These are some labor burden test queries that auditors can make if they have the contractor s or vendor s labor burden breakdown:

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1 Applying Data Mining and Analytics to Efficiently Audit Vendors and Contractors By Paul Pettit, Protiviti Inc. Each year, companies spend billions of dollars to start up, operate and maintain their businesses using outside vendors and contractors. Of this spending, hundreds of millions are estimated to be paid out in erroneous or duplicative charges, or for services outside the original contract. To prevent such massive waste and seek out cost recoveries, auditors need to learn to apply many more data analytical techniques what we might call data mining for auditors. Effective data analysis does not require expensive software like ACL or IDEA with sophisticated functionality. The data analytics we are talking about here can literally be accomplished using Microsoft Excel along with basic search techniques like sorting, filtering, V-lookups, and H-lookups on a contractor s or vendor s detailed transactions within their job cost data. Auditors can perform detailed data analytics on nearly any contractor or vendor in any industry. The techniques are especially valuable for auditing high-risk contracts in which vendors and contractors bill based on cost plus fee, time and materials, or time and expense arrangements. In these types of contracts, there may be a limited fixed scope of work since they involve hiring a lot of people working on an hourly, weekly or monthly basis, plus costs for materials, equipment and expenses. Such contracts are common in the construction industry; but they are also used in companies that outsource their back office functions, law firms that employ contractors during large legal cases, and utilities and insurance firms after storms in emergency response crises. Data analytics are also valuable for companies using many contractors and IT professionals to implement a new ERP system. Three major areas are especially critical to audit when using data analytics: labor, equipment and expenses. Here is a discussion of how data analytics can be applied to each of these areas: APPLYING DATA ANALYTICS TO LABOR CHARGES A multitude of data analytics can be performed on labor charges to validate their accuracy. Ideally, you need to have on hand four data sets in electronic format (preferably as Microsoft Excel or Access files) from each vendor or contractor in order to attain the widest range of analysis, as follows: 1. The original contract including the list of personnel staffed along with their individual job classification, labor rate and burden. 2. All invoices showing what was billed to the company during the contract period. 3. The vendor s job cost data indicating their incurred costs for the project. 4. The payroll files indicating the names of each worker and the amount paid out to them, including fringes and benefits Protiviti Inc. All rights reserved. An Equal Opportunity Employer. Page 1

2 Armed with this data, you can perform a variety of comparative queries among the four sets of data to confirm the validity of every payment. For example, you can verify if the labor rates billed on the invoice match the contracted rates, if each employee s pay rate is properly reflected based on his or her job classification in the payroll files, if the payroll files show that income and unemployment taxes were correctly capped once they reached their legal limits, and if the vendor s project payroll coincides with its invoices. Comparative data analytics can reveal a plethora of errors. Often discovered are pay rates that do not match the original contract, incorrect pay rates for employees relative to their job classification, full pay and fringe benefits billed for independent contractors as if they were full-time employees, erroneous payments for employees beyond the day they resigned or were terminated, overpayments for employee taxes that exceeded their caps, and unreasonable labor charges such as employees who were paid for working 80, 100 or 120 hours in one week. Upon discovery of such errors, further investigation can determine if they resulted from innocent oversights, typographic mistakes or accidental duplicate billings. In the worst cases, data analytics can reveal egregious errors such as invoicing for ghost employees who were not on the job site or home office, or patterns of labor charges suggesting outright fraud. In one case, for instance, we applied data analytics using safety orientation data that revealed a supervisor was taking workers and materials from the job site to renovate his own home while charging their costs to our client. Another key labor data analysis allows you to verify if overtime (OT) is paid. Matching job classifications to the payroll files, for example, can reveal whether exempt employees incorrectly billed OT. Another valuable query is a comparison between working hours and overtime pay to confirm if OT was correctly paid according to your state s labor law. Some states require OT pay only after 40 hours per week while others require OT pay when a worker exceeds an 8-hour shift. This is especially important to get right if people are working non-standard work weeks such as 10-hour shifts four days per week. Many instances of incorrect OT pay result from lack of knowledge or attention to how your state labor laws apply to OT pay. One of the most valuable benefits of getting a vendor s or contractor s job cost data is seeing the breakdown of their labor burden. This refers to the percentage of pay that sits on top of each worker s base rate to cover benefits such as taxes, health insurance, pension, vacation and sick time pay, holidays, training, bonuses and other fringe costs embedded in the worker s fully-burdened hourly rate. Having the labor burden breakdown allows you to verify that the vendor or contractor has not doublebilled the company by charging for fringes, both as they are accrued in the worker s bill rate and as separate expenses to the project. Auditors can do similar queries to check duplicative payments for benefits like phones, computers, and car or truck leases when workers may already have an accrual for these in their labor burden. These are some labor burden test queries that auditors can make if they have the contractor s or vendor s labor burden breakdown: Tax accrual / percentage Insurance accrual / percentage Medical / Dental accrual / percentage Pension / 401K accrual / percentage Vacation accrual / percentage Sick day accrual / percentage Holiday accrual / percentage Training accrual / percentage Vehicle accrual / percentage 2013 Protiviti Inc. All rights reserved. An Equal Opportunity Employer. Page 2

3 Phone accrual / percentage Other accruals (bonus, safety, etc.) APPLYING DATA ANALYTICS TO EQUIPMENT Equipment is another major area where auditors can benefit from running extensive data analytics. To validate these charges, you need to have an electronic list of: All equipment used Each equipment identification number Whether the equipment was purchased or rented How it was charged to the company (hourly, daily, weekly or monthly) and at what rate If there was an operator associated with it How long the equipment was used Whether it was located onsite or offsite Whether the equipment consumed fuel and how much of it Armed with this information, auditors can perform insightful comparative queries to verify a wide range of equipment charges. At the simplest level, data analytics can confirm if the equipment was billed at the correct contract rate and if all equipment billed was actually used on the job site for the amount of time billed by the contractor. Other detailed queries can reveal serious billing anomalies, such as if purchased equipment was simultaneously being rented back to the company, or if equipment that was used for only a short time at the start of a project continued to be billed beyond its actual in-use time. Another common error data analytics can reveal is inflated fees for equipment leasing. This can become evident when equipment is rented on a monthly basis, but the vendor or contractor charges the company for its use on an hourly basis, sometimes for as much as 24 hours per day, thereby substantially increasing its actual monthly cost. Comparing equipment usage to labor time and rates is also useful. For instance, auditors can compare equipment usage with operator labor hours to see if they match. It is not uncommon, for example, to find a crane operator who is paid for an 8-hour shift while the equipment itself is billed out for 12 hours, or vice versa. Similarly, checking fuel costs against equipment usage can confirm the accuracy and veracity of both charges as well as double check if any equipment that sat idle was being billed as if it were in use. With the right data, auditors also can verify that the company was not charged for repairs to equipment that were already included in rental fees, for damages to equipment caused by the vendor s personnel, or for interest fees on equipment that the vendor has purchased for its own use. APPLYING DATA ANALYTICS TO EXPENSES As with labor and equipment charges, auditors can ferret out many types of billing errors on expenses. For instance, you can run queries against job cost data to look for accruals, charge backs, adjustments and inter-company transfers that were passed or not passed through to the company. Another major area of investigation is vendor bonuses charged back to the company. You can check these against the labor burden to see if the bonuses have already been accruing in employee bill rates. You can also validate bonuses against payroll to confirm that the bonuses were actually paid out to employees and not just kept by the vendor. There may be incentives charged to the company that were not earned. Other expenses to verify include certifications and licenses, repairs and insurance claims all of which are likely to be expenses for which the vendor is responsible Protiviti Inc. All rights reserved. An Equal Opportunity Employer. Page 3

4 Finally, auditors can use data analytics to check for unusual items vendors often charge back to clients such as team-building outings and special events used as incentives, or illicit items like golf outings, personal trips, gifts for an employee s spouse or kids, computers for private use, and many other items that the vendor or contractor attempted to include in their expenses. In the grand scheme of a large project, these may amount to immaterial dollars, but they add up over time. If they were not contracted for, they should not be accepted as company expenses. CHALLENGES OF DAT A ANALYTICS The biggest challenge in learning to do comprehensive data analytics is arranging in advance to get all the raw data against which you can run comprehensive queries. Without the four data sets discussed here, auditors are limited in their ability to match up data to validate accuracy and root out errors and mistakes. This means that it is vital to work with vendors and contractors willing to provide their job costs, labor burdens, invoices and payroll data in electronic formats. Companies that frequently work with vendors and outside contractors should negotiate upfront to put auditing rights into their contracts to ensure that their auditors will receive the necessary information in electronic format when it is time to audit. Auditors should also be sure to get an agreement that the audit rights can go back at least two years (and possibly up to four years) from the final payment to the vendor. If the vendor hires subcontractors, the auditing rights must extend to reviewing their books as well, especially if they operate under cost-reimbursable agreements. In addition, it helps to maintain some leverage in the form of money owed or future work to use as recourse in case a vendor balks at providing electronic data in a timely manner. Auditors can help companies negotiate for these rights by informing vendors of the benefits and advantages of cooperating. First, their cooperation means that the auditing process will go more smoothly and minimize disruption at the vendor s office. Second, a comprehensive audit can help the vendor in identifying underpayments and thus money owed to them, not just overpayments. Performing comprehensive data analytics is not hard in and of itself once a company has all the raw data. Checking 10,000 lines of payroll data against labor rates and job classifications takes literally just a few minutes, yet such a simple query can reveal errors worth tens or hundreds of thousands of dollars. We once ran an audit on repair charges embedded in just $20 million out of a $100 million construction project and discovered more than $600,000 in repairs that the vendor had erroneously billed back to the company. Knowing how to perform data analytics offers important benefits for auditors. It helps you mine the job cost data more efficiently and comprehensively. With the right data, you can test 100 percent of the transactions instead of sampling a small number of them. With larger coverage of the vendor s spend, you are more likely to discover errors and incorrect charges, as well as identify opportunities for cost recoveries. Data analytics also assists auditors in identifying patterns that might indicate potential fraud (billings that require you to prove that the vendor or contractor knowingly billed incorrectly with the intent to defraud) as distinct from unintended mistakes and poor oversight. Finally, well performed data analytics can help auditors positively impact the bottom line for their company or their client, often saving as much as the cost of the entire audit, or in some instances, the budget for an entire audit department Protiviti Inc. All rights reserved. An Equal Opportunity Employer. Page 4

5 Paul Pettit, MBA, MS, CCA, PMP, CIA, CRMA, CPEA is a Director for Protiviti s Capital Projects & Contracts practice in Houston, TX. He has more than 20 years experience managing and auditing vendors and contractors, including 10 years working as an engineering and construction contractor. Article from Protiviti KnowledgeLeader KnowledgeLeader is a subscription-based website that provides audit programs, checklists, tools, resources and best practices to help internal auditors and risk management professionals save time, manage risk and add value. Free 30-day trials available. Protiviti ( is a global consulting firm that helps companies solve problems in finance, technology, operations, governance, risk and internal audit. Through our network of more than 70 offices in over 20 countries, we have served more than 35 percent of FORTUNE 1000 and Global 500 companies. We also work with smaller, growing companies, including those looking to go public, as well as with government agencies. Protiviti is a wholly owned subsidiary of Robert Half International Inc. (NYSE: RHI). Founded in 1948, Robert Half International is a member of the S&P 500 index. Protiviti is not licensed or registered as a public accounting firm and does not issue opinions on financial statements or offer attestation services Protiviti Inc. All rights reserved. An Equal Opportunity Employer. Page 5