Predictive Analytics

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Definition - What does Predictive Analytics mean?

Predictive analytics refers to a quantifiable system using basic-to-advanced methodologies highlighting cross-referential information of study case reports covering data metrics related to health and safety risk factors against baseline statistics for limiting or preventing workplace accidents/injuries. Traditionally, predictive analytics was introduced to advance the corporate infrastructure via job performance and streamlined productivity to maximize return on investment (ROI) benefits; however, its application can translate to health and safety dynamics.

SureHire explains Predictive Analytics

The basis for utilizing predictive analytics stems from safety professionals consolidating subjective observations in tandem with database resources that help chart and monitor the multifaceted dimensions in preserving a climate of health and safety. Consequently, many employers are transitioning to automated system platforms incorporating predictive analytics software with the overarching goal of gathering objective feedback showing comparative differences between previous job standards and current applications pending review. For safety professionals, interpreting data falls under categorical brackets to help establish benchmarks to track the difference between lagging data or previous case studies, alongside predictive data tailored to avoiding future cases on the job.

Although many employers use in-house safety professionals to conduct worksite inspections against potential environmental hazards, lax protocol to document repeated violations can heighten the incidence rate of workplace accidents/incidents, affecting the bottom line. For this reason, safety professionals can draw on predictive analytics to isolate fluctuating patterns across the spectrum of safety violations that may occur, suggesting non-compliance by employees or inefficient work practices requiring immediate action.

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