Data entry is, simply said, one of the key activities in business conduct. On a daily basis, we receive data in various forms and import it elsewhere – to programs and archives – in order to arrive at an expected outcome.
In this article, we will take a closer look at what manual data entry looks like, how you can automate it, and what are examples of successful data entry automation.
What is Manual Data Entry?
Let’s begin with manual data entry – what it is and why you would want to automate it in the first place.
Manual data entry describes a process where you physically transfer data from one medium to another, e.g., by receiving and reading a paper copy of a document and then inputting the necessary information from that document into a computer program, a spreadsheet, a database, or any other digital platform.
A person working on data entry can perform several tasks, such as copying, pasting, typing from scratch, or selecting options in the computer program. Since this is a broad definition, the type of data transferred manually can refer to anything – text, numbers, codes, and so on.
The common ground for all these pieces of information and tasks is frustration and routine, which are inherently correlated with administrative work.
Bottlenecks in the Manual Data Entry Process
We’ve established that manual data entry is a common practice and that it causes problems and frustration.
Reportedly, it’s the most hated computer task of all, and many workers agree that it should be automated – three out of every four employees feel that way.
You probably wouldn’t be surprised either that many industries still rely heavily on this type of conduct – research from 2019 reported that over 48% of manufacturing companies were dependent on the manual processing of data.
In fact, administrative tasks prevent workers from realizing their potential and also reduce time to perform more important tasks. Other bottlenecks should be mentioned:
- Human errors & skillset. The most natural obstacle in performing better is the skillset, but also factors that cause employees to lose focus. Bad sleep, health problems, and many other factors lead to errors made in data entry, such as typos, transpositions, or omissions. While mistakes can be amended, they might impact decision-making processes. That leads to bad business decisions, deteriorating relationships with partners and suppliers, or sunk costs of tracing and correcting errors. Some of these errors can be ridiculously expensive, too. Lockheed Martin lost over 70 million USD when the contract the company signed had a missing comma in the agreed-upon price for the products. Another company, Alitalia, lost 7.2 million USD when two zeros were missing from the pricing for a flight to Toronto.
- Scalability challenge & resource cost. Hiring people to perform manual administrative tasks rarely makes them excited about the job. Finding the right people takes time but also generates costs that could easily be transferred elsewhere – salary, larger office space, or costs related to home office support.
- Building-up frustration & job dissatisfaction. Deteriorating job satisfaction is a worrying trend and one on the rise, too. Research from 2022 revealed that over 60% of employees are disengaged at work, and 19% admitted to feeling miserable. Global numbers are even more depressing – a staggering 85% of workers worldwide are dissatisfied with what they do. While the most important causes of dissatisfaction relate to how employees are treated by their managers and what’s expected of them, repetitive tasks are the first early sign that eventually leads to job dissatisfaction and burnout.
Considering all of the above, you could assume that no employer would want to risk having a team of dissatisfied, unmotivated employees who tend to make costly mistakes and whose ability to take on more work is largely limited. Sounds like a nightmare for all parties involved, but sadly, that’s often the reality without automation in place.
What is Data Entry Automation?
The alternative to performing data entry manually is automation.
Automated data entry doesn’t change the core of the process – transferring data from the original source to a destination defined by the user – but brings AI to perform the task for humans, leaving users as supervisors of the process.
Automatic data entry speeds up the process of data collection, which is the most tedious part of the process. Opening a file, understanding its content, copying or rewriting selected information, and reviewing it in the system are all tasks up for grabs when it comes to modern technology.
Some of these tasks can be improved with Robotic Process Automation (RPA), a branch of business technology where computer programs learn how to copy human behavior to perform tasks. Other parts of the process are handled by document automation, which allows users to export data from all kinds of documents in real time and then upload it to the expected destination.
The main purpose of introducing an automation tool that helps with data entry is to save time spent on gathering data and enable scaling, while manual processes leave much to be desired in handling data with high accuracy.
Manual vs. Automated Data Entry
Since both approaches are now clear, we can compare them and see why almost every business operation could use automation. Let’s look at the way the process is set up.
In manual data entry, users download or receive the data source and begin reading and analyzing the contents. The first obstacle appearing in the process is dealing with a multitude of data sources.
Those can vary from digital reports, documents, and forms to paper copies that require scanning and archiving. While we will go through several examples in detail, these so-called “unstructured documents” require a lot of effort. The user needs to create a database – typically an Excel file or a Google Sheets – to combine the data and manually enter them one by one.
Only when the database is populated with entries the user can upload it to a computer program. A slightly more convenient scenario is inputting data directly into such a system without the need to create the database first.
With data capture technologies in place, the user defines the source from which the entry solution pulls documents. The user doesn’t need to open each file separately because document automation involves modern technologies such as OCR (Optical Character Recognition), backed by continual learning and artificial intelligence.
The user logs into the tool and defines all the information that’s required in the workflow. In other words, they define fields that will be recognized and exported into a structured format. After all of the documents are recognized and processed, the user receives a ready-to-use database that can be integrated with the system of their choosing.
Several aspects should be considered here.
- Efficiency. The manual process is always more time-consuming and poses the threat of a higher entry error rate. Business processes optimized by data entry automation are leaner and ready to quickly digest large data batches. A study by McKinsey proves the point – 45% of time spent on manual tasks could be automated easily.
- Human involvement. Entry automation tools empower data entry clerks to perform mundane tasks faster and receive valuable insights for decision-making. The most advanced software revolves around the idea of user supervision, where people can manage and configure the process and adjust and edit the outcome but omit to perform the task end-to-end.
- Cost. In the beginning, automation may pose another incurred cost. Over time, it becomes clear that the savings are found in the turnaround time, increasing the efficiency of business processes and removing the scalability bottleneck.
Now that we have looked at both options, you might be wondering what to look for in your document data automation software.
Key Features in Automated Data Entry Software
- Wide range of document types and processes served. Some of the popular tools available in the market – such as ABBYY, Kofax, or Rossum – are mostly focused on delivering high accuracy on specific use cases and document types in an end-to-end approach. However, business processes often require processing a variety of documents, and that’s where the zero-shot technology becomes essential. Unlike template-based OCR or supervised models, this novel approach does not require the model to be trained on documents. Instead, you can create a custom model on your own and extract data from any document type.
- Adjustable pricing. We’re all price-sensitive, and pricing often plays a decisive role in purchasing any product, SaaS included. When it comes to document data automation tools, you will often encounter subscription packages with a certain cap on the number of documents you can process. While some of them offer a batch of free documents (e.g., Nanonets), some businesses prefer to have more flexibility. Another aspect to pay attention to is the cap on the number of models (often called processes) too. Cheaper tiers may restrict the use of some of such models or allow you to use a limited number of them. That’s when you should opt for a pay-as-you-go model. If a subscription costs an arm and a leg, while your documents aren’t big numbers but have big diversity, this is your best alternative.
- Additional features. In the beginning, you might want to start with software that crosses out just one problem off your list. However, most online tools assist users in solving more than data entry. These features may include converting data to one unified form (useful in processing large batches of document data), document classification (a great solution for a large variety of documents that need to be worked on), page splitting (a snappy solution for handling large PDFs), and others.
Automated Data Entry Use Cases
How is the problem of data entry tasks solved in particular examples?
Let’s take a closer look at several short case studies where Alphamoon can successfully assist business owners in various fields. The benefits are numerous:
- You can get back your precious time
- Elevate the customer experience to another level
- Or have the entire process optimized with real-time data provided right away
And those are some of the examples.
Retail and E-commerce: Retailers Managing Product Catalogs
One of the most common challenges for retailers is monitoring the inventory and – in the case when products can expire – taking the products off the shelves.
Automated data entry in e-commerce can be very helpful here. Here’s an example of how we have set up a process that reads product labels. Alphamoon’s platform will read this data and extract it.
Note that the tool has flagged one of the fields – that means that human intervention is required (you are always in control of the process).
Transactional document processing in Finance and Accounting
Another common use case for automated data entry is working with all kinds of documentation that includes financial data – term sheets, financial statements, credit reports, invoices, and so on. For teams working in the Accounting and Finance departments, manual data entry carries an additional amount of risk associated with errors – such as misspellings in tax reports and other official documents.
We have set up a process to pull data from financial statements in a business credit report process. To simplify the process (this is just an example and not the exact way the tool needs to be configured), we have added the following fields for extraction:
- Cash and cash equivalents
- Inventories
- Total current assets
- Long-term receivables
- Intangible assets
- Total assets
We then uploaded an example of a financial statement and entered the Supervision view to see if all fields were correctly pulled. It’s a matter of seconds to capture data this way and download it all to include in an Excel spreadsheet.
Optimized data entry from financial statements – read how it works and create your account.
The extensive paperwork handled in Law Firms
The legal industry drowns in paper, and the documents handled by lawyers and legal experts tend to be very complex. A common use case that Alphamoon is used for is Trademark registration documents like this:
This workflow is a simple example of automated data entry, and yet it saves a massive amount of time, allowing legal offices that offer trademark registration and processing services to work more effectively. Another good example of such time optimization is notarial acts (or notarial deeds). Long, and complex, this type of document contains data that can be automatically extracted – instead of flipping pages of paper copies.
All things shipping in Logistics and Supply Chain
One of the paperwork heavy-lifters is the logistics and supply chain industries. The amount of various documents is astonishing, with minor details differentiating the types of documents between them. Also, time is important – informing clients about delays regarding their shipments is the key to high customer satisfaction.
To better portray this example, we created a process for bills of lading using one of the ready-to-use templates from Alphamoon. We edited the fields, so for simplification, we selected only five fields to be extracted:
- Shipper Name
- Shipper Address
- BOL Number
- Shipper’s Number
- Gross Weight
We have also set up a simple automation process using the integration with Zapier.
The workflow was then created to send this information to a Google Sheet so that the company has information about times of delivery in one place, always at hand and up to date.
The same workflow could be established in a different way – e.g., transfer data from documents to tasks in Asana, Notion, or any other project management tool.
Create a similar process – start by creating your account and opting for the bill of lading automation template.
Government: Government Agencies Process Various Forms, Permits, etc.
Hardly any other area seems to require entry automation software more than governmental and official institutions. Tons of forms, permits, and other official documents are easy for document processing technology because they do not differ in terms of layouts and often come in digital formats already.
With zero-shot technology, any office can start using the technology right away and worry not about data safety – Alphamoon has the ISO27001 certification and is GDPR-compliant.
Data Entry Automation: Ready to Try It Out Today?
There you go – you’ve entered the world of automated data processing. We hope that paper documents of all sorts will no longer be your, or your team’s, nightmare. Click below to start setting up your own process, and hey – drop us a line whenever you need. We’re always happy to assist you.
FAQ:
- What is an example of AI-Powered Data Entry Automation?
AI-powered data entry automation assists users in various tasks related to processing documents. An example of such automation is a process consisting of three stages:
- The data entry software connects to the source folder, such as Google Drive or e-mail inbox, and pulls documents in order to automatically get relevant documents.
- The processing software, such as Alphamoon, converts the document into a readable format for the machine and pulls relevant information that is defined by the user.
- The data is then automatically added to a user-defined destination (through Zapier integration) or downloaded as an Excel or CSV file.
- Does Data Entry Automation yield cost savings?
Yes, cost savings can be achieved by reducing the need for employees to work on repetitive tasks, which are time-consuming. Operational costs are optimized in the long-run perspective, too, as processing more documents does not require increasing headcount.
- Can you use Alphamoon for handwritten documents?
Although Alphamoon does not support handwritten documents for now, we have worked with clients who tried processing such documents and achieved a satisfying level of accuracy. We recommend to try our tool and test it out!
