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Session 23: Resilience: Methods, Tools and Indicators
Tuesday, 30/Aug/2016:
5:30pm - 7:00pm

Session Chair: Hannah BRACKLEY, Natural Hazards Research Platform
Session Chair: Thomas USLÄNDER, Fraunhofer IOSB
Room: Sertig

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Characterizing Resiliency Risk to Enable Prioritization of Resources

Tracy Chaney MORGAN

nContext / Sierra Nevada Corporation, United States of America

Individuals, companies, cities, states and nations seek to quantify their resiliency, to understand their largest risks and to mitigate these risks. In our global economy, resiliency at each level is dependent on the supply chain.

Organizations must first understand their supply chain and be able to visualize it. We provide situational awareness through geospatial mapping of the supply chain, characterization of the organization value (criticality, monetary value, loss of time) of each supply chain node and dependency on that node. The output of this exercise is an understanding of the organizations’ critical systems and nodes within the supply chain.

After we define the supply chain, we overlay the risks of those geographic areas. These risks include Sustainability, Human Trafficking, Natural Disasters, Cyber, Financial Stability, Political & Society instability, and physical infrastructure in areas of supply, and Resources (Energy, Water, Food, and Land). The risk rating in each of these areas allows organizations to determine where and how to focus critical resources. As conditions change and mitigations occur, the risk rating changes. These risk areas are not independent factors but interrelated.

As an example, for Human Trafficking within the food supply chain, we developed a model to leverage a combination of data source encompassing open source, private and government data sources to categorize the risk for a food supply chain of Human Trafficking/ Forced Labor. From a starting point of over 2,000 vendors within a supply chain and countless nodes, we were able to identify the 120 high-risk vendors globally that should become a focal point for mitigation.

Towards a Novel and Applicable Approach for Resilience Engineering


Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institute, EMI, Germany

Resilience Engineering can provide society and its critical infrastructure and systems with means, methods and technologies to overcome disruptions with as less harm as possible. In this context it is of utmost importance to identify ways to strengthen the adaptive capacity of up to complex socio-technical systems. We try to establish Resilience Engineering as a way of thinking that enables engineers to use their scientific expertise, creative ingenuity and help society to develop tools to handle all kinds of adverse events properly - from critical system disruptions, natural disasters, global terrorism to large-scale infrastructure failure.

For that purpose, we suggest to deliberately limit the scope of Resilience Engineering towards engineering, i.e. mainly technological solutions, in contrast to the main body of Resilience Engineering literature. By that we try to pave the way for the next generation of engineers dealing with the extension from risk analysis and management towards resilience thinking. In short, Resilience Engineering means preserving critical functionality, ensuring graceful degradation and enabling fast recovery of systems with the help of engineered generic capabilities as well as customized technological solutions when the systems witness problems, unexpected disruptions or unexampled events.

One central aspect of Resilience Engineering is the ability to quantify and measure resilience. Only adequate and valid indicators will give us the chance for comparatively and absolutely analyzing various systems with respect to their specific resilience. Finally, we need to be able to develop advanced methods for modelling and simulating, in particular for complex systems and their resilience towards adverse events. The presentation will hint at opportunities and research necessities for developing a new and integrated approach to model, simulate and improve the resilience of complex, interdependent, socio-technical systems.

Resilience in IRGC’s Recommendations for Risk Governance

Marie-Valentine FLORIN1, Igor LINKOV2

1EPFL, Switzerland; 2USACE, USA

Resilience, as a concept, an approach or simply a property of a system, aims to help systems cope with unexpected changes, of various forms. The concept has gained much popularity among scientists and practitioners alike, who are faced with the limits and boundaries of risk management.

In 2005 already, the International Risk Governance Council’s White Paper that develops an inclusive risk governance framework to deal with risks marked by complexity, uncertainty or ambiguity, identified a specific space for resilience. Since then, IRGC has continued to make the case that resilience building can be a relevant strategy for reducing the consequences of certain types of risks, among which emerging risks and slow-developing catastrophic risks.

We propose that resilience strategies should be considered for risks marked by uncertainty and unexpectedness, as often the case in complex adaptive systems, but that other conventional risk management strategies should not be neglected. For example, managers need to identify and address trade-offs between hardening and protection versus resilience and recovery.

We suggest that more work is needed to operationalise resilience approaches, and that this work must include feedback from experiences in organisations that work to building resilience in the context of disaster preparedness and management, engineering design, cyber security or ecological systems. However, advocates of resilience building will need to make the case that metrics for resilience assessment and management must and can be developed, in such a way that robust investment decisions can be made to allocate financial and other resources.

The presentation will present IRGC’s main considerations about resilience, provide examples, list some barriers to implementations and suggest ways to overcome them.

It will also introduce the IRGC resource guide on resilience (2016): a collection of authored pieces to the topic of metrics and indicators for assessing and measuring resilience.

Resilience Analytics: How Are They Generated and Consumed?


Risk Management Solutions, United Kingdom

Catastrophe models, originally developed to help re/insurers price catastrophic risks, manage re/insurance portfolios and ensure long-term solvency, are increasingly being employed by countries and cities to plan for a wide range of potential disasters. In May 2016 in Miami, RMS convened the first international workshop on ‘Resilience Analytics’ for this emerging, interdisciplinary group of government officials. We can expect to see an increasing focus of expertise in the use of resilience analytics at local, regional and national government agencies. This has begun with a renewed emphasis on programmes to collect and maintain detailed information on all the exposure categories across the city: including buildings, infrastructure, people, economic activity and sustainability. We can expect that a software platform, harnessing the probabilistic hazard modelling capabilities which are used by insurance industries, will then empower various actors in city and national administrations to measure, manage, build and fund resilience. These actors will include the Chief Resilience Officer (CRO), the Chief Financial Officer (CFO) and the Disaster Response Manager (DRM). Each will require a customized set of applications. The CRO will interrogate a range of metrics to identify hotspots of risk, as well as to explore the cost-benefit of resilience-building strategies. The CFO will consume Loss Exceedance Probability curves at departmental and administration level, identifying the potential for catastrophes to damage economic activity, increase public sector costs and reduce taxation, as well as analysing the efficacy of various emerging risk transfer mechanisms. Meanwhile the DRM will use the analytics to explore the probabilistic impacts of potential emergency response, shelter and recovery scenarios. The analytical knowledge on resilience that will be gained as a result will inspire and enable new forms of risk reduction and risk transfer, as well as highlight how resilience analytics will come to drive ‘risk-based government’.

Resilience Metrics and Approaches for Quantification

Igor LINKOV1, Cate FOX-LENT1, Marie-Valentine FLORIN2

1US Army Corps of Engineers, United States of America; 2International Risk Governance Center (IRGC), SWITZERLAND

Resilience as a concept has been adopted by a variety of professional fields ─ including psychology, engineering, medicine, and other social and physical sciences ─ and has also served as a tool to address risks in or related to cyber security supply chains, infrastructure, and climate change, among others. This paper will review approaches to quantify resilience reported in the IRGC Resource Guide.

The focus of the review will be on quantifying resilience at appropriate and operational scales, incorporating complexity and ultimately creating actionable recommendations to enhance resilience that are fundamental for improved decision-making and risk reduction policies. Individual metrics of resilience as well as approaches for their integration in indices, scorecard, matrices and decision models will be discussed. Advanced modeling approaches, including network science based models will be presented.

Finally, we will introduce a tried approach to operationalize resilience in agencies that are responsible for disaster risk reduction from natural hazards with regard to property damage, diminished ecosystem services, and loss of life. The structure of the analysis consists of discrete tiers by which users can scale a resilience assessment and management action (simple to complex) relative to the scope and urgency of the risk and the capacity of resource managers (i.e. adequate funding and understanding) to improve system resilience and reduce risk.

A Quantitative Framework to Assess Communities’ Resilience at the State Level


Politecnico di Torino, Italy

This paper presents an analytical approach to assess the resilience of communities and states based on the Hyogo Framework for Action (HFA). The United Nations (UN) through their advancements in the Disaster Risk Reduction have released multiple international blueprints to help build the resilience of nations and communities, among which we mention the Hyogo Framework for Action and the Sendai Framework. The latter is still under development as the risk bases and the resilience indicators are yet to be defined. For this reason, the work presented here is built upon the more complete HFA framework. A number of weighted indicators taken from HFA are used to compute resilience. Those indicators, however, do not affect the resilience index equally. This discrepancy necessitates the need to weigh the indicators on the basis of their individual contribution towards resilience. In order to achieve this, we have used the Dependence Tree Analysis (DTA). This method allows identifying the dependencies between the HFA indicators and the resilience index and evaluate in unbiased way the weight factors of the different indicators.

The paper is also proposing an analytic formulation to assess a new index, Bounce Back index (BBI), which combines both community’s Exposure, Hazard, and Resilience together. To illustrate the methodology in full details, a case study composed of 37 countries is presented in this paper, where the Resilience and the Bounce Back indexes of each country are evaluated.

Untangling the Drivers of Disaster Resilience: Developing a Context, Capacity and Performance Model of Local Government DRR

Benjamin BECCARI

REM Programme, UME School, IUSS Pavia, Italy

This presentation will discuss a new model for understanding the underlying factors that influence how well local governments reduce disaster risk. The model aims to build upon existing literature to develop a systemic understanding of how various factors combine to influence local government performance in DRR. The Context Capacity and Performance model of DRR (CCPDRR) defines three interacting components: context, the setting of a local government organisation; capacity, its governance and resources; and performance, the activities it undertakes to reduce community disaster risks. These three components are further divided into elements based on other theoretical frameworks and empirical research that investigate links between them. The model further hypothesises relationships between the elements.

The relationship between the elements of context, capacity and performance is further examined and elaborated using expert opinion operationalised with the stochastic Decision Making and Trial Evaluation Laboratory (DEMATEL) technique. Divergence between experts and between experts and previously published statistical evidence is analysed to identify where greater agreement exists on the strength of individual influences and where this influence may be less dependent on context. The CCPDRR Model will help guide local governance researchers in the design of large sample statistical studies on DRR performance and in the identification of relevant factors in small sample case studies and the presentation will propose future research directions in this regard. Furthermore the CCPDRR model will assist advocates of DRR to identify optimal policy interventions to drive improved local government performance depending on that local government's context.

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