In this article, you will learn exactly what OCR technology is and why it’s important. We also cover the best practices for implementing OCR in your business processes. Read on to learn more.
OCR (Optical Character Recognition) technology converts printed or handwritten text into machine-readable data. This allows for the automation of data entry and streamlining of various business processes.
Example: A hospital uses OCR to scan patient forms and extract data such as Patient ID #A12345 and diagnosis code ICD-10-CM J20.9. This automatically updates electronic health records and reducing manual entry errors.
Here are some of the most common used cases of optical character recognition technology:
OCR technology is commonly used to convert physical documents into digital formats. This allows for easier storage, retrieval, and management of documents, enabling organizations to maintain electronic archives and reduce physical storage needs.
Example: Libraries use OCR to digitize books and historical documents, making them searchable and accessible online. For instance, Google Books uses OCR to provide digital versions of millions of books.
OCR automates the extraction of data from forms, invoices, and receipts, reducing the need for manual data entry. This improves efficiency and accuracy, particularly in industries like finance, healthcare, and logistics.
Example: The banking industry uses OCR to process checks and invoices quickly. For example, ABBYY FlexiCapture is used to automate data extraction from various document types, reducing processing times and errors.
OCR technology is used to extract text from images, enabling functionalities such as image search, text translation, and content moderation. This is particularly useful in social media and e-commerce platforms.
Example: Google Translate's mobile app uses OCR to recognize text in photos and translate it in real-time, helping travelers understand foreign language signs and menus.
OCR helps in making printed content accessible to visually impaired individuals by converting text into speech or braille. This promotes inclusivity and provides better access to information.
Example: Software like Kurzweil 3000 uses OCR to convert textbooks and printed materials into digital text that can be read aloud, supporting students with visual impairments or learning disabilities.
OCR is used to digitize and organize legal documents, making them searchable and easier to reference. This helps law firms and compliance departments manage large volumes of paperwork more efficiently.
Example: Law firms use software like Adobe Acrobat Pro to scan and OCR legal documents, creating searchable PDFs that facilitate quick retrieval of information during case preparation and compliance audits.
OCR technology is employed in verifying identity documents such as passports, driver’s licenses, and ID cards. This is essential for security and authentication processes in various industries.
Example: Mobile banking apps like those offered by JPMorgan Chase use OCR to scan and verify customer identity documents during the account opening process, ensuring a seamless and secure onboarding experience.
OCR is integrated into content management systems (CMS) to enable text search and indexing within scanned documents. This enhances the ability to manage and utilize content in digital archives and libraries.
Example: Enterprise content management systems like Microsoft SharePoint use OCR to index and search through scanned documents, improving document management and retrieval for businesses.
OCR aids in the preservation and dissemination of historical texts by converting fragile paper documents into digital formats, which can be shared and studied without risking damage to the originals.
Example: The National Archives and Records Administration (NARA) uses OCR to digitize historical documents, such as the U.S. Constitution and other significant records, making them accessible to the public online.
OCR technology is important for a number of reasons, some of the most common reasons include:
Automating data entry with OCR significantly reduces the time spent on manual data entry, allowing employees to focus on more strategic tasks.
OCR minimizes human errors that commonly occur during manual data entry, leading to more accurate records.
By reducing the need for manual labor, companies can save on labor costs and allocate resources more efficiently.
Documents can be processed much quicker with OCR, leading to faster operations and improved workflows.
As a business grows, the volume of documents increases. OCR solutions can easily scale to handle increased workloads without requiring additional staff.
Use our simple 5 step OCR process to efficiently manage your documents. Simply follow the process below.
The document is scanned and converted into a digital image.
Example: A paper invoice from Supplier X, with invoice number INV-12345, is scanned using a high-resolution scanner, creating a digital image file named INV-12345.png.
OCR software analyzes the image and identifies text characters.
Example: The OCR software processes the digital image INV-12345.png and recognizes text characters such as "Invoice Number: INV-12345," "Date: 2024-07-01," and "Total Amount: $1,234.56."
Relevant data fields (such as invoice number, date, and total amount) are extracted from the recognized text.
Example: From the recognized text in INV-12345.png, the OCR software extracts the invoice number "INV-12345," the date "2024-07-01," and the total amount "$1,234.56."
The extracted data is validated against predefined rules to ensure accuracy.
Example: The system checks if the invoice number INV-12345 follows the correct format (e.g., "INV-" followed by five digits), verifies the date format as "YYYY-MM-DD," and ensures that the total amount is a positive numeric value.
The validated data is integrated into the company’s systems.
Example: The validated invoice data (invoice number INV-12345, date 2024-07-01, and total amount $1,234.56) is automatically entered into the company's accounting software, updating the accounts payable records for Supplier X.
To effectively implement OCR for your document processes, here are some best practices you can consider.
Select OCR software that is compatible with your existing systems and meets your specific needs.
Ensure your team is adequately trained to use the OCR software and understands the process.
Keep your OCR software updated to benefit from the latest features and improvements.
Regularly audit the OCR process to ensure data accuracy and address any issues promptly.
Ensure that the OCR solution integrates seamlessly with your business systems for smooth data transfer.
Customize the OCR software to recognize specific fields and formats relevant to your documents.
We hope you now have a better understanding of what OCR is and how to optimize your business processes using this technology. If you enjoyed this article, you might also like our article on how to reduce manual invoice processing or our article on receipt data extraction