Putting the 'where' into your analytics

By Sandra Gittlen, Computerworld |  Business Intelligence, Analytics

At EDENS, a developer, owner and operator of community shopping centers on the East Coast, blending geographic information systems (GIS) and business analytics has enabled a competitive advantage in a fast-paced, crowded market.

The Columbia, S.C.-based company coupled Microsoft SQL Server with Esri's ArcGIS Server and Spatial Database Engine (SDE) to display and analyze its current portfolio of more than a hundred properties and 4,000 other relevant shopping center property locations. EDENS' GIS director, David Beitz, integrates demographic data such as average household income, competition and traffic counts with select map criteria to paint a clear picture for both internal teams and leasing agents to use with potential retailers.

For example, grocery store chains have to closely study trade areas for new development. "They have found that some people just won't cross certain railroad tracks, impacting the site's overall draw," he says. With GIS-enhanced analytics, the development team can quickly rule out some sites -- even if they otherwise appear ideal -- that don't meet specific criteria. "We are able to really hone our presentations and give customers one or two great options. They can tell we've done our homework," he says.

While it's difficult to quantify the impact of GIS data, success is measured by being able to quickly respond to retailers' requests for location and market data to help leasing agents "move a deal forward," Beitz explains. "If you make a retailer wait or provide out-of-date information, then they are more likely to land at another site."

EDENS finds that success is a matter of the quality and quantity of data fed into the analytics system. For instance, though relatively few data points are shared with customers, all information, including confidential prospectus data, is mapped and stored for later use. If the team wants to buy a property down the street from one it looked at in the past, all relevant data is at the ready, avoiding the need to reassemble all the past shopping center and market data. Rapid access makes determination of the soundness of the deal faster and more efficient, Beitz says.

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Originally published on Computerworld |  Click here to read the original story.
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