The code of occupational health and safety (OHS) is an influential regulation to improve the on-the-job
safety of employees. A number of factors influence the planning and implementation of OHS management
systems (OHSMS). The evaluation of OHSMS practice is the most important component when forming
a health and safety environmental policy for employees. The objective of this research is to develop an
intelligent data analysis (IDA) in which possibilistic regression being endowed with a convex hull
approach is used to support the analysis of essential factors that influence OHSMS. Given such subjective
terms, the obtained samples can be conveniently regarded as fuzzy input/output data represented by
membership functions. The study offers this vehicle of intelligent data analysis as an alternative to evaluate
the influential factors in a successful implementation of OHS policies and in this way decrease an
overall computational effort. The obtained results show that several related OHSMS influential factors
need to be carefully considered to facilitate a successful implementation of the OHSMS procedure.