Hashmove
Hashmove
Project overview :
HashMove is at the forefront of transforming the logistics industry, with operations based in the UK and Dubai. This project revolved around the development of a cutting-edge analytics dashboard, aimed at providing a holistic view of a complex logistics network. The dashboard’s primary goal was to offer valuable insights into the performance and operations of a Pakistan-based logistics company, with a focus on multimodal shipments spanning air, ocean, and ground transport.
What we did for this project :
1. Analytics Dashboard Development:
• Created a comprehensive analytics dashboard that integrated various data sources to provide a unified view of the logistics network.
• Focused on optimizing routing and cargo loading through data-driven insights.
2. Key Statistics:
• Mapped 2,000+ shipments across sea, air, and ground transport.
• The dashboard allowed for end-to-end performance tracking across the complex multimodal shipment network.
3. Visualizations Design:
• Designed visualizations that tracked key performance metrics, such as on-time delivery, top routes, booking revenue, and cargo capacity utilization.
• Utilized charts, graphs, and tables to present these metrics clearly and comprehensively.
4. Logistics Network Optimization:
• Created analytics dashboards specifically for transport companies to:
• Map complex shipment flows.
• Identify optimization opportunities and bottlenecks.
• Track vendor service level agreements (SLAs).
• Improve asset utilization.
5. Logistics Dashboard Features:
• The logistics dashboard offered a unified view of sea, air, and ground shipments, facilitating optimized routing and cargo loading.
• Key features included tracking on-time delivery, monitoring capacity utilization, identifying top routes and vendors, and analyzing shipment revenue.
Project results :
The development of the analytics dashboard for HashMove’s logistics network optimization project yielded several significant outcomes:
• Enhanced visibility into the performance and operations of the logistics network, enabling better decision-making.
• Improved routing and cargo loading through data-driven insights, leading to more efficient transport.
• Streamlined monitoring of key performance metrics, including on-time delivery and revenue.
• Identification of optimization opportunities and bottlenecks, resulting in a more agile and responsive logistics network.