If What Gets Measured Gets Done, How Can We Measure Resilience?

Many of us in the disaster-resilience movement have witnessed and participated in the creation of resilience measurement systems. Along the way, we’ve observed that one of the strongest aspects of our movement is also what makes measurement so difficult: diversity. There are so many puzzle pieces that must be considered—economic, physical, political, and social—just to name a few.

In October of this year, we released a paper entitled Understanding the Intersection of Resilience, Big Data, and the Internet of Things in the Changing Insurance Marketplace, in which we explored resilience measurement as well as issues of Big Data and the Internet of Things (IoT). The good news is that the landscape is rich with efforts to apply a measuring stick to resilience from micro- up to macro-levels. The other news is that this issue is mindboggling in its enormity.

So over the next couple of posts, I plan to return to an examination of these issues because Big Data and the IoT can transform the disaster-resilience movement, and the implications are almost unfathomable. These concepts and their intersection present opportunities that we must understand and plan for before we can harvest any benefits, or at least prevent unintended consequences.

The first step is to develop uniform, consistent metrics to gauge progress toward resilient communities. We need verifiable, practical, and replicable tools. And we need to apply these tools to quality data.

At FLASH, we are concerned with community-wide resilience, but our work focuses more particularly on strengthening homes and safeguarding families from the ground up with strong building codes, beyond-code mitigation, and personal preparedness as part of a culture of resilience. These are foundational aspects of community resilience of course.

But here’s the challenge. Data on building characteristics and performance is not historically granular enough to derive ongoing insights except in certain post-disaster situations. Even then, we must obtain onsite analysis. That is why we need forensic engineering efforts like FEMA’s Mitigation Assessment Team post-disaster to assess structural performance, and evaluate failure patterns to inform to better building codes and standards in the future.

But this is where Big Data and the need for quality data (IoT) can make a difference. When IoT generated-data from new or emerging technologies like sensors can give us precise information on how a building performs, how will we leverage the information for better building practices to avoid future losses? Can we use the Big Data generated by the IoT to get ahead of the next disaster instead of learning after the fact? And what are the accepted metrics (if any) to build a credible database for our insights?

One way to understand the potential of Big Data and IoT is to apply the question to modern water detection systems. The marketplace is exploding with products like Fibaro Flood Sensor, Quirky Overflow, Utilitech Leak Detector, Wally, WaterCop, and more. These systems use sensors to detect moisture, temperature, and humidity and can identify water leakage from all kinds of sources like dishwashers, frozen pipes, washing machine hoses, and water heaters. This triggers an alert to the resident who can stop the leak, clean up the water, and prevent or mitigate costly damage and repairs.

This is a very meaningful breakthrough in loss prevention given the billions paid annually in water-involved insurance losses.

But in our vision of Big Data and IoT, we’d take it several steps further. Leak occurrences would be analyzed in the context of type of appliance, type of pipes, weather conditions, age of home, installation methods, etc. And any relevant specifics would be captured to develop insights on better (or worse) performing construction methods, products, and technologies. This data would inform to future products and practices.

From there, a database of homes with certain characteristics would be built. And this same approach using sensors and tech could be applied to many other failure modes from wind to seismic. All of these databases then would become elements of resilience measurement. Indeed, some already are.

The water detection example shows how resilience metrics are a Big Data problem. The myriad water detection devices cited above create data, but how to sort, harvest, and use the data effectively has a long way to go if it will be valuable beyond the individual loss. This type of micro-measurement is just one of the many ways we grapple with resilience measurement.

In our paper, we also examine various macro-resilience metrics/frameworks/indices including the U.S. Resiliency Council’s effort to rank buildings for seismic performance.

The key is working out how the micro-metrics and data can be developed and reliably applied in the macro-context of community resilience. There are existing options. For residential structures, MLS could include scores on the structural integrity, and attendant durability and life expectancy of a home and/or its location relative to natural hazards. Trulia and Zillow can make this information transparent to homeowners, and it would finally be a factor in driving the market value. Think about it. How is it that the most important aspect of a home—its structural integrity—is still not transparent to homeowners?

Cisco projects that by the year 2020 there will be 37 billion smart products on the market. Juniper Research predicts that there will be 10 million smart connected devices by 2017. It’s time for us to figure out a formula to harness the explosion of data that is headed our way.

This is an important conversation that is only beginning. Our next blog will look at the larger issue of Big Data and disaster resilience and how these movements are converging. And, you may want to join us as we spotlight this issue during our 2016 Annual Conference Meeting with a panel entitled The Next Generation of Resilient Communities. We are bringing together leading voices from government, private, and association to share their perspectives on current initiatives, opportunities, and challenges of fostering resilient communities.

Either way, we look forward to the ongoing conversation.



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