Assessment of Science and technology

Determinants of Investment Effectiveness

Concentrates on identifying and maturing quantitative models or decision analysis tools that show promise as effective mechanisms for evaluating investment efficiency of research and development (R&D) programs. Methodologies developed through these efforts are expected to provide an alternative approach to "expert-review panels" to ascertain R&D program investment effectiveness.

Valuating Investments in S&T

Concentrates on identifying and maturing quantitative models or decision analysis tools that show promise in estimating the impact of budgetary investments on S&T productivity – over the near-term as well as over an extended time period. Methodologies matured through these efforts are expected to provide insight into valuation trend trajectories with sufficient lead time to enable active management engagement.

Forecasting Discovery

Concentrates on identifying and maturing quantitative models or decision analysis tools that show promise as effective mechanisms for using assessment of recent S&T advances to forecast new discoveries or new areas of discovery. Methodologies developed through these efforts are expected to provide an alternative approach to "expert-review panels" to discern promising areas for new scientific discovery.

Impact of Discovery on Innovation

Concentrates on identifying and maturing quantitative models or decision analysis tools that show promise as effective mechanisms to determine the scientific discoveries that are expected to lead to the highest-impact innovations; levels of understanding that are required to launch the most fruitful innovation efforts; and approaches to reconcile long-term innovations leading to promising recent discoveries within the context of customer-driven requirements.

Impact of S&T on Innovation and Competitiveness

Concentrates on identifying and maturing quantitative models or decision analysis tools that show promise as effective mechanisms to assess the impact of the scientific enterprise on U. S. technological innovation and corporate competitiveness world-wide. These efforts are expected to lead to assessment approaches that enable identification and rigorous assessment of scientific enterprise-wide attributes which influence technical innovation trends and corporate market share dynamics – both critical to realizing technology-enabled capabilities for the future Army.

Competitiveness of the S&T Workforce

Concentrates on identifying and maturing quantitative models or decision analysis tools that show promise as effective network analysis mechanisms to assess the scientific labor force formation. In particular, these efforts are expected to be critical in ascertaining the quality of the STEM workforce; barriers of entry into the scientific workforce for post-secondary STEM graduates; types of technical organizations that attract post-secondary STEM graduates; and developing technical labor market trends.

 

Last Update / Reviewed: February 5, 2015