Jack Wishart discusses how benchmarking can be used to measure and drive improvements in process safety performance in the energy industry
ASK yourself: what are the process safety goals at your company? You might instinctively answer with a lagging process safety performance indicator (PSPI) such as “x process safety incidents and high potential near misses per year” where x will usually be zero or, in some cases, a number that is lower than your company’s own historic performance. Essentially the goal is either perfection or, at the very least, improvement.
Although useful, lagging PSPIs can be a fairly limited way of measuring performance and maybe you would also answer the question in terms of a number of leading PSPIs such as: number of overdue process hazard analysis follow-up actions; alarm rates; or number of overdue critical inspection tasks. The associated targets for such leading indicators are commonly taken from a relevant industry standard (eg EEMUA 191 – Alarm Systems for alarm rates) or may otherwise be a value that is better than historic performance to again drive a focus on continual improvement.
Assessing process safety management through leading and lagging PSPIs has undoubtedly played a key role in helping to prevent major process safety incidents over the years and will continue to do so for many years to come.
The question that many energy companies have been asking themselves recently is: “As data becomes ever more readily available, is there another lens through which we can assess our own performance?” As a result, an increasing number are turning to “risk quality benchmarking”. This is the process of comparing one company’s performance to that of its peers, which provides an alternative angle to simply considering performance in absolute terms. The aim being to complement traditional PSPI stewardship, rather than replace it completely.
So perhaps a better question would be – is your company “best in class” at process safety management?
This article discusses both how to benchmark and how this approach has already helped drive improvements in process safety performance in the energy industry.
The first step in benchmarking is to establish a site’s “risk quality” against a defined set of criteria. A site should consider a wide range of different incident barriers (both preventative and mitigating) in order to give a thorough overview.
To help structure this first step and identify each of the key incident barriers at a site, it is often useful to split the overall risk quality into different categories such as hardware (the physical aspects of a site) and the management systems (ie work processes). These categories can then be sub-divided into topics, for example systems of work, which can then be further broken down into individual features, for example permit to work, and management of change. A graphical representation of such an approach is demonstrated in Figure 1.
Clearly, not all incident barriers are of equal importance and each feature, topic and category (using the nomenclature of Figure 1) should be given a different weighting to reflect its relative significance. Preventative barriers (anything that helps prevent an incident occurring) are commonly given a greater weighting than mitigating features (anything which helps minimise the impact of an incident once it has occurred). Similarly, a consideration of barriers that have failed and resulted in major incidents can help guide which topics should be given a greater weighting. For example, process isolations (Pasadena, 1988), management of change (Flixborough, 1974), or mechanical integrity (Philadelphia, 2019)1.
Once all incident barriers and their associated weightings have been established, each individual barrier at a site should be assessed and scored – an example scale is shown in Figure 2. These individual feature scores can then be consolidated to give an overall score for each topic, each category and ultimately the overall risk quality depending on the level of detail desired in the subsequent analysis.
Once a site’s own performance is established, the next step is to decide on the most applicable peer group for comparison. Common considerations include:
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