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