Optimizing Pharma Logistics with Advanced Document Processing Solutions
Intelligent Data Extraction
Solution
The project had a deadline of 1 week to configure and deploy a solution to achieve the following:
- process 1 million pages annually
- extract at least 80% of fields without any human involvement
The client manages approximately 1 million delivery notes and invoices annually. Traditional automation solutions like Tungsten, Opentext, or ABBYY were too expensive for their current volume. The challenge was to find a cost-effective solution to automate the reconciliation of goods received in the warehouse with accounts payable records.
A custom automated document processing solution was designed leveraging advanced machine learning to ensure cost-effectiveness and adaptability.
Key Features:
- Automated Data Extraction: For delivery notes, the system extracts header details, shipment dates, and Purchase Order (PO) references. For invoices, it extracts sums, invoice numbers, and associated PO references. This automation significantly reduces manual data entry and streamlines the reconciliation process.
- Adaptive Machine Learning: The solution's machine learning capabilities allow it to adapt to various document formats, improving extraction accuracy over time. It continuously learns from corrections, enabling it to handle diverse layouts with increased precision. This adaptability contributes to high accuracy in information extraction.
- Customizable and Integrated Workflow: The solution offers customizable rules for data validation and exception handling, integrating seamlessly with existing warehouse and accounts payable systems. This integration reduces manual intervention and error risks, while the cloud-based architecture ensures a scalable and cost-effective solution.
Impact
The implementation of the automated document processing solution resulted in significant benefits for the client:
Efficiency Improvement
The system achieved automatic extraction of 83% of fields without any human involvement which will reduce the manual effort required for reconciliation.
Accuracy Enhancement
An impressive overall extraction accuracy rate of 96% surpassed manual processing, and will minimize errors in reconciling goods and billed amounts.
Cost Savings
The use of cloud-based infrastructure kept costs low, providing a scalable solution without the high expenses of traditional automation platforms.