Using HERD Data to Inform Your Research Funding Strategy
Research administrators drowning in data rarely struggle from lack of information – they struggle from not knowing which information matters most. The Higher Education Research and Development (HERD) Survey is a valuable source of intelligence for research funding strategies; yet, institutional actors do not utilize this intelligence resource effectively.
Understanding HERD Survey Data
The HERD Survey, an annual production of the National Science Foundation’s National Center for Science and Engineering Statistics, collects data on expenditures for research and development at U.S. colleges and universities. The survey records R&D spending by field, funding source, and institutional characteristics, creating a potentially rich dataset for strategy.
Every year, over 900 institutions report spending more than $150,000 on research and development for which separate accounts are maintained. This comprehensive census enables unparalleled insight into the national research funding landscape.
Identifying Funding Source Diversification Opportunities
The HERD data shows institutional funding mix, the combination of federal, state, industrial, non-profit and institutional funding of research. It sheds light on dependency patterns and diversification opportunities.
Institutions that rely mainly on the federal government for funding can use HERD data to identify peers who have successfully diversified their funding from non-federal sources. Based on an analysis of comparable institutions, which captures 20% of research funding from business partnerships, and which only captures 5%. This gap is an opportunity.
The HERD further reveals which institutions excel at securing Foundation research. Understanding their research areas, institutional size, and regional location opens up new perspectives on why they succeed when others struggle.
Benchmarking Research Performance
HERD data facilitates advanced benchmarking beyond mere total spend comparisons. By using these analyzes, an institute can assess its performance in a particular research field and identify its competitive strengths and weaknesses, which are not visible in aggregate data.
For instance, your institution may be ranked 50th nationally for total research spending but 15th for environmental science. The area-specific strength suggests potential competitive advantages worthy of emphasizing when pursuing non-federal research funding for environmental areas.
On the other hand, underperforming in areas where peers are strong indicates there is a need for capacity building, or the pursuit of certain research funding may be difficult without strategic investment.
Understanding Regional Research Patterns
Geographic breakdowns of HERD data reveal patterns of research funding by region, a key part of state and regional funding strategies. Numerous states devote ample financial resources to agricultural research. Healthcare investigations or engineering are preferred by others.
By understanding where state and local government research dollars flow, institutions can identify regional research funding opportunities. When a state heavily invests in agricultural research, and your institution boasts capacity in agricultural science, there is a strong case for pursuing state research funds.
The competitive dynamics are also revealed by the regional patterns. How many institutions in your region are competing for similar research funding? What are the geographical advantages? The HERD data responds to these strategic queries.
Tracking Research Funding Trends
According to HERD longitudinal data, research funding trends over time. Which fields are in demand? Which funding sources are growing or shrinking? Strategic planning and resource allocation decisions rely on these trends.
Recent HERD evidence shows, for example, that businesses’ funding of university research continues rising, while some federal sources face uncertainty. Institutions that appreciate these trends promptly position themselves favorably.
Trends that are field-specific matter equally. Funding for computational research may be on the rise while some traditional areas may be decreasing. By understanding these dynamics, institutions can make more informed decisions regarding research capacity investment and funding diversification priorities.
Analyzing Peer Institution Strategies
The HERD data allows for in-depth analysis of peer institutions’ research funding strategies. What non-federal sources do successful peers pursue? In what ways have the funding compositions evolved? What lessons can be learned from their trajectories regarding successful diversification?
Choose the right peer groups, such as institutions of a similar type, with comparable research portfolios, or aspirational peers with equivalent performance. Then analyze their funding patterns to identify strategies you can replicate or gaps that represent competitive opportunities.
This competitive intelligence is especially useful for a non-federal research funding strategy. Non-federal funding is often less transparent than federal funding, which has standardized processes and public success rates. HERD data shows which institutions are successful with diverse non-federal sources.
Identifying Emerging Research Areas
By tracking research expenditures across dozens of fields, HERD reveals emerging areas attracting additional investment. Many of these new fields allow early movers to access non-federal research funding.
Although new interdisciplinary fields may lack established federal funding programs, they are gaining interest from foundations and corporations. By discovering these emerging areas at a preliminary stage- the level of competition will not be that high and institutions having relevant expertise will derive competitive advantage.
Supporting Executive Decision-Making
HERD data provide evidence for strategic decision-making by top executives regarding research priorities, capacity investments, and funding diversification. Leaders can base decisions on comprehensive national data, rather than on anecdotes and partial information.
Institutional leaders need evidence that their investment in research development will yield returns. This evidence is provided by HERD data showing how peer institutions have succeeded with certain funding strategies.
Understanding Indirect Cost Recovery Patterns
HERD collects indirect cost recovery data, shedding light on how different types of funding sources and institution types treat facilities and administration costs. This information is useful in negotiations with non-federal funders and in setting realistic indirect cost expectations.
Certain funding sources generally pay lower indirect costs than federal programs. Being able to understand these trends allows institutions to create suitable cost recovery strategies for different funding portfolios which are assured to full-cost recovery while remaining competitive positioning.
Identifying Collaboration Opportunities
HERD data indicate which institutions of higher education excel in specific areas of research and could serve as collaborators on multi-institutional, non-federal research funding proposals. Many foundations financially support collaborative research focused on difficult challenges that benefit on a multiple institutional perspective.
Instead of guessing which institutions might be strong partners, HERD data identifies institutions that have demonstrated capability and significant research programs in relevant fields.
Limitations and Complementary Data
Although useful, HERD information is not flawless. It records expenditures but not proposal success rates or funding opportunities pursued. It provides yearly snapshots, not for real-time analysis. It focuses on R&D expenditures, not broader research development activities.
An effective research funding strategy combines HERD data with internal proposal tracking, funding opportunities monitoring, and relationships with peer institutions. HERD lays the groundwork, but a robust strategy requires various data sources.
Leveraging Analytics Tools
Raw HERD data can be overwhelming. Transforming data into actionable insights requires analytics tools which effective users use. Business intelligence platforms can visualize trends, benchmark performance, and identify patterns in the data that would be impossible to discern through manual review.
Today’s research administration platforms incorporate analytics that put institutional data into the HERD context. Instead of treating data analysis as a distinct project, these comparison analytics tools are embedded in everyday research administration operations.
For example, Streamlyne Reporting comes equipped with built-in business intelligence tools for research administrators that will integrate HERD data with institutional research data. Through this integrated approach, continuous strategic insights emerge rather than special studies at intervals; institutions can continuously improve their research funding strategies based on a national and institutional base.
Taking Action
Effective usage of HERD data means more than just downloading the annual report. Institutions should assign HERD analysis responsibilities to staff, institute regular competitive intelligence gathering and ensure effective mechanisms are in place to convert insights into actionable funding strategies.
Begin with your top research funding questions. Where are the chances for diversification? Which peer strategies deserve emulation? What are competitive advantages? Where do they exist? Next, make use of HERD data systematically to answer these questions.
Discover how our HERD Visualizer PRO will help you turn HERD data into strategic insights →
