IMARA: A New Approach to Multi-Attribute Risk Assessment Based on Event Data Weighting (Case Study in a Container Terminal)

Many examples tell us that organizations' well-being should be laid upon risk assessments. Typical risk assessments, on the other hand, which produce a list of risk scenarios, more often than not, do not result in enough information for mitigations when it comes to resource limitations such as financial, time, or in this case: delays. Multi-attribute risk assessments give a solid foundation to develop systematic quantitative risk measurements that organizations can use for security mitigations. This study proposes a multi-level and multi-attribute risk assessment method that can be used to prepare mitigations in organization-wide or specific sections of a company. This study presents the evaluation process and results from a case study of a container terminal to evaluate delay risks in its dwelling time processes and to prepare requirements on mitigations based on the risk projections. The proposed method in this study mainly operates within the risk evaluation stage in the risk management lifecycle to complement other methods such as FMEA, FTA, and DEMATEL, which mainly operate within the risk identification and risk analysis stages of risk management. The evaluations in this case study address the efficiency of business process risk factors in a container terminal, not the safety-related risk factors. The proposed method takes event logs from information systems as input to evaluate the risk performances by computing the attributes of the event data. The method also offers risk projections to be treated as a reference to plan for mitigations and determine the likelihood of risk factors. The evaluation results from this case study have provided insights for operation managers and management to perceive and address risks within TPS Surabaya container terminal's business processes. The proposed method is called Improved Multi-Attribute Risk Assessment (IMARA.)