PO matching has evolved, driven by technological advancements such as OCR and RPA. Learn about the challenges of PO Matching and how AI will shape its future.
Purchase Order (PO) matching is a critical process in supply chain management that ensures accuracy and consistency between purchase orders, invoices, and receipts. Over time, PO matching has evolved significantly, driven by technological advancements and the need for streamlined procurement processes. In this blog, we will explore the concept of PO matching, its importance, and the solutions that exist today. Additionally, we will discuss the challenges associated with PO matching and why it remains a complex task.
Who Uses PO Matching and Why?
PO matching is utilized by various stakeholders involved in procurement and finance processes. This includes:
- Purchasing Departments: PO matching helps purchasing departments ensure that suppliers have delivered goods or services as per the agreed-upon terms. It enables them to validate invoices and process payments accurately.
- Accounts Payable (AP) Teams: AP teams leverage PO matching to reconcile invoices against POs and receipts. By verifying the accuracy of invoices, they can authorize payments and maintain financial control.
- Finance and Audit Teams: PO matching plays a crucial role in financial reporting, auditing, and compliance. These teams use PO matching to identify discrepancies, resolve issues, and maintain transparency in financial transactions.
The history of PO Matching
PO Matching is in the midst of a technological revolution. But to understand where we are headed, let’s take a look at where it started and where the technology is today.
The past: Manual PO Matching
In the past, PO matching was predominantly a manual and time-consuming process. It involved comparing paper-based purchase orders with corresponding invoices and receipts. This stare and compare method was prone to human errors, delays, and inefficiencies, often resulting in discrepancies and payment delays.
The present: Automated PO Matching Solutions
With the advent of technology, automated PO matching solutions have emerged. These solutions utilize software and algorithms to match POs, invoices, and receipts, significantly reducing manual effort and enhancing accuracy. Here are some popular PO matching solutions used today:
- Electronic Data Interchange (EDI): EDI allows electronic communication and exchange of business documents between trading partners. It enables automated PO matching by electronically transmitting POs, invoices, and receipts, ensuring real-time visibility and minimizing manual intervention. EDI shifts the onus from the AP staff to the vendor to find the PO associated with the invoice being matched.
- Optical Character Recognition (OCR) Technology: OCR technology converts scanned or digital documents into machine-readable text. It enables automated data extraction from invoices and receipts, facilitating seamless matching with POs. A new template is created each time a vendor is added. Often OCR focuses on the top few vendors that represent the majority of the business. This means that the long tail of assorted vendors is not supported.
- Robotic Process Automation (RPA): RPA technology, when layered with OCR, can use structured data from various sources, including OCR, purchase orders, invoices, and receipts, and validate it against predefined rules. This enables automated matching and identification of discrepancies between POs and other documents. When a rule is violated, human intervention is required and a technical resource will create a new rule to incorporate the new edge case.
Challenges with PO Matching solutions today
While automated PO matching solutions have significantly improved efficiency and accuracy, challenges persist.
In fact, 20% of all invoices need a human to either review or handle the exception. This inefficiency has a price. According to research, solving an easy exception takes about 15 extra minutes (some take several hours). If a company processes 500 000 invoices per year, and 20% needs exception handling, it amounts to 25,000 additional hours, equal to 12 employees working full-time on remedying mismatched invoices.
So what are the factors that lead to PO Matching being so time-consuming for AP teams? Let’s break these hurdles down:
- Data Quality and Variability: Variations in data formats, incomplete or inaccurate information, and discrepancies in document layouts can pose challenges for automated systems, requiring extensive data cleansing and normalization efforts.
- Exception Handling: Certain scenarios, such as partial deliveries, price variations, or specification changes, may require manual intervention and decision-making. Handling exceptions in an automated manner remains a challenge for existing solutions.
- Integration and Interoperability: Integrating PO matching systems with existing ERP (Enterprise Resource Planning) or accounting software can be complex, especially when dealing with multiple systems or legacy infrastructure.
- Supplier Onboarding and Collaboration: Ensuring that suppliers adhere to standardized processes and provide accurate data can be challenging. Supplier education, training, and collaboration are essential for successful PO matching.
These limitations to current automation systems for PO Matching leave finance and accounting teams somewhere between the time-consuming manual matching of the past and having to rely on a technical resource to train these digital systems each time there’s a change. These issues result in inefficient and inaccurate PO matching, leading to delayed payments, supplier disputes, and decreased productivity.
The future: PO Matching with AI has arrived
AI-powered PO Matching is the way of the future and is available today. Advanced algorithms and AI-powered systems can analyze and compare at the line item level including PO lines, invoice lines, and receipts, identifying any discrepancies or inconsistencies. This means AI can match one invoice to multiple POs or many invoices to a single PO. These intelligent systems improve the accuracy, speed, and overall efficiency of PO matching. The process can truly be automated when using a unified AI platform for all PO and non-PO-derived invoices. Finance teams don’t have to worry about unstructured data, onboarding new vendors, exception handling, or having to integrate multiple vendors into their ERP system. It also means they don’t have to wait on a technical resource for help. Rather, they can directly interact with the technology and save time. They can then use that time to focus on higher-value tasks that move your business forward.
What to learn more about the future of PO Matching? Learn how Vic.ai’s Autonomous PO Matching takes companies even closer to truly autonomous accounting.