Hi Marco,
I like your concept of modeling coordination behaviors taken by an enterprise over time. The why of those behaviors, eg causality, is critical imo. Specifically, what inputs or stimuli caused specific decisions or paths taken by individuals within the enterprise? In the stimuli category, exogenous shocks like wars may present a sparse data problem. Meanwhile, not all wars have matching ripple effects, like forced-inflation across broad categories of goods for the global population. Geopolitics and its toolkit of embargoes, sanctions, tariffs, blockades, bans, etc., adds more exogenous shocks to the mix and a similar sparse data problem.
Get Dirk Davis’s stories in your inbox
Join Medium for free to get updates from this writer.
Thus when the model seeks a pattern to procurement decisions taken by the global supply chain function of an enterprise, does it "see" the surface of inputs and stimuli that led to a particular set of decisions during normal, halcyon times (most of the time) versus unusual times impacted by exogenous shocks, which like extreme weather are happening more frequently?
The hospital system that sources liquid helium from bottlenecked-Qatar as the critical cooling agent for its life-saving MRI machines will likely change that procurement behavior going forward.
So to crystallize, would your models, beyond finding patterns in the "what" (coordinated actions taken in the real world), also map those actions taken to specific blends (I think of them as surfaces, geometrically) of inputs or stimuli that fed particular decisions taken at the individual, group and/or aggregated enterprise level?
