Begin with the strategic orientations many have with respect to resilience and anticipation as distinct from each other. Resilience is said to be optimizing the ability to absorb or rebound from shocks, while minimizing the need to anticipate these shocks ahead of time. Anticipation, in contrast, is to optimize the ability to plan ahead and deal with shocks before they happen, while minimizing having to cope with shocks when they do occur. Consider the resulting Table 1:

System designers would like managers to be both optimally anticipatory and resilient at the same time—indeed that managers maximize their “readiness” for whatever arises, whenever. These all-embracing demands can, however, reduce the managers’ much-needed capacity to balance anticipation and resilience case by case.
More, the ideal of stabilizing the task environment so as to minimize the need for both anticipation and resilience—a common enough premise (promise?) of macro-designers—is as impossible to realize as it is irresponsible to promote, when the aim is high reliability in real-time operations.
Explain why being optimally anticipatory and resilient does not encompass the universe of “case-by-cases”. Why is it that we would define “optimality” here in terms of the undifferentiability of cases or what might otherwise be called “normal operations”? Indeed, is it not true that if achieving optimality is possible (it must clearly be desirable!), then there would be no unanticipated “contingency” that nor a contingency from which we could not recover? On that basis, is there ever a deviation from normal baseline operations? That is, are “optimality” and “case-by-case treatment” mutually exclusive states or conditions? Contrapositively, why would there ever be a deviation from optimality if it could be achieved? How would being minimally anticipatory and resilient represent the paradoxical designation “ideal, but impossible” when being minimally anticipatory and resilient appears to be both highly possible and highly typical!
LikeLike