OCR stands for Optical Character Recognition and is the technology that allows software to interpret text on scanned images. When this technology is applied to automating business data entry processes it’s referred to as OCR Data Capture.
Many are familiar with popular desktop OCR applications designed to convert scanned images to editable documents. When this process is applied to specific areas of the document containing data fields it’s called zone OCR. But OCR data capture software is more than just simple zone OCR. Modern applications use some or all of these technologies:
Enterprise data capture systems provide interfaces for scanning, recognition, data verification and export, as well as management and monitoring tools to track large volumes of documents and data through the workflow.
Who can benefit from OCR data capture software?
Any organization that collects data from paper documents, or electronic files like PDF and Office documents, can get a very high return on investment by automating the data entry with OCR data capture software.
You do need to have a significant number of documents to justify the expense. If a one-time data entry task can be done in less than 100 hours then it is not a good candidate for automation with OCR data capture software.
Large reports with thousands of data points and documents that are part of a daily business process offer the best ROI.
Organizations that have many separate departments with data entry tasks can share the budget for data capture software by re-using it for other projects. Your current project may not be big enough to justify the expense, but when combined with one or two others it would be.
How much do OCR data capture systems cost?
The total cost of an OCR data capture solution includes several items:
- Cost of the software, which depends on process volume, number of users, and number of advanced data capture features required.
- Time to install and configure the software
- Recognition templates must be created for each data field on every type of form
- Data exports must be defined and integrated with back-end systems
- User and administrator training
- Labor required to verify the recognition results
- IT infrastructure and maintenance costs
If you have an IT staff that is familiar with document scanning and OCR applications, it is possible to do most of the configuration and maintenance in-house. If not then it is highly recommended that you use our Consulting Services to guide you through the setup process.
Contact Us to get a professional analysis of your project requirements and a full time and cost estimate.
What is the typical OCR data capture workflow?
If you have all of the advanced features enabled, the process of converting a document to live data you can use includes the following steps.
- Paper documents are scanned; electronic files are imported from email or a hotfolder
- Document text is recognized with OCR or extracted from electronic documents
- Classification matches the document to its template
- Data extraction rules locate field regions on the document
- Identified regions are re-recognized with field-specific settings
- Business rules are applied to check the results and flag unexpected values for validation
- Fields with OCR errors or validation flags are presented to an operator for verification
- Once all errors are corrected, data is exported to a file, database or API
- Corrections made in verification are used by AI to train and update field templates
- Exported data flows to business applications via API, database or robotic process automation
How do I find out more?
Data capture projects can require lots of specialized technical knowledge to achieve success. From OCR form design best practices to database integration, APIs and robotic process automation, our experts can guide you through any part of any project no matter the size or complexity. Contact us for a free consultation!