Three-way matching is when, before cutting a check, accounts payable compares the invoice, purchase order (PO) and receiving report associated with the order. This comparison serves as a buffer against error and overpayment, as it checks to ensure that the three most crucial points in the process run consistently, without alteration. For example, if the English department requested (purchase order) five reams of paper at $10/ream, the vendor charged them $50 (invoice), and the English department filed paperwork (receiving report) that their $60 worth of paper arrived, and your university does three-way matching, you know you have to have a serious conversation with someone in the English department.
While this makes the value of three-way matching clear, I know many universities process thousands, if not dozens of thousands, of invoices each month, so the idea of going through this process manually for each and every invoice sounds daunting and, perhaps, not cost-effective. This is a huge problem, because if you’re not saving more on the process than you would “just” overpaying a couple of invoices every now and then, matching is going to be a hard sell for your institution. I remember working with one university that handles roughly forty thousand invoices a month, and it was costing them upwards of $1.5 million fully burdened, monthly!
That’s why many universities are turning to three-way-match automation as means to add accuracy and reduce costs without significantly increasing the amount of time it takes to process an invoice — the latter being a major concern for many universities, who, without implementing measures to streamline, frequently come up against deadlines and late fees. A typically streamlined method would include leveraging advanced capture software to gather the three types of documents associated with an order, extract key data from each, and upload the information into a back-end system that's capable of completing the three-way match extremely quickly and making subsequent retrieval a snap. Alternatively, you could leverage your enterprise resource planning (ERP) or accounting system to extract the data, but the key facet is automating the data extraction and collation.
That same university I mentioned earlier, with the forty thousand invoices per month, moved toward automation, and they saw their cost per invoice drop by more than half, and average processing time go from five days to 24 hours, while increasing accuracy by reducing opportunities for human error.
Learn more about optimizing and automating your AP/AR workflows