How the U.S. Navy Can Become a Better Learning Organization

Abstract

How can the Navy become a better learning organization? This thesis addresses this question by taking a precise look at what a learning organization is, what its essential parts are, and why they are important. This research is qualitative in nature and includes analyses of published literature, public records, congressional testimonies, committee hearings, and documented reform attempts. The work attempts to answer why the Navy has struggled to become a learning organization in the past, where it has found some small successes, and what the reasons are for failure. In summary, smarter organizations are more adaptable to challenging scenarios and change, and both individual sailors and teams are more likely to innovate and find solutions in changing environments when a strong learning infrastructure is in place. A learning organization provides a supportive structure that enables and encourages learning and brings with it a culture of collaboration and innovation by removing some of the barriers that prevent individual learning processes from succeeding by themselves. The Navy's ability to learn as an organization is important because a Navy that has the capability to learn quickly and efficiently has a long-run advantage over its rivals.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1150661

Entities

People

  • Robert J. Kenning

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Cyber
  • Engineered Resilient Systems
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Behavioral Sciences
  • Data Analysis
  • Doctrine
  • Employment
  • Instructors
  • Military Education
  • Military History
  • Military Organizations
  • Military Science
  • Military Training
  • National Governments
  • National Politics
  • National Security
  • Naval Operations
  • Naval Warfare
  • Navy
  • Organizational Structure
  • Personnel Management
  • Second World War
  • Students
  • United States Government

Readers

  • Economics
  • Neural Network Machine Learning.