Workers have for many years become accustomed to transcribing data from a document and manually entering it into a system of record.

Document data extraction, the process of automatically transcribing data digitally can save countless hours of time for employees

Purchase orders; client documents; customer records; invoices—all and more can be quickly and easily scanned for information in an accurate manner, improving data validation.

Combined with machine learning, its capabilities of handling data improve the more the system is used.

This is especially useful when dealing with unstructured documents.

Vendors like DocuWare are increasingly able to provide these functions to SMBs in full with affordability in mind.

The other benefit of having a data extraction system in place is the ability to store your data exactly where you need it.

Processed document information can output into multiple systems and associated with existing data for easy integration.

according to a study by McKinsey Digital, CEOs spend almost 20% of their time on work that could be automated (like analyzing operational data and reviewing status reports).

Document data extraction in action

A business is processing applications for its services manually, requiring employees to pdf documents and then input the data they see into their work computer.

This takes many hours and decision makers are dissatisfied with how slowly it takes for them to respond, so they implement a document data extraction solution to help.

Now, using the solution, PDFs are automatically parsed, scanning each field and reporting the information to a repository, where an RPA bot can then take over the process.

Extracting data from documents like this means workers can spend their time doing something on more valuable operational work, while they’ve saved time and quickened the process.