Measuring for Scientific Impact: Metrics That Drive Laboratory Design

2025 Lab Design Conference speaker—Regal Leftwich, FAIA, AICAE, LEED AP, laboratory design principal, CannonDesign

As laboratories evolve to meet increasingly complex research needs, so must the methods for evaluating their effectiveness. At the 2025 Lab Design Conference in Denver, Regal Leftwich, FAIA, AICAE, LEED AP, laboratory design principal at CannonDesign, presented Measuring for Scientific Impact: Metrics that Impact Laboratory Design, a session focused on how institutions can plan facilities that not only support today’s science but also lay a foundation for future innovation.

The presentation contained four key areas Leftwich explained: “How we measure research impact, four metrics around buildings, benchmarking, and then, of course, cost.”

Designing for research success

Leftwich opened by acknowledging the difficulty in drawing clean lines between design choices and research impact: “I was hoping to have some more definitive correlations around the impact of lab design and research impact. But it turns out, it's really hard.” Still, his presentation explored several ways institutions can better measure and design for scientific effectiveness.

One of the clearest benchmarks available to academic institutions is the updated Carnegie Classification system, which now uses fixed thresholds for R1 designation: $50 million in annual research expenditures and 70 or more research doctorates awarded annually. “This has significantly expanded the amount of R1 institutions that are in this classification,” Leftwich noted, adding that “it’s not so dependent on fluctuations in the industry and in cost for a university to know what they need to be spending.”

Designs should also reflect the spectrum of research—from basic to applied to development-focused work—each with different space needs, timelines, and funding models. “Basic research usually means smaller grants, but they may be more space hungry types of science,” he said. “Development projects… bring in more major capital but require highly specialized spaces.”

Collaboration and flexibility as infrastructure

In today’s research climate, adaptability and interdisciplinary collaboration are no longer optional—they are essential infrastructure. “There's a major shift in how funding science is happening, and it's really reshaping how we need to think about how we design space,” said Leftwich. “Funding agencies… are moving away from individual investigator grants towards large interdisciplinary teams tracking complex, mission-driven problems.”

To support convergence science—think AI, climate change, and pandemic preparedness—labs need visual transparency, shared instrumentation cores, and zones that allow different disciplines to work side by side. “This need for collaboration should be considered essential infrastructure for research buildings,” Leftwich emphasized.

He cited a Johns Hopkins lab project as an example of this philosophy in action: “All the labs are on display within that active atrium… there’s a combination of shared write-up areas, conference rooms that look over the labs, so you can always see someone and relate with someone else in the building.”

Flexibility was also described as non-negotiable. “Science evolves fast… buildings that can’t adapt quickly just become obsolete,” said Leftwich. “Flexibility is future-proofing.”

He outlined three levels of flexibility: room-level (movable benches, reconfigurable utilities), floor plate (adjustable adjacencies), and infrastructure-level (MEP systems that support unknown future uses). “These features obviously cost more upfront, but… they pay off exponentially and do us more resilience in the building design.”

Benchmarking, efficiency, and utilization

When it comes to metrics, Leftwich cautioned against letting efficiency goals override research quality. “Efficiency isn’t the only story. It’s context that matters,” he said. “A 58 percent lab building that… enables world class science is more valuable than a 65 percent efficient building that restricts discovery.”

He described how utilization has emerged as a more nuanced and useful metric. “At its core, utilization measures how often and how intensively a space is used,” he said. But with the rise of automation and AI in research, that can be harder to observe. “Administrators come in: Where’s all the people? Why aren’t they working in the lab? Well, that lab’s running. And that lab may be running more efficiently than with a team in it.”

Real-time monitoring tools such as badge access data, CO2 sensors, or even digital notebooks can help institutions get a clearer picture. “It’s critical for benchmarking and planning renovations and for justifying new capital investments,” he said.

Planning costs and lifecycle value

Cost was another central theme—specifically, how early design choices can shape long-term value. “The most impactful decisions, especially with costs, they're made in the first 10 percent of the design process,” Leftwich explained. “Those decisions have ripple effects… that will last for decades.”

To illustrate cost complexity, he described client missteps when benchmarking against dissimilar projects. “Are you comparing apples to apples?” he asked. “That high one is, you know, solar energy research… the other low one there, that’s at the University of Pittsburgh. What does that have to do with the prices in California?”

In these cases, normalizing cost comparisons—by removing shell/core expenses or aligning by program type—can help clients make more informed decisions.

Looking ahead

Leftwich concluded with a candid assessment: “Everything that we've measured in the past isn't really applicable to the future anymore. And that's the hardest thing.”

From changing research methodologies to the rapid evolution of AI and automation, the lab environments of tomorrow will require new planning frameworks. “It’s important to really focus on the future vision and kind of use all of these metrics as guides, but they won't really be applicable to the visions of tomorrow.”

In short, metrics matter—but only when they are wielded in service of an institution’s evolving scientific mission.

For more information on metrics, data, and evaluating the success of your lab projects, join us at the 2026 Lab Design Conference in Orlando, FL, on May 11-14! Sign up here to receive the latest updates about our agenda and speakers.