Using Analytics to Strengthen Risk Capability and Improve Process Safety Performance

With access to a multi-year data set of over a million incidents from 1000â??s of operating facilities worldwide in the Energy and Chemicals industry, the research team mined the data set to explore the differences in operational risk reduction practices and organizational behaviors which most effectively explain the variation in outcome performance (e.g. Process Safety event rates, recordable injury rates, high-severity incident rates, etc.). By modeling and examining predictive relationships, the study identifies four attributes - worker engagement, process discipline, risk sensitivity, and learning-mindedness â?? as critical for preventing incidents.

Findings from this analytics-based study suggest that operating assets which are consistently operating at a near zero incident rate are companies that, to a greater degree, have successfully engaged their workforce, strengthened their operating discipline, sharpened their risk sensitivity, and become true learning-minded organizations. A learning-minded organization responds to each failure â?? no matter how small â?? deliberately to identify and fully leverage improvement and learning opportunities.

This study provides statistical evidence to support the strong correlation between the measurable characteristics of mature learning capability and outcome performance. The results also define the measurable organizational factors that are necessary to sustain efforts for effectively reducing risks and driving down loss rates.

By deriving these insights from a data set of routine field-level activities, operational measurements may be created to measure progress and drive focus on engagement, discipline, risks, and learning. The paper will conclude by sharing examples of how these measurements are applied on monthly and quarterly management reports to strengthen learning capability and ultimately improve outcomes.