There is a second set of systemic insights that is equally disruptive of the usual way we think about and reason through challenging (often VUCA-Plus) issues. These insights come from the emerging interdisciplinary field of study that is often labeled Complexity Theory. This field focuses on systems that are not just complicated (many parts), but also complex (many interdependent parts)—and it is in their complexity that many systems become chaotic (Miller and Page, 2007). While there are many troubling and unanticipated insights emerging from this field, the one that has received the most public attention is the Butterfly Effect. First offered by Edward Lorenz in his meteorological research, this effect concerns our inability to offer valid predictions regarding the outcome of complex events given that a single (often quite small) event somewhere in the world (the fluttering of a butterfly’s wings) can have a profound, widespread impact. It is because complex systems contain many interdependent parts that one small part can have a major impact on the entire system. Something like this effect might be operating in the case of COVID-19 and other epidemics.
We know, for instance, that the spread of SARS-1 in 2003 can be traced back primarily to one gentleman in China (Christakis, 2020, p. 37). This man, who made his living as a fishmonger, seems to have been a super-spreader of this virus. He was the butterfly of SARS-1. Similarly, the major culprits in the vast spread of Spanish Flue in 1918 were the citizens of Philadelphia. They ignored the warning signs and engaged in many events (including parades) that led to the spread of this virus (that had come to Philadelphia from a merchant ship) (Christakis, 2020, p. 72). Philadelphia was also a butterfly. On the one hand, the Fishmonger Effect came from the actions of one man, while the Philadelphia Effect came from the actions of an entire urban population. Both of these effects could be operating in the spread of COVID-19.
Jay Forrester, the original architect of System Dynamics, often declared: “don’t just do something—stand there!” One of Forrester’s esteemed students and colleagues, Donella Meadows (2008, p. 171) has put it this way: “[There is a broad-based and compelling tendency] to define a problem not by the systems’ actual behavior, but by the lack of our favorite solution.” Meadows (2008, pp.171-172) goes on to describe a typical decision-making process:
Listen to any discussion in your family or a committee meeting at work or among the pundits in the media, and watch people leap to solutions, usually solutions in “predict, control or impose your will”, without having paid attention to what the system is doing and why it’s doing it.
