Spring 2010 issue of Horizons

11. Internal fraud resulting in free production services for friends and family 12. Errors and disputes with customers arising from: • Advertising, promotions and rebate claims • Pricing errors (internal pricing/transfer information) • Returned or refused merchandise • Lost or damaged goods • Concealed shortages • Transportation, freight or routing disputes • Acquisitions or system conversions The key to an effective revenue leakage management program is a thorough understanding of the nature of revenue leakage. Knowing where to look is only half of the puzzle. Analyzing key data within the processes is the other piece of the puzzle, which helps identify the hard-to-spot leaks. When gathering, extracting and evaluating data, ensure the data is accurate, relevant and complete. You may want to extract the following data when analyzing business processes for revenue leakage: ANALYZING THE DATA

Today, there are many tools that can help in the analysis of data, including in-house tools such as Excel or Access. On a broader basis, business intelligence tools, which often leverage data warehouse information, also may be an option for your entity. Lastly, data analysis tools such as IDEA and ACL have user-friendly interfaces that facilitate large volumes of data to be imported and analyzed for inconsistencies, trends and outliers in an efficient manner. 1. Credit Risk: Analyze open customer invoices and the accounts receivable sub-ledger for past-due balances and short-paid invoices. 2. Accounts Receivable: Profile unpaid invoice data by invoice date and due date. Age invoice data and report number of invoices outstanding with totals. 3. Sale Price: Profile sales transactions and identify unit price variances by product code. Interrogate transactions in which the price variance exceeds X percent and profile the results by product, vendor or office. Once the source of the leak is understood, a remediation approach can be developed to ensure the success of revenue leakage management. Remediation actions can take many forms and fit on a broad spectrum. At one end of the spectrum, corrective actions can appear very similar to the kinds of recommendations you would receive from an internal audit for correcting other financial controlling objectives. At the other end of the spectrum, corrective actions may take the form of proactive automated data interrogation, identifying anomalies in transaction data that may indicate errors and potential revenue loss. The following provides some examples of data analysis: FIXING THE LEAK

• Pricing • Invoice and invoice detail • Cash receipts • Cash application • Discounts and allowances • Profit margins

Once data elements are extracted, define an expected outcome. Once the expected outcome is set, you can measure your analysis outcome against that measure. Data analysis also will provide you with additional insights you can use to improve performance, trend key process activities, and refine alerts and triggers that allow you to identify issues before they become pervasive problems.

23 u spring 2010 issue