The institutions built for a predictable world fail in an unpredictable one. Designing institutions for uncertainty requires a different approach than designing for stability.
The Stability Design Assumption
Most institutional design proceeds from a stability assumption: the institution is designed for the operating conditions that its designers anticipate, with adjustments for the range of variation that the designers expect the institution to face. The stability assumption works adequately for the institutions that face a predictable range of operating conditions and fails for the institutions that face the genuinely novel, the genuinely disruptive, and the genuinely unprecedented. The COVID-19 pandemic demonstrated that health systems designed for the anticipated range of public health challenges were not designed for a global pandemic of the specific character that COVID-19 presented. The 2008 financial crisis demonstrated that financial regulatory systems designed for the anticipated range of financial market failures were not designed for the specific failure mode that the shadow banking system produced. In each case, the stability assumption produced a design that was adequate for the anticipated and inadequate for the actual.
Designing institutions for uncertainty requires replacing the stability assumption with the resilience principle: the institution should be designed not for the specific conditions anticipated but for its capacity to function effectively across the full range of conditions that could plausibly occur, including conditions that are currently unanticipated. The resilience principle implies investment in adaptive capacity — in the monitoring systems that detect novel conditions early, the decision processes that can be reconfigured quickly when conditions change, and the redundancy that provides operational continuity when primary systems fail.
The institution designed for stability will perform adequately in stable conditions and fail in novel ones. The institution designed for uncertainty will perform somewhat less efficiently in stable conditions and significantly better in novel ones. The cost of the difference is visible only in the crises that test the design — which is why the investment in uncertainty-designed institutions is consistently underprovided until the crisis that reveals its value.
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