PRINT BOOKMARK

The key to resilience: understanding interdependencies

Donna Huey | 01 Sep 2016 | Comments

Donna Huey recently discussed resilience and interdependency with The Construction Specifier. The following article was originally published by The Construction Specifier.

A perfect storm of risks threatens even the simplest of resiliency goals. There are key dangers to pay attention to while evaluating the relevance of context, contracting, and people as critical factors to achieve goals.

Starting with natural risks, resiliency is how vulnerable one is to hazards—understanding what the pattern or intensity of those hazards is, the response time, and how one can recover. There has been an 80 percent increase in the growth of climate-related disasters between 1980 and 2009. In 29 years, losses have doubled because of disaster. The increasing densities of urban centers, particularly in coastal cities, only push the limit of property and human losses. Even when attributing some of the loss increases to improved reporting, scientists argue two-thirds of the increase is ‘real.’ Certainly, if one were to dispute the increase in frequency, it would still be clear the rising costs are related to increased density in urban centers..

The key challenges of infrastructure risk include:

• adequately maintained structures;
• the pace of technology and new material adoption to improve asset life and performance; and
• prioritizing maintenance or recovery plans based on risk and life line analysis.

The American Society of Civil Engineers (ASCE) 2013, Report Card for America’s Infrastructure estimates the need for $3.6 trillion to raise our infrastructure to acceptable standards. Further, ASCE’s 2015 Report Card for New York’s Infrastructure showed only modest improvements with roads, bridges, and wastewater still reflecting ‘D’ grades.

Another risk to consider involves cyber security. Recent reports predict in the next five years a move from four billion to 30 billion in Internet-connected devices, with a trillion sensors emerging by 2022. Considering the prevalence of personal credit card hacks and identity theft, it is certainly within the realm of possibility there may be a data hack on a smart building or intelligent transport system. In 2014, many in the infrastructure community took careful note of the widely publicized study by Cesar Cerrudo on vulnerability of smart cities. Field tests have shown exposure to traffic sensors in several U.S. cities—couple this with a growing popularity of games and popular products.

A multi-variable problem

Problems arise while in isolation, but together the challenges become a multi-variable problem and infinitely more complex. Having personally worked in the IT side of the infrastructure industry for over 25 years, this author has become familiar with the use of systems’ engineering principles and progressive assurance to protect people from these multi-variable problems—testing individual pieces of hardware or code independently before connecting them together.

However, when the time comes to design or redevelop infrastructure, the luxury of a controlled setting is not always possible. Assumptions need to be made and the interdependencies of these variables must be modeled—it is the real-life, natural elements that will tell the true story of a successful design. Thus, the most important variable to be considered is people. Humans will use and interact with the infrastructure in the environment.

As a result, it is important to evaluate these multi-variable problems with a respect for context—taking into account economic risk, social risk, and the maturity of the community in place to maintain and sustain. To better understand, one can analyze the exponential increase of sensors. The devices come in many shapes and sizes and some can even generate their own power. They are helping designers and engineers understand how their designs are performing—a new live feedback loop has been created because the infrastructure can now ‘talk.’

For example, a new bridge structure loaded up with sensors can tell the operator everything from vibration to loads to wear and tear. Bridges in Atlanta or New York would be connected to servers with teams of people in well-staffed agencies or top-notch consultants evaluating, managing, and leveraging data to optimize maintenance, improve safety, and develop improved designs. Incoming data would feed decision support systems or asset management systems generating predictions, and automating work orders—a great example of making the best of all new technology has to offer.

However, imagine the same bridge in a rural town struggling to make ends meet, with barely enough staff to keep up with the basic needs. How can it take advantage of all this and not be left behind? What about in a developing country? The context in which this bridge sits becomes vitally important. The bridge in the urban setting is quickly integrated into the system of systems. Except in the rural setting, if the data being generated lacks a person or system to interpret or leverage it, there is no meaning to derive, no predictions to be made—would this just be a colossal waste of money? Such a perceived waste can be avoided if the context is evaluated early in the conceptual design stage.

Assuming in each instance somebody is looking to achieve similar levels of resiliency leveraging the latest technology, the context requires different methods of implementation. In the case of the rural location, it means contracting remote monitoring and support; in the case of the developing country, it means perhaps simply the ability to apply the learning derived from similar sensor-laden bridges in other parts of the world. In both instances, when context is considered, operators can still obtain valuable intelligence to ensure future designs are more sustainable.

In the end, the data is generally only as good as the team or system that can interpret the data and leverage it for continuous improvement. It is important people do not become lulled into complacency with respect to technology and allow smart infrastructure make them inferior. These improvements can be readily shared so all stakeholders, regardless of context, improve their infrastructure investment and design decisions. The key is treat the whole patient—step back and understand the context, before trying to devise and implement a more sustainable solution.

Next-generation contracting

In the previous bridge example, considerations are referenced for new methods of contracting in ways that will help cities less-equipped take advantage of technological advancements. This is the tip of the iceberg as it relates to how interdependencies and new technologies could influence planning and contracting in the industry.

As new technology helps improve resiliency decision-making and funding constraints lead to new ways to extend life or lower life cycle costs of assets, we are rapidly seeing changes in our delivery methods. Owners are taking a step back and starting to look at the bigger picture. There is a rise in public-private partnerships (P3) an increasing prominence of Integrated Project Delivery (IPD), and many new terms and conditions in infrastructure design and construction contracts addressing shared risk.

In the midst of the merging of physical and virtual worlds, evidence of new relationships are forming in the supply chain as well. Traditional engineering firms are finding new partners—more collaboration with large IT and system integration companies, more partnerships with financial firms and banks, and learning how to drive more progressive relationships with contractors on much larger scales.

All these new relationships and contracting methods invoke a new line of questioning or self-reflection for many traditional design and engineering firms with respect to their position or ‘fit’ in this evolving supply chain. It is truly imperative for traditional design firms to complement this supply chain disruption with an equal level of disruption considering new ways of working, sparking ‘whole-systems thinking’ and embracing deep technological shifts in the industry.

When delving deeper into the fusing of the physical and virtual worlds, it is important to embrace these changes through a push to accelerate ‘digital engineering.’ Whether an individual leverages related terms such as building information modeling (BIM), this is about the automation of all or parts of the lifecycle of a built asset.

In the private sector, the infrastructure owner is more intensely driven by commercial returns and when he or she sees the clear return on investment (ROI) evidenced through the use of digital engineering and digital asset management, the owner understands and is able to quickly develop new requirements without complex government bureaucracy. The financial world sees it the same way. Lengthy concessionaire agreements on P3 contracts are about ensuring the commercial returns. The benefits of de-risking the ROI by proactive data management means second-guessing enforcement of contractual requirements on the lead designer not an option.

When examining the area of infrastructure resiliency, engineers can be leveraging BIM in more progressive ways, not just for obligatory contract requirements, but by becoming invested partners in driving that ROI—share in the reward, as much as the risk. Addressing level of detail and information in early phase models, BIM can be leveraged for management of Leadership in Energy and Environmental Design (LEED) compliance. Modeling and optimizing carbon and energy efficiency during concept stage will lead to material long-term operating cost reductions. Additionally, designers can leverage frameworks for sustainable return on investment, putting a value on green infrastructure and showcasing long-term benefits for maintenance cost and resiliency.

BIM and related digital engineering services are becoming more the norm. It will be imperative for the design and engineering community to step up and proactively guide how new technologies and research will be applied. Global standards organizations, such as the buildingSMART alliance and Open Geospatial Consortium (OGC), are accelerating involvement to drive these discussions. It is important these talks are infused with infrastructure domain expertise. The design and engineering community need to help make the technology better—truly a call to action for this industry to lead what many call the ‘fourth industrial revolution.’

Importance of people

People are the last, and most important point to understanding resilience and interdependency risks. Education is the best investment for resilience of future cities when it comes down to it. People inherently live in ‘silos’—it is human nature to gravitate toward what is familiar and trusted. Since interdependencies by their very nature require there to be interaction, what happens if people refuse to interact? Leave it to the computers to model these interactions and make the decisions accordingly?

Currently, there is more data than ever and it is impossible to comprehend what that data set will look like one or five years from now. What has become increasingly more important today for industries is society has learned to leverage this data and apply it to the next generation of designs. The data can also be leveraged as a means to bring people together—to break down silos and analyze a situation as a team, recognizing the interdependencies and people are now living in a connected system of systems. It does not help to connect the bits and bytes if people are not connected to make higher order decisions.

Conclusion

One of the most prevalent arenas where these silos are present are where cities are addressing impacts of climate change. Climate change does not pick a specific type of infrastructure or location or socio-economic faction. It cuts across and requires a coming together of disciplines and ideas to drive solutions.

In a recent project supporting climate change management in the Dominican Republic, results are drive by this author has observed that when discussions emphasize people-related aspects, building common interests, discussing experiences, learning from different perspectives, and most importantly, building the relationships that develop.

Many sources of data, tools, and technology will aid and facilitate the work of understanding interdependencies as it relates to resiliency. Data and tools are used to help tell a story, but the heart and soul of these efforts is the coming together of the diverse discipline leaders, evaluating together the interdependencies, sharing knowledge, and ensuring connections are established to other people and resources. These are skills that surpass data and technology, that need to be taught and encouraged. They are sometimes tough abilities for a lot of nuts and bolts engineers, but the development of these services in the industry is what will enable clear recognition of the interdependencies and truly drive resiliency.