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In the first of a two-part series, we examine the critical role that location-based data plays in an organization’s crisis response efforts and how compounding crises lead to an even more immediate need.

While initial outbreaks of COVID-19 hit densely-populated, urban areas of the United States the hardest, the coronavirus is now beginning to surge across less populated parts of America.

Rural counties now have some of the highest rates of Covid-19 cases and deaths in the country, topping even the hardest-hit New York City boroughs and signaling a new phase of the pandemic—one of halting, scattered outbreaks that could devastate still more of America’s most vulnerable towns as states lift stay-at-home orders—Washington Post

The Washington Post article, A deadly ‘checkerboard’: Covid-19’s new surge across rural America, speculates what the next COVID-19 outbreak might look like. “It is coming, and it’s going to be more of a checkerboard,” says Tara Smith, a professor of epidemiology at Kent State University. “It’s not going to be a wave that spreads out uniformly over all of rural America; it’s going to be hot spots that come and go. And I don’t know how well they’re going to be managed.”

Specific geographical information now plays a critical role in response, planning, and execution. One of the many things we’re learning during the crisis is that addressing the ramifications of the pandemic is a location-by-location challenge.

The Shortfall of a Patchwork Response

As the country heads into an anticipated second wave of outbreak, the need for location-based data will continue to play a key role in the success or failure of responses. To date, we have witnessed the varying impact of the outbreak across the country that has, in part, led to a scattered response. Density of population, accessibility to proper healthcare, language barriers, access to testing, and governmental response and education are just a few factors that feed into the endless possibilities for the “perfect storm” to erupt anywhere, at any time.

Lacking a cohesive federal response to the outbreak, the U.S. was left with a patchwork of 50 different responses to the same crisis, with varying degrees of success. In what ultimately turned into a county and locale response within each state itself, Rebecca L. Haffajee, J.D., Ph.D., M.P.H. and Michelle M. Mello, J.D. note:

This is the dark side of federalism: it encourages a patchwork response to epidemics. States and localities may decide to implement aggressive disease-mitigation measures, but need not do so. The defining feature of the U.S. response to Covid-19 therefore continues to be localized action against a threat that lost its local character weeks ago.—The New England Journal of Medicine

An array of micro responses to the outbreak have left organizations working to piece together how to operate across state lines. Many are finding that their disaster or crisis response plans are not sufficient for tackling a national crisis, much less an international one. The details that matter most in mitigating exposure, risk, and uncertainty on an international scale are also found at a local level, meaning organizations need to drive decisions with data collected at a number of levels.

An Ongoing Need for Location Data & Planning

While the need for location-based data has always existed, it was not always viewed as a necessity. Typically used to generate graphics or aesthetically pleasing dashboards, location data can be used to its highest purpose to spot key trends early enough to take action, ensure critical assets are in place where needed, or maintain operations during disruptions.

To this point, we are reminded in the Forbes article This Is Not A Drill: Surviving Radical Disruption With Data Governance, that organizations with an existing investment in data fare better through crises and disruption than those that do not. Cultivating location-based data is not a one-time, checkbox exercise. Rather, it is an ongoing project requiring continual data management, organization-wide standards, and a commitment to best practices. Though initiating this process is likely to be daunting, the disruption created by the coronavirus also provides organizations lacking this investment an opportunity.

Although painful, disruption like this offers organizations the opportunity to reexamine how and why they do things—to use a crisis for good to eventually become better. And organizations with established data governance practices and trusted data are best positioned to make the types of decisions that will ultimately determine their survival.—Forbes

The outbreak has cast light on countless shortcomings—both governmental and organizational—that have fed into each other. Despite this, organizations are presented with the chance to come to terms with what their data should look like. Making significant improvements on this front means connecting critical assets to location-based data.

With infection rates and legislation varying from state to county, organizations need to know what their mobility and operating capabilities truly are. Macro approaches that have carried companies this far are now proving to be less than sufficient. For example, simply knowing the number of ventilators, personal protective equipment (PPE), delivery trucks, or essential personnel is no longer enough. The location of those assets themselves are what truly matters—without data dictating where mission-critical items or people are located, the mere fact that the organization possesses them becomes somewhat useless and diminishes their value.

It is now a necessity to outline which operations or personnel are affected by specific mandates, where assets are located versus where they are needed, and whether there are other location-based threats on the horizon that need to be accounted for. Yet many organizations are not set-up to configure location-based data quickly, especially in the midst of a pandemic and economic downturn. Pulling together and reconciling location-based data for an entire organization is a laborious process that requires following best-practices for an impactful outcome. Doing so requires resources and time—two things that more and more organizations do not have and will likely not have for some time.

When Crises Compound

The world has seen the toll that widespread outbreak of an infectious disease has. At the same time, regions across the United States are experiencing it in a compounded nature. For example, massive flooding has forced thousands to evacuate their homes in Michigan, yet families are choosing to live out of their cars instead of a shelter due to fears of contracting COVID-19. This highlights yet another hole in our nation’s disaster preparedness capabilities.

Additionally, the National Oceanic and Atmospheric Association (NOAA) is predicting a heavy hurricane season in the Atlantic. Not only can we expect a turbulent hurricane season amid an already catastrophic period of flooding in the Midwest, but the south is also predicted to realize a second wave of outbreak sooner than most.

As detailed in the Washington Post article, Disaster season is upon us. The pandemic changes everything, we are left with the stark reality that the pandemic will likely cause destruction that comes hand-in-hand with natural disasters. Two occurrences that are only becoming more common and severe due to climate change and the cultivation of livestock.

These challenges are each daunting on their own, but in the midst of covid-19 and an exhausted disaster-response infrastructure, are we prepared to cope with multiple disasters at once? Even without a pandemic, public health departments and hospital disaster preparedness programs across the United States have been chronically underfunded for more than a decade.—Washington Post

Such compounding crises are unlikely to be a once-in-a-lifetime occurrence. They are, instead, something we will likely see play out in varying degrees of complexity and severity over time. Organizations can, and should, learn from the current crises and plan for the future in a way that will make a difference. How location-based data is used will be a determining factor. Read Part-Two here.