data. A second is to reassert law, as in the various attempts to regulate and control data. Both of these look doomed to fail, at least on their initial terms: the former looks set to, at best, reproduce multiple versions of problematic institutions; the second merely hands over more control to a central authority. Both ‘market sovereignty’ and ‘state sovereignty’ fail when set against the need to bring data under human control. This will not stop their political protagonists arguing for either: a reassertion of neoliberal politics lies in one direction, and potentially ugly nationalism in the other. An anti-egalitarian political right can exist on the basis of either (or, quite possibly, some combination of both at once).

Pistor favours a third option: a reassertion of the fundamental reciprocity – the ‘primitive communism’ – in allowing smaller collectivities of data users and producers to form, then seeking their protection through the use of ‘data trusts’. These would be a mixed form of institution – potentially (if the trustees wished it) operating in a market, enjoying a legal protection, but constituted on the basis of a collective interest. (I have recently discussed such trusts in Creating a Digital Commons.)

The pandemic has shown us how a collective interest can run far ahead of the state: judging by transport usage statistics, the ‘lockdown from below’ was beginning well ahead of the laggardly government response. The range of new governmental powers have not in general been directly used, because the wider social determination of a shared interest in maintaining social distancing, wearing a mask, and so on, has been very solid. The moves towards authoritarian control under Covid-19 – despite the hysterics from the pro-virus right – have occurred out of sight, in the collection, management and analysis of data." (

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