Location Intelligence: Case Study #1
Location Intelligence is used in numerous fields including Commercial Real Estate investment and development, Site Selection, marketing, insurance underwriting, construction, urban planning, and more. During the next few weeks, we’ll be sharing some real-world examples of how we used Location Intelligence to solve challenging problems. Here’s the first of those: Case Study 1: Hurricane Irma During Hurricane Irma, we were tasked by a client to find large improved lots on which to park thousands of flood-damaged vehicles for insurance processing. With the storm only days away from coming ashore, we needed to find options fast. No one knew what kind of damage the storm would cause, and how many vehicles might be affected. We used Location Intelligence to identify and plot potential sites throughout the southern United States for this time-sensitive requirement. But first, we had to find them. We were looking for sites that matched the following description:
10-100 acres
Improved surfaces that could withstand the punishment that would be inflicted by 20-ton articulated forklifts. The surface had to be concrete or at least paved.
In close proximity to major transportation arteries
Already physically secured, or the ability to be secured
Image courtesy The Dirt Ninja
The requirements seemed simple enough, but of course, when combined, the number of qualified properties became very small. First, we used a Google MyMap to share our search progress with our client. This simple and often overlooked Location Intelligence tool is great for quickly creating shareable, interactive maps, and does not require any serious GIS experience to use. To generate feedback from our client in real-time, we plotted potential sites and added notes to each as we identified them. Our client then logged into the map and shared their feedback as we progressed. [We’ll be showing you how to create your own custom map using MyMaps in a coming post.]
Within several hours, we had scoured all of the traditional online databases for commercial properties that would fit the bill, which generally consisted of abandoned industrial facilities with very large parking areas. Next, we reached out to owners of abandoned or partially abandoned malls that would consider leasing us a portion of their parking lot. Shockingly (insert sarcasm here), not many agreed, but we plotted the ones who did. Finally, we decided to look for abandoned airports (read: long, open concrete runways.) During this process, we reached out to the amazing folks at Descartes Labs for help in rapidly identifying potential airports. (Yeah, there’s an app for that.) If you haven’t checked out their GeoVisual Tool, you should. Its Machine Learning application is unreal. To our surprise, there were actually three closed airports within the State of Florida that worked for our purpose.
Ultimately, by the time the storm arrived three days later, we had used Location Intelligence to successfully identify and coordinate about a dozen potential sites for our client. Where there’s a will, there’s a way.