Automation-Driven Efficiency for EU Logistics
Automation-Driven Efficiency for EU Logistics
DURATION
4 Months
DURATION
4 Months
CLIENT
Confidential (EU-based Logistics Enterprise)
CLIENT
Confidential (EU-based Logistics Enterprise)
Automation & Workflow Optimization
Automation & Workflow Optimization
Intelligent Document Processing (IDP)
Intelligent Document Processing (IDP)
Process Engineering
Process Engineering
API & Microservices Development
API & Microservices Development
PROJECT OVERVIEW
PROJECT OVERVIEW
A major European logistics provider faced rising operational pressure from increasing volumes of unstructured Bill of Lading (BOL) documents and rapid morning-cycle data-entry demands. Manual processing resulted in delays, errors, and workforce inefficiencies, especially for Less-than-Truckload (LTL) shipments that required time-sensitive routing and exception handling. To maintain service-level commitments across regions, the organisation needed an automated solution capable of reading varied BOL formats, accelerating morning data intake, reducing manual interventions, and enabling accurate, near-real-time operational decision-making.
A major European logistics provider faced rising operational pressure from increasing volumes of unstructured Bill of Lading (BOL) documents and rapid morning-cycle data-entry demands. Manual processing resulted in delays, errors, and workforce inefficiencies, especially for Less-than-Truckload (LTL) shipments that required time-sensitive routing and exception handling. To maintain service-level commitments across regions, the organisation needed an automated solution capable of reading varied BOL formats, accelerating morning data intake, reducing manual interventions, and enabling accurate, near-real-time operational decision-making.
The Challenge
The Challenge
Manual data entry of thousands of daily BOLs created recurring operational bottlenecks. Key issues included: High error rates due to unstructured document formats · Long processing windows (2–3 hours at day start) slowing downstream operations. · A surge in LTL shipments requiring fast and accurate routing. · Heavy reliance on manual review for exception cases. · Limited scalability as volumes increased. The organisation needed automation that was fast, model-driven, and capable of handling multi-format BOL data while reducing dependency on human validation.
Manual data entry of thousands of daily BOLs created recurring operational bottlenecks. Key issues included: High error rates due to unstructured document formats · Long processing windows (2–3 hours at day start) slowing downstream operations. · A surge in LTL shipments requiring fast and accurate routing. · Heavy reliance on manual review for exception cases. · Limited scalability as volumes increased. The organisation needed automation that was fast, model-driven, and capable of handling multi-format BOL data while reducing dependency on human validation.
WHAT WE DID
WHAT WE DID
TechnePlus designed and deployed an automated data-entry and routing optimisation solution built around intelligent OCR, workflow automation, and exception management. Our work included: · Developing an Intelligent Document Processing (IDP) pipeline to extract structured data from unstructured BOLs · Implementing automated routing recommendations for LTL cases based on volume, lane patterns, and historical accuracy · Accelerating full-truckload processing by integrating automated queue review and reduced manual checks · Running parallel processing instances to manage bulk uploads and minimise day-start delays · Training the automated model on more than 5,400+ BOL variations to maximise reliability · Integrating the pipeline with ERP systems for seamless posting and record updates The result was a shift from manual data entry to a scalable, automated workflow capable of supporting round-the-clock logistics operations.
TechnePlus designed and deployed an automated data-entry and routing optimisation solution built around intelligent OCR, workflow automation, and exception management. Our work included: · Developing an Intelligent Document Processing (IDP) pipeline to extract structured data from unstructured BOLs · Implementing automated routing recommendations for LTL cases based on volume, lane patterns, and historical accuracy · Accelerating full-truckload processing by integrating automated queue review and reduced manual checks · Running parallel processing instances to manage bulk uploads and minimise day-start delays · Training the automated model on more than 5,400+ BOL variations to maximise reliability · Integrating the pipeline with ERP systems for seamless posting and record updates The result was a shift from manual data entry to a scalable, automated workflow capable of supporting round-the-clock logistics operations.
Technology Stack
Technology Stack
Microsoft Flow, PowerApps, Tesseract OCR
Microsoft Flow, PowerApps, Tesseract OCR
