“Collection” is one of the phases that is in every model of the “Intelligence Cycle”, whether that specific model is a 4, 5, 6, or even 7 step model. Even in the models of analysis that are not intelligence focused, collection of data is paramount. I’m going to argue that HUMINT and GEOINT are the most important methods of collection in pursuing our national strategy.
There are almost as many models of the “Intelligence Cycle” as there are arguments against considering the “Intelligence Cycle” as a cycle. Wheaton (2014) points out both the variety of models and his greatest objection, the lack of input from decision makers.
What seems to be missing in criticism of the cycle model is that it is a MODEL...it is something to teach for a basic understanding of the process...it is not a step-by-step procedure. Nor is the only way to approach intelligence problems. It is the first step in the learning process.
Collection of data is central in related concepts of decision-making and analysis. There is the OODA loop (Observe – Orient – Decide – Act) made famous by John Boyd. There is the generalized version of the Johari Window(“Johari window,” 2019): this has not been formalized in any sense, but Hulnick (2006) references Secretary Rumsfeld's use of “unknown unknowns”. Taking away from the Johari use of this model from self-analysis specifically, we can see how this model can show how we need to approach finding out what we need to know. Finally, there is scientific method. There is a definite similarity between these models and the “Intelligence Cycle” in which collection of data plays the key part.
HUMINT should be regarded as the most important type of collection. The primary reason that I argue this point is that HUMINT can explain things in context. Gallagher (2011) suggests that HUMINT is “critical to ensuring that information quantity does not supplant information quality” and “can obtain information that more technologically-oriented assets cannot”. Noting that Gallagher is discussing theatre intel, not at the natsec level, his points still stand. HUMINT is harder to collect (Margolis, 2013), but that is traded off by it’s benefits. Sayre (2004) points out that Allen Dulles had a set of requirements for HUMINT collectors; “HUMINT collectors ought to have great integrity, be receptive to and understanding of foreign points of view, and be able to work well with people under difficult conditions.” These qualifiers can partially explain the quality of HUMINT. Understanding HOW and /or WHY an OPFOR (or any competing influence) decision has been made can aid the policy maker in determining the best action to take.
While Johnson (2011) acknowledges the difficulties of HUMINT collection, he also stresses that it is critical to national security, and suggests improvements to HUMINT collection as he discusses strengthening American intelligence capability.
GEOINT is the second most important type of collection. GEOINT can be simply explained as linking events to place (“Discovering the Unknowns,” 2014). For a more complicated look at what GEOINT entails, we can compare the legal definition (or how the IC defines it) to a more practical definition.
“The term ‘geospatial intelligence’ means the exploitation and analysis of imagery and geospatial information to describe, assess, and visually depict physical features and geographically referenced activities on the Earth. Geospatial intelligence consists of imagery, imagery intelligence, and geospatial information.” (Clapper, 2005).
vs.
“Geospatial Intelligence is a field of knowledge, a process, and a profession. As knowledge, it is information integrated in a coherent space-time context that supports descriptions, explanations, or forecasts of human activities with which decision makers take action. As a process, it is the means by which data and information are collected, manipulated, geospatially reasoned, and disseminated to decision-makers. The geospatial intelligence profession establishes the scope of activities, interdisciplinary associations, competencies, and standards in academe, government, and the private sectors.”
(Bacastow and Bellafiore, 2009)
Note - I rely on Wiki’s quote of this source, as I was unable to locate a copy of this source
GEOINT is at the other end of the spectrum from HUMINT in ease of collection, as another benefit of GEOINT is is adaptability to tech advantages such as automation and data-mining. The following quote should either have you licking your chops or trembling in fear, depending on whether you see yourself as a producer of, or a target of, intelligence.
“In addition to imagery, consider the wide variety of other location-based data being generated every day by human and machine activity. Reflect on the activities and interactions of people revealed in social media. Factor in the location information intrinsic to telecommunications traffic—particularly mobile. Add the measurements and actions of infrastructure elements managed with Supervisory Control and Data Acquisition systems. Couple that with the engineering information contained within infrastructure asset inventories. Add geo-tagged banking and point-of-sale transactions. Finally, at a high level, integrate the economic and social information contained within census data.”
(The United States Geospatial Intelligence Foundation, 2017)
In personal discussion with a former intel guy with the U.S. Army in Iraq, one method of locating jihadis was to identify their use of their cell phones through SNA, then simply locate that phone signal.
GIS software allows management, analysis, and distribution of GEOINT in conjunction with other collection sources, returning us to the simple summary of it’s purpose, linking event to place.
To close with, I’ll make two points:
First, all collection sources must be considered in intel analyis. For example, Cozine (2013), while discussing how to teach intelligence, notes that in the capture of Bin Laden, “GEOINT collected from the sky was combined with HUMINT collected on the ground to determine the best method to launch such an assault.”
Second, I noted in my reading that some argument was often made in favor of one method or another to mitigate deception or disinfo. All methods are subject to deception technique, and this highlights the value of multiple sources to compare data.
REFERENCES:
Bacastow, T.S, and Bellafiore, D.J. (Fall 2009). Redefining geospatial intelligence; American Intelligence Journal,
Clapper, J. (2005). Statutory definition of geospatial intelligence and its amplification. Retrieved from National Geospacial-Intelligence Agency website: https://gwg.nga.mil/ntb/related/GEOINT_Definitions-Amplification_Memosigned.pdf
Cozine, K. (2013). Teaching the intelligence process: The killing of Bin Laden as a case study. Journal of Strategic Security; San Jose, 6(5), 80–87. http://dx.doi.org.ezproxy2.apus.edu/10.5038/1944-0472.6.3S.9
Discovering the unknowns: The importance of geospatial intelligence. (2014, February 12). Retrieved October 21, 2019, from GovLoop website: https://www.govloop.com/discovering-the-unknowns-the-importance-of-geospatial-intelligence/
Gallagher, M. (2011, June 5). Human intelligence in counterinsurgency: persistent pathologies in the collector-consumer relationship. Retrieved from Small Wars Journal website: https://pdfs.semanticscholar.org/237f/7956e55876c66697513b89ed433dcc35b9bf.pdf
Hulnick, A. S. (2006). What’s wrong with the intelligence cycle. Intelligence & National Security, 21(6), 959–979.
Johari window. (2019). In Wikipedia. Retrieved from https://en.wikipedia.org/w/index.php?title=Johari_window&oldid=921867231
Johnson, L.K. (2011). A framework for strengthening U.S. intelligence. Yale Journal of International Affairs Volume 1: 116-131 http://yalejournal.org/wp-content/uploads/2011/01/061210johnson.pdf
Margolis, G. (2013). The lack of HUMINT: A recurring intelligence problem. Global Security Studies, 4(2), 18.
Sayre, R. A. (2004). Some principles of human intelligence and their Application. United States Army Command and General Staff College, Fort Leavenworth, Kansas.
The United States Geospatial Intelligence Foundation. (2017). The state and future of GEOINT 2017. Retrieved from https://usgif.org/system/uploads/4897/original/2017_SoG.pdf
Wheaton, K. J. (2014, June 6). Thinking in parallel: A 21st century vision of the intelligence process. Retrieved August 30, 2019, from Sources And Methods website: https://sourcesandmethods.blogspot.com/2014/06/thinking-in-parallel-21st-century.html