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SmartData Collective > Inside Companies > Location Data + Business Intelligence = Location Intelligence
Inside Companies

Location Data + Business Intelligence = Location Intelligence

Brett Stupakevich
Last updated: 2010/11/10 at 12:55 PM
Brett Stupakevich
4 Min Read
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During the third week of November, the U.S. celebrates National Geography Awareness Week, an annual celebration to promote geographic literacy — something that should be high on the list for anyone involved with business intelligence today. 

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Geographic data has not been commonly used by businesses in data analytics until very recently. In the past, only large government agencies could afford the expensive and complex databases and tools needed to use this highly specialized information. Google and Microsoft changed that by popularizing geographic data with consumers, and it became economically feasible for businesses to use the data with a Web 2.0 services model. (1)

It’s not surprising that we would want to combine geographic and location data with traditional business data used in business intelligence, something referred to today as Location Intelligence. Your customers, your employees, your inventory, your vendors and suppliers, your facilities, and other assets all have a location component. In fact, IDC is said to have estimated that 80% of current business data used in business intelligence has a location component. Location Intelligence can provide new insight into data beyond current business intelligence analytics and can help organizations even further improve business decision making and streamline business processes.

Because Location Intelligence is such a new area, we’re only beginning to understand the potential applications and benefits of combining location and business data together. We will undoubtedly see new and highly creative uses of Location Intelligence over the next few years. For now, here are a few examples of how Location Intelligence is being used today in a a variety of different industries.

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  • In Retail, location services such as Foursquare provide the location information that a customer is at or near a retailer’s store. Combining this with customer data such as preferences and purchase history allows retailers to make timely and relevant offers to consumers that result in additional sales. Decisions about which offers to make might even be based on additional data such as the current weather forecast!
  • Location is extremely important in the insurance industry, where customers and natural disasters are both tied to a location. When a natural disaster occurs, insurance companies have the capability to instantly understand their claims exposure by visually plotting their customer data and the affected area on a map. This also allows them to more accurately estimate the number of resources they will need to service claims in an affected area.
  • Many organizations are beginning to track inventory using RFID tags. The American Red Cross is experimenting with a program that records the location and type of blood in a centralized database. At any given time, the Red Cross would be able to understand the quantity and location of the entire blood supply in order to plan for and react to emergencies.
  • Although Location Intelligence has been used in transportation for quite some time, today it is making new business models possible, such as Zipcar in the U.S. and UK, and a new ride-sharing pilot program introduced by Daimler in Germany called car2gether.
  • Site selection, the decision about where to locate a new store or facility, is probably the most common application of Location Intelligence today. When location data is combined with available real estate, demographic data, data on current customers, and information on the most likely prospective customers, the resulting Location Intelligence can help identify a site location with maximum revenue potential.

Steve McDonnell
Spotfire Blogging Team

Image Credit:  mywonderfulworld.org

(1) Mohr, et. al., Marketing of High-Technology Products and Innovations, p. 496-497

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TAGGED: data analytics
Brett Stupakevich November 10, 2010
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