STEM-Rich Campus
©Regents of the University of Colorado
The University of Colorado Boulder (CU Boulder) is recognized as an academic leader in aerospace engineering, physics, and engineering, having received $33.3 million in aerospace-related research awards in the last fiscal year. In addition to a 180,000-sf aerospace engineering building with state-of-the-art research capabilities, occupied in 2019, CU Boulder is currently planning a new 140,000-sf building dedicated to chemistry and applied mathematics.
PREVIEW Dashboard
Courtesy of CU Boulder
PREVIEW is a digital space planning tool developed over 15 months with input from more than 180 stakeholders across various colleges, schools, and academic partners as part of CU Boulder’s Strategic Facilities Visioning initiative. Consisting of a set of dashboards and data-driven visualization tools, PREVIEW helps campus space planners make informed capital planning decisions that enhance efficiency and innovation.
Prior to the development of a master plan for expansion of research facilities at the University of Colorado Boulder (CU Boulder), campus facility planners conducted a 15-month strategic visioning initiative that resulted in the creation of a digital space planning and visualization tool called PREVIEW. The tool’s data-driven dashboards are now revealing trends that help campus space planners make informed strategic decisions regarding future capital construction by combining detailed information on current lab utilization and capacity with projected growth estimates and ambitious sustainability goals.
As the top non-medical NIH-funded school in the nation and the number one public institution for NASA funding, CU Boulder has a sizeable infrastructure of nearly 1 million square feet of advanced research space. However, growth projections indicated a need to nearly triple current lab space to meet future demands. The university is also targeting a 50% reduction in emissions by 2030, with the goal of reaching zero emissions by 2050.
While research space represents only about 10% of total campus square footage, it accounts for 40% of energy, utilities, and carbon emissions. In order to optimize operating efficiency and identify future construction priorities, a gap analysis was conducted to compare current lab utilization with expected demand.
“We basically analyzed our current facilities and looked at which programs were trying to do the most intensive research, and where the biggest gaps were between what they are trying to do and what their current buildings are capable of,” says Wayne Northcutt, senior planner at CU Boulder. “So we looked at questions like: What is the age of the building? What is the structural system? What is the floor-to-floor height? What are the MEP systems?”
Doing More With Less
The gap analysis indicated that a number of campus lab facilities were being overstretched, with some buildings unable to support research demands due to their age and design.
“That was a real eye-opener,” says Northcutt. “We realized that we needed to dial down some of our expectations and not try to do high-intensity research in buildings that just can’t support it.”
The new research master plan now allows PREVIEW to analyze lab utilization efficiencies, so the space planning team can compare how variables such as building age, program type, and research funding impact utilization efficiency. This data, which is updated annually to ensure accuracy and relevancy, includes detailed information about campus lab capacity, condition, and future needs based on population and various space planning strategies.
PREVIEW consists of three dashboard interfaces: A supply dashboard that shows the current capacity and condition of campus lab facilities; a demand dashboard that forecasts future lab needs based on demographic and planning data; and an options dashboard that enables the simulation and assessment of different planning scenarios. These tools collectively enable data-driven decision-making to optimize the university’s infrastructure investments and align them with the broader strategic goals and evolving needs of the research community.
By organizing faculty and staff according to their research program, title, and role—including research assistants and grad students—planners could determine how many full-time equivalent personnel each lab type typically needs to support. The amount of assignable square footage per employee was then calculated based on program size and lab type, whether it’s a computational dry lab, mechanical engineering lab, or a biochemistry wet lab.
“Using our existing data, we developed what we refer to as a utilization index, which is a simple ratio of how much space a program currently has versus how much space we think they should have. It’s kind of like a golf score. The lower the score, the better; and a score of 1 means that you have exactly the amount of square footage we think you should have,” says Northcutt.
Optimizing Utilization
The average utilization index score revealed that a number of lab spaces were operating below optimal capacity. The data also suggested the potential for reclaiming a significant amount of lab space (i.e. 14% of current lab space on campus) through targeted renovations and other strategies.
“It gave us a very nice snapshot of the average utilization in our lab spaces,” says Northcutt. “Our analysis showed that we didn’t actually need all these new buildings that we thought we should be planning for. We just needed to get better at utilizing the space we have. But that got us wondering if we could use the data to tease out some of the underlying trends and see if there were any other factors contributing to why or how we might not be using our lab space as efficiently as possible.
“There does seem to be a trend showing that utilization gets worse as the age of a building increases. We also looked at how the utilization index compared with research expenditures and found that the more money you’re spending in your lab, the more your space efficiency tends to increase,” says Northcutt.
Another trend indicated by the data was a correlation between utilization efficiency and whether or not a facility is shared—with shared lab spaces showing better utilization scores. This suggests that collaborative research environments not only foster innovation but can also improve space utilization.
“I think it’s possible that, as research campaigns ebb and flow, there is a friendly, competitive pressure to use space as efficiently as possible, as opposed to a siloed program in a chemistry building or something, where they’re the only ones using the space and there’s less competition. When it’s shared, there’s a governance committee that is reviewing any kind of proposal by a PI to expand space where they’re saying, ‘Okay, prove it to us.’ So, there’s a more rigorous oversight process involved.”
Soft Recommendations
The university’s strategic visioning initiative and gap analysis also produced a set of “soft recommendations” for optimizing lab utilization without expanding physical space. These include creating shared governance structures, expanding core lab management, and preventing program silos at all levels by promoting the use of core labs, open labs, and shared buildings.
“The study resulted in what I consider to be a mix of hard and soft recommendations, where soft recommendations don’t require you to build new buildings. I think one of the biggest soft recommendations is to conduct regular ongoing assessments of lab space utilization. What we found with the study is that it really isn’t about quantity; it truly comes down to lab quality.”
By Johnathon Allen
