Uber, Google, Wendy’s, CDM Smith Inc, and Amazon – you couldn’t get a much more diverse set of organizations. A search engine, a fast-food chain, to an online retail store – these businesses might be diverse in terms of their operations, but they’re all linked by certain business practices.
That is, these top business players all utilize geospatial data to optimize their operations for a healthier bottom line. In this article, you’ll discover what geospatial data is and how it’s used by these top 5 businesses to gain a competitive edge.
Let’s jump straight to it.
What is geospatial data?
Geospatial data is also known as place-based or location-based data, such as longitudes, latitudes, stress addresses, and postal codes. Geospatial data analysis collects, displays, and manipulates GIS – Geographic Information System – data like imagery, satellite photographs, and historical data. The aim is to collect, store, retrieve, and display vast amounts of information in a spatial context.
For instance, can you imagine life without GPS?
In this vein, you’ll likely remember buying a paper map to plan your routes from one place to another. This system was slower, hard work, and vulnerable to human error. Today, geospatial data has been a game-changer when it comes to providing location/place-based information. Whether it’s MapQuest, Pokémon Go, Google Maps, or the in-dash car navigation system, everyday citizens use geospatial data more than they know.
How do top businesses use geospatial data?
Just as we rely on geospatial information every day, leaders worldwide use geospatial data to guide them towards making the right decisions at the right time. With that said, let’s take a closer look at how Uber and other top businesses are using geospatial data to optimize their strategic decisions for efficient operations and sustained business growth.
In 2019, Uber brought in $14.1 billion in revenue, showing exponential growth from 2013 (where revenue equals $0.1 billion). Founded in 2009 by Garrett Camp, the organization has since grown into a disruptive tycoon that’s ripped up the cab industry by storm.
Central to its success comes geospatial technology.
With the Uber app, the user can request a cab. This user’s location is then taken and matched with the closest driver. The driver accepts this match and is guided by applying it to the user’s location to transport the user to their chosen destination. This entire process draws from the application’s geospatial data.
This isn’t the only way Uber uses geospatial data — there are countless others. For instance, the application identifies areas with the highest need for drivers and advises active drivers to be near those hotspots during high demand times.
Without geospatial data, Uber would not be the business disruptor it is today.
Google is the goliath of the business world. In the third quarter of 2020, Google’s revenue amounted to $46.03 billion, up from $38 billion in the preceding quarter. Taking a good chunk out of this revenue comes from Google’s map application, which brings $4.3 billion a year.
Google maps has 154.4 million monthly unique users. And behind every map, there’s a much more complex system, the key to your queries but hidden from your view.
This more in-depth system contains the logic of places, all the left and right turns, freeway on-ramps, speed limits, traffic conditions, you name it. And to produce such a system, Google uses geospatial data provided by a third party to deliver digital maps and other dynamic content for navigation and location-based services.
Square hamburgers, sea salt fries, and the addictive Frosty, this fast-food giant brought home $1.687 billion in revenue in 2020.
What’s the secret to Wendy’s success?
I say geospatial data.
Wendy’s carefully researches locations, leveraging mapping software and census data (population information). The fast-food chain searches for sites with a high population and potential customers and looks at household demographics, average income, and nearby businesses.
But this analysis doesn’t stop when the right site has been found. Wendy’s continues to examine this geospatial data after construction at the given location. Before construction, prior construction results can then be compared to continuously tweak and improve their GIS analytics model and processes.
CDM Smith Inc
CDM Smith Inc is a global engineering and construction firm providing solutions in water, environment, transportation, energy, and other facilities. In 2015 the organization’s revenues totaled over $500 million, and one of the reasons for the success has been the organization’s use of geospatial data.
That is, for CDM Smith Inc, geospatial data provides design and engineering capabilities to create plans, layouts, and maps. GIS applications for design and engineering make use of both imaging and planning functions. Such functions mean geospatial data is commonly used in industries such as landscape engineering, environmental restoration, commercial and residential construction, and development. CDM uses geospatial data for environmental engineering and remediation projects.
In 2019, the online retail platform, Amazon, reported a net income of $11.59 billion, up from a $10 billion U.S. net income in the previous year. To stay ahead of the curve, Amazon is always coming up with new and innovative ways of doing business. And one example is Amazon’s Prime Air drone project, expected to officially launch on August 31st, 2020.
By integrating GIS with Artificial Intelligence, it’s possible to fly drones over much larger distances than other previous attempts. Amazon has jumped on this bandwagon, delivering packages by drones. The aim is to deliver packages to customers in 30 minutes or less using unmanned aerial vehicles – drones – operational thanks to geospatial data.
Gain a competitive edge by using geospatial data
As technology advances, geospatial data is becoming more complex, with widening business potential. At the end of this article, we saw how Amazon is combining GIS software with Artificial Intelligence (drones) to expand the use of both. Does this represent the future of things to come regarding geospatial data?
Geospatial data analysis has the potential to:
- Match consumer demographic data with spatial information about the places they live
- Validate existing GIS data sets
- Monitor and report weather
- Survey habitats
- Model landscapes
- Assess disaster damage
While these are just a few examples, by combining geospatial data with AI, the possibilities of its use are expanding. To grasp a competitive edge, and be a top player in the business arena, dig deep and see how you can leverage geospatial data technology for your business operations.