Development of performance indicators using Business Intelligence to optimize the offshore recruitment and selection process in a maritime transport company
DOI:
https://doi.org/10.14488/BJOPM.2982.2026Keywords:
Business Intelligence, Process Optimization, Recruitment and Selection, Offshore Industry, Continuous ImprovementAbstract
Goal: This study aims to develop and implement performance indicators using Business Intelligence (BI) tools to optimize the offshore recruitment and selection process in a maritime transport company, reducing approval time and operational costs.
Design / Methodology / Approach: A quantitative case study was conducted through eight stages: data collection, processing, analysis, process mapping, PDCA (Plan-Do-Check-Act) cycle application, time study, cost analysis, and use of quality tools. Data was obtained from internal company records and analyzed using Microsoft Power BI for visualization and the Fluig system for process automation.
Results: Process automation reduced the average approval time for Personnel Movement Requests (MP) from 24 to 6 days, representing approximately a 75% improvement. Statistical analyses, including descriptive statistics, Welch two-sample t-test, and effect size evaluation, demonstrated that the reduction was statistically significant (p < 0.001) and operationally relevant. Additionally, the process optimization generated cost savings of approximately USD 134,548.21 within one quarter (a 73.7% reduction in related expenses). The use of BI dashboards enabled real-time monitoring and improved managerial decision-making.
Limitations of the investigation: The research focused on a single company in the offshore maritime sector, which limits the generalization of results and does not explore behavioral effects of digital transformation.
Practical implications: The study demonstrates that integrating BI tools with continuous improvement methodologies enhances process efficiency, transparency, and cost control in human resource management.
Originality / Value: This research provides empirical evidence of how BI and workflow automation can improve recruitment performance and operational efficiency in high-complexity environments such as offshore logistics.
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