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Describing and Valuing Interventions That Observe or Control Decision Situations

Author

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  • David Matheson

    (SmartOrg, Inc., 855 Oak Grove Avenue, Suite 202, Menlo Park, California 94025)

  • James E. Matheson

    (SmartOrg, Inc., 855 Oak Grove Avenue, Suite 202, Menlo Park, California 94025, and Department of Management Science and Engineering, Stanford University, Stanford, California 94305-4026)

Abstract

The value of information and value of control calculations have long been two separate parts of a decision analyst’s efforts to extract as much insight as possible from a decision model. This paper unifies these concepts as interventions that modify the structure of the original problem, which have two key properties, purity and quality. Purity is an idealization that leads to Howard canonical form, clarifies the definition of control intervention, and allows us to extend and correct the calculation of the value of control. Quality is a characteristic that leads to generic models of imperfect intervention, which, because of their equivalence to any pure intervention, prevent misguided recommendations when the value of a perfect intervention is high but the value of a somewhat imperfect intervention is low. Quality is a number between 0 and 1 that normalizes and allows comparison of imperfect interventions between applications having very different value scales.

Suggested Citation

  • David Matheson & James E. Matheson, 2005. "Describing and Valuing Interventions That Observe or Control Decision Situations," Decision Analysis, INFORMS, vol. 2(3), pages 165-181, September.
    • Handle: RePEc:inm:ordeca:v:2:y:2005:i:3:p:165-181
    DOI: 10.1287/deca.1050.0045
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    References listed on IDEAS

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    1. James E. Smith & Samuel Holtzman & James E. Matheson, 1993. "Structuring Conditional Relationships in Influence Diagrams," Operations Research, INFORMS, vol. 41(2), pages 280-297, April.
    2. Allen C. Miller, 1975. "The Value of Sequential Information," Management Science, INFORMS, vol. 22(1), pages 1-11, September.
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    Cited by:

    1. L. Robin Keller, 2007. "From the Editor..," Decision Analysis, INFORMS, vol. 4(3), pages 111-113, September.
    2. Jason R. W. Merrick & Fabrizio Ruggeri & Refik Soyer & L. Robin Keller, 2012. "From the Editors---Games and Decisions in Reliability and Risk," Decision Analysis, INFORMS, vol. 9(2), pages 81-85, June.
    3. L. Robin Keller, 2009. "From the Editor..," Decision Analysis, INFORMS, vol. 6(3), pages 121-123, September.
    4. L. Robin Keller, 2008. "From the Editor..," Decision Analysis, INFORMS, vol. 5(3), pages 113-115, September.
    5. L. Robin Keller & Ali Abbas & Manel Baucells & Vicki M. Bier & David Budescu & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Ahti Salo & George Wu, 2010. "From the Editors..," Decision Analysis, INFORMS, vol. 7(4), pages 327-330, December.
      • L. Robin Keller & Manel Baucells & Kevin F. McCardle & Gregory S. Parnell & Ahti Salo, 2007. "From the Editors..," Decision Analysis, INFORMS, vol. 4(4), pages 173-175, December.
      • L. Robin Keller & Manel Baucells & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Gregory S. Parnell & Ahti Salo, 2008. "From the Editors..," Decision Analysis, INFORMS, vol. 5(4), pages 173-176, December.
      • L. Robin Keller & Manel Baucells & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Gregory S. Parnell & Ahti Salo, 2009. "From the Editors ..," Decision Analysis, INFORMS, vol. 6(4), pages 199-201, December.
    6. L. Robin Keller, 2012. "From the Editor---Decisions over Time (Exploding Offers or Purchase Regret), in Game Settings (Embedded Nash Bargaining or Adversarial Games), and in Influence Diagrams," Decision Analysis, INFORMS, vol. 9(1), pages 1-5, March.
    7. Rakesh K. Sarin, 2013. "From the Editor —Optimal Betting, Reducing Unnecessary Mammography in Breast Cancer Diagnosis, Product Line Design, and Value of Information," Decision Analysis, INFORMS, vol. 10(3), pages 187-188, September.

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