Description
Date: 26 March, 2026, 13.00 UTC.
Estimated Time: 1 hr
Language: English
Summary of the lecture
While global injury rates continue to decline, fatalities in high-risk industries have largely plateaued. This highlights a critical gap in how organisations manage and verify the life-saving controls designed to prevent catastrophic events.
In the steel industry, operations involving heavy machinery, high energy sources, working at height, and mobile equipment create persistent critical risks. Preventing fatalities requires more than traditional safety metrics — it requires structured Critical Risk Management (CRM) focused on identifying and verifying critical controls.
In this steelTalk, Simon Barnier, Global Head of Sales – Go To Market at Forwood Safety, will explain how data and Artificial Intelligence are transforming CRM. The session will show how large-scale control verification data, predictive analytics, and AI-driven insights can reveal control gaps, risk hotspots, and emerging trends before serious incidents occur.
What you will learn:
- Distinguish between traditional safety management and Critical Risk Management focused on fatality prevention.
- Understand best practice approaches to identifying and verifying critical controls.
- Recognise how data analytics can reveal emerging risk trends and control gaps.
- Assess the role of AI in improving visibility and preventing catastrophic events in steel operations.
Speaker Introduction
Simon Barnier
Global Head of Sales – Go To Market, Forwood Safety
Simon Barnier is the Global Head of Sales – Go to Market at Forwood Safety, a global leader in Critical Risk Management focused on preventing serious injuries and fatalities in high-risk industries.
He leads Forwood’s international growth strategy across North and South America, Europe, Africa, the Middle East, and Asia-Pacific, working with major industrial organisations to strengthen fatality prevention frameworks.
Simon works closely with executive leaders and operational teams to show how structured Critical Risk Management, supported by data and AI, can move organisations beyond traditional safety metrics towards proactive life-saving control verification.
