WHS Rating

Project status: Complete

Can we help Regulators to predict future non-compliance?

Traditionally WHS Regulators have had few tools available to help predict the risk and likelihood of a business not complying with WHS legislation.

In a system that is heavily reliant on reporting and evidence collected from inspections, there is a wealth of data available that wasn’t being used to its full potential.

Using predictive analytics and machine learning to identify risk

The research team conducted analysis of various data sets including business demographics, WHS compliance history, workers compensation claims performance, and other information sources.

Using a predictive analytics model, this data was considered and tested to identify the predictive power of more than 400 characteristics in determining the risk of a business having an incident in the next 12 months.

A regulatory tool to prevent harm

A WHS risk rating tool was developed that assists WHS Inspectors to estimate the level of risk of a workplace having an incident in the next 12 months.

The predictive modelling tool considers SafeWork NSW data from the past decade, and identifies risks based on the interactions of specific businesses and comparison to similar businesses.

The risk rating tool complements existing decision-making resources available to NSW Inspectors, and based on historical data has proven a high accuracy in being able to successfully predict future incident.

Further reading

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