Monitoring the Health of the Asset Integrity Management System Through the Use of Generic KPIs

Abstract

Abstract The paper presents the motivations, objectives and methodology adopted for establishing an asset integrity performance measurement mechanism utilising generic, readily available leading and lagging key performance indicators (KPIs). The mechanism was developed and implemented within the context of a newly acquired, 20 year old offshore asset. The cornerstone of the system utilises the ‘bowtie’ methodology, within which generic and readily available KPIs are used to measure the health of the barriers. 39 KPIs were identified and deemed of relevance to the management of major incident risk, with up to 20 KPIs mapped to each individual bowtie barrier. This was followed by assigning ‘weighting scores' to reflect their significance, following which the results were fed into a dashboard-type display using a traffic light system. The dashboard caters for senior management, technical authorities and the offshore workforce by displaying three distinct levels of information. The requirement for tracking KPI trends as well as trends in barrier performance were also accounted for in the monitoring mechanism. There were a number of challenges encountered during the development process, particularly regarding the objective measurement of barrier health and effectiveness of key management system elements and ‘personnel related’ barriers (e.g. competence). A number of KPIs were identified for monitoring management system and ‘personnel related’ barriers and incorporated into the overall process monitoring mechanism; in addition to the KPIs set for measuring specific hardware barriers. This ensured that the framework was comprehensively inclusive of all aspects of barrier health management which in turn provides a degree of assurance that process safety is being effectively managed. There are a number of areas where a continuous improvement process will be applied in order to enhance the effectiveness of the system. For instance, the underlying assumptions, aggregation rule sets and mathematical formulae applied will be refined in order to provide a more precise estimate of the barriers' status. Calibration of the ‘weighting scores' and possible modifications to the KPIs is also key to optimising the mechanism developed and ensuring the effectiveness of the process.