How to Increase Operational Efficiency with OCR Automation
By Roxy Grigorescu | January 11, 2018
When undertaking a digitization or digital transformation project, many organizations forget the critical role that optical character recognition (OCR) can play in the process. By incorporating OCR automation into the digitization process—rather than just scanning content in and leaving it at that—image-based content becomes findable, searchable, usable, and easier to analyze.
OCR is also the first step to automating many business workflows. Although transforming paper-based content into digital format is essential to begin harnessing the power of your content, enterprises often stop there—leaving them with a digital filing cabinet that’s just as disorganized as their paper files. This issue can also persist throughout workflows that use a lot of content. Enterprises that need to manually process large files or vast amounts of data often find that they’re being slowed down by the need to examine files manually and extract the relevant data. This leaves employees spending a lot of time sifting through content to add the information to various systems by hand.
Why enterprise OCR helps streamline processes
When organizations face a sudden spike in content—whether it’s due to a period of sustained growth or a merger or acquisition—handling the associated content can be daunting, especially when relying on manual methods alone. It’s a lot more difficult to quickly ramp up and train new employees than it is to add existing software to a task. Beyond the obvious efficiencies and reduction in overhead costs, OCR software is also superior to manual methods because it allows organizations to scale processes down when they’re no longer needed.
Consider the insurance industry, for example. In the case of a natural disaster (such as the recent wildfires in California), the number of insurance claims could increase several hundred times over. Without automated workflows, insurance organizations would need to dramatically increase the number of employees they have on hand—which could result in processing delays as they scramble to hire staff and deal with the massive influx of claims. (To learn how insurance companies are using OCR automation to simplify the claims process and other critical workflows, check out this article.)
However, being able to process claims automatically—using OCR to recognize claims numbers and associate them with a client—means that customers don’t have to wait for insurance companies to complete these steps manually. Instead, their information is directly transferred from one step to the next, saving time and heartache.
Adding OCR automation to your workflows makes your processes a lot more scalable and efficient. By eliminating the manual data entry that’s usually involved, organizations can serve their customers faster and make better business decisions—without needing to wait for images to be read and examined.
How OCR automation reduces risk
Incorporating OCR data capture into your business workflows also decreases the risk posed by manual entry. It’s easy to accidentally enter “O” as “0,” but this type of error can drastically alter your system’s results. This is particularly critical for workflows and industries dealing with sensitive information, or those who face heavy penalties for mislabelled content, such as financial services and pharmaceutical companies.
Automating OCR processes means reducing or eliminating the risk that information will be mislabelled, delayed, or simply missed when it’s being entered in. Instead of needing to check everything over—or risk a business-critical miscommunication—organizations can feel secure in the knowledge that their data has been correctly entered at every step of the way.
Selecting workflows for automation with OCR
Any workflow that requires a lot of content processing, regardless of its risk factor, can be improved with OCR data capture and automation. One example of this is accounts payable processing. Using OCR, organizations can automatically pull the information from an invoice into a machine-readable format to share the total amount with respective stakeholders. If this matches the associated purchase order—the number of which can also be pulled—the invoice date can be automatically associated as well. By pulling information and linking it to pre-approved data rules, payment speed and accuracy is ultimately increased. n needing an employee to check each attachment manually, OCR can immediately transform image-based content into searchable and readable data. That’s the beauty of automation with OCR.
Although organizations may initially be leery of adopting new technologies, OCR offers the immediate benefit of removing steps that end users need to take, and speeding up any digital transformation projects you have on the go. Since OCR helps eliminate manual output, user adoption is often quick and painless, so your customers and teams will see an immediate advantage.
By capturing data using OCR, your organization can save time and reduce costs, all while removing the risks associated with manual entry. By incorporating OCR automation into content-centric workflows, you can eliminate a lot of the tedium and the potential risks that come with manually performing these processes.
If you’re just beginning to automate your processes with OCR, it’s important to note that it’s particularly helpful for processes that have ebbs and flows in demand, and for those that carry a lot of risk if they aren’t correctly interpreted. Ensuring that all your image-based content can be read by machines and humans alike is key to keeping business processes running smoothly, and removing any risk associated with human error.
Whether you’re undertaking a digital transformation project or simply want to make your content workflows run more smoothly, adding enterprise OCR to your toolkit will decrease manual input, save time across the board, and reduce any risks associated with mislabelled content.
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