Automating Straight Bill of Lading (BoL) Document Processing

Challenge

The company, a global medical products leader, manufactures goods at more than 50 facilities worldwide and relies on an extensive network of production and distribution centers. The company was looking to improve its Transportation Spend Management (TSM) program by automating the extraction and validation of key information from freight bill of lading (BoL) documents. For each shipment the company sends or receives, a general ledger (GL) code and cost center are determined using information found in the shipper address and consignee address fields on the BoL.

This information gives the company control and visibility into direct transportation costs, and associates spend with specific departments. If information in the shipper or consignee fields is incomplete or inaccurate, correct GL code and cost center assignment is disrupted. Inaccurate or altogether missing information makes it difficult to answer pertinent questions about logistics operations such as:

• Are we engaged with the right shipping partners, or are there alternatives that can satisfy service level expectations at a more competitive price?
• Are we optimizing our transportation spend when negotiating with carriers, or is our spend fragmented across departments, business units, and/or service providers?
• Are we being billed accurately or are we overpaying? How can we streamline costs associated with our freight settlement process?
• How do our transportation costs align with the rest of the market? Are we spending more or less than other companies?

Solution

The company sought a solution that would reduce the number of errors when extracting information from documents, automate data validation including cross referencing outputs with external data sources, and provide confidence intervals for GL code and cost center matches.

Super.AI’s Intelligent Document Processing (IDP) proved to be the ideal solution to the company’s bill of lading document processing challenge. Our next-generation IDP leverages the latest AI and on-demand data processing crowd to extract information from any document quickly and with guaranteed quality. In collaboration with super.AI, the medical products company was able to quickly automate BoL document processing. This not only reduced errors in data extraction by more than 95%, but allowed the company to:

• Validate that the amount charged matches line items by weight.
• Validate shipper name and address using external data sources.‍
• Improve automated flagging of duplicate document submissions.

This was made possible thanks to the flexible nature of our IDP offering, which is built on top of a unified AI platform for unstructured data processing. Although the medical products company initially sought a solution to a specific problem that was impacting their TSM program, they quickly realized additional opportunities once their data was made available to the super.AI platform.