What is Situational Intelligence?


By definition, situational intelligence implies several things:

First, “situation” suggests an understanding of what has happened in the past, what is happening now and what might happen in the future.

Next, since situations are inherently complex, they typically involve multiple assets, resources and events, many of which may exist outside the control of an organization.  The ability to correlate disparate data from many different systems and data sources is required to comprehend the scope and impact of situations.

Third, to acquire “intelligence” requires an understanding of what, when, why, how and where something happened or might happen.  Implicit in this understanding are the concepts of spatial analysis (e.g. “what is nearby?”), temporal analysis (e.g. “how has it evolved?”) and nodal analysis (e.g. “what is the impact on other assets/resources?”).

Situational intelligence incorporates and applies data and understanding from six different domains to assist organizations in solving complex, big data problems. These domains are:

Situational Intelligence Components

  • Business Systems
  • Real-time Operations
  • Physical Locations
  • External Data
  • Analytical Models
  • Mobile Data



Situational intelligence systems commonly comprise three components:

  • Data gathering and normalizing: Organizations own and access many separate sources of IT, operations (OT), and external data.  These sources need to be brought together into a single environment and normalized so that they can be combined and correlated.
  • Data correlation and analysis: Once data from appropriate sources is gathered and normalized,  various data sets are correlated and analyzed within specific business contexts to solve problems and uncover new opportunities.
  • Data visualization: Rendering correlated and analyzed information in a combination of geospatial and tradition analytical formats gives users a fast and intuitive way to recognize what decisions must be made and what actions must be taken.

In summary, situational intelligence arms both business and technical personnel with timely and accurate information to make informed real-time decisions.

To learn more about situational intelligence, see this white paper.


Welcome to the Situational Intelligence Blog


The recent advent of wearable digital devices, such as Google Glass and Apple Watch, begs an interesting question: Just how much data can we effectively access and apply in a given situation?

This question grows by orders of magnitude when applied to corporations, governments, and other large organizations. Executives, financial analysts, operations specialists and others now have huge amounts of data available, but lack effective tools to analyze that data quickly and intuitively to solve real-world problems.

When faced with critical decisions and an overwhelming volume and variety of data, how can organizations increase their situational intelligence?

This blog will explore the causes, challenges, effects, solutions and players in analyzing and transforming big data into situational intelligence. While the blog’s focus will be on the business and human aspects of situational intelligence, we’ll include discussions about the technology that can enable improvements to situational intelligence.

We welcome your comments, questions, and submissions.