<![CDATA[The discipline of Occupational Health and Safety (OHS) is undergoing a paradigm shift driven by advances in wearable technology and machine learning. Lagging indicators, such as the Total Recordable Incident Rate (TRIR), have been historically considered the most common risk management metrics for gauging the safety performance of risk managers. Such measures merely describe what occurs once one has been defeated, but not the option of preventing the initial loss. The paper endorses the proposal to change to leading indicators, controlled by predictive analytics and the Internet of the Worker (IoW). By studying real-time biometric and environmental information, organizations would be able to identify pre-incident behavior patterns and prevent losses. This paper will examine the technically based infrastructure of the IoW, validate the financial case, using the Total Cost of Risk (TCOR) analysis, and a holistic ROI model, the underwriting implications of the Experience Modification rate (EMR) optimization and Schedule Rating and the ethical remit of data governance and just culture that must accompany the implementation of these technologies, based on the frames of the Associate in Risk Management (ARM) system]]>
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