Business Preparedness and Hurricane Risk Hurricanes are one of the more predictable natural disasters compared to events such as earthquakes, wildfires and tornadoes. Meteorologists gather data to predict when, where and with what intensity the next hurricane will occur, with generally accurate results. As shown in the figure below, the forecasting capability of the National Hurricane Center has improved substantially over time. Risk management/ loss prevention professionals, however, have not applied the same type of science-based methodology to risk mitigation. The result is that many companies are ill-prepared for the economic impacts of a hurricane in both the short and long term. In this report, we outline key data points that demonstrate the opportunity companies have to recover quickly and capture market share after a hurricane. Companies that are prepared to handle temporary loss of business can return their operation to normal more expeditiously than others, and are well positioned to meet consumer demand.
Forecasting the 2018 Hurricane Season A year after one of the most destructive Atlantic hurricane seasons in recorded history, the United States is now entering the peak period of the 2018 hurricane season. The Colorado State University Tropical Meteorological Project (TMP) predicts that twelve named storms will emerge this season including five hurricanes and one that will reach major hurricane status. While hurricane activity in 2018 is expected to be lower than average, economic losses from tropical storms and hurricanes in the United States have increased dramatically over time. Yale economist William Nordhaus estimates that average damage from hurricanes in the United States will increase by $10 billion per year and that catastrophic events like Hurricane Katrina will nearly triple in frequency. A recent report from the National Oceanic and Atmospheric Administration highlights four daunting trends that amplify hurricane risk: 1. Rising sea levels will increase storm surges during tropical storms 2. Rainfall rates will increase during storms 3. Cyclone intensities will increase by up to ten percent 4. The number of intense tropical storms will likely increase, even as the number of storms remains steady Hurricane Track Forecasts are Increasingly Accurate Track Error in Nautical Miles 500 400 300 200 1970 79 1980 89 1990 99 2000 09 2010 17 100 0 0 24 48 72 96 120 Hours
The rise in hurricane risk is exacerbated by coincident economic trends. The rapid buildup of structures along the coast has greatly increased the value of assets at risk. Population growth and infrastructure spending, especially in coastal, tourism areas, is on the rise, putting more people and businesses at risk. Florida, which is regularly in the path of hurricanes, typifies these trends. Consider the annual population growth rates of the following Florida communities: Florida Population Growth: Year-Over-Year Forecasted Growth Market Change Growth Population Fort Myers 3.6% 25,600 775,200 Orlando 3.2% 75,400 2,596,700 Palm Beach 2.8% 23,800 1,524,900 Fort Lauderdale 1.8% 33,700 1,978,300 Jacksonville 1.9% 30,600 1,638,000 Tampa 1.8% 60,700 3,139,000 Miami 1.4% 22,500 2,790,500 Hurricane Damages Have Grown Substantially Over Time The economic impact of hurricanes continues to grow over time. The graphic shows total damages from hurricanes in the United States over the last six decades. Economic losses have increased more than seventy-fold since the 1960s, with each decade realizing more hurricane losses than in decades past. Going forward, the trend of increased hurricane destruction is expected to continue. $250 $200 (in billions) $150 $100 Observed Projected $50
Hurricane FEMA Declarations Since 1960 Less than 5 6 to 10 11 to 15 16 to 20 Per Capita Damages from Hurricanes Since 1960 Less than $1,000 per person $1,000 to $10,000 per person $10,000 to $50,000 per person Greater than $50,000 per person Hurricane Risk is Concentrated Geographically Of course, not every person, business and structure in the United States is at risk of sustaining hurricane damage. In the United States, past and forecasted damages due to tropical storms are distributed unevenly across coastal geography. The first map shows the count of hurricane-specific Presidential Disaster Declarations from 1960 to the present. The second shows per capita damage to structures caused by named storms alone. These data underestimate the total economic losses facing coastal communities and businesses, but they still show pockets of extreme loss and the geographic territoriality of hurricanes. The large and growing population centers in these regions are attractive markets to many industries such as retail, travel and tourism, and service-based businesses. It is economically prudent to operate in these markets but only if hurricane mitigation is a priority.
New Orleans Fraction of Housing Damaged Less than 20% 20% to 40% 40% to 60% 60% to 80% 80% to 100% Direct vs. Indirect Economic Losses Economists make a distinction between direct and indirect economic losses. In context of a natural disaster, direct losses typically refer to damages sustained by buildings and infrastructure. Indirect losses, in contrast, reflect losses attributed to business down time and decreased consumer spending. These losses are capable of rippling through an economy, impacting businesses not directly damaged by a storm. In 2008, three years after Hurricane Katrina, researchers found that the indirect economic losses rivaled the direct costs of the storm. Combining all factors more intense storms, increasing economic concentration on the coasts, and rising total costs relative to direct losses tropical storms and hurricanes are a top risk management priority for businesses operating in high-risk areas today. The Effects of Hurricane Katrina The economic story of Hurricane Katrina is instructive. As shown in the above graphic, Hurricane Katrina caused immense damage along the coast of Louisiana and Mississippi. Among the hardest hit parishes was Orleans (i.e., New Orleans) where 71% of housing structures sustained damages.
Before Katrina: 10,500 After Katrina: 7,888 2004 2006 Establishments Relative to 2004 10,500 Other Retail Trade Professional, Scientific, and Technical Services Educational Services Health Care and Social Assistance Arts, Entertainment, and Recreation Accommodation and Food Services 9,500 8,500 1998 2000 2002 2004 2006 2008 2010 2012 2014 Hurricane Katrina Reduced Competition According to data from the United States Census Bureau on County Business Patterns, the number of businesses in Orleans Parish decreased from 10,500 in 2004 to 7,888 in 2006 a 25% reduction. This reduction had a major impact on the competitive landscape across several industries, as the donut charts above illustrate. A 2016 study after Hurricanes Katrina and Rita found that larger firms were more likely to survive. Smaller firms are less equipped to sustain hurricane damages in part because they lack the capacity to invest in risk mitigation and recovery services.
John van de Lindt, professor of Civil Engineering and Co-Director of the NIST Center for Excellence for Risk-Based Community Resilience Planning at Colorado State University, notes: Hurricanes come in many sizes and intensities; they bring to light any weakness in the connections in and between physical infrastructure, technology, and our societal and economic structure beginning at landfall and persisting for years and even decades during recovery. With planning and better engineering and coordination across [experts] this negative impact can be lessened and in some cases virtually eliminated. 1.3 1.2 Business Establishments in New Orleans Consumer Income in New Orleans Consumer Income Per Establishment 1.1 1.0 Before Katrina 1,217 0.9 After Katrina 1,776 0.8 1998 2000 2002 2004 2006 2008 2010 2012 2014 Hurricanes Alter the Economic Landscape More than a question of survival, planning in advance of hurricane risk presents survivors with economic opportunity. As shown in the above line plot, data from the Bureau Economic Analysis shows that total consumer income in Orleans Parish decreased less than the loss in establishments in the immediate aftermath of the storm. Additionally, consumer income also increased more quickly in subsequent years. The faster recovery of consumer demand relative to the count of businesses translated into a 46% increase in the total income per establishment ratio after the disaster. The businesses that survived Hurricane Katrina were poised to thrive in the following decade.
Conclusion Many businesses believe that if they have enough insurance, they will be able to lessen the economic impact a hurricane could have on their operation. This is short-sighted. It does not take into account factors such as prolonged periods of business down time, employees taking leave to handle the impacts of the storm, and the loss of market share to firms that return to full capacity more quickly. These types of non-insurable losses are the cornerstone consideration of a sound hurricane risk mitigation plan. Shoring up vulnerabilities, creating redundancy in mission-critical systems, using data to forecast potential impacts, and communicating/practicing operational procedures across the enterprise in advance of a hurricane are just some of the measures that could help a business survive, and even thrive, long after the storm has passed. Sources 1. Colorado State University Tropical Meteorological Project (https://tropical.colostate.edu/) 2. NIST Center for Excellence for Risk-Based Community Resilience Planning at Colorado State University (http://resilience.colostate.edu/) 3. Nordhaus WD. The economics of hurricane and implications of global warming. Climate Change Economics. 2010; 1(1): 1 20. 4. Hallegatte, S. An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina. Risk Analysis: An International Journal. 2008; 28(3), pp.779-799. 5. Craioveanu, M. and Terrell, D. The impact of storms on firm survival: a Bayesian spatial econometric model for firm survival. In Spatial Econometrics: Qualitative and Limited Dependent Variables. 2016; pp. 81-118. We Never Sleep. www.pinkerton.com