Purchase Order vs. Invoice: A Deep Dive on Similarities and Differences
Get a comprehensive overview of a purchase order vs. invoice, including when businesses use each, what information goes in them, and more.
Invoice processing remains a time-consuming and expensive task for many businesses. According to Business Insider’s accounts payable process automation report, 36% of firms still use paper invoicing and 47% rely on manual processes for approval. Automation solutions for the payable process can bring tremendous business benefits.
In this article, you’ll find out about the problems faced by manual invoice processing and semi-automated processing that use traditional optical character recognition (OCR) and invoice templates. You’ll see how, by using fully automated invoice OCR tools instead, you get compelling business benefits and amazing productivity improvements.
Traditionally, invoices were processed manually by accounts payable (AP) teams. They reviewed invoices, checked for errors, verified details with other departments, entered data into an accounting system, and sent them for review by senior accountants or management. Many companies use this approach even now but it brings many long-term business challenges:
These challenges prevent manual invoice processing from scaling up your business beyond a few vendors.
Due to the challenges of manual invoice processing, most businesses have been using semi-automated data capture that combines traditional OCR software and invoice templates.
Given the wide variations in invoice layouts, businesses need some way to help software identify invoice text as appropriate invoice fields. Invoice templates help address this problem.
An invoice template consists of positional data and parsing rules that enable the invoice tool to identify unstructured text in an invoice as structured data as long as the invoice conforms to that template. Some invoice scanning software provides visual editors to create invoice templates easily.
But such capture solutions have two fundamental limitations:
The two critical limitations of templates and traditional OCR result in many more problems:
Fully automated invoice OCR tools that understand invoices the way people do — using machine learning and artificial intelligence — provide solutions to all these challenges. They combine state-of-the-art deep learning models for vision, text recognition, language understanding, and spatial understanding to provide highly intelligent and accurate invoice processing.
The biggest business benefit of Width.ai’s automated invoice OCR tool is drastically lower costs. Automated invoice processing doesn’t require much supervision to begin with and even that reduces as the tool automatically adapts to your invoices. Costs of other tasks like invoice matching are also reduced thanks to the high reliability of automated invoice OCR.
Per-invoice cost reduces by as much as 85% compared to manual processing and 70% compared to the template approach.
Invoice automation reduces the end-to-end time for processing one invoice to just three seconds compared to two hours for manual processing and 20 minutes for the template approach.
Reduced costs and time are not the only benefits. Let’s understand all the primary advantages and functions of Width.ai’s automated invoice OCR tool.
The tool does not require any invoice template whatsoever. Its deep learning models are already trained to understand thousands of real-world invoices of the most common invoice layouts out there. Additionally, it creates customer-specific pipelines adapted to your specific invoices and data requirements.
The invoice OCR tool supports a huge number of formats:
The invoice OCR tool supports end-to-end AP automation by sending the extracted invoice data to an ERP system like SAP FICO or to another accounting software, CRM, database, email, or some management workflow.
The accuracy of extracted data is very high. The results can be reliably used for other tasks like financial report generation and invoice matching.
Taking just three seconds to accurately process an invoice, the invoice OCR software can handle millions of invoices per day. If your organization has historical invoices (even typewritten or handwritten), we can create extra cloud resources to process them fast. Historical invoices enable your business intelligence teams to detect long-term business trends.
The tool comes with built-in support for over 50 common invoice fields. But it also lets you add the custom fields you want. Some of the custom fields we have seen include:
In addition to the common fields, it can identify important details like special payment terms using deep language models. For example, it uses natural language processing to identify a sentence with payment terms and file it against the payment field.
Width.ai’s enterprise-grade automated invoice processing software can be quickly integrated into your accounting practices in just six steps.
For a smooth transition to our invoice OCR tool, we start by understanding your existing invoicing workflows:
These details help us plan the deployment and infrastructure necessary for your workload.
With a deployment plan in place, configure the tool to fetch your invoices:
Although the tool can handle a wide variety of invoice layouts right out of the box, your organization may have invoices with unique layouts and custom fields. So, to boost accuracy and correctness, we fine-tune the tool’s deep learning models on your invoice and receipt samples to create a customer-specific invoicing pipeline just for your business.
The invoice OCR tool can export the extracted data to different formats, cloud storage services, local storage systems, third-party software, or workflows. You can configure it to select invoices using some conditions (like a date range) and export them to specified storage destinations. Or send invoices that go over some threshold amount to a management approval workflow.
Following configuration and fine-tuning, the tool’s ready for bulk invoice capture with little operator intervention.
Unlike traditional OCR which relies only on pixels and contours in images and suffers from lower accuracy, our fully automated invoice OCR tool identifies invoice data just like people do by combining visual, linguistic, and spatial characteristics. These details help accurately identify an element as a purchase order or an invoice number, and so on.
The outcomes of this step are the extracted fields and their values for each invoice. This data is exported to a structured format like JSON or XML or another software like ERP.
The tool measures precision, recall, and F1 scores to help you judge the effectiveness of your fine-tuning. It also generates confidence scores for each extraction to help you find problematic invoices and further fine-tune the tool on them.
The tool also lets you monitor its progress in real-time and alerts you to any processing problems over Slack, email, Jira, PagerDuty, or your CRM.
You’ve seen all the features and benefits of Width.ai’s invoice OCR tool powered by the latest deep learning technologies. At Width, we have years of experience developing data capture software for business processes in multiple industries. Contact us to see a demo of our touchless invoice processing.
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