ISE Magazine –Volume 49: Number 03
By Igor Linkov, Benjamin D. Trump and Cate Fox-Lent
Disasters, both from the natural and built environments, are a fact of life. While thankfully uncommon, their arrival can trigger catastrophic shocks that may take years or even decades to recover from. To combat these disasters in the United States, federal and state governments have implemented risk management practices. These efforts are centered on vulnerable areas that are more susceptible to disruptions that can evolve into disasters. As with any government entity, these agencies are required to meet their mission statements within a given budget, so they must make deliberate choices with respect to the degree of preparation and development they take in a particular community. The challenge lies in making the best use out of the tax dollars available to combat a seemingly infinite array of hazards that the future holds.
Here lies the crux of the matter – uncertainty of disaster, the high degree of uncertainty in the potential threats coupled with increasing interdependencies among everyday infrastructure and utilities make disaster preparation efforts all the more difficult and contentious. These interconnections lash together information systems, the energy grid, various civil works projects, transportation networks, health services and community structures in a manner that a dramatic shock to one area has the potential to trigger cascading failures into others.
In various cases of disaster, local communities and regions required considerable resources to restore infrastructural and commercial assets. In fact, compared to daily life prior to the event, many remain at reduced levels of economic, social, structural and health well-being.
Finding a better way
There is a better way to equip vulnerable regions before a disaster, enabling them to withstand risk and recover quickly. We propose the paradigm of resilience, rather than risk, management.
Planners now see resilience analysis as an approach to empower such regions to bounce back to an equivalent or even an improved state. The National Academy of Sciences, in its manuscript Disaster Resilience: A National Imperative, defines resilience as “the ability to plan and prepare for, absorb, recover from and adapt to adverse events,” and this definition has become widely cited. Methodologically, this definition is further expanded into industrial and systems engineering, where many publications on the subject have emphasized the need to develop resilience within critical infrastructure and networks, which are increasingly complex and interconnected.
As a potential complement or supplement to traditional risk assessment, resilience is defined by a few marquee features. The first is a focus on complex and highly uncertain risk management problems, particularly within low-probability, high consequence cases. After all, many of these potential events might never occur.
Resilience analysts are inherently interested in dealing with the unknown, where they are tasked with preparing a system for shocks that could challenge its ability to perform efficiently under stress. Another key feature to consider is the passage of time. More specifically, a strategy of resilience aims to develop a system that can be brought back to full or improved efficiency and delivery of services as quickly as feasible.
An additional point of contrast between the methodologies includes how resilience has a broader, systems wide view of problem-solving as opposed to risk management. Risk analysis may be performed for a limited system of integrated components, but resilience analysis considers threats to systems of infrastructure, society and the environment that could have profound consequences on a population level. Interdependencies and connections between information, physical, social and environmental resources can foster an environment where a reduction in performance or failure in one area (i.e., information systems) can result in cascading failures in others (i.e., the delivery of energy, medical care, transportation networks and other vital services).
By its nature, resilience analysis forces its users to consider a wide range of implications both within and beyond the management project at hand, with particular focus on those low probability, high-consequence events that have the potential to shake up the system dramatically. This feature is of particular importance to an industrial and systems engineering approach to various infrastructural projects and network services, where a global approach to prepare for, absorb and recover from potentially catastrophic shocks is required to avoid total system failure.
When all your domains are connected
Such system failures are the result of several characteristics of 21st century society, including the increasing interconnectedness of social and cognitive processes with physical structures and equipment (as exemplified by the growing interest in the internet of things, digital health records and electric vehicles).
The field of operations research and systems engineering has developed tools to streamline processes and improve efficiency, but one consequence is that there is now minimal redundancy or flexibility in the systems. This makes it all the more difficult to manage disruptions or failures.
Resilience concepts include the application of redundancy, flexibility, adaptability, modularity, decentralization or centralization (as appropriate) and robustness. While improving system hardness and developing such system features (e.g., redundancy) post hoc is possible, it is often an expensive addition that may tax available budgetary resources and ultimately make once-efficient systems unattractive and inflexible options. Luckily, tools exist to help analyze systems through the lens of both performance and resilience.
Resilience thinking is a practice that seeks to identify where critical system interdependencies exist and to estimate how potential cascading effects may result in system failures. This is a methodologically important and complex task, yet few options have been discussed within scholarly literature to promote resilience in various physical, social, cognitive and infrastructural systems.
Following the matrix
A resilience matrix is another option to understand system functionalities and requirements to promote resilience. Using such an approach allows analysts to identify directly how various decision alternatives perform with respect to the plan, absorb, recover and adapt phases of resilience. The results can help indicate how systems analysts should best promote resilience analysis for a given project before, during and after a decline in service and efficiency.
This approach ultimately indicated areas of potential investment to strengthen community resilience to reduce losses and improve communication and performance during a storm and improve response post-event to prevent lasting damage to the local economy, environment, public health and other relevant systems. The same team demonstrated the matrix approach in the Mobile Bay region in Alabama, this time considering not just housing but the environmental health of the bay, the beach tourism industry and the economy of the port. Improvements in these sectors can ensure that the regional major economy continues to function, supporting employees and homeowners as they recover.
When completed, each of the matrix’s cells contains a score that indicates the overall ability of the system to perform in each domain at each stage of the disruptive event. This allows for rapid gap analysis and ensures that a portfolio of proposed projects is selected or developed specifically to address the lower performing areas of the system, without redundancy in efforts. Although these studies have looked at subsystems of communities, colleagues Daniel A. Eisenberg, Igor Linkov, Jeryang Park, Matthew E. Bates, Cate Fox-Lent and Thomas P. Seager outline metrics for applying the matrix to ecosystems, cyber networks and engineered structures.
New thinking, new approaches
How does resilience thinking lead to changed approaches?
In New York, community groups working with NY Rising: Community Reconstruction Program, an initiative designed to help 124 communities damaged by tropical storms and hurricanes, identified several potential investments. The investments included mobile, solar-powered phone charging stations that could be used year-round as well as in the event of a power outage and development of neighborhood action teams that specific neighborhood needs to authorities.
In Alabama, improvements might take the form of hurricane certification for contractors, replacing wood utility poles concrete versions and replacing bulkheads with living shorelines and natural revetments. All of these are aimed at reducing the impacts, or improving the recovery and adaptation, of critical services.
Overall, resilience analysis is a budding approach that is relevant to the strengthening of various industrial, social, environmental and economic systems in a 21st century world rife with uncertainty and the potential for cascading risk effects. Among others, the two methodological options examined here serve as some of the best discussed approaches to review system resilience and subsequently prioritize decision-making to strengthen system resilience. This can be especially helpful for communities that are vulnerable to ecological threats established and conventional risk management approaches and industrial and systems engineers charged with preserving system functionality in the midst of high uncertainty.
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