Optimal Planning and the Menace of Bureaucratisation
* Article: Automating away the centre? Optimal planning and the menace of bureaucratisation. By Max Grünberg. Competition & Change, November 2023
URL = https://journals.sagepub.com/doi/full/10.1177/10245294231218868
"the following paper begins with a first part providing a historical introduction to optimal planning, while also briefly sketching classical Soviet command planning and its shortcomings."
Note MB: undoubtedly one of the best 'total' histories of production optimization through planning and algorithms.
Abstract
"Within the wider discourse on economic planning, this paper critically interrogates practical challenges in applying optimisation algorithms to achieve allocative efficiency on the scale of national economies. In questioning whether contemporary information technology solves the shortcomings of Soviet command planning, the paper provides a historical introduction to optimal planning and engages with four fundamental problems optimal planners would face, namely: the concern of computational complexity, the challenge of generating the economic data necessary for the constitution of such a system, the issue of reconciling a static optimum with the dynamism of real economies, and ultimately the relation of optimisation solvers to a hierarchy of ends. Besides epistemic concerns, the greatest risk of such a planning framework is constituted by the possibility of a slow descent into an authoritative system that would mirror the Soviet experience because of its reliance on bureaucratic institutions to make this machine work."
(https://journals.sagepub.com/doi/full/10.1177/10245294231218868)
Excerpts
See also:
The Use of Optimisation Algorithms in Corporate Internal Planning Processes
Max Grünberg:
"One such method is mathematical optimisation. Today all successful companies deploy some form of optimisation algorithm in intra-planning processes, whether it is for supply chain scheduling, to determine warehouse layouts, cargo fleet routing, or for the optimal use of machinery. But can such a technology, which has proven its efficacy on the enterprise level, be applied to work in the interest of workers within a post-capitalist society collectively planning production? For many critical observers, such algorithms are lumped together with other algorithmic management technologies and seem merely to be the cause of alienation by intensifying labour. However, an economic system that wishes to reduce working hours and avert ecological collapse by reducing resource consumption, through means other than austerity, would also have to deal with such issues as the optimal use of resources. This is also why the coordinative challenge of a socialist mode of production remains to transcend the allocation through the price mechanism with a more rational form of distributing scarce resources. At stake is whether mathematical approaches can assist in the coordination of material flows to realise a post-capitalist future.
To better understand this fundamental challenge and to grasp why optimisation algorithms are even discussed today it might be helpful to conceptualise the economy to be in search of allocative efficiency in order to realise the greatest possible satisfaction of needs. This search space is of course restricted by natural and social constraints and has a dynamic and static dimension to it. Despite their practical entanglement, one can here think of dynamics as dealing much more with the uncertainty of future changes, while statics relate more to the present state of the economy. A short example can better illustrate this. Say a given economy has the capacity to produce a million units of a certain microprocessor, but total demand exceeds this quantity. At this point, the dynamic planning decision could be made to increase supply or develop a new type of chip, both requiring investment in new capital stock such as lithography machines. If one wishes to hand over such investment decisions neither to the market and financial speculation nor to bureaucrats but to socialise the investment function then this economy would require what Aaron Benanav (2020) calls democratic ‘planning protocols’, or what Maxi Nieto (2021) refers to as ‘investment councils’. Yet, to implement this, it will still require allocative decisions in the present that in many cases will take place under scarcity. Required resources for a new semiconductor fabrication plant might also be demanded elsewhere in the economy and limiting factors will likely not allow to satisfy all productive demands.2 The same applies to our processors. Until production is ramped up to meet demand, one would face a state of shortage, requiring again decisions on where this scarce good is best allocated. While in their opposition to finance capital, there seems to be a rough consensus among socialists on the dynamic aspects of planning towards the democratisation of the investment function, the widest dissent can be encountered in solving this static allocation problem, which comes down to the question of who gets what in the economy at a given point in time."
(https://journals.sagepub.com/doi/full/10.1177/10245294231218868)
Five general Trajectories for Dealing with Allocative Efficiency
Max Grunberg:
"Who gets what in the economy at a given point in time?
So far, our imaginative space seems to be constrained to five general trajectories of dealing with the static aspect of allocative efficiency.
The first trajectory for solving this problem is the status quo of the market order. It is the price mechanism still present in market socialist proposals, which steers the flow of scarce resources into the direction of the most profitable enterprises. As a point of departure, this is what socialists still dedicated to the idea of an economic plan wish to transcend.
Second, following on from Soviet command planning, these allocative decisions could be taken up again by bureaucrats. Marx disparagingly called this the ‘papacy of production’, and – after the experience of actually existing socialism – any such return to economic despotism seems to present the least desirable alternative.
Third, as an inversion of such bureaucratic centralism, one could agree to grant the immediate producers full control over the allocation of the products of their labour, which would amount to an equally irrational dictatorship of the periphery, or an anarchism without markets, due to their particular interests and limited scope of societal needs.
A fourth trajectory, favoured by most anti-authoritarians today, would be to solve this problem through a deliberative negotiation process involving everyone affected to reach consensus. Based on voluntarist principles, it is the utopian belief that the allocative efficiency of a world economy would harmoniously emanate from the multitude. In a slightly more bureaucratic form, this hope is articulated today in Pat Devine’s (1988) call for negotiated coordination. Even in the unlikely case that consensus on the allocation of millions of scarce goods could be achieved among the participants4 by horizontal means with a myriad of meetings taking place simultaneously, each individual allocation decision would have cascading effects within the economy resulting in a recursive loop of permanent renegotiation, which would paralyse the economy in an inconclusive state and reinforce desperate calls for a rationing by price or bureaucratic hierarchies to resolve persistent conflicts.
Finally, the fifth and last resort humanity seems to have for coming to terms with the complexity of this allocative task is some form of algorithmic mediation."
(https://journals.sagepub.com/doi/full/10.1177/10245294231218868)