Safe As Podcast

Is your injury rate telling you next to nothing about fatality risk?For years, 'safety' has been measured by counting what went wrong - e.g. recordables, TRIFR, LTIFR. But serious injuries and fatalities, or SIFS, haven't followed the same consistent downward trend.This raises the question: are we measuring the 'wrong' thing?This video unpacks a 2026 study from Bayona, Hallowell and others who analysed 999 field assessments from 31 utility & construction companies, testing whether two short-term measures predicted serious harm potential.The measures were:a) Pre-job safety brief (PJSB) quality: evaluating the engagement and thoroughness of pre-task discussionsb) High-energy control assessment (HECA): the proportion of high-energy hazards with a direct control in place.They found:1) Companies with better pre-job briefs tended towards better energy controls2) Each 1-point increase in HECA was associated with ~3% fewer expected SIFsThey also found that better pre-job briefs were linked to ** more ** reported SIFS, but does this represent better reporting, or something else?Ref: Bayona et al. (2026), Journal of Safety Research, 98, 175–189. Study: https://doi.org/10.1016/j.jsr.2026.06.007Support the channel: https://buymeacoffee.com/benhutchinson#SafetyScience #SIF #SeriousInjuryPrevention #HOP #SafetyLeadership #ConstructionSafety

“There’s nothing new since the 1980s there”In part 1 of my interview with Dr Steven Shorrock. He's worked for about 30 years as a psychologist and human factors engineer in aviation, air traffic management, rail, healthcare and chemical manufacturing. Steven questions how much of HOP and the “new view” really comes from human factors and ergonomics research. He argues that many principles popularises older ideas rather than adding truly new thinking. And while some of its claims have strong evidence behind them, others have little, and few seem to come with methods you can actually use.We unpack:a. Safety as a feeling and a belief & why people at the sharp and blunt ends experience it so differentlyb. How his views have developed over the years since the Safety-I/Safety-II white paper with Dr Erik Hollnagelc. Why the evidence is strong (e.g. how WAI differs from real work and why people have to adapt), and where evidence is thind. What's changed in aviation & healthcare over time, including team-based quality reviewse. How storytelling can make systems thinking accessible, rather than jargonf. Why investigations often stop at human errorSteve’s blog: humanisticsystems.comResources & Links:Website & Articles: https://safetyinsights.orgSupport the channel: https://buymeacoffee.com/benhutchinson

This ep unpacks the 1998 Esso Longford gas plant explosion in Victoria, drawing on the safety science and sociological research from Emeritus Professor Andrew Hopkins.We move past proximal causes (like equipment failure) to unpack:a) how organisations construct causesb) manage chronic alarm fatiguec) distort safety metricsd) process critical operational feedbackSupport the channel: https://buymeacoffee.com/benhutchinson

Are higher-energy hazard interactions more likely to seriously injure or kill people?In this ep, we unpack the empirical link between energy exposure and SIFs - where over 500 injury reports were analysed, and injury energy magnitude was estimated using leading information.Key concepts were energy magnitude - being the amount of energy present; and energy intensity - how concentrated that energy is over the contact area. E.g. a sharp object can create greater harm than a blunt object carrying the same energy.Study Reference:Hallowell, M. R., et al. "Energy-based safety risk assessment: does magnitude and intensity of energy predict injury severity?" Construction Management and Economics.

Can AI help us identify critical safety blind-spots before disaster?Part 2 interview with Professor Robin Dillon-Merrill (Georgetown University, McDonough School of Business), who unpacks her 20+ years of research on decision-making under risk, outcome bias, and how organizations misinterpret near misses.We discuss:a) why near-miss biases shape human decision-making & how we can build robust systems to counter them catch them b) why technical experts are uniquely positioned to simulate counterfactuals ('what could have happened, but didn't')c) how well-intended safety messaging becomes background noise without institutional actiond) how cutting-edge AI & machine learning can triage gigantic incident datasets before catastrophe.Plus, Robin discusses real-world safety challenges with autonomous vehicles, such as Waymo vehicles illegally passing school buses in Texas.Resources & Links:Website & Articles: https://safetyinsights.orgSupport the channel: https://buymeacoffee.com/benhutchinson

Today we unpack a study tracking 1,422 procedural steps across 40 petrochemical operations. Using their Skip-Order-Action (SOA) Framework, they explored how frontline personnel navigate written instructions in practice: revealing that roughly 1/3 of steps depart from prescribed methods even when tasks are completed successfully. We explore how: a. the SOA framework functions b. how workers using paper instructions followed fewer steps as the task progressed (e.g. dropping from ~75% adherence to 55%)c. what these findings mean for safety professionals advancing a Safety-II / HOP approachReference: Ashraf, A. M., Peres, S. C., & Sasangohar, F. (2025). Beyond Compliance: Investigating Work-as-Done in Procedural Work with the Systematic Skip-Order-Action (SOA) Framework. Resources & Links:Website & Articles: https://safetyinsights.orgSupport the channel: https://buymeacoffee.com/benhutchinson

What happens when a high-authority automated system operate with an incorrect model of reality?This question is explored via Dekker & Woods’ (2024) article on automated systems that are Strong, Silent, and Wrong.We explore the breakdown of human-automation coordination, mode confusion, and automation surprises, using the Boeing 737 MAX MCAS accidents as a central example. Learn how complex system design must prioritize observability, redirectability, and graceful failure.Ref: Dekker, S. W., & Woods, D. D. (2024). Wrong, strong, and silent: What happens when automated systems with high autonomy and high authority misbehave? Journal of Cognitive Engineering and Decision Making, 18(4), 339–347.Resources & Links:Website & Articles: https://safetyinsights.orgSupport the channel: https://buymeacoffee.com/benhutchinson

Can fatigue cause visual blindness in plant operators and drivers?In this video, I review a 2019 study from Li et al. (Automation in Construction) who used wearable eye-tracking tech to measure how prolonged excavator operation / time-on-task fatigue impacts hazard detection and visual attention.Namely, whether the operators notice workers walking behind the excavator over a shift.Key findings:a. Hazard miss rates increased over 40% after 60 mins. Overall detection rates dropped to 70% at 36 minutes and down to 60% by the 60-minute mark.b. Operators took significantly longer to recognize peripheral hazards as fatigue increased.c. Visual attention on the excavator side mirrors and rearview mirrors decreased over the task. Operators stopped scanning peripheral blind spots and focused almost exclusively on the central display directly in front of them.Resources & Links:Website & Articles: https://safetyinsights.orgSupport the channel: https://buymeacoffee.com/benhutchinson

Do we routinely mistake good luck with systemic resilience – until something blows up?Today I speak with Professor Robin Dillon-Merrill (Georgetown University, McDonough School of Business), who breaks down her 20+ years of research on decision-making under risk, outcome bias, and how organizations misinterpret near misses.We discuss:• The differences between resilient vs vulnerable near misses: How the perceived ‘margin of safety’ desensitizes organizations to risk when luck is the primary reason failure was averted.• Managing outcome bias: Why leaders who experience lucky successes are possibly judged as more competent and promotable than those who face bad luck, even when their underlying decision quality is identical.• Counterfactual thinking: How processes used by NASA facilitate teams to evaluate alternative outcomes and decouple decision quality from outcomes. • Gathering info: Why decision makers consistently stop searching for critical warning signs long before they have sufficient data.• Why ‘speaking up’ campaigns fail: Safety reporting programs may be ineffective for recognising an issue since the issue isn’t recognised as danger in the first place.Resources & Links:Website & Articles: https://safetyinsights.orgSupport the channel: https://buymeacoffee.com/benhutchinson

Does a Human & Organizational Performance (HOP) initiative improve learning and the quality of actions? And what happens when the initiative stops?This quickisode unpacks Christopher Mastrangelo’s 2026 Master’s thesis examining a multi-year HOP implementation at a large biopharmaceutical company. His project tracked operational data from 2020 through July 2025 across key metrics: a. deviation initiation ratesb. root cause classification practicesc. CAPA types, andd. cultural persistence after formal support was removed. The HOP initiative seemingly resulted in:a. A drop in quality deviationsb. A shift away from findings of 'human error' towards organisational improvementsc. Fixing systems rather than retraining peopleAnd what happens when the HOP initiative and key stakeholders are dissolved? After the dedicated HOP team was dissolved in mid-2024, formal training scores dropped, and 'human factors' classifications (e.g. focusing on people rather than the system) crept back in. But, frontline work execution and proactive learning mindsets persisted. Resources & Links:Website & Articles: https://safetyinsights.orgSupport the channel: https://buymeacoffee.com/benhutchinson