Use of Optimisation Algorithms in Corporate Internal Planning Processes

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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."