Systems Science asks the question, "What is the relationship between the processes we control and the outcomes we achieve?"

We use principles of systems thinking as well as a variety of evidence-based
conceptual models to better understand complex problems in dynamic environments,
so we can engineer effective solutions.


Key elements of systems science include:

  • Eliminating waste and errors
  • Conducting multi-method needs assessments and root cause analyses
  • Evaluating risk and reliability of designed solutions

Examples of our work in systems science include:

  • Ambulatory Re-Design
  • Always Quiet at Night Root Cause Analysis