Structured analytic techniques for intelligence analysis free download

Richard J. Kilroy, Jr. Coastal Carolina University. Christopher K. University of Groningen. Charles E. University of Detroit Mercy. Key features.

For instructors. Select your digital copy vendor:. Using the analytic techniques contained in this primer will assist analysts in dealing with the perennial problems of intelligence: the complexity of international developments, incomplete and ambiguous information, and the inherent limitations of the human mind.

Understanding the intentions and capabilities of adversaries and other foreign actors is challenging, especially when either or both are concealed. Moreover, transnational threats today pose even greater complexity, in that they involve multiple actors--including nonstate entities--that can adapt and transform themselves faster than those who seek to monitor and contain them. Finally, globalization has increased the diversity of outcomes when complex, interactive systems such as financial flows, regional economies or the international system as a whole are in flux.

The first hurdle for analysts is identifying the relevant and diagnostic information from the increasing volume of ambiguous and contradictory data that is acquired through open source and clandestine means. Analysts must also pierce the shroud of secrecy--and sometimes deception--that state and nonstate actors use to mislead. A systematic approach that considers a range of alternative explanations and outcomes offers one way to ensure that analysts do not dismiss potentially relevant hypotheses and supporting information resulting in missed opportunities to warn.

Cognitive and perceptual biases in human perception and judgment are another important reason for analysts to consider alternatives. As Richards Heuer and others have argued, all individuals assimilate and evaluate information through the medium of "mental models" sometimes also called "frames" or "mind-sets".

These are experience-based constructs of assumptions and expectations both about the world in general and more specific domains. These constructs strongly influence what information analysts will accept--that is, data that are in accordance with analysts' unconscious mental models are more likely to be perceived and remembered than information that is at odds with them.

Mental models are critical to allowing individuals to process what otherwise would be an incomprehensible volume of information. Yet, they can cause analysts to overlook, reject, or forget important incoming or missing information that is not in accord with their assumptions and expectations.

Seasoned analysts may be more susceptible to these mind-set problems as a result of their expertise and past success in using time-tested mental models.

The key risks of mindsets are that: analysts perceive what they expect to perceive; once formed, they are resistant to change; new information is assimilated, sometimes erroneously, into existing mental models; and conflicting information is often dismissed or ignored. Intelligence analysts should be self-conscious about their reasoning processes.

They should think about how they make judgments and reach conclusions, not just about the judgments and conclusions themselves. Pherson showcase fifty-five structured analytic techniques—five new to this edition—that represent the most current best practices in intelligence, law enforcement, homeland security, and business analysis.

Author : U. Moreover, transnational threats today pose even greater complexity, in that they involve multiple actors-including nonstate entities-that can adapt and transform themselves faster than those who seek to monitor and contain them. Analysts must also pierce the shroud of secrecy-and sometimes deception-that state and nonstate actors use to mislead.

These constructs strongly influence what information analysts will accept-that is, data that are in accordance with analysts' unconscious mental models are more likely to be perceived and remembered than information that is at odds with them.

Structured analysis is a relatively new approach to intelligence analysis with the driving forces behind the use of these techniques being:.

In general, the Intelligence Community began focusing on structured techniques because analytic failures led to the recognition that it had to do a better job overcoming cognitive limitations, analytic pitfalls, and addressing the problems associated with mindsets. Structured analytic techniques help the mind think more rigorously about an analytic problem. In the geospatial realm, they ensure that our key geospatial assumptions, biases, and cognitive patterns are not just assumed correct but are well considered.

The use of these techniques later helps to review the geospatial analysis and identify the cause of any error. Moreover, structured techniques provide a variety of tools to help reach a conclusion. Even if both intuitive and scientific approaches provide the same degree of accuracy, structured techniques have value in that they can be easily used to balance the art and science of their analysis.

It is clear is that structured methodologies are severely neglected by the geospatial community. Even in the rare cases where a specific technique is used, no one technique is appropriate to every step of the problem solving process.

There are two ways to view the nature of these techniques. Heuer categorized structured techniques by how they help analysts overcome human cognitive limitations or pitfalls to analysis. Heuer's grouping is as follows:. These different groupings of the techniques notwithstanding, the analysts should select the technique that best accomplishes the specific task they set out for themselves.

The techniques are not a guarantee of analytic precision or accuracy of judgments; they do improve the usefulness, sophistication, and credibility of intelligence assessments.