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Document processing is a critical part of logistics and supply chain management. Traditionally, logistics document processing is done manually, making it an error-prone and time-consuming process.
However, with recent technological advancements, it is now possible to automate supply chain document processing using OCR tools, automation, and artificial intelligence.
In this article, let’s get an insight into logistics document processing and look at how you can benefit from intelligent document processing.
Logistics and supply chain processes involve a lot of documentation. From paper to digital documents, a lot of data is captured, shared, and maintained by logistics companies and involved parties. Efficient data processing leads to a smooth flow of information as shipments move around the world.
In order to understand the importance of document processing, let’s imagine an order placed online goes missing. Now, it can be tracked up to its last recorded location based on the document entries.
If maintained properly, this documentation can also be used for an insurance claim. So we see documentation plays a critical role in the logistics industry.
There are a variety of documents that are used in logistics and supply chain management, such as
Each document type plays an important role in ensuring that shipments are processed smoothly and efficiently. By processing each document properly, logistics companies can better manage their operations.
Documents such as purchase orders, invoices, and bills play a vital role in the smooth functioning of the logistics and supply chain industry. They can track and manage the movement of goods and materials through the system.
Document processing involves the entire cycle of creating, managing, and using these documents.
The document processing workflow typically starts with the creation of a document template.
The template is then filled out with the relevant information for each transaction. It may include the item number, description, quantity, shipping address, payment amount, and tax details.
Once the document is complete, it may be maintained physically or converted into a digital format to be stored in a database or other electronic repository.
The details are retrieved from the database and used to generate shipping labels, packing slips, tracking orders, confirm deliveries, and settle disputes.
Logistics document processing through legacy systems involves the following steps:
The process can be tiresome and time-consuming when handling thousands of shipments per day. But document processing is a vital part of ensuring your business runs smoothly.
Therefore, you must ensure that data is accurately entered into your systems. You can make better decisions and optimize your business operations with accurate and up-to-date information.
Businesses can improve efficiency and reduce costs by automating the logistics document processing as many tasks as possible.
Document processing automation in the logistics and supply chain industry refers to using technology to streamline the creation, management, and distribution.
It involves leading technologies like OCR (Optical Character Recognition), Artificial Intelligence (AI), Electronic Data Interchange (EDI), barcoding, and electronic scanning.
Automated document processing systems can read and interpret data more accurately than humans; hence, they help minimize mistakes.
They are more efficient than manual processes, as the system can complete mundane tasks faster. It helps achieve the goal of improving accuracy and speeding up documentation processing by streamlining tasks.
Data processing in most logistics companies is still done using traditional OCR software. However, it is slow and expensive, and creating new templates for each document is challenging.
Automated intelligent document processing software is a much better solution. It is much faster and more accurate than traditional OCR. AI eliminates the need for manually setting up rules and preparing templates.
The AI OCR Process involves the following steps:
AI-powered OCR and automation document processing software become more intelligent the more it is used. Like any machine learning technology, the system learns from information gathered over time and improves its effectiveness.
With the help of AI/ML tools, logistics companies can customize the software/tool to meet their specific needs and interests to get personalized results.
In addition, automating document processing can help ensure that all relevant documents are available when needed. It also improves communication and coordination among logistics companies, suppliers, delivery vendors, and customers.
There are many benefits of automating document processing in logistics and supply chain, including:
The large amounts of paperwork associated with logistics document processing can be easily handled through AI-driven OCR automation tools. The key steps include
The first step in automated logistics document processing, document classification involves automatic sorting of documents. The documents are classified according to their type and usage.
Machine learning algorithms recognize the patterns in the documents and assign them to the correct category, like Commercial Invoices, Bills of Lading, Customs Declaration, and Accounts Payable Invoices.
The next step involves extracting relevant information from the documents to create a database or populate the information in a transportation management system (TMS).
It is done using machine learning algorithms, which are able to identify the essential data points from the documents and extract them accurately. The unstructured data is then structured and mapped to the respective document schema.
If any extraction exceptions are encountered, the system alerts the logistics-focused exception manager. It provides the reason for each exception. Manual approvals or corrections are allowed for these exceptions.
Once approved, the app automatically updates and syncs the information with the TMS.
ML technology learns from such encounters and can be improved based on user feedback.
The data scanned from paper-based documentation is transferred to the TMS and made available for users.
The new information of each document is updated in its existing records to ensure updated and accurate data is released.
The final step in automated logistics document processing involves the analysis of extracted data. The insights are used to make decisions about the logistics business.
For example, it can measure performance, identify trends, and make predictions about future sales.
Data related to the consignment, such as exporters' and consignee details, purchase order numbers, invoice numbers, origin and destination countries, ports of loading and discharge, and description of goods can be extracted from the packing list. It also has other important information such as marking, numbering, terms of delivery, and terms of payment.
Details like the type, quantity, and destination of goods being carried can be extracted from the bill of lading.
The recipient's name, invoice number, transaction details, product description, and shipping address are some of the information that can be extracted from the proof of delivery document.
Essential details such as inspection date, location, purchase order number, contact details of the importer, country of origin, product details, description from Bill of Lading, gross weight, and name of the authorizing person can be extracted from the document.
It mentions the details of the producer and expiration date. Other data that can be captured from the document are the destination and the country of export.
Insurance details can be extracted from it as it includes the name of the insurer, goods insured, and insurance amount. Key aspects covered by the policy are also mentioned on the certificate.
The document includes physical characteristics like the size or weight of each item. Details about the type and number of items can be extracted from the document.
Information related to the goods, like overall weight, purchase order number, order date, delivery date, and names of sender and receiver is mentioned on the document. These can be extracted for document processing.
Details of the consignor, consignee, and declarant can be extracted from the document. A movement reference number, details of the type of goods, packaging, and currency of transaction are other essential details mentioned in the declaration.
The document has details like the UN number of the product, name, quantity, and nature. Division or class of the product, dangerous goods packing group, emergency contact details of the shipper, along with contact details and address of the consignor and the consignee, can also be extracted from the declaration.
Now, you must be wondering which are the best OCR tools for automated document processing in the supply chain industry. Though all tools perform the basic document processing functions, only industry-specific software can be of help.
The top tools for automated logistics supply chain are:
Automated document processing is no longer an indulgence for logistics companies. It is a necessity to keep pace with the evolving industry landscape and meet the rising demand.
AI OCR document processing allows humans to focus on higher-value work without struggling with mundane tasks.
Automated document processing in logistics and supply chains can save businesses time and money. It can also improve data accuracy and efficiency. When choosing a solution, it is important to consider the needs of your business.
The right solution will make document processing easy and help you make better decisions about your business.
Before making a decision, test out the automated document processing tested and used by companies in the Logistics and Supply chain industry from us at Butler Labs. Try Butler Labs Document AI tool for free to test the platform’s effectiveness.
