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Location intelligence (LI), or spatial intelligence, is the process of deriving meaningful insight from geospatial data relationships to solve a particular problem. It involves layering multiple data sets spatially and/or chronologically, for easy reference on a map, and its applications span industries, categories and organizations It is generally agreed that more than 80% of all data has a location element to it and that location directly affects the kinds of insights that you might draw from many sets of information. Maps have been used to represent information throughout the ages, but what might be referenced as the first example of true location 'intelligence' was in London in 1854 when John Snow was able to debunk theories about the spread of cholera by overlaying a map of the area with the location of water pumps and was able to narrow the source to a single water pump. This layering of information over a map was able to identify relationships, and in turn insights that might otherwise never have been understood. This is the core of location intelligence today.
Deploying location intelligence by analyzing data using a geographical information system (GIS) within business is becoming a critical core strategy for success in an increasingly competitive global economy. Location or GIS tools enable spatial experts to collect, store, analyze and visualize data. Location intelligence experts are defined by their advanced education in spatial technology and applied use of spatial methodologies.
Location intelligence experts can use a variety of spatial and business analytical tools to measure optimal locations for operating a business or providing a service. Location intelligence experts begin with defining the business ecosystem which has many interconnected economic influences. Such economic influences include but are not limited to culture, lifestyle, labor, healthcare, cost of living, crime, economic climate and education.
The term "location intelligence" is often used to describe the people, data and technology employed to geographically "map" information. These mapping applications can transform large amounts of data into color-coded visual representations that make it easy to see trends and generate meaningful intelligence. The creation of location intelligence is directed by domain knowledge, formal frameworks, and a focus on decision support. Location cuts across through everything i.e. devices, platforms, software and apps, and is one of the most important ingredient of understanding context in sync with social data, mobile data, user data, sensor data, using platforms as CartoDB where data as a service and the analytical and visualisation tools blend together to create a business friendly environment.
In 2012, Wayne Gearey from the commercial real estate industry was selected to offer the first applied course on location intelligence at the University of Texas at Dallas. In this course, Gearey defines location intelligence as the process for selecting the optimal location that will support workplace success and address a variety of business and financial objectives.
Geoblink defines location intelligence as the capability to understand and optimize a physical network of points of sale in the process of making business decisions.
Pitney Bowes MapInfo Corporation describes location intelligence as follows: "Spatial information, commonly known as "Location", relates to involving, or having the nature of where. Spatial is not constrained to a geographic location however most common business uses o spatial information deal with how spatial information is tied to a location on the earth. Miriam-Webster® defines Intelligence as "The ability to learn or understand, or the ability to apply knowledge to manipulate one`s environment." Combining these terms alludes to how you achieve an understanding of the spatial aspect of information and apply it to achieve a significant competitive advantage."
Definition by ESRI is as follows: "Location Intelligence is defined as the capacity to organize and understand complex data through the use of geographic relationships. LI organizes business and geographically referenced data to reveal the relationship of location to people, events, transactions, facilities, and assets."
Definition by Yankee Group within their White Paper "Location Intelligence in Retail Banking: "...a business management term that refers to spatial data visualization, contextualization and analytical capabilities applied to solve a business problem."
Today, location intelligence is used by a broad range of industries to improve overall business results. Applications include:
- Communications & telecommunications: Network planning and design, boundary identification, identifying new customer markets.
- Financial services: Optimize branch locations, market analysis, share of wallet and cross-sell activities, mergers & acquisitions, industry sector analysis, risk management.
- Government: Census updates, law enforcement crime analysis, emergency response, environmental and land management, electoral redistricting, tax jurisdiction assignment, urban planning.
- Healthcare: Site selection, market segmentation, network analysis, growth assessments.
- Higher education: Student Recruitment, Alumni & Donor Tracking, Campus Mapping.
- Hotels & restaurants: Customer profile analysis, site selection, target marketing, expansion planning.
- Insurance: Address validation, underwriting and risk management, claims management, marketing and sales analysis, market penetration studies.
- Media: Target market identification, subscriber demographics, media planning.
- Realestate: Site reports, comprehensive site analysis, retail modeling, presentation quality maps.
- Retail: Site selection, maximize per-store sales, identify under-performing stores, market analysis.
- Transportation: Transport planning, route monitoring.
- K-12 : School Site Selection, enrollment planning, school attendance area modification (boundary change), school consolidation, district consolidation, student achievement plotting.
- Data Resources For Real Estate And Business Geography Analysis. Thrall,G.,I.,Ph.D.(2009)/Professor, Department of Geography, College of Liberal Arts And Sciences and Miller Center For Retail, College of Business, University of Florida
- George Moon (2008-00-00). "Location Intelligence – Meeting IT Expectation" (PDF). Pitney Bowes. Retrieved 2015-10-05. Check date values in:
- ESRI. "Using Location Intelligence to Maximize the Value of BI" (PDF). Retrieved 2015-10-05.
- Marcus Torchia (2009-00-00). "Location Intelligence in Retail Banking" (PDF). Pitney Bowes. Retrieved 2015-10-05. Check date values in: