Onward through the Fog: Uncertainty and Management Adaptation in Systems Analysis and Design

Abstract

Policy analysts have always lived with great uncertainty. We have long had tools for handling some of that uncertainty. But now that policy analysis has been around for a while, work in many fields has fallen into stereotyped problem formulations and analytical approaches. In particular, treatments of uncertainty are typically quite incomplete and often conceptually wrong. This report argues that these shortcomings produce pervasive systematic biases in analyses. Problem formulations suppress uncertainty about the world and ignore the capacity of the analyzed systems to adapt to the unanticipated. System design ignores opportunities to hedge or respond instead of predicting. System evaluation discounts strategies that hedge or respond. Policy analyses change in specific ways if their problems are formulated with a fuller recognition of uncertainty. Management capability -the ability to respond and adapt-becomes a resource, with a cost and an effectiveness, to which funds can be allocated in competition with more familiar uses of funds. Analytical tools change to incorporate options for management. Given that uncertainty is pervasive and generally cannot be counted completely, the logic that connects the analysis to the world changes as well: Our models are not necessarily adequate representations of reality.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1990
Accession Number
ADA256825

Entities

People

  • James S. Hodges

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Attrition
  • Fire Control Systems
  • Logistics
  • Munitions
  • New York
  • Operations Research
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Risk
  • Second World War
  • Storage
  • Systems Engineering
  • Test And Evaluation
  • United States

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Artificial Intelligence
  • Economics