Labs often take pride in how much they can handle with limited resources. Teams adapt to staffing shortages, rising sample volumes, aging equipment, and manual workarounds because the work still gets done. Over time, however, those adaptations can quietly become operational liabilities.
A workflow that appears successful on paper may actually be running on excessive overtime, institutional knowledge, or employee burnout. Minor inefficiencies become normalized. Small quality risks start accumulating. And because the lab continues meeting deadlines, leaders may not realize how fragile the operation has become until something finally breaks.
Curtiss McNair Jr., vice president of operations at PanGIA Biotech, has seen how easily that can happen in high-volume laboratory environments. Earlier in his career, McNair helped oversee a laboratory operation that processed more than 95 million tests annually using highly manual workflows. The lab was used to receiving more than 3,000 FedEx boxes containing roughly 22,000 tubes within a two-hour window. Every sample required multiple relabeling steps and extensive manual handling.
From the outside, the operation looked highly effective. Turnaround times were maintained, throughput remained high, and error rates stayed below one percent. But internally, the strain was becoming impossible to ignore.
“Our systems were under pressure,” McNair explained. “The demand was increasing. Business was growing. But the cracks were starting to show. Put anything under enough pressure, and you'll see the cracks.”
Efficiency can hide operational fragility
One of the biggest challenges for laboratory leaders is recognizing when a process has become unsustainable before performance declines become obvious.
Teams often compensate for inefficient systems through experience and effort. Employees memorize workarounds, absorb extra responsibilities, stay late, or manually correct recurring problems. Those behaviors can make fragile systems appear stable.
McNair noted that his accessioning teams routinely worked extremely long shifts to keep pace with demand. Staff became highly skilled at operating within the manual system, but the model could not realistically scale with continued growth.
This creates a dangerous situation for leaders because success metrics may still appear positive:
- Turnaround times remain acceptable
- Quality indicators stay within thresholds
- Productivity targets are met
- Customer complaints remain low
Meanwhile, employees are carrying increasing operational risk behind the scenes.
“One percent error” sounds manageable until leaders calculate what that means at scale. In McNair’s case, even a relatively low error percentage translated into hundreds of thousands of affected samples annually.
Signs that a workflow may no longer be sustainable
Operational strain rarely appears all at once. More often, labs drift into unsustainable patterns gradually. Leaders become accustomed to the pressure because the environment has operated that way for years.
Several warning signs often appear before a larger operational failure:
- Overtime becomes routine rather than occasional
- Employees rely heavily on undocumented workarounds
- Training new staff becomes increasingly difficult
- Teams depend on a small number of highly experienced employees
- Minor quality issues become normalized
- Staff burnout and turnover begin increasing
- Small process delays create outsized downstream disruption
McNair warned against becoming overly attached to familiar workflows simply because they have historically worked well.
“Success today does not equal success tomorrow,” McNair notes.
Pressure-test systems before a crisis forces change
Many organizations wait too long to evaluate operational resilience because current workflows still appear functional. By the time leadership acknowledges the need for change, teams may already be exhausted and resistant.
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McNair recommends that leaders actively challenge their systems before a crisis does it for them.
“If you want to challenge your systems, challenge yourself, challenge your teams, put it under a little bit of pressure and see what’s there,” he explains.
That does not mean intentionally overwhelming employees. Instead, leaders should regularly assess:
- What happens if sample volume increases suddenly?
- Which processes rely too heavily on manual intervention?
- Where are employees compensating for weak systems?
- Which workflows break down when key personnel are absent?
- What tasks consume large amounts of labor without adding proportional value?
These discussions should involve bench-level staff whenever possible. Employees closest to the workflow often recognize operational weaknesses long before leadership sees them in performance metrics.
Avoid mistaking familiarity for stability
One reason unsustainable workflows persist is because teams become emotionally attached to them. Employees take pride in making difficult systems work, especially in high-performing laboratories.
McNair describes this as “the risk of comfort” and warned that stability can sometimes hide decline.
That attachment can make modernization efforts more difficult later. Teams may resist automation, process redesign, or workflow standardization because the existing system feels familiar and proven, even when it is creating long-term operational risk.
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Leaders can reduce that resistance by involving staff earlier in operational improvement discussions instead of waiting until major change becomes unavoidable. Small process improvements introduced consistently over time are often easier for teams to absorb than large-scale reactive overhauls.
Sustainable operations require continuous reevaluation
McNair encourages leaders to regularly step back from day-to-day production demands and ask whether current workflows could realistically support future growth, staffing changes, or additional operational pressure. Bringing frontline employees into those conversations early often reveals process weaknesses and improvement opportunities leadership may not see on dashboards alone. Labs that continuously reevaluate how work gets done are generally better positioned to adapt before disruption forces major change.
