The Location Intelligent Enterprise: Enhancing Business Intelligence with Location

By Louella Fernandes

Location is a critical component in almost every business transaction. Although a lot of data have a location dimension, whether it be customers, stores, warehouses or other assets, this information is rarely exploited in traditional business intelligence (BI) analysis. To gain maximum value from the ever-increasing volumes of data, companies need to make use of the location element to gain deeper business insight in order to improve competitiveness and business performance.

Today, location intelligence has evolved from the once exclusive domain of GIS expert users. While GIS and BI have traditionally addressed different needs, these technologies have now converged, enabling business analysts to extend their view of the enterprise by integrating geospatial data with business information. At the same time, the growing consumer experience of mapping information is driving business awareness of location exploitation for commercial purposes. Consequently, today's location intelligence products offer more flexibility and ease of use than traditional GIS, and can be integrated with existing business intelligence platforms.

Location intelligence solutions extend beyond simply visually representing data on a map. They combine the analytical power of databases with the geographic capabilities of maps, allowing business users to explore and analyze relationships between geographic data and business data. Database vendors such as Oracle, IBM and Microsoft also offer spatial data support signifying the growing importance of spatially enabled corporate databases. Meanwhile many business intelligence vendors, including Business Objects, Cognos, Microstrategy and Information Builders, have offered location intelligence capabilities through partnerships with vendors such as ESRI or Pitney Bowes MapInfo. Other BI data visualization vendors also offer spatial analysis through, for instance, integration (or mashups) with services such as Google Maps, enabling an enhanced view of the data.

While BI tools are ideal for analyzing who, what and when (customer, product, time), this analysis falls short of answering questions in relation to where, such as the relationship between where customers live and where they make their purchases. So let's consider some of the primary benefits of a location-enhanced business intelligence platform.
  • Use existing BI investments
Location intelligence is designed to take advantage of geospatial information already stored within a database. Therefore, the location intelligence solution can operate within the existing BI environment, meaning users can use the mapping function as part of their existing application without having to be GIS experts. This also means that IT departments are not required to maintain, learn and use two sets of administrative tools or train users on different applications. This utility saves both hardware costs and enhances user productivity.
  • Data enhancement
The key to exposing the benefits of location intelligence is enhancing information through integration with other sources of geospatial data. In site selection, for example, customer location data, combined with reference data on rail networks, power lines and road network geography, all integrated on a single map could quickly show where you might locate a manufacturing plant. These reference data can be delivered via Web services, ensuring that reference data are accurate and up-to-date.
  • Enhanced visualization and analysis
The visual power of maps reveals trends, patterns and insights that are not as easily detected in other data presentation formats, such as tabular views or even the ubiquitous bar and pie charts. In insurance, for example, only a map can easily expose the inherent relationship between customers, property and the risks associated with a specific geography, such as flooding or hurricanes. Similarly, potential risk areas for crime, healthcare issues and employment can also be best viewed graphically against maps. Maps can be used for sophisticated queries without the user needing to know a query language like SQL. For example, using reference boundaries (such as census or postal) together with customer locations, a user can select all prospects within a 15-mile drive time of a series of store locations.
  • Map-driven dashboards
The dashboard is a familiar graphic tool for business users to access key performance indicators, and can be used to better understand what has happened, when and why. Enhancing these dashboards with mapping visualization also offers businesses the opportunity to bring spatial analysis to a wider audience, moving from it being a tool for the GIS and BI specialists only, to a true tool for all business users.
  • Bi-directional interactivity between map and report
Location intelligence enables users to interact with both map and data, with changes made to the map reflected in the report, and vice versa. For instance, via a graphic geographic representation an insurance company can zoom in on a particular location to identify policyholders who live in the path of a storm or flood plain. The company can use both existing customer information, which will have been geocoded to a position on a map, together with third-party data on weather and climate changes. The user can then zoom in on the map and be presented with report data on the relevant policyholders, and then toggle between the map and report data to locate those policyholders who are most exposed to the risk of a storm or flood.
  • Predictive analytics
Predictive analytics encompasses a variety of techniques from statistics and data-mining that process current and historical data in order to make "predictions" about future events. Predictive analytics enables organizations to gain valuable customer and market insight, to predict, for example, purchasing behavior characteristics for any product or service. Insurance companies use predictive analytics to forecast how long policyholders will live or their likelihood of being involved in a car accident. Incorporating spatial modeling capabilities and techniques and using map visualizations enhances the power of predictive analytics by enabling analysts to quickly identify and explore findings using intuitive visualization techniques.

Businesses continue to be challenged with gaining intelligence from the huge volumes of data they capture and manage. Those that have added location intelligence tools to their BI platform are reaping the benefits through optimization of their operations by analyzing and targeting products or services more effectively. The opportunity for location intelligence lies in capitalizing on the location-specific information that is already available within these data. Now is the time for organizations which have yet to make the move to seriously consider the opportunity that location intelligence presents.

Published Friday, October 5th, 2007

Written by Louella Fernandes

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