Intelligence Analysis Behavioral and Social Scientific Foundations (2011) / Chapter Skim
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2 Operations Research and Intelligence Analysis--Edward H. Kaplan
2 Operations Research and Intelligence Analysis--Edward H. Kaplan
Pages 31-56
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From page 31... ...
I close by suggesting some possible applications of these ideas to intelligence analysis, including the use of OR to study the intelligence production process.
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"systems of interest" can be studied using mainstream OR ideas, while operations research can assist in the study of questions that focus more on an adversary's intentions by complementing other methods such as game theory (see Fingar, Chapter 1, and Bueno de Mesquita, Chapter 3, both in this volume) .2 As an example, 2 As will be discussed later, the interdisciplinary field of decision analysis focuses on indi vidual and group decision making; this field includes some operations research ideas, but also relies heavily on research in psychology, economics, and statistics.
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Royal Air Force Operational Research Section employed statistical analysis, deductive methods from the physical sciences, and common sense to analyze both offensive and defensive operations with an eye toward reducing their own casualties while inflicting maximal damage on the enemy (Dyson, 2006)
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, the first published text in the field. In addition to the merchant marine convoy problem discussed earlier, reported applications include finding the best search patterns to locate enemy ships and submarines, evaluating the trade-offs in the following situations: • Using planes as merchant marine escorts and having these same planes bomb U-boat docks; • Attacking enemy ships versus attacking the factories that produce ships; • Determining the required forces of different types to undertake various military operations; • Evaluating rapid maneuvering versus antiaircraft fire to defend warships against Kamikaze suicide plane attacks; • Developing countermeasures to enemy radar; and • Evaluating weapons effectiveness and determining the best methods for using them.
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From page 35... ...
The International Federation of Operational Research Societies boasts 48 active national member societies, and current applications beyond those found in the military abound in both the public and private sectors, as discussed next. SELECTED CURRENT OPERATIONS RESEARCH APPLICATIONS Manufacturing and Supply Chain Management Returning to the definition of OR as the scientific study of operations for the purpose of making better decisions, manufacturing operations 4 Some operations research programs can also be found within or in conjunction with mathematics or statistics departments.
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-- such as suppliers, manufacturers, and retailers, each with their own incentives -- to better coordinate entire supply chains? These questions and more fall within the subfield of manufacturing and supply chain management.
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; operations researchers typically apply queueing (or waiting line) theory to this type of problem (Gross et al., 2008)
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30) ; • Weyerhaeuser operations researchers solved the problem of " .
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THE OPERATIONS RESEARCH APPROACH TO PROBLEM SOLVINg How do operations researchers get started with a new project? Leaving to the side purely mathematical studies meant to improve the quantitative methods of OR, the goal of an applied study is to improve decision making.
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From page 40... ...
Understanding the environment and/or system in question requires substantive expertise. Such expertise is often best gained via direct observation, which is why operations researchers have been known to ride around in police patrol cars, spend time on factory floors or in warehouses, or observe the formation and dissipation of lines at banks, on highways, in call centers, or at Disney World.
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From page 41... ...
, one should be aware that the methods themselves are active subjects of research among mathematical operations researchers, and new extensions and results for these techniques continue to be discovered. Optimization problems involve the maximization or minimization of some objective function (e.g., maximize profit, minimize cost)
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From page 42... ...
. Another point of intersection is with rational choice and game theory models in economics and political science, which proceeds under the assumption that individuals behave as if they are experts at solving decision analysis problems and regularly do so in their strategic decision making (see Bueno de Mesquita, this volume, Chapter 3)
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From page 43... ...
On the other hand, if the incremental benefit is much larger than the incremental cost, unless one is quite certain that the risky alternative will fail, it appears advantageous to "go for it." 0 Status Quo Go/No Go Success b p Risky Alternative Failure -c 1−p FIgURE 2-1 Go/no go decision tree. p = Probability of risky alternative succeeding c = Cost b = Benefit
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From page 44... ...
Conversely, a riskprone decision maker might not be willing to part with this gamble unless offered at least, say, $6. Decision analysis offers both methods for assessing whether a decision maker is risk averse or risk prone (or risk neutral for that matter)
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This is an example of what operations researchers call random incidence (or length-biased sampling in statistical parlance)
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In the HIV prevention example, this rule says that prevention programs should be funded in order of most to least infections prevented per dollar (Institute of Medicine, 2001)
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A common problem faced by project managers is to schedule the various activities that must be completed to finish a project. The term "project" can be interpreted quite broadly, with examples ranging from construction projects to fundraising campaigns to weapons development programs to terror attacks.
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In this field a preliminary analysis based on incomplete data may often be much more valuable than a more thorough study using adequate data, simply because the crucial decisions cannot wait on the slower study but must be based on the preliminary analysis. The big improvements often come from the first quick survey of a new field; later detailed study may only gain small additional factors." Given the military origins of OR and both the military and systems aspects of intelligence analysis, it should not prove surprising that operations research has been applied to intelligence analysis on occasion.
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From page 49... ...
all discuss the use of basic probability models, including Bayes' Rule, with an eye toward assessing the likelihoods of various events or "states of affairs," but there is no focus on operations in this otherwise engaging work. Operations ideas are almost entirely absent from intelligence analysis primers distributed by national intelligence agencies (Defense Intelligence Agency, 2008; U.S.
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, interdicting these activities can still delay the overall project by 34 percent. Again, the idea is not that this model tells intelligence analysts the precise state of a proliferator's nuclear weapons program, but it does suggest which production activities are crucial in the overall development project, and consequently what parameters might deserve a more focused intelligence effort.
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The relationships between the instigation and planning of terror attacks and the use of undercover intelligence agents can be characterized using queueing theory. Viewing terror plots as the "customers" and undercover agents as the "servers," queueing theory allows one to estimate the number of waiting customers based on the servers' utilization in a manner analogous to how one might estimate the number of waiting customers in a call center from the utilization of servers there (Kaplan, 2010)
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From page 52... ...
Example: Modeling Intelligence Operations The production of intelligence analysis can itself be viewed as a process characterized by oft-repeated operations of different types. For example, at the macro level, one can ask whether the "intelligence cycle" -- requirements planning, data collection, data processing and exploitation, intelligence analysis and the production of intelligence reports, and product dissemination to government or military decision makers (the "consumers")
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From page 53... ...
and dissemination capability needed to handle the volume of new product that would be produced by a UAS investment." As another example, consider the allocation of intelligence analysts to different geographic regions of interest, or to different intelligence problem sets. The allocation of workers to tasks forms the basis for a classic OR model known as the assignment problem (Ahuja et al., 1993; Hillier and Lieberman, 2010)
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1999. Psychology of intelligence analysis.
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1983. The principles and applications of decision analysis (2 vols)
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2009. A tradecraft primer: Structured analytic techniques for improving intelligence analysis.
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