Most of the problems in procure-to-pay compliance arise because businesses are more focused on completing their review than on the quality of the review. This can result in inappropriate transactions slipping through, which has the potential to expose the company to risk, wrong audit findings, and reputational damage. It is becoming clear that traditional systems and staffing aren’t sufficient. Analytics is essential to help monitor procure-to-pay transactions because it is fast, unbiased, and can find hidden issues within the data.
In this blog, we present three ways how analytics solve problems in procure-to-pay process:
Analytics Provide Full Coverage
Most companies face similar procure-to-pay challenges; their transactions and complexity increase year-after-year, yet they are being asked to reduce risks and costs. This is not easy to do because the procurement team cannot carry on with increased transaction volumes and external difficulties. Organizations, on the other hand, are concerned about what auditors will identify.
Analytic systems can assess all of the transactions in-line and in real-time, tracking issues before payment occurs. Auditors usually sample transactions, but the risk with sampling is that not every purchase is reviewed, leaving organizations exposed.
Current Systems Utilize Business Rules, But Not Analytics
Most organizations expect their procurement, travel & expense programs will protect the reputation of the business and will operate efficiently and effectively. They define these rules to control risk and save costs where they can. The procurement team can view within their data for specific items where a business rule can be defined. However, they can’t use statistical analysis to enhance their management. That is where analytics come in to picture.
Analytics can identify unseen patterns, such as transactions that are outside of regular usage. The transaction may not set off any business rule, but analytics could identify it as something unusual of standard buying patterns. This could include purchases made off-hours, purchase quantities that exceed normal usage, and so on.
Analytics Can Aggregate Data from Different Systems
When it comes to procurement management systems, most organizations struggle with dissimilar data. Even when they have an ERP system that is intended to integrate data, they often have a separate expense or procurement system and have P-Card data that is not fully integrated. The company may have an imaging system, but that system likely doesn’t decode the text to images for analysis. With several systems that do not communicate with each other, it becomes difficult to get a holistic view of the operation and find complex issues.
Many organizations have used significant manual processes to review and audit their procurement data. With increasing transactions, they don’t have enough resources to manage and go through everything they need to review, so human error is inevitable. Due to staffing and system constraints, they depend on sample audits as opposed to a broad review; it means many transactions get no review. The trouble here is that sometimes, the highest risk transactions are low cost and are easily skipped over, even though many low transactions can carry significant risk.
Finding Insights through Analytics in the Procurement
Data analytics can help reduce the risks in transactions, pulling all of the data and information together to form insights. Analytics can find many things that are unlikely to be caught through traditional reviews such as duplicate payments that are initiated through multiple systems, sensitive items purchased through P-Cards, POs issued after Invoices are received, and much more.
Without advanced analytics, data is just data. It is a massive pile of information that is difficult to sort through and gain insight from. Once analytics is implemented, you can find unseen patterns, trends, and risks in an automated fashion. Analytics can also work in-line and in real-time to spot issues before they occur.
An automated, rules-driven procure-to-pay system that utilizes analytics in this fashion can help your business significantly reduce risk, avoid fraud losses, and manage your reputation more effectively than your traditional systems alone.