Logical Workflow Solutions for Labs: Designing Around How Work Happens in Real Life
Early involvement from end users helps reveal workflow details and hidden constraints that can shape more effective, functional laboratory design.
In many lab projects, the people making decisions about space are not the ones using it day to day. Leadership defines priorities, including how much space is needed, what functions must be accommodated, and how the lab should support broader organizational goals. Meanwhile, scientists and end users understand how the work happens. They know how samples move, where delays occur, what needs to be close, and what cannot overlap.
In theory, these perspectives should align. In practice, they often do not.
I have seen labs that were designed with little to no input from the people who use them. On paper, everything checked out. Equipment was accounted for, adjacencies made sense, and the space met program requirements. But once the lab was in use, small issues began to surface. Not because the design was wrong, but because there were details only the end users understood. How often a step repeats. Which process quietly becomes a bottleneck. What absolutely cannot sit next to something else, even if it looks fine in a layout. Those details rarely come up unless the right people are involved early.
The disconnect is usually not intentional. It is often a result of how projects are structured. Input from end users is filtered, summarized, or introduced too late to influence key decisions. By the time detailed feedback is gathered, major planning moves such as layout, adjacencies, and infrastructure are already in place. At that point, workflow is no longer being designed. It is being adjusted to fit.
When workflow is not fully understood early, the issues that follow are rarely dramatic. They show up in smaller ways. A technician has to cross the lab multiple times to complete a routine process. A shared piece of equipment creates just enough delay to slow everything around it. Storage is technically available, but not where it needs to be when work is happening. None of these problems would stop a project. But together, they shape how the lab functions every day. Over time, people adapt. They change how they move through the space, relocate materials, and create informal workarounds. Eventually, those adjustments become part of the workflow. From the outside, everything appears to be working. In reality, the space is no longer supporting the process. The process is compensating for the space.
A more effective approach starts earlier and focuses on the process first. Before layouts are developed or programs are finalized, there needs to be a clear understanding of how the lab operates today and how it is expected to evolve. This does not require mapping every variation, but it does require honest conversations about how work gets done.
A simple framework can guide this:
Understand the current state: What works well today? Where does work slow down? Which steps happen most often, and which ones create friction? The goal is not to document everything. It is to identify patterns.
Define how the science is changing: Labs are rarely static. New equipment, new processes, and scaling requirements all affect workflow. If those changes are not understood early, the space can fall out of sync quickly.
Identify what needs to change: Once the present and the future are understood, the focus shifts to alignment. What needs to change in the space to support the new workflow? What can remain, and what no longer works?
These discussions are most useful when they involve the people who experience the workflow every day. Not through layers of translation, but directly. They often surface constraints and opportunities that do not appear in drawings.
In many projects, planning begins with a program. Teams define the number of benches, equipment counts, headcount, and square footage. Workflow is often expected to fit within that structure. That approach works to a point, but it limits how effective the space can be. When workflow is treated as secondary, it has to adapt to decisions that have already been made.
A more effective approach is to reverse that sequence. Start with how work moves through the lab—what happens first, what follows, where processes intersect, and where delays are most likely. Then develop a layout that supports those sequences. Adjacency still matters, but sequence matters just as much. A lab can have the right adjacencies and still feel inefficient if the order of operations is not supported. Clear direction in how people, materials, and samples move through the space often has a greater impact than proximity alone.
One of the most effective ways to improve workflow is also one of the simplest—involve the right people earlier.
This does not mean involving everyone in every decision. It means identifying the people who understand how the work happens and giving them a chance to respond before key decisions are fixed. Even asking end users to review a layout before it is finalized can change the outcome. Not as a formality, but as a way to catch issues that are easy to miss.
They often point out details such as:
Steps that happen more frequently than expected
Areas where congestion builds
Processes that should not overlap
Tools or materials that need to be within immediate reach
Individually, these observations may seem minor. Together, they determine whether the workflow works in real-life applications.
In regulated environments, workflow is directly tied to compliance. In cGMP facilities, the separation between clean and dirty processes, or between different stages of production, must be clearly supported by the layout. When it is not, that responsibility shifts to procedures and personnel. This introduces risk. Procedures can compensate for design gaps, but they rely on consistency over time. Designing the space to support these separations reduces that burden and makes compliance easier to maintain.
Flexibility is often treated as a primary goal in lab design. The idea is to create a space that can adapt to any future need. In practice, too much flexibility can dilute workflow. When spaces are overly generic, it becomes harder to optimize them for any specific process. Equipment may be movable, but movement introduces inefficiency. People spend more time adjusting the space instead of working within it. A more balanced approach is usually more effective. Design for how the lab operates now, while allowing for targeted adjustments where change is most likely. Flexibility works best when it is intentional.
Support spaces such as write-up areas, storage, and staging zones are often treated as secondary. In reality, they have a direct impact on workflow.
When they are not well integrated, small disruptions begin to add up:
Time spent searching for materials
Tasks spilling into lab space
Unnecessary movement between activities
These issues may seem minor, but they occur throughout the day. When support spaces are planned as part of the workflow, not as an afterthought, the lab functions more smoothly.
The most effective labs share a common quality. The workflow feels intuitive. This does not mean the work is simple. It means the space aligns with how the work is done. People do not have to think about where to go next. Movement through the lab follows a natural sequence. You may not notice when it works. You will notice when it does not.
Achieving this level of alignment requires more than technical expertise ... it requires creating space early in the process for meaningful conversations. Not just about how much space is needed, but about how the lab operates in reality. Where it slows down. Where it breaks. How it is expected to change. Without that, workflow becomes something that is assumed rather than understood. And when that happens, the impact appears later, in day-to-day operations, through small inefficiencies that build over time.
Logical workflow solutions are not about making a lab look efficient—they are about making it function efficiently under real conditions. This is why feedback from end users is critical. When workflow is understood and integrated into the design process from the beginning, the results are often subtle. Fewer delays. Fewer conflicts. Less need for adjustment. In a lab environment, that absence of friction is often the clearest sign that the design is working as intended.
