Automated load bidding

Carrier Case Studies

Automated load bidding

CLIENT – Assed owned carrier
SKILLS – Dot Net core, React, SQL, Azure services

Automated load bidding
Project description

The customer provides logistics and transportation services. The customer is primarily a trucking company (a carrier) who has 370+ different type of trucks/equipment and provide time-critical transportation services throughout North America.

Business needs:
  • We receive open loads (or orders) through email. These open loads are received by web-bidders who spend a lot of time in manually verifying if the service can be rendered or not. The service is based on availability/tracking updates and 90% of the open loads are rejected. This activity of rejection is time-consuming and gives no monetary benefits to the company
  • Data stored in multiple systems makes it difficult for web bidders to focus on their primary duties.
  • Matches for the open load are selected manually which is error prone and not fast enough. The best matches are sent back to the requester (placed loads) to approve. If the requester agrees, the open loads are awarded.
  • Since these open loads are time sensitive, they move to “expired” if matches are not found in time or are “declined” if not accepted
Solutions:
  • A new system pulls open loads/opportunities from multiple TMS, Load boards and shows that on single platform.
  • A rule engine automatically accepts or rejected the load bit and response is sent to the customer.  
  • Accepts loads, appropriate truck match is performed by a matching engine based upon availability of trucks and presented to operations team to perform allocations.
  • This bidding application is web based interface built using modern technology and architecture with flexible architecture for future upgrades.
Customer benefits:
  • Reduction on repetitive workload on operations teams.
  • Maintenance of partner SLA by immediate response to bids received.
  • Improve operation process for bid management and asset allocation.
  • Improved efficiency of load delivery with right asset allocation to appropriate load.
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