Intelligent Document Processing in Logistics and Supply Chain

Intelligent Document Processing in Logistics and Supply Chain

Logistics and supply chain management have become one of the most essential processes and a strategic necessity in the world of business. Businesses today need to survive in hyper-connected, globally competitive environments, which can thrive only through effective and efficient supply chain management.

Logistics document processing is a crucial aspect of logistics management to handle the intricate network of moving goods and information. It involves acquiring, organizing, and managing various documents like purchase orders, invoices, delivery notes, packing slips, regulatory and customs, etc.

The companies have started recognizing the need for custom AI models in logistics document processing and the benefits of implementing them. But it’s s a challenging task requiring a large infrastructure setup, cost, and expertise. Intelligent document processing solutions are a boon to industries like Logistics that processes diverse documents and formats in large volumes as part of their operations.

IDP for Logistics and Supply Chain

The rise of AI has spurred the creation of intelligent document processing solutions that cater to various complex use cases in Logistics. The adoption of IDP solutions enables logistics companies to stay ahead of the competition. Compared to the former methods of document processing, enabling document automation has many advantages such as:

  • Streamlining workflows with automated procurement systems for indirect goods, which were traditionally given lesser importance than direct goods.
  • Real-time monitoring of inventory, product identification for shipping, optimizing pick-ups, and more.
  • Enabling predictive analytics to identify future trends for understanding demand forecasting, pricing, and more.
  • Matching invoices with varying structures and layouts against purchase orders in real-time for payment services.
  • Driving business transformation by automating data capture and extraction, reducing errors and time in the supply chain.

The following are the steps in data extraction process

  • Removing noise and deskewing by document pre-processing.
  • Classification of documents with the help of AI to identify the formats (PDF, Jpg, Png, etc), structure, and type of document.
  • Data extraction retrieves the values by recognizing the type and format of the data.
  • Data validation identifies any inaccuracies in the extracted data and highlights them for manual validation while simultaneously training AI.

By implementing Intelligent Document Processing in Logistics and Supply Chain the software gets more intelligent the more it is used. With the help of machine learning, the system learns from the information gathered over time and improves its effectiveness.