SAP EHS - Risk Assessment Model designed using Supervised and Unsupervised Learning

Risk assessment is a strong component in promoting health and safety culture in an organization. It cuts across multiple departments and must be evaluated holistically.

The important question is “Does our Risk Assessment process follows a holistic process “. Usually risk assessment models are looked in isolation where holistic risk features that may contribute to holistic risk assessment determination are absent.

We propose an innovative risk assessment model using Big Data approach from multiple applications in the organization that may hold the data useful in determination of Risk. We propose an innovative data model that integrates data from various SAP/ ERP applications and proposes a holistic risk assessment predictive model.

There are multiple data sources for example in SAP application that can help determine risk. Some of the examples of those applications are Incident Management, Emission Management, SAP Work Permit Management, SAP Plant Maintenance, Management of Change and Risk Assessment application.

Our framework model collects data from all these application and uses machine learning algorithm to predict risk in a holistic sense. The risk therefore is assessed from all relevant features and mathematically quantified with machine learning algorithms.