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Over the last several years, dramatic advancements in Machine Learning have created many new solutions for processing complex documents. Two benefits from these advances are:
- The transformation of the freight invoice process
- The scaling down of costs associated with this repetitive task.
Companies must organize multiple freight shipments daily while adhering to a host of standards, contract specifics, and deadlines. Each transaction requires detailed notes and forms to be converted into freight invoices. Keeping the system accurate, efficient, and timely poses a challenge to every logistics company.
The need to transform the freight invoice process created opportunities for significant transition across the accounting landscape. Current Machine Learning uses complex algorithms to read formats, languages, and characters formally unrecognized. Now, data collection and storage have simplified the process by using data in ways that not only lift freight invoicing to new levels of accuracy and efficiency but also reduce turnaround times.
Machine Learning enhanced OCR has made complex documents in multiple industries readable, indexable, and searchable. Inside the freight invoice processing system, personnel have labored to reduce errors, generate timely turnaround, and make optimal use of personnel. That possibility has been realized in the automation of invoicing systems that now can be made specific to company needs instead of one basic framework for the industry. Evaluation of millions of invoices has also generated readable patterns exposing deviations from contract and rate specifics.
Manual freight invoicing begins with unraveling myriads of complex data. Human error has proved to be the number one cause of error generation due to the repetitive nature of the process. More personnel must scrutinize the input to find errors so that audits can run smoothly. Consideration must be given to double billing, over and under billing, rate accuracy, and a multitude of required information often placed in odd configurations on the data sheets.
As business expands, so does the cost of generating the freight invoice. Errors also slow audits, so costs rise. The greater the volume of business, the more time is lost to error discovery and correction. Client relations are at risk when errors slip by. Miscalculations, keying errors, and deviation from contracts and standards slow the process while cost rises. Turnover in personnel further slows the pace while training and onboarding continue. A tightening in the system through ML OCR redirects energies and skills to accomplish goals more efficiently.
Automation of processes through machine learning significantly upgrades each area of invoice creation.
- ML-enhanced OCR reduces errors by upgrading its capability to read and accurately record data from various formats, texts, languages, and characters.
- Processing time from generation to turnaround is reduced from days to minutes.
- Cost Reduction
- Personnel needed to generate invoices is reduced to 15%.
- Audits are simplified through error reduction, thereby reducing the audit cost.
- Audits ensure that contractual agreements are met and all potential discounts are captured.
- ML looks for patterns that create a negative impact on cash flow.
The cost of invoice processing in a logistics atmosphere is greatly reduced by transitioning to ML-enhanced OCR automation. Beyond reducing expenses connected with manual in-house processing, machine learning algorithms produce data analytics to recognize patterns of concern and assist with strategic decisions.
The marriage of Machine Learning and Optical Character Recognition presents a transformative solution to the challenges inherent in freight bill processing. This innovative approach addresses the complexities associated with data variability and paves the way for a more accurate, efficient, and cost-effective future in the logistics and transportation industry. As businesses embrace these technological advancements, they position themselves to thrive in the dynamic landscape of the evolving freight management ecosystem.
At iTech Data Services, we specialize in outsourcing and automation solutions for freight invoice processing and audit services that improve profitability while reducing risk. We invite you to contact the iTech team to discuss your freight invoice processing or audit needs.