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January 21, 2015

Making the Business Case for Location Analytics

What role, if any, could locations analytics–defined as the ability to gain insight from the location or geographic component of business data–play in enhancing the value of business intelligence?

The answer to the geo-data puzzle, according to a proponent of this business intelligence approach, has three parts. San Diego-based Centigon Solutions Inc. argues that combining business and geographical data can unlock insights but most organizations don’t know where to begin.

The company is of course offering a roadmap for how to apply location analytics.

In one use case, Centigon’s mapping analytics tool was used to provide an overall view of infrastructure along an earthquake- and tsunami-prone coastline of eastern Japan. Simple calculations were applied in order to rate facilities based on criteria like water shortages, displaced employees and related factors.

The business intelligence product was a “geographic risk scorecard” that could be used to mitigate risks by comparing a user’s facilities to others unaffected by disasters like earthquakes and tsunamis.

In this use case, the diagnostic tool eliminated the need to “hunt and peck” for data, Centigon claimed, allowing the user to more quickly determine the level of risk and how to mitigate that risk.

In another use case, a large heavy equipment vendor that leverages the GPS location of its products also applied rapidly updated geo-data to reduce its sales cycle. Using real-time location data allowed the equipment vendor to determine the availability and cost of relocating machinery to far-flung work sites.

Location intelligence, Centigon asserts, can help organizations track and prioritize assets. The result, it says, are faster decision-making and reduce costs for customers.

In a third use case example, business and geographic data were combined from different sources to come up with new insights. In this example, a New York City logistics company combined location data about where its drivers were getting the largest parking tickets on the city’s clogged streets. The combined data gauged the cost of parking tickets issued by the city’s transit cops in public parking zones and areas designated as loading zones.

“Combining parking ticket data with city transit data allowed the

logistics team to understand where excessive tickets occurred,” Centigon said, “and how to recommend alternative solutions.”

The resulting cost savings were attributed to having a visual aid that was used to direct company drivers to spots where, if they were ticketed, it wouldn’t cost the logistics company as much.

The geo-data vendor is also pitching its analytics solution to asset managers, including real estate, fleet management and shipping containers. Centigon claims location intelligence combined with other layers of business data saves time and money when comparing asset performance.

The company rolled out a new version of its CMaps Analytics Designer on Jan. 17 that includes, among other enhancements, new layer types.

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