Data-Driven Supply Chain Operations-The Pilot Case of Postal Logistics and the Cross-Border Optimization Potential

Area of Science:

• Logistics and Supply Chain Management
• Operations Research
• Information Technology in Logistics

Background:

• The logistics sector faces pressure to optimize delivery processes and adopt new technologies for improved performance.
• Increasing demands for cost reduction, environmental sustainability, and enhanced customer satisfaction drive the need for innovation.
• The transition towards Logistics 4.0 necessitates advanced solutions for real-time process management.

Purpose of the Study:

• To assess the process optimization potential in the postal sector through the integration of new digital technologies.
• To evaluate the impact of real-time simulation and scenario analysis on delivery process efficiency.
• To investigate the role of a Cognitive Advisor in managing intraday changes and supply chain disruptions.

Main Methods:

• Designed a pilot experiment integrating digital technologies for cross-border delivery process assessment.
• Utilized event processing based on digital representation and scenario analysis.
• Employed a Cognitive Advisor for simulation and Key Performance Indicator (KPI) monitoring.

Main Results:

• Demonstrated real-time process optimization capabilities for managing intraday changes.
• Achieved potential improvements in utilization by up to 50%.
• Showed reductions in costs and route length by 12.21%.

Conclusions:

• The integration of new digital technologies, particularly the Cognitive Advisor, offers significant potential for optimizing postal delivery processes.
• A dynamic approach to managing supply chain disruptions is enabled through sophisticated data analytics.
• The research presents a novel approach to real-time simulation for postal delivery optimization.