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Optical Character Recognition (OCR) is a technology that converts different types of documents, such as scanned paper documents, PDF files, or images captured by a digital camera, into editable and searchable data.
In the logistics industry, OCR finds its application in automating data extraction from various documents like shipping labels, bills of lading, and invoices. This technology significantly reduces the need for manual data entry, thereby minimizing human error and expediting the processing time.
In this article, we'll delve into how OCR technology can bolster your logistics operations by enhancing data accuracy and streamlining workflow.
Evolution of OCR in logistics
Early adoption
In the initial stages, the logistics sector recognized the value of OCR primarily as a tool for converting physical documents into digital formats. Major logistics companies like FedEx and UPS led the way by deploying OCR technology for specific use cases such as scanning and interpreting shipping labels.
The technology revolutionized sorting and routing processes by dramatically reducing the need for manual labor and minimizing human errors. With the OCR systems in place, these companies could automatically read labels, sort packages, and streamline the overall shipping workflow.
Modern applications
Today, OCR technology plays a multifaceted role in logistics, extending its functionalities far beyond simple label reading. Below are some of the key areas where OCR now makes a significant impact.
- Document management: Advanced OCR solutions can scan a broad range of documents—invoices, contracts, or compliance documentation—and convert them into editable and searchable digital files. This transformation facilitates efficient records management by making it easier to store, access, and retrieve essential information quickly.
- Automated data entry: One of the most game-changing applications of OCR in logistics is its capability for automated data entry. OCR software can scan documents and directly populate fields within logistics management systems, thereby reducing manual data entry to a great extent. This automation leads to a significant reduction in human error and increases overall operational efficiency.
- Freight management: OCR technology now comes with the ability to recognize and extract essential data from a multitude of shipping documents like bills of lading or airway bills. Once the OCR system captures this information, it integrates seamlessly with freight management systems to provide real-time tracking updates and streamline shipment workflows.
Components of OCR in logistics
Component #1: Text capture
Text capture serves as the entry point for any OCR workflow in logistics. In this phase, scanners or cameras scan the physical document or image that requires processing.
It was once necessary to use expensive, specialized hardware to achieve clear scans. But the integration of OCR into everyday devices like smartphone cameras has removed the need for this. Additionally, technological development in the OCR software itself has made it possible to capture usable images in areas with varying degrees of lighting and visibility.
Component #2: Text recognition
During this phase, specialized algorithms analyze the scanned image to identify individual characters and symbols. The software maps these visual elements to their corresponding machine-encoded text characters.
One of the remarkable features of advanced OCR systems is their ability to recognize text in multiple languages, alphabets, and fonts, thereby making them extremely versatile.
Text recognition is crucial because any error at this stage could lead to incorrect data extraction, compromising the integrity of the whole process.
Component #3: Data extraction
During extraction, customized rules and patterns guide the OCR software to pull out specific pieces of information relevant to logistics operations.
For example, the system might extract shipping details like tracking numbers, consignee addresses, and item descriptions from a bill of lading. Similarly, it could pull line-item specifics, such as product codes and prices, from an invoice.
In the example below, OCR technology from PackageX is used to extract data from a bill of lading.
The accuracy of this phase is pivotal, as the extracted data will feed into various functional areas like inventory management, billing, and shipping.
Component #4: Data integration
The final step involves seamlessly integrating the extracted data into a logistics management system. In this phase, automated workflows use the OCR-extracted data to perform various tasks like updating inventory levels, generating customer invoices, or providing real-time shipment tracking.
By directly populating the system, OCR minimizes the need for manual data entry, thereby reducing errors and increasing overall operational efficiency.
It's worth noting that modern OCR solutions often come with APIs that allow for easy integration with various types of management software, offering flexibility and scalability.
Mailrooms use OCR to automate package receiving and pickup
In the logistics sector, OCR technology is revolutionizing package management and delivery. One striking example comes from the property management domain, where PackageX Receive — our OCR-enabled digital mobile application — has substantially improved package processing efficiency.
Faced with a 22% surge in package deliveries during the pandemic, our client, a property management service provider, grappled with constrained mailroom storage space. Their previous system took seven minutes on average to process a single package, leading to a backlog and poor resident experience.
Now they’re using OCR technology that instantly reads package labels and automatically outlines the next steps in processing. This reduced the processing time to mere seconds per package, allowing for a more efficient use of mailroom space. Furthermore, the app sends immediate notifications to residents, encouraging timely pickup and reducing package loss.
But the impact of OCR technology goes beyond just speed. The app's accurate tracking features have brought lost package instances down to nearly zero. In addition, it has improved same-day package pickups by 38%, optimizing storage duration and freeing up mailroom capacity.
AWH uses OCR to verify consignment information automatically
By implementing an OCR solution, the logistics and warehousing company AWH achieved significant energy savings and elevated work efficiency, addressing longstanding challenges such as manual data entry, accuracy, and timely processing.
Before the OCR integration, AWH grappled with issues like manual intervention, duplicate key entries, and overstaffing, according to John Kilbride, the company’s Chief Information Officer (CIO). After analyzing existing processes, they developed a fully automated solution that streamlined AWH's consignment management process.
The OCR technology reads and verifies consignment information automatically, extracting key data and line items. The system then exports this verified data into AWH’s logistics system, subsequently feeding it into a record management solution. The process automates the creation of a filing path based on the extracted data, sparing operators from manual filing tasks.
According to Killbride, this OCR-based automation freed up staff to focus on more value-added tasks. The impact extends beyond mere efficiency gains and ensures that AWH meets crucial compliance standards.
The business case for OCR in logistics
In 2022, the OCR market size was $10.6 billion and is projected to reach $39.7 billion by 2030, growing at a CAGR of 16%. This escalating market size signifies the increasing trust and integration of OCR technology across various sectors, including logistics.
The current generation of OCR technologies offers impressive levels of accuracy when it comes to reading and understanding printed or handwritten text. These capabilities present valuable applications for digitizing documents, automating data entry, and enhancing compliance processes within logistics.
Considerations for using OCR in logistics
As you weigh the value of incorporating OCR into your logistics operations, you should evaluate the following questions with your team.
Is manual data entry draining resources?
Many logistics companies face the tedious task of manually entering data from shipping manifests, invoices, and bills of lading. OCR can swiftly convert these paper-based documents into digital formats, automating the data entry process. By doing so, it not only reduces human error but also frees up personnel to handle more complex tasks, increasing overall efficiency.
Reports highlight that over 40% of employees spend at least a quarter of their week on repetitive tasks, with data entry often topping the list. And the desire for automation is strong, with 70% of workers identifying the reduction of time spent on such repetitive tasks as the prime benefit.
This isn't just a matter of preference. Automation stands to reclaim hours of work: nearly 60% of workers believe they could save at least six hours a week if automation were implemented, time they would redirect towards more valuable, rewarding work.
From a warehousing and logistics standpoint, if we assume it takes an average of two minutes to enter data for a single shipping label, a worker could process about 240 labels in an eight-hour shift. For a company handling 10,000 shipments per day, this would require roughly 42 full-time employees for data entry alone.
Do you face challenges in compliance and document verification?
Logistics operations must adhere to numerous regulatory guidelines, often necessitating rigorous document verification. OCR can facilitate this by quickly scanning and cross-referencing documents, ensuring they meet the required standards. This can be especially crucial in international shipping where discrepancies in documents result in costly delays.
Is paper-based documentation slowing down your supply chain?
A lag in the flow of information, especially if relying on paper-based systems, can cripple a logistics operation. OCR can digitize important documents in real-time, thereby speeding up information flow and decision-making. Faster access to data can improve coordination among suppliers, distributors, and customers, optimizing the entire supply chain.
In summary, OCR offers an extensive array of solutions that can dramatically benefit logistics functions, from automating data entry to enhancing document verification and speeding up information flow. As you contemplate integrating OCR into your logistics business, concentrate on the areas where automation and data digitization will deliver the most impactful gains.
Getting started with OCR in logistics
If you're a logistics professional looking to integrate OCR into your existing workflow, follow these steps to get started.
Step 1: Identify the need
Pinpoint the areas in your logistics operations that could benefit from converting physical or digital images of text into machine-encoded text. Frequent applications include automating invoice processing, digitizing shipping labels for tracking, and extracting information from customs documentation.
Step 2: Set clear objectives
Clearly define what you hope to accomplish with OCR technology. Are you looking to speed up document handling, improve the accuracy of inventory tracking, or reduce manual data entry errors? Your objectives will inform your technology choices and implementation strategy.
Step 3: Select the right technology
A variety of OCR platforms and tools are available, catering to different needs and budgets. If you're just getting started, open source options like Tesseract may suit your needs. For more advanced and customizable solutions, consider enterprise-grade options that offer features like multilingual support, API integration, and a scalable cloud-based platform.
