Leveraging Data-Driven Process Mining Insights for Efficiency, Compliance, and Accountability: Enhancing Safety Inspections in a Specified City

Safety inspections play a pivotal role in ensuring the well-being of individuals and the structural integrity of buildings. This study delves into the analysis of safety inspections within a specified city, leveraging a dataset encompassing over 100,000 records. The analysis was executed using Disco Fluxicon, a process mining tool, which provided insights into critical facets of the safety inspection process. The methodology involved the redefinition of attributes, revealing bottleneck activities, highlighting exceptional behavior cases, and employing data-driven decision-making. The study identified major bottleneck activities in the inspection process, including ‘issued,’ ‘permit finaled,’ and ‘approved,’ indicating the need for targeted optimization. It also unveiled the significance of exceptional behavior cases and their role in guiding tailored approaches. The analysis empowered regulatory bodies with data-driven insights to enhance resource allocation and decision-making. These findings offer the potential for an efficient and adaptive safety inspection process, translating to quicker project approvals and improved resource allocation, ultimately boosting the construction sector's confidence and economic growth. The study's insights foster transparency, accountability, safety, and compliance in the specified city. A streamlined inspection process contributes to economic growth, job creation, and enhanced quality of life for residents and workers. Leveraging these findings, the city can create a safer and more efficient inspection environment, promoting confidence and progress.