Data entry automation fixes bad processes and provides a solution to bridge gaps between software systems.
While there are two popular approaches to automating data entry for enterprise content, manual offshore keying for data collection is not one of them.
This article will focus on the benefits of performing data entry with two intelligent process automation solutions:
- Robotic process automation (RPA)
- Intelligent document processing (IDP)
Table of Contents:
- 3 Examples of Data Entry Automation
- What is Data Entry Automation?
- History of Data Entry
- Features of Data Entry Software
- Benefits of Data Entry Automation
- When to Use RPA for Data Entry Automation?
- When to Use Intelligent Document Processing Instead for Data Entry?
- Difference Between RPA and Intelligent Document Processing
What is Data Entry Automation?
Data entry automation are software-oriented solutions that vastly optimize data entry processes by replacing or decreasing manual tasks. This kind of software usually extracts data from images, electronic documents, PDFs, e-mails, paper documents or web pages and format the data in the format or structure of your choice (such as XML, CSV, JSON, CMIS, XSLT, etc.). They use technologies like OCR technology (optical character recognition) or ICR (intelligent character recognition) to simplify data ingestion processes.
While it may seem obvious that software would replace "stare-and-compare" work, it has not always been feasible from a cost perspective.
To understand why automation is such a hot topic now, we must first dive into the past and understand how we got here.
A Brief History on Data Entry
An enterprise running on a single software system would rarely need manual data entry outside of subject matter experts collecting and entering data into the system.
However, as software has evolved, the concept of a single platform being used by all business units has absolutely eroded. There are now point solutions for everything and no enterprise runs on a single behemoth system (an idea left behind in the '90s).
Add to the plethora of software solutions available today the practice of growth by acquisition and web-based content delivery. You then understand why getting all core systems "talking" with each other is a monumental task.
For a long period of time it was simply cheaper to manually enter data from one source of information to another. And probably true that there was no alternative.
Demand for data entry clerks reached an all-time high in the late '80s as platform-based enterprise resource and planning solutions began to take hold.
Data entry remained in demand until a steep decline in the early 2000's. By 2012, the allure for manual data entry all but disappeared thanks to increases in technology.
But not all manual data was eliminated! There was still the problem of documents and data feeds from externally-controlled systems.
Now, modern data entry automation technologies are removing the last of the tedious repetitive manual administrative tasks; finally making it cheaper to onshore all data entry with software.
Key Features of Data Entry Software:
- Customizable Interface Features - Dozens of features can be customized, like checkboxes, dates, labels and text through drag-and-drop interfaces
- Data Versatile - Recognize and classify multiple forms of data and sources
- Easy Integrations - Point-and-click data and integration with ERP software and automation tools like Clockify, Trello, Zapier and Workato to leverage many capabilities and optimize data entry
- Track assignment and management - Add new tasks through validation rules, assign them to certain team members and alerts will notify when data needs a manual review
- Project Tracking - Monitor all project updates, changes and tasks in real time from anywhere.
Why Should You Invest in a Data Entry Software Solution? What are the Benefits?
- Decrease overall costs and paperwork: The traditional method of managing data and paper documents means paying for printers, expensive toners, filing cabinets, storage space, and employees to organize the files and key in the data into your business or content management system.
All of these operational and overhead costs can be greatly reduced with data entry software. You can also greatly cut the costs of manual data entry errors, which leads us to...
- Saving costs by eliminating manual data entry errors: Did you know that a Gartner study shows that a manual data entry error in financial processes results in an average of 25,000 of extra work at the cost of about $878,000 annually?
By automating manual data entry with software, accurate data is entered into ERP, business content management systems, or accounting systems. When a discrepancy or mathematical error is found by the software, those instances can be flagged for a human to review them.
- Increased accuracy leads to better decisions: Data entry automation tools use AI and machine learning to integrate accurate data into business intelligence systems. With valid and complete information, leadership has more data to make important decisions.
- Saving time leads to more valuable work: Incredibly fast data entry means employees don't spend their time doing things manually. And all data (like invoices, receipts and files) can be managed in a few clicks. As a result, employees have the time to concentrate on work that is more valuable to the organization.
- Improved workflow efficiency: By leveraging intelligent data entry software, manual work and workflow complication can be greatly reduced. Workflow steps can be set up so only certain people have access to digital copies that concern them or their department.
3 Examples of How Data Entry Automation Software is Saving Time Right Now:
1) Legal and Compliance
Legal and compliance tasks are difficult to perform and have traditionally required expensive manual data parsing, review, redaction, and moving files.
In the case of a legal discovery request or new compliance initiative, an IDP solution will parse a vast content management system for certain data and either redact it or return all documents containing the needed information to an RPA bot.
The bot delivers documents into a workflow for further processing.
No manual searching, and no manual data manipulation.
2) Automating Invoice Data
Or imagine an AP automation workflow that integrates invoice information into multiple systems.
Because invoices arrive from thousands of vendors daily, RPA bots are great for moving documents from cloud- and local-based sources like email, fax, and file shares into IDP workflows.
IDP processes invoices to extract and validate invoice information. The invoice, along with relevant extracted metadata is delivered back to the RPA bot.
The bot will then take the invoice information and integrate it where it’s needed for approvals and fast payment.
Full data entry automation.
3) Data Entry Automation at Banks and Credit Unions
In the financial sector, customers demand real-time access to their data.
Institutions that process 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.
When Should You Use RPA for Data Entry Automation?
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
- 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.
When Should You Use Intelligent Document Processing Instead 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.
- Mortgage / lease files
- 3rd party forms
- Digital transactional / B2B data
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.
IDP is well-suited for more complex knowledge work because it combines technologies like:
When to Combine RPA and IDP for Data Entry Automation
The very best approach to automating data entry is with a combination of these tools. Organizations using only either RPA or IDP will quickly move beyond the original use-case as their automation journey matures.
And it makes sense – most companies will start with either IDP or RPA, but rarely both.
Automation Software: What's the Difference Between Robotic Process Automation and Intelligent Document Processing?
Automation software using RPA starts with the low-hanging fruit of manual and repetitive data entry tasks. As automation maturity improves, more complex subject matter-intensive business process are replaced. This is where IDP comes into play.
While RPA works out of the box on many different types of processes, IDP creates custom solutions for very 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 the organization's 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:
Organizations starting their data entry automation journey with IDP will quickly realize the value in delivering structured data from unstructured sources into bot workflows.
Transforming Data Processes Isn't So Hard
With all the above use cases, data validations and human-in-the-loop workflows guarantee 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.