The content capture market has really taken off since the dawn of the industrial scanner and MFP machines, yet there are a number of issues that still arise from the massive volume of organizational content.
For example, at one time there was only one point of input in an organization, let’s say a scanner, for example. Now, there are multiple sources of input in each department: fax machines, scanners, email, etc. Moreover, increasingly content is digitally born created from Office systems, email, web forms, etc. It’s no longer just about scanning paper piles.
Capture solutions need to be able to identify the capture source, the structure of the document, and the channel for distributing that information. It becomes more complex the more sources of input you add, and the more channels of distribution your organization contains.
What can help this process is auto-classification, which is essentially the understanding of what an input document is, the ability to decide what the document or image contains, what information needs to be extracted, and where the document needs to route to – either within a workflow or repository context. At one time this whole process was done manually. Now, with intelligent metadata-driven rules engines, much if not all of this process can be automated.
There are a number of other issues capture professionals face day to day. Take a look at this short video with capture specialist Harvey Spencer for more information.