Location intelligence is defined as the capacity to organize and understand complex data by using geographic relationships. In other words, we talk about location intelligence when an organization manages to bring together business intelligence (BI) and geographic analysis to discover powerful new insights. And indeed, the primary benefit of location intelligence is comprehensive analytics, not just the ability to see where something happens or exists.

According to industry observers, such as Gartner, vastly improved and more sophisticated analytics represents the next evolutionary step in business intelligence. Moreover, these observers say that adding new capabilities such as spatial analytics maximizes the value of a BI system to expose insights that drive better decision making. In fact, Gartner has for the past 10 years consistently ranked business intelligence as one of the top technology priorities of CIOs. Quite obviously, because business intelligence unites data, technology, analytics, and human knowledge to optimize decision making.

At its most basic level, BI is reporting since it combines data from different systems and repositories (such as sales, marketing, operations, finance, procurement, HR) into a data warehouse, that in turn enables exploration and analysis. However, in recent years, BI has expanded beyond reporting to include predictive analytics, “what-if” scenario analysis, unstructured data analysis, and more, that guide companies in their business ventures.

Simply because any analysis relating to business processes, such as customer relationship management, marketing promotions, service and supply chain optimization, risk management, and operational efficiency, benefits when location and business data combine to make sound data-driven decisions.

Forward-looking organizations are therefore adding spatial analytics and interactive mapping to their BI systems to enhance their decision making and proactively manage their operations.

Visualizing the influence of location on behaviors, activities, and processes improves straightforwardly data-driven decision making.

By Daniela La Marca