5 Ways Government Departments Can Save Money

by Ted London

There are significant opportunities for government and higher ed institutions to reduce their procurement and travel expenses using predictive analytics. Historically, building analytical models had been a challenge due to the complexities of analyzing data across the entire procure-to-pay cycle. Data are often disjoined across ERP, Procurement, Travel, and P-Card systems. Even when data is available it is often spread across multiple tables within complex databases. Also, once data is extracted, it is stored in different formats, and it can require significant manual manipulation.

However, new tools are in place that can now automatically consolidate this data, and analytics can provide valuable insights to reduce costs and risk to organizations. Through this risk modeling, waste, fraud and abuse can be found and corrected, before any financial outlays take place, saving millions of dollars per year. Here are five ways to save money every government department should know about.

1) Use Scores To Measure the Risk

As described in a recent article by Spend Matters, predictive models can help organizations reduce cost, while also identifying waste, fraud and abuse. Analytical models can score 100% of procure-to-pay transactions for risk in line, and in real-time. Models can identify anomalous transactions that put the organization at risk. This could include potential waste and fraud, or situations that risk data security issues or HIPAA violations, as just two examples. Automated risk scoring also reduces the effort to review and monitor purchases, by allowing staff to focus on transactions that truly need their attention.

2) Use Analytics to Reduce PO Leakage

Organizations spend considerable time and effort setting up master contracts for commodities purchased in bulk. These allow for deep discounts. While individual staff members may not buy in bulk, across the enterprise volumes exist to get significant price discounts. However, many of these discounts are missed, costing the organization millions in total. This is referred to as PO leakage.

PO leakage can be caused in a number of ways. Sometimes leakage occurs because of the perception that it is easier to just use a purchase card (P-Card). It can also occur because of cumbersome purchase processes that disincent staff members from using the master contract. Regardless, when leakage occurs the organization loses the discount and does not get credit for their full volume for future discounts. While purchasing and ERP systems can catch some leakage, most are not able to catch the bulk of leakage. One reason is that many of these transactions occur using a P-Card, which occurs outside of the full procurement process. When a P-Card is used, data on the actual commodity purchased may only be available in level 2 or 3 bank data. However, through analytics, leakage can be identified and reduced.

3) Redirect staff to higher value work

Almost every employee who has travelled for the Government or a University knows the significant time and effort required to prepare their voucher, assemble receipts, and face multiple reviews where small issues or insufficient documentation is questioned. Even when automated systems are available, considerable manual processes are created to review travel expense reports. Staff spends lots of time reviewing transactions, making the review process both expensive and inefficient.

When small transactions are questioned, staff spends significant effort updating their documentation. The reason for this level of scrutiny may be that guidelines are well documented, and the staff who review these purchases need to justify their positions. So they question items which might only be pennies over the limit or where a receipt is not itemized. The opportunity for organizations is redirecting these resources to transactions with a much higher overall risk. Even small dollar transactions, depending on their nature, could lead to millions in HIPAA violations, or put critical data at risk.

4) Prevent Social Engineering Fraud

Criminals are getting more creative and bold. In some instances they are working to change bank routing information for existing vendors, or trying to add themselves as a vendor and then send in completely false invoices for payment. They build relationships with AP staff, so their invoices and payments seem completely normal. To combat this, analytics and models can detect this type of fraud, stopping what could be hundreds of thousands (or millions) in payments before they occur.

This fraud can be identified in multiple ways. First, a risk model can detect a change in the bank routing instructions and mark it with a risk indicator. This will alert the organization to confirm the bank information with the vendor before making payment. In addition, Know Your Supplier (KYS) tools can verify that any bank information provided for payment is actually tied to that supplier. Through both of these methods, organizations can be confident that payments are valid, saving money and ensuring accuracy in payment.

5) Reduce Duplicate Invoice Payments

Most ERP systems are designed to prevent duplicate payment of a single invoice. The challenge is that the business rules within the ERP system do not cover all use cases, and some duplicate payments are still issued. The second invoice may have a slightly different invoice number or date. Worse still, many ERP systems have a single vendor under multiple vendor numbers, so the duplicate invoice could be tagged to a second instance of the same vendor. Duplicate payments can result in significant efforts to recover the funds, and can also result in significant losses if the duplicate payments are not discovered, or reported by the vendor.

Analytics can automatically review an invoice and determine its statistical similarity to all previous invoices within a specified time period. If the invoice has similarities even without exact matches to invoice number, name of the vendor, address of the vendor, or amount of the invoice, it can be scored for a review as a potential duplicate. This approach can save hundreds of thousands of dollars per year (or more) over traditional methods using standard ERP functionality.

Conclusion

As described above, most organizations can achieve significant savings through the use of analytics. A recent article says top procurement departments spend about 20% less than average departments. Through predictive analytics many savings are possible: