Quantitative Intelligence Analysis

Title:                      Quantitative Intelligence Analysis

Author:                  Edward Waltz

Waltz, Edward (2014). Quantitative Intelligence Analysis: Applied Analytic Models, Simulations And Games. Lanham, MD: Rowman & Littlefield Publishers, Inc.

LCCN:    2014027175

JF1525.I6 W395 2014


  • The intelligence analyst and synthesis — Modeling in intelligence — Mental models in intelligence analysis — Translating mental models to explicit sharable models — Explicit models in structured and quantitative analysis — Explicit models of analytic thinking — Explicit models of the targets of analysis — Analytic wargaming in intelligence — Model-based support to collection and operations — Implementing the discipline of explicit quantitative modeling and analytic gaming.


Date Posted:      March 24, 2017

Reviewed by Hayden B. Peake[1]


In his foreword to Quantitative Intelligence Analysis, former DDI and NIC chairman John Gannon observes that, “In my early years as an analyst and manager…individual brainpower and expertise were the coin of the realm. Methodological approaches, by contrast, assumed time-consuming and credit-sharing collaboration, which was less valued.” He sums up the situation saying, “This undercurrent of resistance to tools and techniques both from individual analysts and the bureaucracy itself, was endemic in the Community into the 1990s.” (p. xx)[2]

Since then, the advancing information age and the high volume of data involved in analysis has imposed changes in that approach. Today, Intelligence Community analysts routinely employ state-of-the-art, structured analytic techniques such as those described by Richards Heuer and Randolph Pherson.[3] “Brain-power,” writes Gannon, “is now viewed as enhanced by the rigor of modeling, dynamic simulations, and interactive games that are the wave of the Intelligence Community’s collaborative future.” (p. xxii)

In Quantitative Intelligence Analysis, Dr. Edward Waltz, a senior researcher at Virginia Tech University who has studied these new methods, provides the conceptual background and illustrates the practical application of these techniques in the form of models. The models Waltz has devised “refer to the detailed and often technical descriptions or representations of the analysts’ thinking” about the subjects with which he is confronted. (p. 1)

Waltz defines the models in the analyst’s mind as implicit and those in words, graphics, or on a computer terminal as explicit. He goes on to explain their limitations—how implicit mental models are transformed into explicit computer models, and how they are applied to intelligence problems. The models discussed are illustrated with graphic representations and narrative explanations of what the analyst is thinking or the computer is executing. Then he devotes chapters to show how they are used in target analysis, wargaming, and collection operations that illustrate the power they confer on collaborative work and how teams interact. He offers “case studies” to clarify the process.

A word of caution is warranted here: the procedures illustrated by graphic representations are rather complex. Moreover, the case studies are very general, which is to say that this is not a primer. The quantitative aspect of the book refers to mathematical probability and statistical methods used to evaluate data, but for the most part no detailed explanation of the underlying mathematics is included. He only describes their functions. (p. 131)

Quantitative Intelligence Analysis is not a step-by-step, how-to book and is probably best suited for the  classroom or for experienced analysts who haven’t employed these techniques in their work. But it does demonstrate the complexity of modern analytic procedures; the potential value of team analysis; and the extensive technical support now required compared to the John Gannon era. In that sense it reveals what modern intelligence analysis has become.

[1] Peake, Hayden in The Intelligencer: Journal of U.S. Intelligence Studies (22, 3, Winter 2016-17, pp. 121-122). Hayden Peake is the Curator of the CIA’s Historical Intelligence Collection. He has served in the Directorate of Science and Technology and the Directorate of Operations. Most of these reviews appeared in recent unclassified editions of CIA’s Studies in Intelligence, Other reviews and articles may be found online at http://www.cia.gov

[2] See Jack Davis, “Why Bad Things Happen to Good Analysts,” at https://www.cia.gov/library/center-for-the-study-of-intelligence/csi-publications/csi-studies/studies/vol-60-no-3/davis-why-bad-things-happen-to-good-analysts.html from his chapter in George, Roger Z. (2014) and James B. Bruce, eds. Analyzing Intelligence: National Security Practitioners’ Perspectives, 2nd ed. Washington, DC: Georgetown University Press, which describes his view of the pressures on analysts that have led to biased analyses.

[3] Richards J. Heuer Jr. (2011) and Randolph H. Pherson. Structured Analytic Techniques for Intelligence Analysis . Washington, DC: CQ Press

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