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Time, Systems, and Subsystems

Over the past few years, a global integration of people, production, products, and services has evolved. This is a very tightly coordinated system that allowed work to move across space more frictionlessly than ever before. It relied on people moving across countries. It built sectors that relied on one another, driven by market forces.

One of the truly interesting things is that it permitted integration of subsystems that move very slowly to be served and be served by sectors that move much more quickly. So, slow-moving institutions, like universities, could provide graduates to the technology sector that permitted its rapid development. Even though it takes four years to produce a new computer science graduate with a bachelor’s degree, the interface between slow moving university curricula and technology companies coped. Tech companies provided instruction in the Microsoft way, the Amazon way, or the Google way, that permitted ingestion of talent into fast changing companies. The linkages between the academic sector and the technology sector thrived.

From the other side, the technology sector helped import digital operations to governments. Slow-moving institutions and fast-moving institutions found a way to stay integrated and co-dependent.

One mental image of this is a set of gears that interlock but move at very different revolutions per minute. They are codependent; they help one another and need one another.

Enter SARS-CoV-2 that produces COVID-19.

Many have noted that within a matter of days and weeks the connections among the subsystems broke down. When locales closed down activities or when the epidemic hit a business with a fury, the people supplying materials and services to another sector stayed home; linkages among sectors were broken. We saw farmers destroy crops and milk products because they had no transportation to market. We saw hospitals without protective gear because international factories and international shipping were curtailed. The speed of the effects on connections among subsystems was astonishing.

Of interest in this view of sectors that are slow moving but connected to ones that are fast moving is that the sectors with slow moving environments seemed to suffer most. With COVID-19, a fast-moving disrupter was introduced that affect all persons in all sectors. But fast moving sectors have a built-in advantage in those situations because they tend to have more advanced adaptive characteristics. Slow-moving sectors struggled.

I’m told that in some biological systems, a subsystem linked to another that becomes hostile attempts to isolate itself, in order to assure its survival. One interpretation of the rise of nationalism across the globe might be linked to a similar tendency in human-directed systems, the nation state whose populace views interdependencies as hostile to its welfare attempts to isolate and become more self-sufficient.

Of course, one cannot overnight move to self-sufficient isolates after years of developing a globally interdependent design, production, supply, dissemination, and consumption system. Fast-moving social movements or global epidemics, once launched, interact with slow-moving systems that have difficulty changing quickly. Friction in the system of gears mentioned above occurs. Such friction can harm interconnections but also break individual gears.

Given the penetration of globalization, the slow-moving subsystems can little afford to isolate. Change, occurring more rapidly than their designs anticipated, will occur. However, when leaders in slow-moving subsystem recognize the heightened pace of change, they can prompt adaptation without delinking from other systems. When they can do so, they can achieve the continued fruits of interdependence.

One thought on “Time, Systems, and Subsystems

  1. One way to perform risk analysis so as to have a “heads up” concerning the likely economic results from various system breakdowns is to employ breakdown simulations using Social Accounting Matrix (SAM) model simulations for predicting short-term results and Computable General Equilibrium (CGE) model simulations for predicting long-term results (i.e. results that include the possibility of price adjustments as part of the results). Employing such simulations not only provides warnings about likely consequences (including which economic sectors and demographic groups are likely to be affected), it also suggests which economic linkages are candidates for being modified in advance (and which demographic groups are candidates for “first aid”) to lessen negative results of specific system breakdowns. Country A closes borders for some reason (pandemic, for example) — SAM and CGE analysis has suggested likely results and has suggested linkages in need of risk abatement measures (and has identified demographic groups for which “first aid” should have been prepared) for Country A as well as for Country B, Country C, …

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