爱豆传媒

About this report

How we conducted our research

At 爱豆传媒, we pride ourselves on our integrated research and engagement process.  Our advisory team conducts user research, analyzes the competitive landscape, and identifies patterns and trends, with data underpinned with interviews, observations, workshops, surveys, and data mining. We combine stories and statistics to uncover insights you can act on, helping clients with the most complex business management challenges as well as design of assets.

In this white paper, we provide a way for institutions to understand how productive their research space is and strategies to increase productivity at a time when funding is uncertain. 爱豆传媒鈥檚 higher education team plotted research revenue for 111 R1 institutions in the United States against their research space, using data from the . This allows us to see which institutions are making the most of their physical spaces 鈥� those with higher revenues per square foot of space can be characterized as more 鈥減roductive鈥� in their research in a spatial sense. 

Understanding revenue per square feet provides a starting point to see how productive your research space is. From there you can look for ways to increase it with strategies like densification (less space per researcher), more efficient infrastructure, and more effective support services. 聽Through our experience in planning, programming, and engineering of research facilities for higher education institutions across the US and the globe, we help our clients increase revenues, improve efficiencies, and reduce costs using the following strategies for optimizing research space.

Research expenditures are a coarse but popular way of quantifying research activity; for example the new Carnegie Classifications set thresholds of $50M for R1 institutions and $5M for R2 institutions. Not surprisingly, HERD data is reported as research expenditures. Research expenditures tend to be highly correlated with research revenues. Research by the Council on Governmental Relations found that the difference between expenditures and revenues is about 11.5%; that expenditures exceed revenues by an average of 11.5%; institutions thus pay for 11.5% of expenditures out of other funds.

At this time of financial uncertainty with federal research grants being cancelled and negotiated formulas by which institutions are reimbursed for indirect research costs (maintenance, support staff, facilities, etc.), what universities need is more revenue, not necessarily more expenditure. The bottom-line metric institutions ought to improve is their revenue per square foot 鈥� the productivity of their research spaces.

To convert from expenditures to revenue, expenditure data was discounted by 11.5% to calculate revenue, assuming all other dollars supporting research projects were brought in from outside sources. Revenue data was then broken down by research type to just those dollars spent on science and engineering projects, and then compared to the amount of net assignable square feet of science and engineering research space to assess productivity as a measure of dollars per square foot.

Improve productivity

1. Increase research space productivity (Research dollars per square foot)

As funding opportunities change the landscape for academic research, federal indirect funding for infrastructure, support services, and facilities and administrative (F&A) costs is likely to decrease. This will have a direct effect on institutional funding models for research facilities and may require some rethinking on how to best allocate and utilize research space on and off campus.

The first step in making data-informed decisions on how to best use research facilities is to assess the utilization and productivity of existing spaces. One key measurement of utilization is research dollars per square foot of research space, or 鈥榬esearch space productivity鈥� as described above. Data from HERD for 111 R1 institutions shows an average of $408 per net assignable square foot (NASF) of research space. Understanding how you compare to peer and other institutions provides the foundation for you to develop a plan for change.

Taking the measurement of utilization (research space productivity) introduced above, we separated the 111 R1 institutions into quartiles showing distinct distributions of total research revenue. While the highest performing institutions tend to have higher research revenues, there are many examples of institutions with revenues under $250 million that use their space as productively as institutions with $1 billion in research revenue.
Among both public and private universities, there is a direct relationship between research revenue and research space productivity; among private universities, each increase in research revenue is associated with a greater increase in research space productivity (as shown in the scatterplot below).

2. Focus on high-performance research areas

After developing a baseline understanding of how your research facilities compare across the higher education landscape in terms of revenue per square foot, think about how space use impacts your overall research investment portfolio. Certain types of research, such as physical sciences, biomedical sciences, and engineering, are very intensive in terms of physical space, infrastructure, and maintenance.

On the other end of the spectrum, research in computer and information science, math, and social sciences have fewer space and infrastructure requirements and greater opportunities for research productivity (as shown in the box and whisker plot below).

There are many ways to measure research such as patents and intellectual property created as well as impact on society. Financial measures are a crucial supplement to traditional measures of research output, allowing assessment of whether research activities are sustainable and can achieve their desired impact on students and society. Revenue can and should inform how you focus and prioritize among research areas. Our analysis of the research investment profiles of R1 institutions in this study shows that schools in the top quartile of research space productivity (鈥淓xcelling Institutions鈥�) allocate their research investment across subjects differently from schools in lower quartiles. On average, the institutions that are excelling at research space productivity are more focused. These institutions:

• receive a higher portion of their research funding for life sciences (76% versus 57% for other institutions)
• receive a lower portion of their research funding for engineering (9% versus at 19% for other institutions)
• receive a slightly lower portion of their research funding for social sciences, computer and information sciences, geosciences, psychology, and math (11% in total, versus 13% for other institutions).

Digging in more deeply, the major distinguishing factor between institutions with the lowest level of space productivity (鈥淒eveloping鈥�) and the second quartile institutions (鈥淓merging鈥�) is their emphasis on physical sciences. 鈥淓merging鈥� schools, on average, had double the relative investment in physical science expenditures (from 6% to 12%), with minor reductions across social sciences, computer and information science, and life science.

The consolidation of research revenue into the areas of life sciences, engineering, and physical sciences continues in “Emerging” and “Innovating” institutions. Among both groups of institutions, less than one in seven research dollars is spent outside of these research areas.

Top-performing 鈥淓xcelling鈥� institutions are truly specialists, focusing three of every four research dollars into life sciences research. Schools that have higher research revenues generally have greater research space productivity (see scatterplot). These highly specialized research spaces are very expensive to set up and operate but bring in a lot of federal and non-federal funding sources. Furthermore, life sciences research is the area most in jeopardy of NIH overhead cost recovery reductions.

While life sciences research can be highly productive, creating new dedicated research space for life sciences can be costly, considering the amount of infrastructure required. On the other hand, research space for computer and information sciences (CIS) requires very little infrastructure, often requiring nothing more than repurposed office space. A laptop, a whiteboard, and cup of coffee might be all the equipment needed.

As funding declines in life sciences and other areas, overall research space productivity will likely decline in most institutions, but particularly in 鈥淓xcelling鈥� schools with large life sciences programs. So while 鈥淓xcelling鈥� schools may be the most efficient in terms of overall research productivity, with less funding for life sciences on the horizon, consider adjusting your research investment profile to include more highly productive areas like CIS, math, and social sciences.

Across all R1 institutions in the analysis, aggregate research space productivity was highest for CIS research, with a mean of $747 per SF. Mathematics and social sciences research, which have similarly low infrastructure requirements, also have relatively high research space productivity. Therefore, as institutions consider how to restructure their research spaces and portfolios, CIS, mathematics, and social sciences stand out as strong options for the marginal repurposed square foot. On the other side of the efficiency continuum, geosciences labs are the least productive, with a mean of $219 in total revenue per square foot.

While CIS might be the most productive in research revenue per square foot, compared to life sciences and engineering, far less funding is available overall for CIS, social sciences, and mathematics. This means that the transition will be highly competitive. However, certain schools stand out from the crowd in the amount of funding they receive for these subjects. Carnegie Mellon, MIT, and the University of Southern California have achieved far better-funded CIS programs than their peers without devoting exorbitantly more space than other schools; the same can be said about Iowa State鈥檚 mathematics and statistics programs, as well social sciences at the University of Michigan-Ann Arbor. Not all these schools are in the top quartile of overall research space productivity, but they serve as valuable precedents for other institutions seeking to capture more revenue in these areas.

3. Create high-performing teams

Consolidating and optimizing research spaces can significantly enhance the performance of research teams while reducing costs. Institutions can improve efficiency by identifying opportunities for shared research spaces, co-locating teams with similar objectives, and adapting space allocations based on shifting research methodologies.

For example, research groups moving from experimental to computational work often require fewer infrastructure resources, enabling thoughtful reallocations that maximize utility. Renovating older spaces to better serve current research missions and fostering interdisciplinary collaboration through shared environments can also boost productivity and innovation.

The at Carnegie Mellon University is a prime example of these principles in action. In this project (currently under construction), research facilities will be organized thematically rather than departmentally. This improves space utilization while enhancing opportunities for collaboration. This approach allows for shared resources and adaptability, leading to greater efficiency and research output.

Additionally, balancing laboratory areas with spaces dedicated to data analysis, writing, and collaboration is critical. Allocating more space for these lower cost functions could help you increase your overall research space productivity. By transforming underutilized laboratory areas into write-up or office spaces, institutions can also better meet the needs of their teams while lowering indirect costs. These strategies ensure long-term sustainability and position research facilities for continued success.

Decrease costs

1. Designing for economic and environmental sustainability

It is critical that any institution understands its infrastructure operating costs, primarily its mechanical systems serving research spaces and the energy these systems use. Following best practice operating procedures can significantly reduce operating costs and allow more money to flow towards research to help close the gap created by the decrease in federal funding.

Measures to implement include, among others, unoccupied space temperature setbacks, unoccupied airflow setbacks, fume hood face velocity reductions, and optimized exhaust fan controls. By utilizing resources such as the I2SL Lab Benchmarking Tool, facilities can quickly understand their research space energy performance as it relates to high performing buildings, similar enhancement worked on Draper Laboratories in Kendall Square and at Williams College in Massachusetts. Once benchmarking is established, these tools can be utilized to suggest cost saving measures specific to the space, along with estimated costs to implement, energy savings, return on investment, and next steps to execute the measures.

2. Plan for flexibility to support changing needs

Designing research spaces for adaptability and future-proofing is critical for environments that support rapidly changing research needs. Research facilities benefit immensely from flexible layouts that allow for easy reconfiguration between dry labs, computational labs, and wet labs without disrupting overall operations.

MIT鈥檚 new Schwarzman College of Computing, incorporated a flex lab concept. Spaces can be converted as needed鈥攕uch as transitioning to high-density fume hood-driven labs鈥攚ith minimal structural or equipment modifications. Planning ahead with conversion plans ensures that spaces remain agile and can evolve in phases to accommodate future needs without requiring extensive retrofitting. 爱豆传媒’s work on a data science facility for a top-rankedresearch institution illustrates how flexibility can be effectively implemented. The design approach blends adaptable lab configurations, phased conversion planning, and sustainable system integration to create a versatile and forward-looking research environment.

Universities can learn lessons in flexibility from the private sector too. Our laboratory designers collaborated with AstraZeneca to integrate flexible design principles into their Discovery Centre in Cambridge, UK. All labs are organized on modular planning grids, featuring fully mobile laboratory furniture that connects to MEP services using ‘plug and play’ strategies. Each floor houses six 10,000-square-foot labs, providing large open spaces that encourage sharing and collaboration. Enclosed labs were provided only after a rigorous screening process to minimize cellular spaces, ensuring environmental and biosafety requirements were met. Planning for flexible spaces in addition to flexible systems will help you increase productivity.  

Drawing from their expertise in complex lab fit-outs, our work demonstrates the potential for flexible design to meet evolving research demands. Critical to this work is guiding stakeholder input from the university鈥檚 facilities and operation team, as well as its environmental health and safety team. Confirming design standards with good, better, and best tiers of performance, allows clear options to be developed and testing using a comprehensive life cycle cost analysis process.

To support adaptability, research facilities should consider shared thermal resources and integrate high-performance systems, such as all-electric central plants with advanced heat recovery and airflow controls. These systems can align with institutional sustainability goals while optimizing operational efficiency. Another key component of designing for flexibility is ensuring robust and scalable technology infrastructure. Research facilities should anticipate growing data exchange needs and integrate solutions that allow for increased data storage density within a fixed or shrinking footprint. Scalability in technology systems ensures the facility remains at the forefront of innovation, while staying within the bounds of electrical utility limitations.

3. Be more efficient with staff and support

To enhance research support services, consolidate disparate, distributed resources into a centralized service center. By merging redundant service providers, such as distributed finance, compliance, communications, and IT teams, institutions can streamline operations, cut costs, and foster collaboration. Centralizing support staff in one location also simplifies navigation for researchers, reducing the time spent seeking assistance across scattered offices.

Start with an inventory of research support services, analyzing their locations, usage, and sizes of both square feet and staff FTE. Some of the financial support services to consider: grant writing, pre-award specialists focused on preparation, submission, and compliance; and post-award specialist focus on administering research projects. You can also consider institutional review boards (IRB) tat ensure training and compliance with standards and regulations; development officers to identify funding opportunities and build relationships; and technology support including cybersecurity, maintaining databases, etc. In terms of the research content and administration, consider data management through your library and/or IT, scholarly communication of research findings through your library and communication functions, as well as research administration to set strategy and oversee all the above.

This shift allows researchers to focus more on their work while benefiting from easily accessible, high-quality support services. A centralized model encourages resource sharing, minimizes duplication, and creates a more efficient, user-friendly experience鈥攗ltimately fostering a more productive research environment. By aligning infrastructure and expertise, higher education spaces can better meet the evolving needs of their research communities.

爱豆传媒 has worked with dozens of institutions to analyze, optimize, and reorganize support services; such as work with NYU鈥檚 research technology organization and NC State鈥檚 libraries. From these service and staffing model projects, we鈥檝e learned that institutions need to start with a solid understanding of the current state. Even a list of all the services you offer can be revealing 鈥� when we put each of these on a post-it note on the wall, leaders always realized how much they are doing and how much they need to focus. Once you have this list, you can then overlay transaction data to see how much they are used and staffing data. Analyzing staff FTE by service (i.e., how much of each person鈥檚 time is spent on say outreach vs. Training vs. Communication) is equally revealing. Then you can look at future staff FTE by service considering what you need to add or grow compared to services to sunset and associated staff to reallocate.

We also helped the College of Engineering at Carnegie Mellon University for research that shifted focus toward more large-scale research projects that are technically and administratively more complex. Key actions toward achieving the new focus were to provide more training, grant writing, and research support services in a consolidated and efficient way. This helped CMU expand its research portfolio into larger research projects, that generally have greater space efficiency.

Facilitate change for the future

Research facilities and campuses are often the most complex, challenging, and time-sensitive projects. The project process and space transition can be difficult for research stakeholders to engage in and accept. Developing a change management program will help stakeholders navigate these complex projects by preparing, equipping, and supporting them to adapt to change successfully.

Change management programs can also provide benefits in various ways including increasing the velocity of change efforts; building awareness of links between strategic objectives and research space change; minimizing work disruption and impact on productivity; and enhancing stakeholder satisfaction and performance.

The adoption of substantial change can be a long, iterative process that spans the project from the earliest stages of planning, through implementation and post-project maintenance. Perseverance and a well-structured and executed change management program are paramount to create a seamless transition from old spaces and ways of working and to achieve the project goals. The steps in a change management program are incremental, but often overlap and continue to inform the process throughout the program:

• Visioning to create and build consensus on the project and program vision, standards and goals for the new spaces and norms to guide the change management efforts.
• Employee engagement to identify opportunities and pain points, and to build consensus and buy-in. These engagements provide information and support to help stakeholders adapt to evolving norms and behaviors by co-creating tools, resources, and guidelines for space use.
• Communication plan and relocation preparation to finalize and implement comprehensive change communication plan, provide stakeholders with all information and process to provide feedback to the project team and leadership.
• Post-occupancy evaluation to collect feedback and data to assess the transition鈥檚 success, measure productivity, and identify areas for improvement.

Without change management, implementation of ideas to prioritize research areas, optimize infrastructure, increase flexibility, and consolidate research services will fall flat. In fact, Prosci found that projects with effective management are .When managed correctly, projects really can get results. Our work with the University of Michigan to create a 鈥渃enter of centers鈥� brought together dozens of different institutes and centers to share services and spaces. This  resulted in productivity gains of 4.26 hours per person per week. This success came not only from a flexible design and reorganized support services, but from change management that included defining norms, creating a welcome guide, and meeting with groups to onboard and orient them to new spaces and new ways of working in them. Likewise our to create a flexible administrative workplace strategy at the University of Minnesota reduced space by 36% while reducing response times by 69%. To get these results, we partnered with human resources to create a robust communication plan and conducted workshop to define norms, learn technology, work flexibily, and manage differently.

Conclusion: Adapting in order to thrive

Leaders need to act now. In today鈥檚 rapidly changing higher education research environment, where technological and economic shifts are transforming research collaborations, facilities, and funding models, a strategic and adaptable approach to research space management is vital.

• Improve the productivity of research spaces by embracing data-informed decisions.
• Use revenue as one input to focus your research efforts on high performing areas.
• Foster collaborative teams by created common themes and creating common ground in shared spaces.
• Make these research spaces  sustainable and flexible.
• Analyze, optimize, and find opportunities to centralize support services to decrease costs and increase revenue.

Taken together, these practical and achievable strategies can help your institution quickly navigate and adapt to an uncertain future, while ensuring that research facilities remain vibrant hubs of innovation and discovery.