Traditional means of document processing depend on staff members to handle data manually. Whether it’s invoices, quotes, orders, remittances, or any document — everything has to be manually read and keyed in, day in and day out.
Back in the day, when the paperwork was limited, manual document processing made sense because it was feasible. But with data-driven companies scaling their businesses and with the option of automated tools, asking your staff to process the documents manually is no longer practical.
In this article, we discuss the major pitfalls of manual data entry and talk about automation as a sustainable alternative.
Back in 2019, a mere 55 billion of the world’s whopping 550 billion invoices were exchanged electronically. All the rest were paper-based at some level and required manual processing. And that’s just the overview of various other intricate issues tied up with manual data processing:-
Companies are still dependent on spreadsheets along with ERP systems, among other business software that requires tedious labor for processing data. 23% of salespersons say manual data entry is the single biggest challenge when using their CRM. Not only that, as much as 84% of all small businesses are reliant on manual data entry.
On the other hand, until 2020, 31% of businesses have adopted automation in some form or the other, and almost 64.8% of businesses have invested more than $50 million in big data and AI in 2020 alone to improve productivity. This has been prompted by advances in big data processing and the growing confidence in AI-powered decision-making.
Despite taking a huge amount of processing time, manual data entry error rate is quite high in most industries - being deemed one of the biggest hindrances in their growth. According to a report from SiriusDecisions, contact records from 10-25% are comprised of critical data errors that directly impact a business’s operations.
Manual data entry, by definition, is a slow and time-consuming process. And since it’s not practical to expect your staff to work at a constant rate throughout the day - given fluctuation in productivity from boredom and fatigue - there are often delays in the turnaround time. The exercise itself is quite time-consuming and leaves little room for analysis and strategizing and much room for a higher manual data entry error rate. For instance, single data entry speed runs at about 10-15,000 keystrokes every hour. No matter how impressive you find it, it is still much slower than a machine.
That’s why financial institutions, among others, are now prioritizing digitization. UnionBank of the US, for instance, has reduced turnaround time for digitizing loan documents from 15 days to 5 days.
A survey from Experian showed that 83% of organizations recognize data as the cornerstone of their business strategy, and yet a substantial 69% confess they are plagued by the issue of inaccurate data.
Businesses that rely upon manual tasks for mundane tasks like data entry are being left behind in all aspects, including performance, productivity, employee satisfaction, and yes — revenue.
There are significant hidden costs associated with manual data entry. Apart from costs for quality checks, and losses due to incorrect information from human error, there are fees for late payments, issues with cash flow, poor vendor relationships, and employee changeover relationships that can drive your revenue south.
Here are some of the major industries that are pioneering automation in data entry. Let’s look at how they implement it and the benefits they derive from it.
The categorization of any amount owed by your company, your accounts payable (AP) process is responsible for managing debts and invoices. Here’s how this field is automating data entry:
Banks combat redundant manual data entry, human error, and frauds. In contrast, bank statement software with Intelligent Character Recognition or ICR is now being used for processing handwritten surveys and bank cheques.
Similarly, for insurance, processing claims is a tedious task and traditionally demands a whole infrastructure to support staffing, training, IT systems, and whatnot. But with increasing digitization in the insurance sector, we now have what’s called Intelligent Document Processing or IDP. This technology is powerful enough to extract data from unstructured and complex documents, including forms that usually require manual processing because the generic OCR can’t analyze it meaningfully.
Manual data entry and processing is a taxing affair both for the employer and the staff and also financially and mentally. With the logistics sector now pioneering automation in terms of document data extraction, here’s what makes it a cost-effective venture:
The quickest and the most effective alternative to manual data entry is an automated setup. With the help of AI and smarter OCR, you can complete redundant and otherwise time-consuming tasks without much effort. Yet, technology can only do so much.
Humans must train machines to perform clearly delegated tasks and proactively interpret the derived results. Adjustments or human input might be required if the outcomes are indeed counterintuitive.
Here's what machines can do:
But truly, machines can only make an educated guess, but it’s the experts who will have to confirm the results. The goal is to train the machines, so they can make near-perfect guesses.
And when it gets down to the brass tacks, in the collaboration of AI and humans, it’s the latter that has to input the least and reap the most benefits. In the right setup, human-machine collaboration can result in error-free data extraction and processing.
With Docsumo’s Document AI and Intelligent OCR technology, automation meets decisioning and analytics. Whether it’s pay stubs, invoices, or actionable data, all your high-volume, repetitive tasks get completed seamlessly. Our technology promises to drastically reduce turnaround time and improve accuracy.
Everything - from uploading documents to editing and validating fields to downloading CSV/Excel/JSON - our solution has it all sorted out. Let ‘s schedule a demo and let Docsumo take care of your data entry blues.
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
With an automated data extraction solution, loan documents can automatically be processed end-to-end without any human errors and delays. Automation in loan document processing prevents downtimes, eliminates data redundancy, and allows companies to respond faster to client queries. By combining machine learning with deep learning and OCR, companies can eliminate huge costs, derive actionable insights, and streamline loan processing and approvals through efficient data extraction and analysis.
Mortgage lenders receive multiple identity and income verification documents along with different forms from loan applicants in a variety of formats and styles. Traditional OCR solutions fail to extract data from these semi-structured documents and that’s why more and more lenders are adopting intelligent document processing solutions. IDP solutions not only extract data correctly, they are able to validate extracted data against predefined rules in order to improve accuracy.
Intelligent Document Processing is an automation technology that captures information from a myriad of documents and data sources, extract data, and organizes it for further processing. IDP solutions enable businesses to seamlessly integrate with core processes, eliminate manual labour, address challenges faced in reading different document layouts, and meeting legal & compliance requirements. Accurate data is the foundation of every organization, and IDP assists businesses in dealing with the complexity of processing huge volumes of documents, helping them automate manual data entry processes, and move away from traditional semi-automated OCR workflows.