In this blog, we offer plenty of insights into the benefits that automated invoice data capture can deliver to your business. For instance, you can read about its impact on data entry costs and accounts payable (AP) efficiency. We also offer guidance in selecting the best invoice processing solution for your company.
To help you use these resources to their fullest potential, we're going to break invoice data capture down into the methods and tools it requires. You’ll see how your company benefits when you automate accounts payable data entry. We’ll also take a quick look at the difference between structured and semi-structured data and its relevance to invoice processing. By the time we're done, you should have a deeper understanding of this vital business operation and the advantages intelligent data extraction can deliver.
The invoice data capture process
Let's start with the process itself. Invoice data capture is the entry of invoice details into an accounting system. This system can be as simple as a paper ledger with records of outgoing payments, the vendors that received those payments, and payment dates. That might be good enough for a small mom-and-pop outfit, but think about the utter chaos such a system would create in a major global corporation.
Paper trails are, and always will be, crucial to transparency in reporting and auditing; fortunately, we no longer need to take the term “paper” literally in this context. AP teams can now use invoice data extraction methods that provide secure, reliable, and cost-effective digital paper trails. As you will see, some of these methods still require a considerable amount of manual work despite the fact that automated options are readily available.
Invoice data capture methods
There are three ways of collecting information from invoices: manual data entry, template-based OCR solutions, and smart automated OCR solutions. All have their place, though advances in smart technologies and the evolution of AP best practices are rendering some methods obsolete.
Manual data entry
Here's a breakdown of the manual invoice data entry process:
Receive paper invoice. Open accounting software. Look at paper invoice. Enter PO number into header field for PO number in accounting software. Look at paper invoice. Enter vendor name into header field for vendor name in accounting software. Look at paper invoice….
You get the idea. We could replace “paper invoice” with, say, “pdf invoice”, the difference being that the data entry clerk copy-pastes invoice details into accounting software instead of typing them. Day after day after day.
Manual data entry in any context is clearly a tedious spirit-draining task, regardless of whether your company outsources it or keeps it in-house. And as the spirit wanes, the potential for errors rises. As melodramatic as that sounds, it’s true, and the fact remains that manual invoice data capture can create all kinds of problems, including late payments, lost early payment discounts, and friction with vendors.
With the arrival of OCR came the hope of dramatic reductions in man-hours spent on invoice data extraction. OCR software scans printed documents, or reads electronic documents, and collects the text contained within them. AP professionals use this solution to capture invoice data, which they then process and store.
There are two OCR variants: template-based and automated. The former requires manual effort to maintain and prevent errors; the latter offers the option of running an accurate and efficient touchless AP process.
In this approach to data capture, OCR software reads an invoice and captures data according to predefined rules and templates. It has come a long way in its decades-long history as the go-to solution for digital invoice processing. Template-based OCR extracts data more accurately now, just as long as the software is reading characters in layouts it’s been trained to understand. This means your AP colleagues must set up templates and rules for every format of invoice they receive.
If your business has all its suppliers submit invoices with the exact same layout, this is a pretty feasible solution. However, the invoices your company’s AP unit is processing are more likely to be formatted differently. And at least one staff member has to handle such tasks as accuracy verification, PO matching, and initiating approval and payment processes.
Smart OCR invoice scanning
Also known as cognitive invoice data capture software, a smart OCR invoice scanning platform understands the information it is extracting. Applying machine learning technology, the software learns how to recognize and capture relevant data in various document layouts with continued use. This eliminates the need to manually set up new templates every time the AP team receives new invoice layouts. This is about as "set it and forget it" as an invoice data capture service can get.
You can set up a smart OCR invoice scanning solution to fully automate AP data entry. You could even go so far as to create a completely touchless AP process if your business is comfortable with having software approve invoices. However, the reality is that you’re always going to need a human in the loop to monitor accuracy and ensure every step is running smoothly.
While an automated invoice data capture solution may seem like an obvious upgrade for AP, finance professionals are understandably a bit wary about progressive technologies like AI and machine learning, as well as the very idea of cloud-based SaaS solutions. If you’re committed to introducing cognitive data extraction to your company’s AP workflow, you might need to put some extra effort towards getting buy-in from your company’s decision-makers.
Structured vs. semi-structured data
Documents with structured data are identical in terms of structure and appearance. Information is categorized, labeled, or positioned clearly. For example, the fields in a multiple choice test are going to be laid out exactly the same for every student taking the test. So a traditional template-based OCR solution can easily process documents with structured data, with minimal setup and maintenance requirements.
Invoices, on the other hand, are semi-structured documents, meaning they have the same basic structure but may have different layouts and content. They contain certain constants, such as date, vendor name, and total amount due; they also have a number of variables, including line items, discounts, or penalties. The location of each header field may also differ greatly from invoice to invoice. In this case, a template-based OCR solution can waste man-hours and cost, and increase the potential for errors. A smart OCR scanning platform, however, gets better at processing semi-structured documents with continued use.
Help grow your business with better invoice data capture
When considering which areas of your business could use an upgrade, take a good look at your company’s AP process. You might find opportunities to introduce efficiencies, boost productivity, and cut costs across departments simply through improved invoice processing. Of the technological solutions that can help you achieve this, Make sure you spend some time looking into specialized intelligent invoice data capture software. A smart OCR invoice scanning platform that automates accounts payable data entry could end up being vital to helping your company achieve its strategic objectives.
If you want to analyze your own use case, book a call with one of our automation experts here.