Most companies have data that can be used to prioritize and analyze employees, processes or workspaces at elevated risk. But currently, most organizations must first compile and export their data from multiple environmental, health, safety, and quality (EHSQ) and human capital management (HCM) platforms and then analyze it outside of these applications using tools, such as Microsoft Excel, Cognos, or Tableau.
Advancements in data science dramatically improve the information available to EHSQ professionals. Data science is making ‘Big Data’ applications, such as predictive analytics, mainstream. Predictive analytics allows you to add a future-looking element to your data that was not previously possible. Predictive analytics finds patterns in data to predict a future state by using those patterns. Although predictive models are not the crystal ball that gives the exact time and place that an event will occur, they can find patterns associated with elevated risk.