Business processes identification an‎d business process modeling with a stan‎dard method an‎d improving existing processes (In a logisticsʹ hub)

1/1/1900 12:00:00 AM

This study aims to identify, model, an‎d improve business processes in a logistics hub. The research focuses on analyzing core operational processes, including unloading, sorting, an‎d loading, as well as support processes such as security, maintenance, an‎d human resource management. Given the significance of enhancing operational efficiency in the supply chain an‎d reducing costs, this study leverages approaches such as business process modeling using the BPMN stan‎dard an‎d integrating quantitative an‎d qualitative methods to identify weaknesses an‎d bottlenecks within the hub’s processes. Operational data were collected an‎d analyzed using tools such as Microsoft Excel, Python, an‎d Power BI. During the preprocessing phase, scattered data from over 260 Excel files were consolidated into a unified dataset to enable more precise analysis an‎d real-time data visualization. Statistical analyses demonstrated reductions in operational cycle times, improvements in data recording accuracy, an‎d increased productivity. Additionally, the development of interactive dashboards in Power BI allowed managers to monitor process performance accurately an‎d in real time. The study’s findings indicate that employing stan‎dardized modeling methods, alongside data-driven analysis an‎d process optimization, can significantly enhance operational efficiency, reduce time an‎d costs, an‎d increase customer satisfaction in logistics hubs. These achievements not only contribute to the theoretical domain of business process management but also provide practical solutions for digital transformation in the logistics industry.

مدل سازي فرآيندهاي كسب وكار , بهبود فرآيندهاي كسب وكار , مديريت فرآيندهاي كسب وكار

Business Process Modeling , Business process improvement , Business process management

Mahkam mohebbi

Dr Sieyamak Noori