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Quantitative Approaches to Representing the Value of Information within the Intelligence Cycle

Author

Listed:
  • Christopher M. Smith

    (TRADOC Analysis Center, Monterey, CA, USA)

  • William T. Scherer

    (Department of Systems and Information Engineering, University of Virginia Charlottesville, VA, USA)

  • Andrew Todd

    (Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA, USA)

  • Daniel T. Maxwell

    (KaDSci, LLC, Springfield, VA, USA)

Abstract

The authors propose that valuation of information metrics developed near the end of the intelligence cycle are appropriate supplemental metrics for national security intelligence. Existing information and decision theoretic frameworks are often either inapplicable in the context of national security intelligence or they capture affects from inputs aside from just the information or intelligence. Applied information theory looks at the syntactic transmission of information rather than assigning it a quantitative value. Information economics determines the market value of information, which is also inapplicable in a national security intelligence context. Decision analysis can use the value of information to show the expected value of perfect information (EVPI) and the expected value of imperfect information (EVII) and although this method can be used with utility theory and not just monetary objectives, it has been shown that decision makers within the intelligence community (IC) have difficulty agreeing upon how to value objectives within analysis. Additionally, it is difficult to determine how decision makers use intelligence in the decision-making process, which makes existing decision theoretic methods problematic, and might include inputs from variables besides just the intelligence.

Suggested Citation

  • Christopher M. Smith & William T. Scherer & Andrew Todd & Daniel T. Maxwell, 2015. "Quantitative Approaches to Representing the Value of Information within the Intelligence Cycle," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 6(4), pages 1-21, October.
  • Handle: RePEc:igg:jsds00:v:6:y:2015:i:4:p:1-21
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