10 hurricane takeaways from 2018

by Jen Smoldt on June 4, 2019

Hurricane Florence SK view 2

While the 2019 hurricane forecast is quite favorable (NOAA is predicting a 40 percent chance of a near-normal season with 4 to 8 hurricanes and 2 to 4 of them major), it comes with the reminder that it only takes one. Being prepared means being able to handle the trend of back-to-back hurricanes like we saw in 2017, along with the intensity of hurricanes like Michael and Florence in 2018. As you recall, Florence stalled and brought massive inland flooding to the Carolinas. And, six months after making landfall, Hurricane Michael was upgraded to a Category 5 hurricane by NOAA scientists who determined wind speeds had reached 160 mph at landfall.

How effectively you prepare for and respond to hurricanes can either be an asset to your business or a detriment. By moving from "react and respond" to a more proactive "prepare and serve" approach, you can meet the growing demands and expectations of your customers and shareholders. To do so, streamlined access to a diverse set of expert hazard data is imperative to managing response efforts and customer satisfaction.

Events like last year's hurricanes Michael and Florence create a scramble to find and access the right hazard data—from wind to surge, inland flooding, and aerial imagery. Then, the exhaustive work of understanding and interpreting all the data begins. But, you shouldn’t have to be a GIS expert to keep up with and make sense of all the data. Below are a few best practices to help your operations run smoother this hurricane. For a complete list of best practices, download our 2018 Hurricane Guide:


During a hurricane: Understand your actual exposure and make sense of all the data

1. Check for regular data updates: Consult with your solutions provider(s) about when to expect updates from various data providers

Florence SpatialKey

NOAA forecast data, including wind, surge, and precipitation, was some of the first available to SpatialKey users with Hurricane Florence, along with data from KatRisk, JBA, and Impact Forecasting. Users can bring in their policies in force (PIF) and overlay expert data to understand potential business impact.  

2. Follow weather-related Twitter accounts like:

  • National Weather Service (@nws)
  • NOAA (@noaa) 
  • National Hurricane Center Atlantic Ops (@NHC_Atlantic)
  • The Weather Channel (@weatherchannel) 
  • FEMA (@fema)

3. Ensure you can understand actual exposure: Pinpoint areas with high concentrations of risk and understand actual exposure, not just TIV.

4. Turn around event footprints and models quickly: As data becomes available, ensure you’re able to get it into usable formats.

  • Don’t underestimate the complexity and time required to transform file formats and load sophisticated data from multiple providers (e.g. more complex shapefiles require pre-processing). 
  • Ensure you have the in-house GIS expertise to work with complex and sophisticated data, or consider outsourcing to your solutions provider. 
  • Make certain your system can handle more demanding thresholds (e.g. more people trying to use the system during an event, loading of complex and large file formats, etc.), and consider your integration set up and APIs

5. Don’t fall victim to analysis paralysis: 

  • Use a geospatial analytics solution to help you “move the levers” and understand your sensitivity to model outputs. For example, KatRisk’s Hurricane Harvey event footprint and JBA’s Harvey footprint were two vastly different views of hazard:
KatRisk_JBA comparison

SpatialKey’s comparison slider tool shows KatRisk’s Harvey event footprint on the left and JBA’s Harvey footprint on the right, enabling users to compare two sources of expert data against their portfolio at one time. They tell two different stories but both views are equally valuable: KatRisk’s event footprint shows forecasted flood potential while the event was unfolding, whereas JBA’s footprint is based on a view of extents during a point in time (timestamp).



After a hurricane: Use post-event data and visual analytics to understand potential losses and quickly respond to claims

6. Respond to claims faster and estimate losses with the right data: Access to post-event data is paramount. For example, the ability to bring in aerial imagery may help pinpoint potential claims and more accurately assess damage before claims are even filed.

close up of hurricane florence NOAA aerial

NOAA aerial imagery (shown above) is essential ground-truth data that helps insurers assess damage. With SpatialKey, users can use this data plus their policies in force (PIF) to expedite and validate incoming claims.

7. Plan a debrief immediately following each event: Discuss what went well and where improvements can be made.

8. Consult with trusted advisors: Tap into industry experts, such as SpatialKey account managers if you’re a current client, who can provide added perspective and suggestions for improving your process, data sources, and share how the rest of the market responded.

9. Assess and review vendor performance: Which solutions providers shined and who wasn’t as responsive or attentive to your needs?

10. Conduct an end-of-season historical analysis/audit: Understand gaps in your processes, analytic tools, data, and concentrations of accumulations so that you can spot trends and make changes prior to next season (e.g. How quickly were you able to generate an accurate estimate of losses?).  

It may also be valuable to conduct a hurricane dry run with your organization—bring in representatives from claims, portfolio management, underwriting, and marketing to stress test against your internal processes using past scenarios, such as hurricanes Florence, Harvey, and Matthew. For steps on how to conduct a dry run, download our full 2018 hurricane guide.

As always, SpatialKey is here to help you navigate all the data available to you, and aid in understanding a hurricane’s impact to your portfolio throughout the event. Get in touch to learn more about our hurricane data and analytics.

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Topics: Event response, Hurricane Data, Hurricane Season

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