Beyond Extraction and Classification

The decision to start using automated document classification and extraction is important. When to run those routines is perhaps more important.

Document Classification and Other Workflows

Recently, I observed a series of complex workflows within a single organization. They weren’t using electronic classification of incoming documents. As a result, their downstream workflows became inefficient. Documents in this workflow separated by complexity as soon as they came in, but weren’t scanned until multiple steps down the chain. This resulted in a scanning bottleneck after the first two steps of the documents life within the organization. It also created a delay in workflows when that document was available for downstream processes.

The reason for not scanning the document initially came down to the fact that sorters were under pressure to get documents into a manual data entry queue as quickly as possible.  The workflow was an inefficient process of sorting, data entry, lab, and finally, scanning.

The Need for Automated Classification and Extraction

With automated classification and extraction, it becomes possible to front-load the work of entry and classification. Since the bulk of data extraction doesn’t need manual entry and the classification is automatically proposed, the work can be front-loaded. This has the potential to create enormous efficiency gains throughout the organization.

In a lab setting, it allows for the billing team to get documentation the moment it comes into the lab, allowing for faster follow-up on discrepancies. It also means the lab has the potential to run without large amounts of paper. This has a huge potential to reduce errors.

The takeaway is that software for automated extraction and classification does more than just extract and classify.  It can also impact your workflows, optimizing your processes to save time and effort.

If you’d like to learn more about how automated extraction and document classification, read more here.