Standard operating procedures give laboratory managers the consistency and predictability they depend on. Yet that same obsession with stability produces a frustrating paradox: scientific training demands innovation, but the daily workflows of a lab are engineered to resist it. Speaking at the Lab Manager Leadership Summit, Scott Hanton, PhD, editorial director of Lab Manager, urged leaders to stop treating operational transitions as chaotic disruptions and start managing them as structured, scientific processes.
Scott Hanton, Editorial Director at Lab Manager.
Hanton framed the stakes in blunt terms. "I thought in running a business, that a business was either going forwards or backwards," he explained. "There was no neutral, and so if you thought that you were just staying the same, everybody else was passing you." His central argument was that by adopting a structured approach and prioritizing empathy when managing laboratory teams, lab leaders can transition their operations from rigid bureaucracies into agile, resilient environments of continuous improvement.
The paradox of laboratory predictability
Most laboratories are deliberately built to make change difficult. Validated methodologies, strict regulatory standards such as the Centers for Medicare & Medicaid Services Clinical Laboratory Improvement Amendments (CLIA) standards, and repeatable instrumentation workflows all exist to minimize variability. So when a manager tries to introduce a new system, software platform, or workflow, they are effectively fighting the very architecture that guarantees the lab's quality.
That institutional inertia is reinforced by the people at the bench. By training and temperament, laboratory professionals are disciplined, data-driven skeptics, conditioned to treat any disruption to their validated baselines with suspicion. The instinct to protect what works is a feature, not a flaw—but it makes change unusually hard to land.
Hanton's warning is that avoiding change is ultimately a fatal strategy. Technological disruption, regulatory shifts, funding volatility, and retirements all guarantee that stability is an illusion. He pointed to a guiding principle from the Center for Creative Leadership: "There is no growth in the comfort zone. There is no comfort in the growth zone." The leader's job, then, is to find equilibrium—pushing innovators forward while giving more conservative team members enough security to adapt.
The Satir curve and the valley of despair
To guide a technical team through a major transition, managers need to understand that change rarely moves in a smooth, linear line. It follows a predictable emotional curve with distinct phases:
- Old status quo: the initial state of comfort, consistency, and standardized operations.
- Resistance: the immediate skepticism and pushback when a foreign element or new workflow appears.
- Chaos (the valley of despair): the critical pivot point where workflows slow, error rates spike, and frustration peaks.
- Transforming idea: the solution, perspective shift, or turning point that resolves the chaos.
- Integration: the hands-on phase of practicing and merging the new process into daily routines.
- New status quo: the stabilization of the new workflow into a modern baseline of efficiency.
When a "foreign element"—a LIMS upgrade, say, or a safety policy overhaul—is introduced, the team reacts with resistance. As the old order breaks down, the lab descends into the valley of despair, where things genuinely get harder before they get easier. This is where many managers make their fatal mistake: they declare the initiative a failure and revert to the old process.
Hanton argued that halting an initiative mid-dip is a recipe for chronic instability. "Step one was that we were going to start a change. Step two was holy crap, I was not happy, and step three was the valley of despair, so why, why did you want to stop in the valley of despair and just do it over again? That was insanity, right, so you needed to drive through that valley of despair and drive the change home." Change, he noted, triggers a psychological response much like grief. By offering clear reasoning, visible personal benefits, and time to adjust, leaders can help their teams climb out of chaos toward a new equilibrium.
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Applying an engineering framework to laboratory transition
Because scientists distrust abstract management theory, Hanton advocated a systematic, five-step change recipe developed at the global engineering firm Air Products.
- Define the opportunity: Identify the change with clear, concise, and concrete statements of improvement. Hanton advised managers to practice "management by walking around" and question unquestioned processes. This allows for a change opportunity to be identified, providing an ideal starting point for mastering the change management process in laboratories.
- Share the vision: Paint an authentic, tangible picture of the future lab—cutting sample turnaround times, improving data quality, reducing manual transcription, or preventing compliance errors.
- Build support and commitment: Because scientists are trained skeptics, they require data, logic, and proof. Show how the change benefits individuals directly, whether by saving steps, simplifying reporting, or reducing safety risks.
- Implement the change: Move from strategy to execution. Every action item specifies who does what, and by when. Lab managers must also establish key performance indicators (KPIs) that predict the future, rather than simply summarizing historical errors.
- Sustain and make it stick: Once the change is integrated, the leader must secure the gains. This involves celebrating milestones, reinforcing new behaviors, and formalizing the change in the lab's SOPs.
Team dynamics: the 25/50/25 rule and the "bandit on the train"
When a major change arrives, teams tend to split into three groups. Roughly 25 percent are early adopters who instantly see the value. About 50 percent are fence-sitters, the cautious majority who want proof before committing. The final 25 percent are resistors who believe the change is unnecessary, overly complex, or doomed.
Many managers burn their leadership capital arguing with that final quarter. Hanton called this counterproductive. "You didn't want to go argue with the people who were resisting you, they were just going to resist harder," he advised. "You had to go after the people on the fence, convince the people who were on the fence to come off that fence on your side. If you could get them off the fence and on your side, they would do the work." Win the middle 50 percent and you build a 75 percent majority; past that tipping point, peer pressure and social proof quiet the remaining resistors.
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To stress-test a change and defuse opposition early, Hanton cited a tactic he attributed to innovation consultant Charlie Prather: put a "bandit" on the train. When assembling the team responsible for executing a change, deliberately invite one of the most respected and vocal resistors. The bandit surfaces every critique and failure mode in advance, letting the team fix vulnerabilities before launch. And if the manager wins that visible skeptic over, the convert often becomes the project's most persuasive advocate.
Building the business case
Direct reports are only half the challenge. Many managers find their biggest roadblocks come from above, where pitching a major instrument purchase or software implementation to executives can feel futile.
The friction comes down to a language barrier. Scientists speak in precision, analytical sensitivity, audit trails, and throughput. Executives speak in risk, revenue, strategy, and politics. To successfully pitch initiatives to senior leaders, particularly when justifying major shifts like lab digitalization strategies or proposing analytical instrumentation investments that must also meet strict FDA guidelines on regulatory data integrity, laboratory managers must build a robust, business-oriented business case.
That means framing the change in terms of corporate values such as safety, patient outcomes, or compliance; monetizing the benefits by translating technical metrics into reduced labor costs, added capacity, or avoided penalties; and outlining the risk of inaction, including system failures, lost accreditation, or declining throughput.
Sustainable integration: burning the ships
A strong launch doesn't guarantee a lasting change. To stop teams from sliding back into old habits, leaders must remove the pathways to the past—what Hanton called "burning the ships."
During his time at Intertek, his facility pursued ISO/IEC 17025 laboratory accreditation, which required scientists to log all raw data and sample tracking in standardized, traceable systems instead of informal paper workarounds. To enforce it, Hanton and his quality manager came in over the weekend and confiscated every pack of Post-it notes in the building. Monday brought an uproar, but they held firm and redirected staff to the new electronic logbooks. "Post-its were not part of our quality system," he told them. "That thing you were going to write down and stick to the monitor, write it down here where we told you to write it down, where we had an audit trail and we had traceability, because we didn't have any audit trail or traceability when that post-it fell off your monitor."
Removing the fallback left staff no choice but to adapt—but Hanton paired enforcement with relentless communication. He invoked the "Rule of Seven," the guideline that a message must be encountered across multiple channels at least seven times before most people absorb it. "If you think you've communicated enough, you have not communicated enough," he said. "If you think you've communicated enough, double it. Communicate more."
Building an adaptive laboratory culture
Tactics and enforcement matter, but the ultimate goal is a culture that embraces continuous improvement on its own. Hanton recommended a three-pronged strategy.
The first prong is cultivating emotional and psychological safety in the lab. Drawing on Daniel Coyle's The Culture Code, he described safety as an environment where people can bring their best selves to work without wearing a mask. A leader's first response to bad news should be gratitude for the honesty; managers who shoot the messenger teach staff to hide errors, seeding future quality and safety failures. Citing Amy Edmondson's The Fearless Organization, Hanton noted this allows teams to operate collectively without fear of humiliation, which in turn drives improved innovation, performance, and growth.
The second prong is a growth mindset. By framing process improvements as scientific experiments, managers turn change from an administrative chore into an analytical exercise. "I ran a business using the scientific method," Hanton reflected. "I just ran a million experiments and did again the things that worked." The cycle is familiar: observe a bottleneck, propose a hypothesis, run a localized pilot, analyze the data against performance metrics, and learn whether to scale, refine, or pivot. Framed this way, failure stops being shameful—it becomes data for the next iteration.
The third prong is alignment with organizational core values. Every initiative should anchor to what the parent organization already prizes—safety, data integrity, customer satisfaction. Hanton pointed to the work of Frances Frei and Anne Morriss, who define leadership as empowering people through one's presence and ensuring that impact persists in one's absence. True alignment means scientists wear eye protection and document raw data correctly even when no one is watching. And when a change maps to senior leadership's goals, managers can ride a wave of existing support, making funding, time, and cooperation far easier to secure.
Final thoughts
Laboratory leaders ultimately face a binary choice: be the changer, or wait to be the changed. For those who understand the dynamics of technical environments, the proactive path is clear. By treating transition as a systematic, data-driven science—combining a rigorous five-step framework with deep empathy for the human element—managers can guide their teams through the valley of despair and emerge with something better. In doing so, they elevate their labs from simple data factories into adaptive, strategic, and resilient hubs of scientific excellence.
