Research Analytics Using the Higher Education Research and Development Survey (HERD) to Impact Institutional Strategy

As funding opportunities for sponsored research and development become more competitive and funding agencies hold research entities more accountable, research support professionals, such as research impact librarians, research data analysts, vice presidents for research, and provosts, need to develop new skills to meet these demands. These skills should help research support professionals make important institutionally-focused decisions to support their research strategy, infrastructure, and create pathways for significant investment.

To be effective, techniques should employ advanced data analytics, business intelligence tools, and benchmarking datasets. This project will first collect empirical evidence of promising applications of data for institutional decision-making, benchmarking, and best practices development, and then train a select but diverse group of research support professionals in data-driven decision making and relevant analytical techniques.

Growth in the research enterprise, facilitated by strategic data-informed decision making, not only has a positive impact on faculty recruitment and retention but also provides opportunities for expanded student participation in research, strengthens quality graduate programs, and creates economic impact for the local and regional economies. Enhancing these skills to help professional better support research is particularly important for smaller and minority-serving institutions to help them focus their funding requests and remain competitive.

The National Science Foundation’s National Center for Science and Engineering Statistics’ annual Higher Education Research and Development (HERD) Survey is one source of benchmark data. This project will conduct a national survey of higher education institutions to collect data on the effective use of the HERD survey data in institutional planning and support.

The survey will identify what HERD data are most used and useful as well gather ideas of other data and benchmarks that would be of use to institutions to help make their decisions. Then, the project will host an in-person workshop that will use the SCOPE framework for responsible research evaluation (developed by the International Network of Research Management Societies’ Research Evaluation Working Group, INORMS-REG) to help institutions expand their metrics of research evaluation and make better informed decisions about research funding strategies.

This workshop will include analytical training on predictive analytics, analytical tools, data visualization, and network analysis, elevating the skills of research support professionals to focus and grow research at their institutions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.