Scientists reviewing data charts during root cause analysis in a laboratory setting.

Root Cause Analysis: The Fix for Recurring Lab Errors

A practical guide to strengthening your quality system, reducing repeated nonconformances, and creating a proactive, solution-focused culture

Written byLauren Everett
| 5 min read
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Root cause analysis plays a pivotal role in quality management, yet many analytical labs struggle to apply it effectively. When done well, it drives lasting improvements and prevents repeat issues—but common missteps can derail the process.

In this Q&A, laboratory quality expert Brenda Shalloo shares her perspective on how labs can move beyond surface-level fixes and address deeper system flaws. She offers practical insights on what makes root cause analysis effective, how to avoid common traps, and how labs can build a more proactive, solutions-focused culture.

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Brenda Shalloo

In your experience, what are the most common quality failures in analytical laboratories?

In my experience, one of the most common quality failures in analytical laboratories is placing blame on individuals rather than examining weaknesses in the quality system itself. A fundamental principle I follow is to shift the perspective from “Why did this person make a mistake?” to “How did the quality system allow this mistake to happen?”

Focusing on system-level failures rather than individual oversights is critical for building a culture of continuous improvement. People often approach quality issues and root cause analysis with reluctance or even fear. However, when you engage them as partners in identifying how the system can be improved, it not only fosters accountability but also encourages proactive problem-solving. This approach helps prevent future issues and strengthens overall quality ownership across the team.

What would you say are the most common root cause analysis failures in analytical laboratories? 

One of the most prevalent root cause failures I’ve observed in analytical laboratories is the over-reliance on “lack of training” as the default root cause. While training is undeniably important, citing it as the root cause is often a superficial fix rather than a true diagnosis. If a training program already exists and was delivered, then the real question becomes: why wasn’t the training retained or applied?

“Training” should only be considered a root cause when it genuinely doesn’t exist, not when it's a convenient explanation. Otherwise, you risk addressing symptoms instead of the underlying issue.

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How would you describe your overall approach to root cause analysis in the lab? What principles guide your process?

My approach to root cause analysis is centered around what I call the “Rule of 3 Whys.” While some methodologies advocate for five whys, I’ve consistently found that asking “why” three times is typically sufficient to uncover the underlying issue without overcomplicating the process.

For example, as we just discussed, I often challenge the default assumption that “training” is the root cause. One incident that illustrates this point involved employees not knowing where the spill kit was located, an issue uncovered during an internal audit where three different staff members couldn’t identify its location.

So, I applied the Rule of 3 Whys:

  • Why #1: Why didn’t the employees know where the spill kit was?
    Answer: Because they forgot its location after their safety training.
  • Why #2: Why did they forget its location?
    Answer: Because the spill kit was stored inside a closed cupboard and wasn’t visible.
  • Why #3: Why wasn’t it visible?
    Answer: Because the cupboard wasn’t labeled.

Once we labeled the cupboard clearly, the issue never recurred. If we had defaulted to retraining employees, we might have wasted time and still not resolved the problem. This example highlights the true value of structured root cause analysis: it enables us to implement simple, effective fixes that prevent recurrence, rather than treating symptoms.

How do you ensure that you’re addressing the true root cause and not just a symptom of a larger issue?

I focus on depth, breadth, and follow-through in the root cause analysis process.

First, a thorough root cause analysis must go beyond the immediate failure to explore systemic vulnerabilities. I ask whether the issue could manifest in other areas of the lab or under slightly different conditions. This helps determine if we’re dealing with an isolated incident or a symptom of a broader system weakness.

Second, I emphasize cross-functional input during investigations by engaging stakeholders from various areas of the lab. Continuously reviewing non-conformances with other leaders often reveals overlooked contributing factors and helps prevent narrow or biased conclusions. This collaborative approach ensures a more comprehensive understanding of the issue and leads to more effective, sustainable corrective actions.

Third, once a corrective action is implemented, it’s critical to validate its effectiveness over time. I establish a pre-determined review interval, the timeline of which will depend on the risk level, to assess whether the same issue has reoccurred or if any unintended consequences have emerged. The absence of recurrence is one of the clearest indicators that the true root cause was identified and addressed.

Can laboratories leverage technology to enhance the effectiveness of root cause analyses?

Absolutely. Laboratories can significantly enhance the effectiveness of root cause analyses by leveraging technology, particularly through modern quality management systems (QMS). These systems can automate key tasks, such as alerting teams when corrective actions are due for review, ensuring that follow-up activities aren't overlooked.

QMS platforms also allow teams to search historical records to identify recurring nonconformances, which is invaluable for recognizing patterns and systemic issues. Additionally, these tools support cross-functional collaboration by centralizing documentation and communication, reducing the need for excessive meetings and improving transparency.

Artificial intelligence is also emerging as a powerful tool in root cause analysis. AI-driven systems can analyze large data sets to identify hidden trends, flag anomalies, and even suggest potential causes based on historical data and similar events. This helps labs troubleshoot more efficiently and make data-informed decisions faster than traditional methods allow.

By integrating these technologies, laboratories can not only streamline the root cause process but also improve accuracy, consistency, and long-term quality outcomes.

How do you ensure that corrective actions derived from root cause analyses are effectively implemented and lead to continuous improvement?

Ensuring that corrective actions are effectively implemented and contribute to continuous improvement requires a systems-thinking mindset, active monitoring, cross-functional collaboration, and a sustained commitment to quality.

Rather than focusing solely on individual errors, I prioritize identifying and addressing failures within the management system. This approach enables deeper analysis of systemic issues that, if left unaddressed, can lead to recurring problems.

To ensure effectiveness, I establish clear follow-through mechanisms, including:

  • Monitoring the closure of corrective actions to ensure timely and complete implementation.
  • Conducting internal audits to verify that the changes are embedded into daily practice.
  • Reviewing outcomes in management meetings to align leadership and operational priorities.
  • Performing annual procedure reviews to assess long-term effectiveness and identify opportunities for further refinement.

These practices not only validate that corrective actions are working but also provide opportunities for the quality function to engage with all levels of the organization. This fosters a proactive culture, where potential issues are identified and improved upon before they escalate into nonconformances.


Brenda Shalloo is a seasoned scientist and industry leader with over 20 years of experience in environmental and cannabis laboratory operations. She holds a B.S. in Biology from Arizona State University and began her career as an environmental chemist specializing in GC-MS analysis. Brenda quickly established herself as a leading expert in the field, eventually co-founding Arizona’s first medical marijuana testing laboratory, only the fourth such facility in the United States, and became the first female principal scientist in the cannabis testing industry.

Throughout her career, Brenda has demonstrated a strong ability to build and manage compliant, ISO/IEC 17025:2017-accredited laboratories. She has served as chief operations officer and chief scientific officer for two cannabis testing laboratories, where she led technical operations, business strategy, and regulatory compliance efforts. Brenda also held the roles of quality control manager and certified internal auditor, overseeing quality systems, performing internal audits, and supporting third-party assessments.

Her expertise has impacted cannabis laboratory development and regulatory frameworks across seven US states. She has collaborated with regulatory agencies in six states and served as chair of the Independent Laboratory Advisory Committee for the State of Nevada. In March 2024, Brenda earned her lead auditor certification and has since reviewed and observed numerous assessments of ISO/IEC 17025-accredited laboratories. She also serves as an instructor for ANAB, delivering courses on Internal Auditing, Lead Assessing, and ISO/IEC 17025:2017 fundamentals.

About the Author

  • Lauren Everett headshot

    Lauren Everett is the managing editor for Lab Manager. She holds a bachelor's degree in journalism from SUNY New Paltz and has more than a decade of experience in news reporting, feature writing, and editing. She oversees the production of Lab Manager’s editorial print and online content, collaborates with industry experts for speaking engagements, and works with internal and freelance writers to deliver high-quality content. She has also led the editorial team to win Tabbie Awards in 2022, 2023, and 2024. This awards program recognizes exceptional B2B journalism and publications. 

    Lauren enjoys spending her spare time hiking, snowboarding, and keeping up with her two young children. She can be reached at leverett@labmanager.com.

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