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Utility Safety in Depth – The Safety Alchemist: Gina Vanderlin, CUSP, CSP, CHMM, CIT – Data into Utility Safety Insights

Written by Podbean Account on . Posted in Utility Safety in Depth Podcasts.

Read the article: https://incident-prevention.com/blog/confronting-data-bias-to-improve-safety-outcomes/

Effective mitigation requires leaders to regularly audit data, standardize definitions and measurement practices, and create psychologically safe reporting environments.

This podcast episode features Gina Vanderlin, CUSP, CSP, CHMM, CIT, Health and Safety Program Manager at PSEG Long Island and a self-professed “Safety Alchemist”. In a deep dive with host Kate Wade, Gina explores how safety professionals can transform raw data and standard procedures into meaningful organizational change. The conversation focuses on her Applied Alchemy article series for Incident Prevention magazine, specifically highlighting the hidden dangers of data bias and the evolving safety risks associated with new energy technologies like lithium-ion batteries.

Key Takeaways

  • The Concept of Safety Alchemy: Rather than just following compliance-based checklists, a “safety alchemist” blends diverse disciplines—such as behavioral science, decision science, and engineering—to transform information into actionable insight.
  • The Evolution of Battery Hazards: As utilities integrate EVs and grid storage, employers must reconsider hazard communication. Batteries often bypass traditional scrutiny because they are classified as “articles,” but damaged or failing batteries introduce significant chemical and fire risks.
  • Data Bias in Safety Management: Bias is a natural human trait, but in safety data, it can lead to “ghost” weaknesses. Gina identifies five key biases—survivorship, selection, measurement, historical, and algorithmic—that can cause a safety system to drift away from reality.
  • The “Geographic Presumption”: Under a new OSHA letter of interpretation (Jan 2026), injuries caused by personal devices (like e-cigarettes or personal chargers) in the workplace are generally considered work-related and recordable.
  • Improving Decision Quality: The common thread across all safety domains is decision quality. Improving how workers interpret information and how leaders prioritize resources is the most effective way to address the plateau in Serious Injury and Fatality (SIF) rates

Questions & Answers

Q1: How does Gina Vanderlin define “Decision Quality” in the context of utility safety?

A: Gina defines it as the core issue connecting diverse safety topics. It involves how individuals and organizations interpret information to make choices. If decisions are made based on flawed assumptions or biased data, the entire safety system can fail to address real-world risks.

Q2: What is a specific example of how data bias has physically impacted safety training?

A: Gina points to CPR training, noting that 95% of mannequins are anatomically male. This lack of representative data creates a “modesty deterrent” and technical discomfort, resulting in women being 14% less likely to receive CPR during a public medical event.

Q3: What does Gina suggest is the biggest pitfall for organizations rebranding their programs as “SIF-focused”?

A: The pitfall is rebranding on paper without actually improving the quality of investigations or examining the decision-making conditions that led to the exposure. Simply changing the name of a near-miss program doesn’t change the safety outcome if the underlying system remains the same.

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