You have a software package that relies on optical character recognition (OCR) to classify, pick up words, numbers or phrases from a document. As long as the quality of the document is mostly clean, everything works well. However, what happens when the document arrives and the quality is simply, not good? Does the software give up and run away with its tail between its legs? Are there any options to classify or capture anything on these documents?
It’s easy to mistake Optical Character Recognition (OCR) as a one-trick pony.
After all, pulling text out of an image to make it usable in other applications is an impressive trick. Don’t be content to think that’s all OCR can do for you though. By combining OCR output with other technologies, it’s possible to make substantial improvements to workflows throughout an organization. Incoming document workflows are the first and most obvious place that OCR can make a major impact.
Courts are consistently trying to keep pace with rapidly changing technology. As important as keeping pace with technology is to the future of the courts, it is also critical for courts to a have a vision, holistic plan and buy-in from key stakeholders before jumping into the deep end of the pool. Implementing technology without a well thought out plan is a recipe for disaster.
Even if you have a current system to store your documents, and your employees use the world’s best labeling system, they may not put everything back in the same place. Nor will they necessarily place paperwork back in the same order within the label. The most up-to-date or accurate version could be found out of order...
Every good process has a starting point. In the instance of making the perfect peanut butter and jelly sandwich, “first you take the peanuts and you crush ‘em, you crush ‘em" view entire peanut butter and jelly sandwich process here. Whereas, the first step of a government data entry process, is document handling. First you take the paper documents, and you sort ‘em, you sort ‘em. Then you take the documents and you scan ‘em, you scan em...
Automated Document Classification is defined based on your business requirements and documents. Documents may be classified according to subjects or based on other attributes such as; document type, author, printing year, etc.
Once these classifications are defined, documents stored in an assigned repository or arriving by fax, e-mail or via an upstream workflow, are sent to an Automated Document Classification application.