
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
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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