Data entry automation is critical for onboarding new customers, processing B2B data, or during an acquisition. There are two approaches to automating data entry for the modern enterprise, and manual offshore keying is not one of them.
This article covers the benefits of using automation software like robotic process automation (RPA) and intelligent document processing (IDP) to automate data entry.
1. When Should I Use RPA for Data Entry?
RPA is best suited for automating data entry when the source data is highly structured. Because RPA bots are designed to automate highly repetitive, time consuming, and tedious tasks, they work well with 100% predictable data.
Great examples include logging into websites to upload / download / enter information, moving data between databases / applications, and working with any structured form or document that hasn’t been printed and scanned.
The best way to think about RPA is that it is an unskilled robot that repeatedly performs a strict set of functions. You can imagine what would happen on a manufacturing assembly line if the parts on a conveyor belt get off by just a few inches. Everything would stop.
And no one can argue the efficiency of robots in manufacturing.
2. When Should I Use IDP for Data Entry?
IDP is a great automation tool for data entry from highly unstructured or semi-structured data sources. IDP is designed to “read” documents, understand their intent, and find specific pieces of information.
The most widely accepted uses are with invoices, mortgage / lease files, 3rd party forms, digital transactional / B2B data, and contracts. IDP eliminates human error on big document processing projects.
The best way to think about IDP is that it is a programmable set of technologies working in concert to discover and then extract information that isn’t in 100% predictable places or in a format that changes often.
2.5 Combining RPA and IDP for Data Entry Automation
The very best approach to automating data entry is with a combination of tools. Organizations using only either RPA or IDP will quickly move beyond the original use-case as their automation journey grows. And it makes sense – most companies will start with either IDP or RPA, but so far – rarely both.
Data entry automation with RPA starts with the low-hanging fruit of manual and repetitive tasks. As automation maturity improves, it moves on to more complex subject matter-intensive business process, and this is where IDP will come into play.
Think about data entry automation with IDP as an ingestion engine. It is a platform configured with a subject matter expert's (SME) knowledge on a case-by-case basis. While RPA works out of the box on many different types of processes, IDP creates custom solutions for specific use-cases. For IDP to work on lease processing, for example, an SME is needed to configure the system to process the leases according to existing standardized workflows and policies.
IDP delivers highly targeted data that would otherwise be impossible for bots to work with.
In fact, research firm Gartner, Inc. says that “by 2022, 80% of RPA-centric automation implementations will derive their value from complementary technologies.”
Organizations starting their data entry automation journey with IDP will quickly realize the value in delivering structured data from unstructured sources into bot workflows.
In the case of a legal discovery request or new compliance initiative, a bot kicks of a request to parse a vast content management system for certain data and return all documents containing the needed information. Then the bot would deliver these documents into a workflow for further processing. No manual searching, and no manual data entry.
Or imagine an accounts payable bot that integrates invoice information into multiple systems. Because the invoices come in from thousands of vendors daily, IDP is needed to deliver up critical invoice information to the RPA solution. The bot will then take the invoice information and integrate it where it’s needed for approvals and fast payment. Full data entry automation.
In the financial sector, customers demand real time access to their data. Institutions processing paperwork faster gain more customers and retain them. Imagine a 400+ page loan packet that contains financial instruments and disclosures that exist in any number of formats or layouts. An RPA bot sends these packets to the IDP solution for document classification and data extraction. All necessary data is labeled, extracted, and delivered to the bot for entry in loan origination and audit systems for near real-time processing.
With all the above use cases, data validations are happening and there are human-in-the-loop workflows that ensure data accuracy. There is power in connecting these enterprise systems together.
You can see how converging multiple technologies like RPA and IDP revolutionizes data entry automation. There are truly very few manual business processes that cannot be automated with extremely high accuracy and with no human error.