Resilience Analytics
A Guide to Implementation
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Beschreibung
How much disruption can your system absorb before it stops doing its job? Few organizations can answer that question with a number, and many have quietly stopped expecting to. This book argues that they should expect to, and shows how. Trump and Linkov draw together the working tools of resilience science, from structured expert judgment and capability scorecards to network models, dynamic simulation, and decision analysis, into a single methodology that scales to an organization’s stakes and budget. Readers learn to describe a system the way disruptions actually experience it, across its equipment, its data, its people, and its relationships; to find the weak points whose failure spreads; and to compare competing investments in units a budget meeting can argue about. The book is equally candid about the numbers themselves, showing where resilience metrics deserve trust, where they mislead, and how to tell the difference. For readers who encountered the case for resilience in The Science and Practice of Resilience, this volume carries the idea into daily analytical practice. Risk analysts, infrastructure engineers, emergency managers, resilience planners, supply chain and cybersecurity professionals, defense and national security analysts, and public policy officials responsible for critical systems will find this an ideal resource.
How much disruption can your system absorb before it stops doing its job? Few organizations can answer that question with a number, and many have quietly stopped expecting to. This book argues that they should expect to, and shows how. Trump and Linkov draw together the working tools of resilience science, from structured expert judgment and capability scorecards to network models, dynamic simulation, and decision analysis, into a single methodology that scales to an organization’s stakes and budget. Readers learn to describe a system the way disruptions actually experience it, across its equipment, its data, its people, and its relationships; to find the weak points whose failure spreads; and to compare competing investments in units a budget meeting can argue about. The book is equally candid about the numbers themselves, showing where resilience metrics deserve trust, where they mislead, and how to tell the difference. For readers who encountered the case for resilience in The Science and Practice of Resilience, this volume carries the idea into daily analytical practice. Risk analysts, infrastructure engineers, emergency managers, resilience planners, supply chain and cybersecurity professionals, defense and national security analysts, and public policy officials responsible for critical systems will find this an ideal resource.
Provides the actual analytical methods that convert resilience principles into defensible quantitative outputs Shows how the disruptions of 2020–2025 reveal cascading, cross‑domain failure as a defining risk for modern systems Final chapters cover real-time monitoring, agentic AI, digital twins, and cross-sector standardization
Autor*in
Benjamin D. Trump
Themen in »Resilience Analytics«
resilience analytics resilience assessment critical infrastructure resilience resilience matrix resilience quantification resilience metrics cascading failure analysis infrastructure risk assessment network resilience cyber-physical systems resilience supply chain resilience disaster resilience Stress and resilience resilience engineering agent-based modeling resilience