With all the hype around robotic process automation (RPA), it can be helpful to remember that the vast majority of the data running through RPA automations originates or terminates with a document. In fact, I’d estimate that about 80% of RPA automations fall into this category.

Because so many RPA automations involve documents, we’re able to identify common document processing patterns and use cases. Here are the five most common ways companies are using RPA to enhance document processing:

1. Transactional Data Entry, or Straight-Through Processing

Transactional data entry is the mother of all unattended bot automations.

Unattended bots do not run on a user’s personal workstation. Rather, they run on one or more physical or virtual machines tasked with performing more batch-oriented and longer running transactions. Unattended bots are custom-made to process documents that flow into the enterprise on their own timetable, and where timely and hyper-accurate data entry into downstream line of business systems is critical.

We are talking about an organization’s most important operational documents such as invoices, insurance claims, electronic medical records, shipping documents, etc. This is the data lifeblood that courses through the veins of every organization. No matter the document, the processing pattern is often the same:

  • Documents are acquired and ingested.
  • OCR and machine learning auto-categorize documents and extract transactional data.
  • Extracted data is validated against internal data sources.
  • Validated data is automatically entered into downstream line of business systems via the application’s user interface (just like the user does it).
  • Real-time prompts are generated and presented to skilled knowledge workers to handle exceptions.
  • Transactions are recorded and logged for audit and compliance purposes.

RPA makes the elusive, Brigadoon-like promise of straight-through processing a reality. While transactional data entry is usually handled by unattended bots, there are many attended bot uses as well. The bang for your buck will vary depending upon document volume, duration of the transaction, and verification requirements.

Related Article: Busting 8 Robotic Process Automation Myths

2. Document Acquisition

Document acquisition is not always a simple task. While most document processing platforms can acquire documents from scanners, cameras, watch folders, and email accounts, this is far from an exhaustive list of the channels through which documents enter the enterprise. Many organizations are also forced to acquire documents from locations such as websites, FTP sites, EDI translators, and more.

Consider this use case for a defense contractor that provides government procurement solicitation information to its subscribers. Prior to implementing RPA bots, staff members would trawl multiple government sourcing sites throughout the day looking for new and modified solicitations. This is time-consuming and tedious work.

After implementing RPA, workers were freed up to handle more customer service-oriented functions while letting the bots comb the sites, determine which solicitations are new (versus updates), and update their internal solicitation tracking system accordingly. The result is faster, more frequent, and more accurate processing for a fraction of the manual cost.

Another company receives most of its orders from one large customer that posts orders on its various divisional websites and also sends orders via EDI. Before implementing RPA, this organization had dedicated personnel to monitor both the websites and its EDI account for incoming orders. After implementing RPA, those document sources are now monitored and processed by bots, which in turn send the orders to fulfillment and accounting. The company reports order processing costs have declined 25% and order volume from the customer is up 12% based on increased customer satisfaction.

RPA can be an incredibly powerful multi-channel document acquisition tool.

3. A Shortcut (i.e., 'jumpto') to Necessary Documents

The top reason organizations give for not centralizing their document repositories or duplicating documents across line of business systems is the need to locate documents from different contexts. Meaning, accounting may need to retrieve an invoice from a supplier record within an ERP system, while an HR professional may need to view a change of life event form from within an EHRS.

Satisfying these requirements would normally involve creating a custom connection to the repository from each application screen, in each line of business system. Not only is this a ton of work, but in most cases, it is impossible to do.

However, via an RPA attended bot, a “jumpto” button can easily be placed onto any screen with no changes to the application required. When pressed, this button kicks off an automation that extracts screen data to establish context and then uses that data to “jumpto” the related document.

The attended bot functions as a universal adapter that can determine application and data context for a given user and present the user with the right document(s). The same is true for contextual requests flowing in the opposite direction, or something called “reverse jumpto.” For example, if a user is viewing an image (such as an invoice), the user can click the jumpto button, which extracts the metadata required to establish context and navigates through the ERP system to the related bill.

Learning Opportunities

The possibilities of creating a powerful, contextually hyperlinked experience among data, documents, and system records are endless.

Related Article: BPA vs. RPA: How Are They Similar, How Are They Different?

4. QuickCopy

Despite the power of machine learning and its ability to perform document auto-classification and data extraction, many documents are still manually indexed or supplemented with metadata from line of business systems.

“Quickcopy” is the process by which a user opens a record in a line of business system, and via the same button described above, kicks off an automation that extracts select pieces of data from one or more application screens, and then quickly copies them to the metadata fields of the open document. As with jumpto, the user can reverse quickcopy by pushing data from the metadata fields accompanying an open document to fields within the selected record in the line of business system.

Sidenote: the more you adopt the jumpto pattern, the more jumpto allows you to interact with documents in a central repository from any application screen on the desktop.

5. Document Assembly and Forms Extraction

Document assembly and forms extraction have been around forever. By leveraging the power of RPA, any application screen(s) can easily be used as the source to assemble a document, or as the destination for data extracted from a form.

In the case of document assembly, data is extracted from application screens and assembled into a document or email. Think of it as a universal mail merge capability that can be added to any application that assembles or injects data into any document. A great example is the creation of a contract in DocuSign that acquires inputs from one or more selected records in an application.

Forms extraction is really just the other side of the same coin. In this case, data is extracted from a form and inserted into the fields of an open application record. Document assembly and forms extraction are equally used by both attended and unattended bots.

Related Article: Business Process Management vs. Robotic Process Automation: How to Choose

Do You Know the Way to RPA?

RPA and document processing go together to boost productivity like peanut butter and jelly. Borrowing from these five patterns can inject greater efficiency into the productivity-draining tasks that could be slowing down your organization.

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