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IDA takes a comprehensive simulation-driven approach to map out all aspects of sustainment and their effects on readiness outcomes

Robust Data-Driven Decision Making


Data visualization / dashboards

  • Quickly provides ground truth
  • Good for diagnosing shortcomings
  • Can’t make predictions
  • Can’t tie decisions to outcomes


Correlative studies

  • Statistical approaches including machine learning
  • Historical trends can reveal which factors may drive performance
  • Not enough details to support decision-making using “what-if” scenarios

DoD does very little of this approach →


End-to-end simulation

  • Explicitly model all aspects of sustainment (spares, manpower, operations, maintenance)
  • Make predictions on how specific investments cause changes in readiness
  • Model quality is contingent on data quality
  • Heavy initial lift to build the model