Tag: effectiveness paradox

Sidney Dekker: The Safety Scientist Who Influences How I Think About Quality

Over the past decades, as I’ve grown and now led quality organizations in biotechnology, I’ve encountered many thinkers who’ve shaped my approach to investigation and risk management. But few have fundamentally altered my perspective like Sidney Dekker. His work didn’t just add to my toolkit—it forced me to question some of my most basic assumptions about human error, system failure, and what it means to create genuinely effective quality systems.

Dekker’s challenge to move beyond “safety theater” toward authentic learning resonates deeply with my own frustrations about quality systems that look impressive on paper but fail when tested by real-world complexity.

Why Dekker Matters for Quality Leaders

Professor Sidney Dekker brings a unique combination of academic rigor and operational experience to safety science. As both a commercial airline pilot and the Director of the Safety Science Innovation Lab at Griffith University, he understands the gap between how work is supposed to happen and how it actually gets done. This dual perspective—practitioner and scholar—gives his critiques of traditional safety approaches unusual credibility.

But what initially drew me to Dekker’s work wasn’t his credentials. It was his ability to articulate something I’d been experiencing but couldn’t quite name: the growing disconnect between our increasingly sophisticated compliance systems and our actual ability to prevent quality problems. His concept of “drift into failure” provided a framework for understanding why organizations with excellent procedures and well-trained personnel still experience systemic breakdowns.

The “New View” Revolution

Dekker’s most fundamental contribution is what he calls the “new view” of human error—a complete reframing of how we understand system failures. Having spent years investigating deviations and CAPAs, I can attest to how transformative this shift in perspective can be.

The Traditional Approach I Used to Take:

  • Human error causes problems
  • People are unreliable; systems need protection from human variability
  • Solutions focus on better training, clearer procedures, more controls

Dekker’s New View That Changed My Practice:

  • Human error is a symptom of deeper systemic issues
  • People are the primary source of system reliability, not the threat to it
  • Variability and adaptation are what make complex systems work

This isn’t just academic theory—it has practical implications for every investigation I lead. When I encounter “operator error” in a deviation investigation, Dekker’s framework pushes me to ask different questions: What made this action reasonable to the operator at the time? What system conditions shaped their decision-making? How did our procedures and training actually perform under real-world conditions?

This shift aligns perfectly with the causal reasoning approaches I’ve been developing on this blog. Instead of stopping at “failure to follow procedure,” we dig into the specific mechanisms that drove the event—exactly what Dekker’s view demands.

Drift Into Failure: Why Good Organizations Go Bad

Perhaps Dekker’s most powerful concept for quality leaders is “drift into failure”—the idea that organizations gradually migrate toward disaster through seemingly rational local decisions. This isn’t sudden catastrophic failure; it’s incremental erosion of safety margins through competitive pressure, resource constraints, and normalized deviance.

I’ve seen this pattern repeatedly. For example, a cleaning validation program starts with robust protocols, but over time, small shortcuts accumulate: sampling points that are “difficult to access” get moved, hold times get shortened when production pressure increases, acceptance criteria get “clarified” in ways that gradually expand limits.

Each individual decision seems reasonable in isolation. But collectively, they represent drift—a gradual migration away from the original safety margins toward conditions that enable failure. The contamination events and data integrity issues that plague our industry often represent the endpoint of these drift processes, not sudden breakdowns in otherwise reliable systems.

Beyond Root Cause: Understanding Contributing Conditions

Traditional root cause analysis seeks the single factor that “caused” an event, but complex system failures emerge from multiple interacting conditions. The take-the-best heuristic I’ve been exploring on this blog—focusing on the most causally powerful factor—builds directly on Dekker’s insight that we need to understand mechanisms, not hunt for someone to blame.

When I investigate a failure now, I’m not looking for THE root cause. I’m trying to understand how various factors combined to create conditions for failure. What pressures were operators experiencing? How did procedures perform under actual conditions? What information was available to decision-makers? What made their actions reasonable given their understanding of the situation?

This approach generates investigations that actually help prevent recurrence rather than just satisfying regulatory expectations for “complete” investigations.

Just Culture: Moving Beyond Blame

Dekker’s evolution of just culture thinking has been particularly influential in my leadership approach. His latest work moves beyond simple “blame-free” environments toward restorative justice principles—asking not “who broke the rule” but “who was hurt and how can we address underlying needs.”

This shift has practical implications for how I handle deviations and quality events. Instead of focusing on disciplinary action, I’m asking: What systemic conditions contributed to this outcome? What support do people need to succeed? How can we address the underlying vulnerabilities this event revealed?

This doesn’t mean eliminating accountability—it means creating accountability systems that actually improve performance rather than just satisfying our need to assign blame.

Safety Theater: The Problem with Compliance Performance

Dekker’s most recent work on “safety theater” hits particularly close to home in our regulated environment. He defines safety theater as the performance of compliance when under surveillance that retreats to actual work practices when supervision disappears.

I’ve watched organizations prepare for inspections by creating impressive documentation packages that bear little resemblance to how work actually gets done. Procedures get rewritten to sound more rigorous, training records get updated, and everyone rehearses the “right” answers for auditors. But once the inspection ends, work reverts to the adaptive practices that actually make operations function.

This theater emerges from our desire for perfect, controllable systems, but it paradoxically undermines genuine safety by creating inauthenticity. People learn to perform compliance rather than create genuine safety and quality outcomes.

The falsifiable quality systems I’ve been advocating on this blog represent one response to this problem—creating systems that can be tested and potentially proven wrong rather than just demonstrated as compliant.

Six Practical Takeaways for Quality Leaders

After years of applying Dekker’s insights in biotechnology manufacturing, here are the six most practical lessons for quality professionals:

1. Treat “Human Error” as the Beginning of Investigation, Not the End

When investigations conclude with “human error,” they’ve barely started. This should prompt deeper questions: Why did this action make sense? What system conditions shaped this decision? What can we learn about how our procedures and training actually perform under pressure?

2. Understand Work-as-Done, Not Just Work-as-Imagined

There’s always a gap between procedures (work-as-imagined) and actual practice (work-as-done). Understanding this gap and why it exists is more valuable than trying to force compliance with unrealistic procedures. Some of the most important quality improvements I’ve implemented came from understanding how operators actually solve problems under real conditions.

3. Measure Positive Capacities, Not Just Negative Events

Traditional quality metrics focus on what didn’t happen—no deviations, no complaints, no failures. I’ve started developing metrics around investigation quality, learning effectiveness, and adaptive capacity rather than just counting problems. How quickly do we identify and respond to emerging issues? How effectively do we share learning across sites? How well do our people handle unexpected situations?

4. Create Psychological Safety for Learning

Fear and punishment shut down the flow of safety-critical information. Organizations that want to learn from failures must create conditions where people can report problems, admit mistakes, and share concerns without fear of retribution. This is particularly challenging in our regulated environment, but it’s essential for moving beyond compliance theater toward genuine learning.

5. Focus on Contributing Conditions, Not Root Causes

Complex failures emerge from multiple interacting factors, not single root causes. The take-the-best approach I’ve been developing helps identify the most causally powerful factor while avoiding the trap of seeking THE cause. Understanding mechanisms is more valuable than finding someone to blame.

6. Embrace Adaptive Capacity Instead of Fighting Variability

People’s ability to adapt and respond to unexpected conditions is what makes complex systems work, not a threat to be controlled. Rather than trying to eliminate human variability through ever-more-prescriptive procedures, we should understand how that variability creates resilience and design systems that support rather than constrain adaptive problem-solving.

Connection to Investigation Excellence

Dekker’s work provides the theoretical foundation for many approaches I’ve been exploring on this blog. His emphasis on testable hypotheses rather than compliance theater directly supports falsifiable quality systems. His new view framework underlies the causal reasoning methods I’ve been developing. His focus on understanding normal work, not just failures, informs my approach to risk management.

Most importantly, his insistence on moving beyond negative reasoning (“what didn’t happen”) to positive causal statements (“what actually happened and why”) has transformed how I approach investigations. Instead of documenting failures to follow procedures, we’re understanding the specific mechanisms that drove events—and that makes all the difference in preventing recurrence.

Essential Reading for Quality Leaders

If you’re leading quality organizations in today’s complex regulatory environment, these Dekker works are essential:

Start Here:

For Investigation Excellence:

  • Behind Human Error (with Woods, Cook, et al.) – Comprehensive framework for moving beyond blame
  • Drift into Failure – Understanding how good organizations gradually deteriorate

For Current Challenges:

The Leadership Challenge

Dekker’s work challenges us as quality leaders to move beyond the comfortable certainty of compliance-focused approaches toward the more demanding work of creating genuine learning systems. This requires admitting that our procedures and training might not work as intended. It means supporting people when they make mistakes rather than just punishing them. It demands that we measure our success by how well we learn and adapt, not just how well we document compliance.

This isn’t easy work. It requires the kind of organizational humility that Amy Edmondson and other leadership researchers emphasize—the willingness to be proven wrong in service of getting better. But in my experience, organizations that embrace this challenge develop more robust quality systems and, ultimately, better outcomes for patients.

The question isn’t whether Sidney Dekker is right about everything—it’s whether we’re willing to test his ideas and learn from the results. That’s exactly the kind of falsifiable approach that both his work and effective quality systems demand.

Beyond “Knowing Is Half the Battle”

Dr. Valerie Mulholland’s recent exploration of the GI Joe Bias strikes gets to the heart of a fundamental challenge in pharmaceutical quality management: the persistent belief that awareness of cognitive biases is sufficient to overcome them. I find Valerie’s analysis particularly compelling because it connects directly to the practical realities we face when implementing ICH Q9(R1)’s mandate to actively manage subjectivity in risk assessment.

Valerie’s observation that “awareness of a bias does little to prevent it from influencing our decisions” shows us that the GI Joe Bias underlays a critical gap between intellectual understanding and practical application—a gap that pharmaceutical organizations must bridge if they hope to achieve the risk-based decision-making excellence that ICH Q9(R1) demands.

The Expertise Paradox: Why Quality Professionals Are Particularly Vulnerable

Valerie correctly identifies that quality risk management facilitators are often better at spotting biases in others than in themselves. This observation connects to a deeper challenge I’ve previously explored: the fallacy of expert immunity. Our expertise in pharmaceutical quality systems creates cognitive patterns that simultaneously enable rapid, accurate technical judgments while increasing our vulnerability to specific biases.

The very mechanisms that make us effective quality professionals—pattern recognition, schema-based processing, heuristic shortcuts derived from base rate experiences—are the same cognitive tools that generate bias. When I conduct investigations or facilitate risk assessments, my extensive experience with similar events creates expectations and assumptions that can blind me to novel failure modes or unexpected causal relationships. This isn’t a character flaw; it’s an inherent part of how expertise develops and operates.

Valerie’s emphasis on the need for trained facilitators in high-formality QRM activities reflects this reality. External facilitation isn’t just about process management—it’s about introducing cognitive diversity and bias detection capabilities that internal teams, no matter how experienced, cannot provide for themselves. The facilitator serves as a structured intervention against the GI Joe fallacy, embodying the systematic approaches that awareness alone cannot deliver.

From Awareness to Architecture: Building Bias-Resistant Quality Systems

The critical insight from both Valerie’s work and my writing about structured hypothesis formation is that effective bias management requires architectural solutions, not individual willpower. ICH Q9(R1)’s introduction of the “Managing and Minimizing Subjectivity” section represents recognition that regulatory compliance requires systematic approaches to cognitive bias management.

In my post on reducing subjectivity in quality risk management, I identified four strategies that directly address the limitations Valerie highlights about the GI Joe Bias:

  1. Leveraging Knowledge Management: Rather than relying on individual awareness, effective bias management requires systematic capture and application of objective information. When risk assessors can access structured historical data, supplier performance metrics, and process capability studies, they’re less dependent on potentially biased recollections or impressions.
  2. Good Risk Questions: The formulation of risk questions represents a critical intervention point. Well-crafted questions can anchor assessments in specific, measurable terms rather than vague generalizations that invite subjective interpretation. Instead of asking “What are the risks to product quality?”, effective risk questions might ask “What are the potential causes of out-of-specification dissolution results for Product X in the next 6 months based on the last three years of data?”
  3. Cross-Functional Teams: Valerie’s observation that we’re better at spotting biases in others translates directly into team composition strategies. Diverse, cross-functional teams naturally create the external perspective that individual bias recognition cannot provide. The manufacturing engineer, quality analyst, and regulatory specialist bring different cognitive frameworks that can identify blind spots in each other’s reasoning.
  4. Structured Decision-Making Processes: The tools Valerie mentions—PHA, FMEA, Ishikawa, bow-tie analysis—serve as external cognitive scaffolding that guides thinking through systematic pathways rather than relying on intuitive shortcuts that may be biased.

The Formality Framework: When and How to Escalate Bias Management

One of the most valuable aspects of ICH Q9(R1) is its introduction of the formality concept—the idea that different situations require different levels of systematic intervention. Valerie’s article implicitly addresses this by noting that “high formality QRM activities” require trained facilitators. This suggests a graduated approach to bias management that scales intervention intensity with decision importance.

This formality framework needs to include bias management that organizations can use to determine when and how intensively to apply bias mitigation strategies:

  • Low Formality Situations: Routine decisions with well-understood parameters, limited stakeholders, and reversible outcomes. Basic bias awareness training and standardized checklists may be sufficient.
  • Medium Formality Situations: Decisions involving moderate complexity, uncertainty, or impact. These require cross-functional input, structured decision tools, and documentation of rationales.
  • High Formality Situations: Complex, high-stakes decisions with significant uncertainty, multiple conflicting objectives, or diverse stakeholders. These demand external facilitation, systematic bias checks, and formal documentation of how potential biases were addressed.

This framework acknowledges that the GI Joe fallacy is most dangerous in high-formality situations where the stakes are highest and the cognitive demands greatest. It’s precisely in these contexts that our confidence in our ability to overcome bias through awareness becomes most problematic.

The Cultural Dimension: Creating Environments That Support Bias Recognition

Valerie’s emphasis on fostering humility, encouraging teams to acknowledge that “no one is immune to bias, even the most experienced professionals” connects to my observations about building expertise in quality organizations. Creating cultures that can effectively manage subjectivity requires more than tools and processes; it requires psychological safety that allows bias recognition without professional threat.

I’ve noted in past posts that organizations advancing beyond basic awareness levels demonstrate “systematic recognition of cognitive bias risks” with growing understanding that “human judgment limitations can affect risk assessment quality.” However, the transition from awareness to systematic application requires cultural changes that make bias discussion routine rather than threatening.

This cultural dimension becomes particularly important when we consider the ironic processing effects that Valerie references. When organizations create environments where acknowledging bias is seen as admitting incompetence, they inadvertently increase bias through suppression attempts. Teams that must appear confident and decisive may unconsciously avoid bias recognition because it threatens their professional identity.

The solution is creating cultures that frame bias recognition as professional competence rather than limitation. Just as we expect quality professionals to understand statistical process control or regulatory requirements, we should expect them to understand and systematically address their cognitive limitations.

Practical Implementation: Moving Beyond the GI Joe Fallacy

Building on Valerie’s recommendations for structured tools and systematic approaches, here are some specific implementation strategies that organizations can adopt to move beyond bias awareness toward bias management:

  • Bias Pre-mortems: Before conducting risk assessments, teams explicitly discuss what biases might affect their analysis and establish specific countermeasures. This makes bias consideration routine rather than reactive.
  • Devil’s Advocate Protocols: Systematic assignment of team members to challenge prevailing assumptions and identify information that contradicts emerging conclusions.
  • Perspective-Taking Requirements: Formal requirements to consider how different stakeholders (patients, regulators, operators) might view risks differently from the assessment team.
  • Bias Audit Trails: Documentation requirements that capture not just what decisions were made, but how potential biases were recognized and addressed during the decision-making process.
  • External Review Requirements: For high-formality decisions, mandatory review by individuals who weren’t involved in the initial assessment and can provide fresh perspectives.

These interventions acknowledge that bias management is not about eliminating human judgment—it’s about scaffolding human judgment with systematic processes that compensate for known cognitive limitations.

The Broader Implications: Subjectivity as Systemic Challenge

Valerie’s analysis of the GI Joe Bias connects to broader themes in my work about the effectiveness paradox and the challenges of building rigorous quality systems in an age of pop psychology. The pharmaceutical industry’s tendency to adopt appealing frameworks without rigorous evaluation extends to bias management strategies. Organizations may implement “bias training” or “awareness programs” that create the illusion of progress while failing to address the systematic changes needed for genuine improvement.

The GI Joe Bias serves as a perfect example of this challenge. It’s tempting to believe that naming the bias—recognizing that awareness isn’t enough—somehow protects us from falling into the awareness trap. But the bias is self-referential: knowing about the GI Joe Bias doesn’t automatically prevent us from succumbing to it when implementing bias management strategies.

This is why Valerie’s emphasis on systematic interventions rather than individual awareness is so crucial. Effective bias management requires changing the decision-making environment, not just the decision-makers’ knowledge. It requires building systems, not slogans.

A Call for Systematic Excellence in Bias Management

Valerie’s exploration of the GI Joe Bias provides a crucial call for advancing pharmaceutical quality management beyond the illusion that awareness equals capability. Her work, combined with ICH Q9(R1)’s explicit recognition of subjectivity challenges, creates an opportunity for the industry to develop more sophisticated approaches to cognitive bias management.

The path forward requires acknowledging that bias management is a core competency for quality professionals, equivalent to understanding analytical method validation or process characterization. It requires systematic approaches that scaffold human judgment rather than attempting to eliminate it. Most importantly, it requires cultures that view bias recognition as professional strength rather than weakness.

As I continue to build frameworks for reducing subjectivity in quality risk management and developing structured approaches to decision-making, Valerie’s insights about the limitations of awareness provide essential grounding. The GI Joe Bias reminds us that knowing is not half the battle—it’s barely the beginning.

The real battle lies in creating pharmaceutical quality systems that systematically compensate for human cognitive limitations while leveraging human expertise and judgment. That battle is won not through individual awareness or good intentions, but through systematic excellence in bias management architecture.

What structured approaches has your organization implemented to move beyond bias awareness toward systematic bias management? Share your experiences and challenges as we work together to advance the maturity of risk management practices in our industry.

Meet Valerie Mulholland

Dr. Valerie Mulholland is transforming how our industry thinks about quality risk management. As CEO and Principal Consultant at GMP Services in Ireland, Valerie brings over 25 years of hands-on experience auditing and consulting across biopharmaceutical, pharmaceutical, medical device, and blood transfusion industries throughout the EU, US, and Mexico.

But what truly sets Valerie apart is her unique combination of practical expertise and cutting-edge research. She recently earned her PhD from TU Dublin’s Pharmaceutical Regulatory Science Team, focusing on “Effective Risk-Based Decision Making in Quality Risk Management”. Her groundbreaking research has produced 13 academic papers, with four publications specifically developed to support ICH’s work—research that’s now incorporated into the official ICH Q9(R1) training materials. This isn’t theoretical work gathering dust on academic shelves; it’s research that’s actively shaping global regulatory guidance.

Why Risk Revolution Deserves Your Attention

The Risk Revolution podcast, co-hosted by Valerie alongside Nuala Calnan (25-year pharmaceutical veteran and Arnold F. Graves Scholar) and Dr. Lori Richter (Director of Risk Management at Ultragenyx with 21+ years industry experience), represents something unique in pharmaceutical podcasting. This isn’t your typical regulatory update show—it’s a monthly masterclass in advancing risk management maturity.

In an industry where staying current isn’t optional—it’s essential for patient safety—Risk Revolution offers the kind of continuing education that actually advances your professional capabilities. These aren’t recycled conference presentations; they’re conversations with the people shaping our industry’s future.