Geospatial analysis can be very difficult to do well. Much of the difficulty is cognitive and not related to an individual's ability to use the technical tools, i.e., GIS. It takes far greater mental agility than gathering evidence supporting a single hypothesis that was pre-judged as the most likely answer. To develop and retain multiple spatial schemes in working memory and note how each item of information fits into each hypothesis is beyond the mental capabilities of most analysts. (Note: Working memory tasks include the active monitoring or manipulation of information or behaviors.)
Moreover, truly good geospatial analysis requires monitoring your progress, making changes and adapting the ways you are thinking. It is about self-reflection, self-responsibility, and initiative to achieve the analytic results within the time allotted. This mental agility can be accomplished with the help of a few simple thinking tools discussed here.
Heuer makes three important points relative to intelligence in his work, the Psychology of Intelligence Analysis [1].
He provides the following series of images to illustrate how poorly we are cognitively equipped to accurate interpret the world.
Question #1: What did you see in the figure? The answer is at the bottom of this page.
Question #2: Look at the drawing of the man in the upper right. Are the drawings all of men? The answer is at the bottom of this page.
Question #3: What do you see—an old woman or a young woman? The answer is at the bottom of this page.
Now look to see if you can reorganize the drawing to form a different image of a young woman, if your original perception was of an old woman, or of the old woman if you first perceived the young one.
According to Heuer, and as the above figures illustrate, mental models, or mindsets, or cognitive patterns are essentially the analogous image by which people perceive information. Even though every analyst sees the same piece of information, it is interpreted differently due to a variety of factors. In essence, one's perceptions are morphed by a variety of factors that are completely out of the control of the analyst. Heuer sees these cognitive patterns ;as potentially good and bad for the analyst. On the positive side, they tend to simplify information for the sake of comprehension but they also bias interpretation. The key risks of mindsets are that:
Therefore, since all people observe the same information with inherent and different biases, Heuer believes an effective analysis method needs a few safeguards. The analysis method should:
What is required of analysts is a process for challenging, refining, and challenging their own working mental models. This is a key component of his Structured Analytic Techniques (SATs), which include Analysis of Competing Hypotheses.
These problems notwithstanding, cognitive patterns 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 mindset problems as a result of their expertise and past success in using time-tested mental models.
Answer #1: The article is written twice in each of the three phrases. This is commonly overlooked because perception is influenced by our expectations about how these familiar phrases are normally written.
Answer #2: The above figure illustrates that mind-sets tend to be quick to form but resistant to change by showing part of a longer series of progressively modified drawings that change almost imperceptibly from a man into a woman. The right-hand drawing in the top row, when viewed alone, has equal chances of being perceived as a man or a woman.
Answer #3: The old woman’s nose, mouth, and eye are, respectively, the young woman’s chin, necklace, and ear. The old woman is seen in profile looking left. The young woman is also looking left, but we see her mainly from behind so most facial features are not visible. Her eyelash, nose, and the curve of her cheek may be seen just above the old woman’s nose.
Structured analytic techniques are simply a "box of tools" to help the analyst mitigate the adverse impact on analysis of one's cognitive limitations and pitfalls. Taken alone, they do not constitute an analytic method for solving geospatial analytic problems. The most distinctive characteristic is that structured techniques help to decompose one's geospatial thinking in a manner that enables it to be reviewed, documented, and critiqued. "A Tradecraft Primer: Structured Analytic Techniques for Improving Intelligence Analysis [2]" (CIA, 2009) highlights a few structured analytic techniques used in the private sector, academia, and the intelligence profession.
Structured thinking in general and structured geospatial thinking specifically is at variance with the way in which the human mind is in the habit of working. Most people solve geospatial problems intuitively by trial and error. 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:
Others have grouped techniques by their purpose:
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.
It is often difficult for an analyst to determine the next step in an analytic process or to visualize how various techniques and tools fit together. Using the below as a list of the common GIS operations, the analyst might use:
The Structured Geospatial Analytic Method (SGAM) provides the means to relate the analytical step to the Structured Analytic Technique (SAT) and then to the appropriate geospatial operation. The following table summarizes this mapping:
Structured Geospatial Analytic Method Step |
Structured Analytic Technique | GIS Operation |
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Step 1: Question |
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Step 2: Grounding
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Step 3: Hypothesis Development |
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Step 4: Evidence Development |
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Step 5: Fusion |
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Step 6: Conclusions |
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The Intelligence Community began to use structured techniques because of analytic failures related to cognitive limitations and pitfalls or biases. The use of SATs does not guarantee getting intelligence analysis right, because there are so many uncertainties. SATs help to reduce the frequency and severity of error. These include SATs that partially overcome cognitive limitations, address analytic pitfalls, and confront the problems associated with mindsets. SATs help the mind think more rigorously about an analytic problem. Specifically, they ensure that assumptions, preconceptions, and mindsets are not taken for granted but are explicitly examined and tested. The use of SATs also helps to review the analysis and identify the cause of any error.