Using Knowledge Management to Improve the Effectiveness of Data Fusion Centers

Area of Science:

• Intelligence studies
• Information science
• Organizational management

Background:

• Data fusion centers, created post-9/11, face persistent underperformance issues.
• Intelligence products from fusion centers frequently fail to align with supporting organizations' missions.
• Historical barriers to effective information sharing have hampered fusion center operations.

Purpose of the Study:

• To identify historical barriers hindering information sharing in data fusion centers.
• To propose actionable strategies for enhancing fusion center efficiency and effectiveness.
• To leverage knowledge management principles for improved intelligence product generation.

Main Methods:

• Analysis of historical data and authorial experience through a knowledge management framework.
• Application of structured analytic technique exercises.
• Integration of knowledge management tools and concepts.

Main Results:

• Identification of key barriers to information sharing within fusion centers.
• A proposed framework integrating structured analytic techniques and knowledge management.
• Demonstrated potential for improved knowledge flow and intelligence product quality.

Conclusions:

• Knowledge management offers a viable approach to overcoming information sharing barriers in fusion centers.
• Structured analytic techniques, when combined with KM, can significantly enhance intelligence product relevance and quality.
• Fusion centers can achieve greater mission support and effectiveness through strategic KM implementation.