Executive Summary
For many organizations, the ERP is an entrenched system of record. However, ERPs are not optimized for all the complex activities occurring today, such as matching printed or electronic invoices with supplier master data, purchase orders, shipping, tax and discount data. Since it can be cost-prohibitive to replace a legacy ERP, companies often augment them instead with document management systems. Historically, these systems relied on optical character recognition (OCR), which could be cost-prohibitive and still required a high level of manual intervention to
ensure data quality. Fortunately, the latest generation of document management systems are better able to “learn” patterns and fix data issues automatically, reducing the need for manual intervention and lowering the total cost of ownership over time. Because they also can match data from disparate systems and pull it together in a cohesive, understandable way, these solutions are proving to be an excellent fit for end-to-end processes like purchase-to-pay,
order-to-cash and record-to-report.
The Evolution of Document Processing Solutions
The limitations of legacy ERP systems created an opportunity for solutions that
automate financial processes and bring together unstructured information in diverse
formats with structured data. This enables validation and consistency of information at
every process stage, improving visibility and audit support.
The earliest document processing systems involved optical character recognition (OCR).
Initially, these systems were seen as a cure-all for the “paper problem.” Unfortunately,
the full benefits promised by first-generation OCR solutions seldom materialized due to
their high error rates and insufficient integration with other business systems.
Data capture and invoice processing solutions have improved significantly in recent
years, but human intervention is still sometimes necessary. Many newer document
processing systems can take otherwise unreadable information from XML or EDI
transactions and tie it to a customer order or invoice, making it far easier for a human to
read the document and address exceptions. Today’s systems take data from paper, faxes, email attachments, portal submissions or other electronic communications and transform it into a digital format. This technology, which goes by a variety of names – intelligent data capture (IDC), advanced recognition (AR) or intelligent document recognition (IDR) – has greatly increased the accuracy of information accuracy through its ability to “learn” to recognize supplier invoice layouts and “verify” document details against data elements from ERP and purchasing systems. It is essential to note that document processing systems have evolved from simple imaging tools and now provide broader process flow and content management capabilities, as we discuss below.
Using Document Processing in the Financial Supply Chain
Several process areas in the financial supply chain are suitable for document processing automation. In fact, there are advantages to seeking a cross-process solution. The purchase-to-pay processes, where buyers and sellers trade the most information, offer the best fit. The physical documents involved in the record-to-report process can also be automated to bring data into the system of record, traditionally the ERP.