The past, present, & future of document processing
We’re going to take a short trip back in time to look at the history and evolution of document processing. Then we’ll look into the future to see how the digitization of data capture solutions can benefit companies like yours.
Data processing services
Data is one of the most fundamentally important elements of your business’s operations. Without the correct data in the correct format, your teams will be unable to achieve their objectives. Accounts payable (AP) teams need the data in invoices in order to ensure that they are properly paid. Healthcare professionals access and manage the data in patient reports, and manufacturing companies rely on the data in inventory documents. This data, in its various forms and sources, is absolutely essential to your organization. The real challenge is how to process the data.
The problem is that most business data today is stored in unstructured formats. This is one way of saying that the vast majority of professionals utilize PDF scans of paper documents to share data back and forth throughout an organization. The problem is that PDFs store document data in an image format. This image merely displays the document but provides no way for computer systems to recognize and record the data.
Solving this problem is the goal of manual data entry. Manual data entry is one of the oldest and most established ways of doing data processing in business. In this method, employees simply read the documents and type the data out into a structured format like an Excel spreadsheet. Although this way of data processing is well-established, it possesses several inherent drawbacks. It is expensive, error-prone, and tedious. Inevitably, paperwork piles up on your teams’ desks, causing demotivation and potentially driving some of your most talented employees out of your organization.
One way to avoid the pitfalls of manual data processing is to utilize data processing services. These services give you the opportunity to outsource your data processing so that your team can spend more time on the tasks that can grow your business. There are various types of data processing services you can implement.
One data processing services example is data annotation outsourcing. Data annotation is the process of labeling data to help artificial intelligence systems learn how to recognize data types and produce useful output. By outsourcing data annotation, you can relieve your own employees of the burden of having to do this time-consuming task.
The importance of data processing in business cannot be understated. It’s vital to understand both the positives and negatives of outsourcing data processing. Furthermore, it’s possible that software might be a better solution for alleviating your employees, capturing data with greater accuracy, and maintaining complete control over your data processing.
Data entry services
When it comes to dealing with tedious and repetitive business tasks that can sidetrack operational initiatives, there are often two ways to address them. When looking at any data entry services list of data processing companies, you’ll often find them offering BPO options. BPO is an acronym for business process outsourcing and refers to the notion we have already discussed – hiring a professional data entry services firm to process your data for you. Another method is to set up a shared services solution (SSC). A shared services center is an internal business unit that is responsible for handling data processing tasks (or any other specific process) for all departments within your business.
BPOs do have some advantages over SSCs. Because they often have more experience and resources than your organization, BPOs often offer more savings and faster implementation than an internal solution like an SSC. BPOs also give you flexibility in terms of the size of your financial commitment.
On the other hand, SSCs give you complete control over your data. This is a huge advantage in terms of business objective alignment and data security. With the right software tools, SSC can dramatically cut the costs of data processing and enable all of your various business functions to be streamlined. Although they may take longer to implement, SSCs more than compensate for that over time, thanks to the better results they can deliver.
Before processing cycle
Before outsourcing or building your own internal business unit, it’s important to fully understand the data processing cycle. This cycle outlines the journey that data takes as it moves through various stages in your business. First of all, the raw data is collected. The raw data can come from a variety of sources. As we have already mentioned, many of the sources will be in unstructured formats. The next step is preparation. In this phase, the raw data is filtered to remove duplicates and errors. Preparation could also be referred to as validation. The goal of this stage is to ensure that only the best quality data is used in business processes and decision-making. After that phase comes input. Input is simply the process of converting the raw data into a format that is machine-readable. Input can be done manually, it can be outsourced, or it can be automated using the software.
After that, the data is processed and then sent to an output system or stored, depending on its function. We’ve found that examples are often helpful when discussing these topics. There are several examples of data processing that we could look at, but accounts payable (AP) is one of the best. In AP, the raw data is collected in the form of invoices (often either in paper or PDF format). This data is prepared and then input into an accounting or ERP system. After that, it is processed, and the vendor or supplier is paid according to the collected data. Then, a new invoice arrives, and the cycle begins again.
Types of data processing
There are, generally, three main types of data processing companies can choose to utilize. The first is manual data processing, the shortcomings of which we have already discussed. The second is outsourced data processing services. These can be very effective and affordable but require you to give up most of your control and can result in a lack of innovation when it comes to workflows. The third type of data processing is automated data processing utilizing a software platform. This third method of data processing may be the most ideal because of its ability to process data rapidly and accurately without sacrificing data security and control.
The right kind of software can result in huge savings of both time and money and can simplify your data processing, leaving your teams with more time to focus on the tasks and activities that really matter to your organization. Consider an example of data processing using this method. An invoice comes to an employee on your AP team. They upload it to a system that automatically extracts the data and exports it directly to the destination system instantly. Furthermore, consider that the same employee could batch process hundreds of invoices in exactly the same manner. This speed allows you to get near real-time data processing completely automatically.
Outsource data entry services
Even though utilizing outsourced data entry services may sound like an effective alternative to manual data entry, it does have some pretty serious downsides. First of all, outsourced data services do create third-party risks for your data security. It’s vital to find a trusted partner to help you manage your data if you want to go this route. Another issue with outsourced data entry services is the lack of adaptability. The service provider is going to have their own fixed methods that may or may not suit your specific needs. Keeping your data processing in-house gives you the opportunity to customize and improve your data processing workflows. Instead of relying on online data entry services, it frequently makes more sense to utilize effective automation software to maintain complete control over your data processing tasks.
Data annotation services
As we have already mentioned, one of the big uses of outsourced data processing is data annotation services. The vast majority of artificial intelligence and machine learning systems process text data. In order to train these machines to be able to accurately process this text, data annotation is frequently required. The more labeled data these machines have to work with, the more accurate their processing becomes.
However, manually labeling and categorizing all the data required for these machines can be an enormous challenge. That’s why many companies look to data labeling companies that have the experience and technology to complete these kinds of tasks quickly and accurately. Online data processing companies can be a very convenient solution for organizations looking for a rapid and affordable way to annotate their data.
Image data entry services
Image data entry services are designed to help organizations extract and export data stored in images and PDF files so that it can be used in systems and stored in the correct destinations. However, relying on outsourced data processing for image data entry has all the pitfalls we have already mentioned. That’s why it makes more sense to rely on software-based data processing solutions. One great example of an intelligent data processing (IDP) platform is Rossum.
Rossum makes it easy to collect and upload raw data from several different channels. Then, with just a few clicks, you can automatically extract and export the data you need from one, or hundreds, of documents. Finally, with Rossum’s flexible API, it’s easy to build an integration with your destination applications and systems, allowing you to build completely paperless workflows.
- Accounts Payable process steps
- AI image processing
- AP Automation
- AP Automation software
- Data entry process
- Data entry tools
- Intelligent Process Automation
- Invoice processing automation
- Medical claims processing
- OCR solutions
- Online OCR software
- PDF data
- PDF OCR software
- What is OCR software?
- Workflow automation tools