Exceptions happen! When working with advanced technologies in Data Capture and forms processing, you will always have exceptions. It’s how companies choose to deal with those exceptions that often make or break an integration. Too often exception handling is not considered for data capture projects, but it’s important. Exceptions help organizations find areas for improvement, increase the accuracy of the overall process, and when properly prepared for keep return on investment ROI stable.
There are two phases of exceptions, those that make it to the operator driven quality assurance step, and those that are thrown out of the system. It would take some time to list all the possible causes of these exceptions but that is not the point here, it’s how to best manage them.
Exceptions that make it to the quality assurance ( QA ) process have a manual labor cost associated with them, so the goal is to make the checking as fast as possible. The best first step is to use database look up for fields. If you have pre-existing data in a database, link your fields to this data as a first round of checking and verification. Next would be to choose proper data types. Data types are formatting for fields. For example a date in numbers will only have numbers and forward slashes in the format NN”/”NN”/”NNNN. By only allowing these characters you make sure you catch exceptions and can either give enough information for the data capture software to correct it ( if you see a g it’s probably a 6 ) or hone in for the verification operator exactly where the problem is. The majority of your exceptions will fall into the quality assurance phase. There are some exception documents that the software is not confident about at all and will end up in an exception bucket.
Whole exception documents that are kicked out of a system are the most costly, and can be if not planned for be the killer of ROI. The most often cause of these types of exceptions is a document type or variation that has not been setup for. It’s not the fault of the technology. As a matter of fact because the software kicked the document out and did not try to process it incorrectly it’s doing a great job! What companies make the mistake of doing is every document that falls in this category gets the same attention, an thus additional fine-tuning cost. But what happens if that document type never appears again, then the company just reduced their ROI for nothing. The key to these exceptions weather whole document types or just portions of one particular document type is to set a standard that indicates an exact problem has to repeat X times ( based on volume ) before it’s given any sort of fine-tuning effort.
Only with an exceptional exception handling process will you have an exceptional data capture system and ROI.
Chris Riley – Sr. Solutions Architect
Ilya Evdokimov is a long-term practitioner and expert in leading Optical Character Recognition (OCR), Data Capture and Document Processing techniques, technologies and solutions. With over 15 years of experience spanning enterprise software implementations, mobile applications development, cloud-based systems integration and desktop-level automation, Ilya Evdokimov uses through industry knowledge and experience to achieve high efficiency and workflow optimization in most challenging paper-dependent and digital image capture environments.