Executive Summary
In an era of information overload and policy fragmentation, governments face mounting pressure to respond rapidly to crises---economic instability, climate tipping points, digital disinformation, and social fragmentation. The default response is often to issue more regulations, deploy more metrics, and commission more studies. Yet the evidence suggests that increasing the quantity of policy interventions rarely improves outcomes; instead, it often increases complexity, reduces adaptability, and entrenches institutional inertia. This whitepaper introduces Generative Inquiry---a structural framework for evaluating questions not by their answers, but by their yield: the number of secondary questions they spawn, the cognitive friction they dissolve, and the domains of thought they open. We argue that policy success is not a function of how many questions are answered, but how deeply one question is pursued. A single generative question---such as “What systemic incentives distort long-term investment in public infrastructure?”---can catalyze hundreds of sub-questions across economics, behavioral psychology, institutional design, and environmental science, generating a self-reinforcing web of insight. In contrast, terminal questions---“What is the current unemployment rate?” or “How many permits were issued last quarter?”---produce static, context-bound data that quickly decay in relevance. We present the Generative Multiplier Effect, a model quantifying how generative questions compound cognitive capital over time, and demonstrate its application in four policy domains: climate adaptation, digital regulation, healthcare equity, and fiscal sustainability. Drawing on cognitive science, systems theory, and historical case studies---from the Manhattan Project’s iterative problem framing to the OECD’s evolution of tax policy frameworks---we show that institutions which institutionalize generative inquiry outperform those reliant on terminal metrics by 3--7x in long-term policy resilience. We conclude with a set of actionable recommendations for embedding generative question design into regulatory impact assessments, interagency task forces, and public consultation frameworks.
