In this article, you will learn exactly what OCR Data Entry is and how it improves efficiency. We also share our simple OCR process for data entry of documents. Read on to learn more.
OCR data entry involves converting documents like scanned papers, PDFs, or images into editable and searchable data. "OCR" stands for Optical Character Recognition. This technology extracts and recognizes text from images or scanned documents.
Example: Using Tesseract OCR, a company can scan and convert printed reports into editable text, streamlining their data entry process and minimizing errors. This enhances data retrieval speed and improves overall document management efficiency.
Use our 10 step optical character recognition process for data entry to efficiently manage your data processes.
Before scanning, ensure that your documents are in optimal condition to reduce errors during the OCR process. Proper preparation involves aligning documents, removing any creases, and ensuring they are clean.
Example: You have 50 printed invoices from various suppliers. Before feeding them into your Canon DR-C225 scanner, ensure each invoice is flat, free from any tears or marks, and neatly aligned to avoid misfeeds.
Using a high-quality scanner is essential to produce clear and accurate digital images of your documents. This digital conversion is the foundation for effective OCR processing.
Example: Use the Canon DR-C225 scanner to scan the prepared invoices at a resolution of 300 dpi, generating high-resolution PDF files that will be easy to process with OCR software.
Once your documents are digitized, the next step is to upload these files to OCR software. This stage involves preparing the documents for text recognition by the software.
Example: Upload the scanned invoice PDFs to ABBYY FineReader, which is known for its robust OCR capabilities, setting the stage for accurate text extraction.
The OCR software analyzes the uploaded images and converts the detected text into an editable format. This step involves the software recognizing individual characters and applying appropriate formatting.
Example: ABBYY FineReader processes the uploaded PDF files, accurately converting the text from the invoices, such as the supplier’s name, invoice number, and item descriptions, into editable Word documents.
After text recognition, the next step is to extract relevant data fields from the recognized text. This involves identifying specific information like dates, names, and financial figures.
Example: Use ABBYY FineReader’s data extraction tools to pull out specific fields from the invoices, such as invoice numbers, due dates, and total amounts due, organizing them into a structured format.
It’s crucial to verify the accuracy of the data extracted by the OCR software. This step involves cross-checking the extracted data against the original documents and correcting any errors.
Example: Cross-reference the total amounts extracted from the invoices with the original printed versions, correcting any discrepancies directly within ABBYY FineReader to ensure data accuracy.
Once the data is verified, export it into a format that suits your needs, such as Excel or a database. This step allows for easy data analysis and integration with other systems.
Example: Export the verified invoice data into an Excel spreadsheet, creating a comprehensive ledger that can be used for financial analysis and reporting.
After processing, securely store both the digital copies of the documents and the extracted data. Proper storage ensures that the information is easily retrievable and well-protected.
Example: Save the digital copies of the invoices and the associated Excel file to a secure cloud storage service like Google Drive, ensuring that the documents are both backed up and accessible when needed.
To maximize efficiency, integrate the extracted data with other business systems such as accounting or enterprise resource planning (ERP) software. This facilitates seamless workflow integration.
Example: Import the Excel file containing the verified invoice data into QuickBooks, streamlining the process of updating accounts payable and enhancing overall financial management.
To maintain high levels of accuracy and efficiency, it’s important to regularly review and refine the OCR process. This involves adjusting settings and adopting new practices as needed.
Example: Conduct quarterly reviews of ABBYY FineReader’s performance, updating the OCR settings based on feedback from the accounting team and the types of documents being processed, ensuring continual improvement in recognition accuracy.
GreenLeaf Botanicals is a leading organic skincare supplier that aims to adopt OCR data entry to streamline their invoice processing and reduce manual errors. Here's how they implemented our simple 10 step process. Simply follow the steps below.
GreenLeaf Botanicals receives a variety of documents, including supplier invoices and product labels for items such as HVC-100 and OGS-200. Before scanning, the documents are checked for cleanliness, alignment, and any physical damage to ensure they are ready for an accurate OCR process.
Using a Fujitsu fi-7160 scanner, GreenLeaf Botanicals digitizes their invoices and product labels at 300 dpi. High-quality scans of HVC-100 and OGS-200 labels are essential for precise OCR processing and data extraction.
The scanned files, including the invoices for HVC-100 and OGS-200, are uploaded to Tesseract OCR software. The software prepares these digital images for text recognition, ensuring that all relevant details are captured accurately.
Tesseract OCR software processes the uploaded documents, converting the text from the HVC-100 and OGS-200 invoices and labels into editable formats. This step ensures that product information, batch numbers, and supplier details are correctly recognized.
Key data fields, such as batch numbers, expiry dates for HVC-100 capsules, and pricing details for OGS-200 serum, are extracted from the recognized text. This information is then organized into a structured format for easy access and further processing.
GreenLeaf Botanicals cross-checks the extracted data against the original documents to ensure accuracy. Any discrepancies found in the HVC-100 or OGS-200 information are corrected before moving forward.
After verification, the data is exported into GreenLeaf Botanicals’ inventory management system in CSV format. This includes detailed records of HVC-100 and OGS-200 stock levels, ready for further analysis and integration with other business systems.
The digital copies of the invoices and extracted data are securely stored in GreenLeaf Botanicals’ encrypted cloud storage. This ensures that critical information regarding HVC-100 and OGS-200 is both backed up and easily retrievable.
The verified data is then integrated into GreenLeaf Botanicals’ SAP ERP system. This step allows seamless updates to the company’s inventory and financial records, particularly for popular products like HVC-100 and OGS-200.
To maintain optimal efficiency, GreenLeaf Botanicals regularly reviews and refines their OCR process. Adjustments are made based on the types of documents processed, ensuring continual improvement in the accuracy of HVC-100 and OGS-200 data recognition.
Here are some of the benefits of using OCR data entry:
OCR data entry automates the process of converting paper documents into digital format, significantly reducing the time and effort required for manual data entry. This leads to faster processing and turnaround times for business operations.
OCR technology minimizes human errors that often occur during manual data entry. This ensures that the data entered into Excel is more reliable and precise, leading to better decision-making.
By reducing the need for manual data entry, businesses can save on labor costs. Additionally, the increased accuracy of data entry can prevent costly mistakes and reduce the need for rework.
OCR software allows for easy organization and storage of digital documents. This makes it simpler to retrieve, analyze, and manage large volumes of data within Excel, improving overall data management practices.
Digitized documents can be easily shared and accessed by multiple stakeholders within the organization. This enhances collaboration and ensures that everyone has access to the most up-to-date information.
Integrating OCR data entry with Excel can automate repetitive tasks, freeing up employees to focus on more strategic activities. This streamlines workflows and improves overall productivity.
Digital documents can be stored securely with access controls, reducing the risk of data breaches associated with physical documents. This ensures that sensitive business information is protected.
As businesses grow, the volume of data they handle increases. OCR data entry systems can easily scale to accommodate larger amounts of data, ensuring that the business can continue to operate efficiently without being bogged down by manual data entry tasks.
We hope that you now have a better understanding of what OCR data entry is and how it works. If you enjoyed this article, you might also like our article on OCR Data Extraction or our article on OCR vs Text Recognition.