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1/ 1100%实际尺寸适合宽度适合高度适合页面自动

CASE STUDY | TRANSPORTATION & LOGSITICS Challenge Despite the adoption of EDI, AFS still received millions of paper invoices with no consistent design. Their existing OCR system was largely unable to work with unstructured and semi-structured documents. In addition, their existing systems could only capture data from two fields per document. Verifying and entering data for the remaining fields required 25 full- time data entry operators. To accommodate growing invoice volume due to rapid business expansion cost-effectively, AFS sought a solution to: • Process invoices faster and more accurately • Extract a greater variety of invoice information • Optimize headcount requirements Solution ABBYY IDP’s highly accurate extraction of structured data from unstructured invoices decreased mailroom and data processing staff by 43 percent, and turnaround time improved by 50 percent. The solution’s classification accuracy eliminated the need for separator sheets, resulting in $60,000 of annual savings. The flexibility of ABBYY IDP has allowed AFS to continually increase the types of invoice data that is automatically extracted. Value Invoice processing turnaround time reduced by 50% Straight-through processing of unstructured invoices Staff requirements reduced by 40+% $60,000 in annual savings AFS Scales Advanced Freight and Account Payment Solutions as the Business Grows “ABBYY keeps bringing a lot of efficiency into our processes for paper invoices. Our operators fly through the OCR results much faster and more efficiently than it would have been with manual keying.” Randy Broom IT Director, AFS AFS combines a data-driven approach with time-tested skills to drive measurable savings and optimize essential elements of its customers’ logistics operations. After adopting ABBYY intelligent document processing (IDP), AFS cut invoice processing time and head count roughly in half. AFS scaled the solution with ease, managing steadily growing numbers of invoices and extracting more types of valuable data to provide better analysis and higher cost savings for its customers.

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1/ 1100%实际尺寸适合宽度适合高度适合页面自动

CASE STUDY | TRANSPORTATION & LOGSITICS Challenge Despite the adoption of EDI, AFS still received millions of paper invoices with no consistent design. Their existing OCR system was largely unable to work with unstructured and semi-structured documents. In addition, their existing systems could only capture data from two fields per document. Verifying and entering data for the remaining fields required 25 full- time data entry operators. To accommodate growing invoice volume due to rapid business expansion cost-effectively, AFS sought a solution to: • Process invoices faster and more accurately • Extract a greater variety of invoice information • Optimize headcount requirements Solution ABBYY IDP’s highly accurate extraction of structured data from unstructured invoices decreased mailroom and data processing staff by 43 percent, and turnaround time improved by 50 percent. The solution’s classification accuracy eliminated the need for separator sheets, resulting in $60,000 of annual savings. The flexibility of ABBYY IDP has allowed AFS to continually increase the types of invoice data that is automatically extracted. Value Invoice processing turnaround time reduced by 50% Straight-through processing of unstructured invoices Staff requirements reduced by 40+% $60,000 in annual savings AFS Scales Advanced Freight and Account Payment Solutions as the Business Grows “ABBYY keeps bringing a lot of efficiency into our processes for paper invoices. Our operators fly through the OCR results much faster and more efficiently than it would have been with manual keying.” Randy Broom IT Director, AFS AFS combines a data-driven approach with time-tested skills to drive measurable savings and optimize essential elements of its customers’ logistics operations. After adopting ABBYY intelligent document processing (IDP), AFS cut invoice processing time and head count roughly in half. AFS scaled the solution with ease, managing steadily growing numbers of invoices and extracting more types of valuable data to provide better analysis and higher cost savings for its customers.

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