How Can Predictive Analytics Transform Workplace Safety in High-Risk Industries?

Occupational health and safety (OHS) remain critical concerns, especially in high-risk industries like manufacturing and construction. Traditional reactive approaches often fall short in preventing incidents. A recent study highlights the potential of predictive analytics, driven by machine learning and statistical modeling, to proactively identify and mitigate risks. Implementing such technologies could revolutionize OHS practices, but challenges like data fragmentation and resource constraints persist. What steps can organizations take to integrate predictive analytics into their safety protocols? How can HR professionals champion this shift towards a more proactive safety culture?

Occupational Health and Safety (OHS) Concerns

The occupational health and safety (OHS) has remained a critical concern. OHS is not a direct functional area for HR; rather, it falls under the EHS department, which operates under the statute of the Director of Factory. The Factory Manager and Occupier are the key personnel. The EHS department, especially, formulates the policy under government guidance for each category of industries (high-risk), whether it be manufacturing or construction.

At present, the traditional reactive approaches are not existing. The new ILO and WHO recommended approach has become operational. The key note is that monitoring falls short in preventing incidents. Industries in rural sectors are more exposed to OHS threats. HR has turned into a puppet in those areas because their direct involvement is minimal. The role of HR has to be redesigned under the statute to play a key role.