In the last blog, we saw how documents could be centrally captured in high volumes to remove paper from the process, and give employees access to the digital form of that document as quickly as possible. The benefits of this improved visibility can be extended to all locations, all channels, and all departments ─the topic of this month’s blog. We will also explore how an imaged document is now primed for more advanced capture technologies, such as automated document classification, document separation and data extraction that drastically improve operational efficiency in document processing operations.
The general rule for minimizing document processing times is to digitize the document as early in the business process as possible. This, combined with an increasingly mobile and distributed workforce, brought about the concept of distributed capture: capture that occurs at remote and satellite offices, field offices, broker offices and the like, using mid-range scanners and multi-function devices. But it didn’t stop there. Capture moved further from corporate to land in the hands of customers themselves, who began capturing documents using desktop scanners and mobile devices.
Which brings us to the topic of multichannel capture. Many organizations dealing with customer-facing, information-intensive business processes struggle with supporting all the communication channels their customers demand and their competitors offer. Customers send documents through email, mobile apps, and web portals, and, yes, some still use fax and snail mail. To keep competitive and operationally efficient, companies must support these channels of communication with consistent, reliable user experiences regardless of the chosen channel, as well as a single ingestion point and connection to the systems of record that run the business.
For an effective capture implementation, you must not only consider capturing documents across all locations and all channels, but also managing capture across the enterprise. Each department will have its own set of documents received by customers that need internal processing, with its own data needs and set of business rules. To avoid a departmental island mentality, smart organizations have implemented enterprise-wide digital mailrooms to process all incoming documents. These digital mailrooms are typically in the form of geographically strategic shared service centers or business process outsourcers; their sole job is to get the right documents to the right people, processes and systems at the right time using software automation.
Digital mailrooms—and in fact, most of the more advanced capture implementations today—will go beyond imaging and indexing of documents to automating the heavily manual processes of document classification, document separation and data entry; this is collectively known as “transformation” or transforming documents into useful business information. Take, for example, an insurance claim. Without transformation, a human must manually identify the document as a claim, separate it from any attachments, and route it to the right people to process; those people must then manually enter data from the claim into a claims management system. For some types of insurance claims, this means hundreds of fields to enter for a single claim. Now multiply that effort by thousands of claims received each month—not to mention all the manual data collection and verification from other systems and all the human reviews that must occur before approving the claim (more on how to digitize this in later blog posts).
This manual document processing approach is slow, error-prone, costly, and not scalable as the business grows—symptoms that are addressed by transformation’s ability to automate document classification, document separation and data entry. Teams of dozens dedicated to data entry can be drastically reduced, redeployed to other more value-added functions, or made more productive during high-demand periods or as the business grows. In short, transformation spawns a highly productive document processing operation.
We can apply transformation to any document entering the organization, paper or electronic. Capturing information from invoices and matching with ERP system data; extracting government tax and census forms; classifying mortgage applications and related documentation and extracting information for underwriting; and classifying and extracting medical records for EHR are just a few examples.
Acquiring document-based data is just half the equation, however. In my next blog post, we will uncover a different, but related world of structured electronic data trapped in internal and external systems that also needs acquiring by the business process: enter robotic process automation.