Cognitive Bias in Engineering Decision-Making (APPEL-CBED)


  • Lessons Learned for Mission Success
    Lessons Learned for Mission Success

This one-day course will use case studies to enable participants to identify the central role that poor communication and cognitive biases can play in mishaps, accidents, anomalies, and failures. The case study method will help participants understand how decision-making can be compromised at all levels in an organization through reliance on heuristics (mental shortcuts) such as groupthink, optimism bias, confirmation bias, and the normalization of deviance. Case explored during this course include the following: Challenger, Columbia, AC-67, NOAA N-Prime, BP Deepwater Horizon

This course is designed for NASA's technical workforce, ranging from discipline engineers to project managers to safety and mission assurance team members. It is appropriate for practitioners at any career development level but may be of greatest relevance to team/subsystem leads and project managers/project systems engineers.

Common Competencies
  • C2.2 Team Dynamics and Management
  • C4.2 Communication
  • C4.3 Leadership
  • C4.4 Ethics
  • C5.2 Knowledge Sharing

Upon completion of this course, participants will be able to:

  • Define and give examples of heuristics and cognitive bias
  • Identify the kinds of communication problems that commonly create anomalies, mishaps, accidents and failures
  • Identify the heuristics and biases relevant to the Challenger accident
  • Analyze the role of cognitive biases and poor communications in the Challenger accident
  • Apply insights derived from communication and cognitive errors to current projects within the NASA culture
  • Identify their most likely communication and cognitive bias “blind spots”
  • Articulate multiple mitigation techniques applicable to each time of communication error and cognitive bias identified during case study analysis
  • Synthesize insights derived from case study analyses into an action plan for reducing communication and cognitive bias errors and improving decision-making processes back on the job

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