There have been numerous articles throughout the year about government organizations and universities lacking the staff and tools to review 100% of their transactions. Most of the issues with procure-to-pay compliance arise because many staff reviewing transactions are more focused on completing their review than on the quality of the review. This can result in improper transactions slipping through, which has the potential to expose the organization to risk, bad audit findings and reputational damage.
It is becoming clear that legacy systems and staffing simply aren’t sufficient. Analytics is critical to help monitor procure-to-pay transactions because it is fast, unbiased and can find hidden issues within the data.
This article from the State of West Virginia is a perfect example: "More than 17% of Purchase Card transactions lacked sufficient documentation". Not all of these transactions were improper, but the lack of documentation when spread across 126,000 annual P-Card transactions in West Virginia, shows the risk organizations face from fraud, waste and abuse.
Procure-to-pay: 3 Ways Analytics Solves Problems
(1) Analytics can provide 100% coverageMost organizations face the same procure-to-pay challenges; their transaction volumes and complexity increase year-after-year, yet they are being asked to reduce risks and costs. This is difficult to do because staff cannot keep up with increased transaction volumes and external complexities. Organizations, on the other hand, are worried about what auditors or external oversight will find.
Analytic systems can review all of the transactions in-line and in real-time, catching issues before payment occurs. Auditors typically sample transactions, but the risk with sampling is that not every transaction is reviewed, leaving organizations exposed.
(2) Existing systems utilize business rules, but not analytics.Organizations expect their procurement, travel and expense programs will protect the reputation of the organization and will operate efficiently and effectively. They write these rules to manage risk and save costs where they can. They can look within their data for specific items where a business rule can be written. However, they cannot use statistical analysis to enhance their management. That is where analytics comes in.
Analytics can identify hidden patterns, such as transactions that are outside of normal usage. The transaction may not trigger any business rule, but analytics could identify it as something atypical of normal buying patterns. This could include purchases made off hours, purchase quantities that exceed normal usage, and so on.
(3) Analytics can aggregate data from disparate systems.When it comes to procure-to-pay systems, most organizations struggle with disparate data. Even when they have an ERP system which is meant to integrate data, they often have a separate expense or procurement system and have P-Card data which is not fully integrated. The organization may have an imaging system, but that system likely doesn’t translate the text to images for analysis. With multiple systems that do not communicate with one another, it becomes difficult to get a holistic view of the operation and identify complex and often subtle issues.
A lot of organizations have instituted significant manual processes to review and audit their data. With growing transaction volumes, they don’t have enough staff to manage and sort through everything they need to review, so human error is inevitable. Due to staffing and tool constraints, organizations rely on sample audits as opposed to a comprehensive review, which by definition means that many transactions get no review. The problem here is that sometimes, the highest risk transactions are low cost and are easily skipped over, even though many low dollar transactions can carry significant risk (e.g., data security, HIPAA, PII).
Procure-to-pay Results: Finding Insights Through AnalyticsData analytics can help connect the dots, pulling all of the data and information together to form insights. Analytics can identify many things that are unlikely to be caught through traditional reviews:
- Duplicate payments that are initiated through multiple systems
- Outlier analysis for statistically unusual purchases (quantities, timing, etc.)
- PO Leakage where items were purchased without using preferred contracts
- Split procurements, across different channels, employees and dates
- Sensitive items purchased through P-Cards
- Purchase Orders issued after Invoices are received
- Text on receipts, contracts, or invoices that identify problematic or carry risk
An automated, rules-driven system that utilizes analytics in this fashion can help your organization significantly reduce risk, avoid fraud losses and manage your institutional reputation more effectively than your legacy systems alone.