Effective and efficient safety programs rely upon accurate and consistent risk assessments. Underestimate risk, and our safety and health programs become ineffective, as employees whose risk was underestimated continue to perform their duties with the risks unabated. Overestimate risk, and our programs become inefficient, as limited resources are wasted on risk controls where none were needed.
In general industry, formal risk assessments are often made qualitatively, using a matrix approach with severity and likelihood of harm as key inputs (Figure 1). Accurate and consistent risk assessments require selection of the correct severity and likelihood inputs. In particular, a clear understanding and assessment of the adequacy of controls is critical for selection of the correct likelihood input parameter and is therefore a critical determinant for the accuracy and consistency of risk assessments.
Techniques developed to support formal layer of protection analysis (LOPA) in the process industries hold promise for improving our understanding of controls used in general industry. In particular, LOPA concepts may be able to increase our understanding of the strength and reliability of various options in the hierarchy of controls.
LOPA is a semi-quantitative approach to risk assessment. It uses order-of-magnitude control layers as basic building blocks to systematically understand the risk controls that are in place, and whether adequate protection is provided for a particular scenario outcome.
The LOPA control-layer building blocks are called independent protection layers (IPLs). IPLs are very similar in concept to layers of protection in the commonly used "Swiss Cheese" hazard control model (Figure 2), and their relative strength corresponds roughly with the traditional hierarchy of controls. However, there are rigorous rules for their proper validation and use. Understanding IPLs and the rules for their use may provide promising opportunities for improving the accuracy and consistency of general-industry, matrix-based qualitative risk assessments.