When something goes wrong in a laboratory, leaders often respond by tightening oversight, clarifying rules, and reinforcing compliance. Given the environment, that reaction feels both logical and necessary.
But in a Harvard Business Review article, Kendra Okposo, director at the Change and Transformation Center of Expertise at BTS and co-lead of BTS’s DEI practice group, argues that this approach can produce a counterintuitive outcome: compliance without commitment. Over time, that dynamic may reduce transparency and weaken ownership of outcomes.
When accountability becomes performance, not ownership
In laboratory settings, accountability is often treated as a control function: defining expectations, monitoring adherence, and correcting deviations. Okposo’s framing challenges that assumption, suggesting that increased pressure can shift behavior toward risk avoidance rather than engagement with problems.
In practice, that can mean fewer open admissions of error, slower escalation of issues, and a preference for “safe” answers over accurate ones. The result is not stronger accountability but performative accountability. For lab managers, the distinction matters. A team can appear compliant while quietly becoming less responsive to uncertainty.
Shifting the focus from enforcement to conditions
Rather than asking how to enforce accountability, Okposo suggests a different starting point: what conditions make accountability something people actually choose? In this framing, accountability is shaped less by oversight and more by the environment around it.
Three forces consistently influence whether ownership emerges:
- Mindset shapes how people interpret responsibility. Employees may act from a place of self-protection or from a sense of reliability and contribution to shared outcomes.
- Meaning provides context for why the work matters. When purpose is clear, accountability is less about compliance and more about commitment to outcomes and shared goals.
- Mechanisms include the systems, rituals, and structures that either support or hinder openness. These can include feedback practices, meeting norms, and organizational responses to mistakes that encourage learning rather than avoidance.
Taken together, these elements shape whether accountability is experienced as enforcement or ownership.
What this looks like in practice
In the BTS case study described in the article, a global transportation organization was managing increased complexity as it scaled. Leadership found that inconsistent accountability was slowing decision-making and weakening cross-functional trust. Rather than introducing more controls, the intervention focused on how accountability was practiced in daily work.
The key shift was not procedural—it was behavioral. Leaders worked to surface how responsibility was shared, how problems were discussed, and how feedback was exchanged under real operational pressure.
Key takeaway for lab environments
For laboratory teams, the lesson is less about the structure of the program and more about the mechanism of change: accountability improves when it is practiced in how work is discussed, not only enforced through policy.
Three transferable lessons emerge:
- Ownership improves when expectations are co-defined, not just assigned
- Transparency increases when mistakes are discussed without immediate defensiveness
- Follow-through strengthens when reflection is built into routine operational checkpoints
Accountability in lab operations
In laboratory environments, accountability is often assumed to be a compliance outcome. But this framing suggests it is more accurately a relational and behavioral outcome shaped by daily interactions.
When teams trust that raising issues will not automatically trigger blame, they are more likely to surface problems early. When leaders model acknowledgment of errors, they signal that learning is part of performance, not separate from it.
The operational impact is less about eliminating mistakes and more about improving how quickly teams detect, discuss, and respond to them.
What lab leaders can take away
The practical implication is a shift in focus:
- From enforcing accountability to designing conditions that support it
- From tracking compliance to observing how problems are surfaced
- From correcting behavior after the fact to shaping how teams respond in real time
In this framing, accountability is not a system imposed on a team. It is a pattern that emerges from how work is led, discussed, and reinforced over time. By auditing your daily laboratory rituals rather than simply rewriting your standard operating procedures, you can cultivate a research environment that naturally detects errors faster, protects data integrity, and adapts to uncertainty with resilience.
This article was created with the assistance of Generative AI and has undergone editorial review before publishing.
