After the failure of geographic information systems (GIS) to catch the eye of corporate computing, a new breed of location intelligence (LI) software is poised to make its play in the enterprise. The convergence of LI with business intelligence (BI) to support decision making was discussed in some depth at the recent Location Intelligence 2008 conference in Santa Clara, California. Convergence is being driven by Web 2.0 mashups that connect BI to online LI services like Google Maps and Microsoft Virtual Earth to overcome the traditional cost and complexity of GIS development. But LI still has to overcome some significant technical and organisational hurdles before it becomes a fixture in mainstream corporate computing environments. LI and BI technologies have evolved in parallel universes. LI is the new term for what used to be called geographic information systems, or GIS - a 'proprietary' tagged technology that hasn't yet been accepted as part of the fabric of mainstream business applications. In contrast, BI technology has advanced much further, showing the hallmarks of a mature technology - declining development complexity and cost, better usability and rising user adoption. But it still hasn't fulfilled its potential - less than 20% of corporations still use BI regularly. Marrying BI to the power of freely and widely available services like Google Maps promises to solve the 'last mile' challenge in BI - that is, getting more people involved in analysis of the business. Yet this marriage has never been fully consummated, even though over 80% of corporate data has some kind of geographic element attached to it. Location data still remains grossly underutilised in corporate environments.
That's slowly changing now. Widespread consumer adoption of online mapping services (350 million downloads of Google Earth to date), a multiplying (almost daily) number of location-focused data sources (RFID, spatial databases, geo-coded documents, etc) and advances in wireless and remote sensor technologies that get data to and from virtually anywhere now presents a promising set of business and technical drivers for pulling LI into enterprise IT infrastructures. The advent of web services and mashups has also simplified what used to be complex development of GIS with modular plug-and-play software that is cheaper to implement. Web 2.0 applications for the masses have also made location technologies more prevalent on the Web - Google Maps on Craigslist, for example, has raised more user awareness of LI than all the stuffy marketing around GIS for the past twenty years. Location enabling enterprise applications like BI is clearly a white space. But LI first has to address several technical and mental challenges. The first is to move LI away from the proprietary GIS front ends of yesteryear (a huge roadblock to adoption and use). The key is integrating LI into desktop business applications and processes that workers are already used to working with. In other words, LI should not be sold as another technology - companies aren't looking to buy maps or force users to learn a new tool. Rather they want to include LI as part of existing applications or processes to solve real-world business problems. While it's true that LI has a mature set of technologies supporting it, pushing it to the enterprise without a compelling business case or paying attention to customer demand and need is the wrong way to go.
Data access, at least affordable access, is another barrier that has kept LI stuck in the mud. LI is unique in that it needs a full set of reference data that is not always readily available or cheap. Data integration and quality are also sticky issues for LI since it usually comes from a multitude of proprietary data sources. The issue of data quality is something that LI vendors try to cake over. They do so at their peril. Data quality doesn't go away in a map - in fact it becomes more apparent. Fortunately, specialist companies like Safe Software are starting to address issues of getting geo-location data to match, and geo-coding techniques are also getting more sophisticated. That's making the underlying spatial reference layer more accurate and consistent.
Evolving standards for geospatial data is another hurdle. The Open Geospatial Consortium (OGC) continues to make steady, if slow, progress to providing codified standards for spatial IT infrastructures that enable interoperability between applications and data. In addition, maturing standards like ESB and XML and flexible SOA architectures and APIs are also opening up ways for LI systems and data to interact with applications like BI. Finally, and perhaps most important of all, is a need to break away from the 'them and us' mindset. LI isn't the 'centre of the universe', in spite of the value location-based data can add to the enterprise mix. Nor should location data be siloed into a special database and specialised set of IT skills. Technically, location data should be treated no differently from other enterprise data streams. In short, LI needs to break away from its clique mentality and start listening more to the rest of the IT industry.
