Improving Data Analytics to Shape Your Internal Audit Plan (article)
New regulations, changing political and business landscapes and advancing technologies keep risk in a constant state of evolution. Management, boards of directors and other stakeholders look to the internal audit function to identify, categorize, and provide insight into how these risks affect their organizations. Internal auditors today are expected to go further than simply ensuring effective internal controls, often becoming tasked with facilitating enterprise-wide risk management programs and identifying areas for cost reductions or operational improvements. Traditional risk assessments can collect intelligence around perceived risk, but many internal audit functions have found that incorporating a variety of new, diverse data sets into existing analytic models can provide new insights at minimal cost.
The Case for Improved Analytics
Organizations are constantly capturing and storing information to help provide them with a more complete picture of their products, clients, employees, or operations. Data analytics is the process of taking that stored information and analyzing it computationally to reveal patterns, trends, and associations. With advances in technology today, organizations are able to analyze the captured information more quickly so that they can act on cost savings, customer relations, and process improvement opportunities in real time. For example, a shipping company has historically collected information about package movements to provide intelligence about on-time arrivals, route efficiencies, and areas for cost savings. By implementing a more advanced analytics program around data collected from the shipping trucks and carriers themselves, the company could now monitor performance in real time and make adjustments to routes and schedules quickly to cut fuel costs and delivery times.
Reshaping Your Internal Audit Plan
An annual internal audit plan will assess, categorize, and control the risks facing your organization, but these risks are often identified through perceptions from management, sample testing, and benchmarking against similar organizations. Data analytics can supplement the internal audit plan by providing a more defined view of where critical risks exist based on known information. If a national restaurant chain can only afford to audit a handful of locations annually, it may use factors such as revenue, geographic location, or changes in management to select which locations make the most sense to include in its internal audit plan. If the internal audit function took the POS, inventory, order, and payroll data from each location and analyzed it to identify variances, abnormalities or new patterns, the restaurant chain could use this information to make an informed selection of the best locations to conduct its internal audit.
There are now many examples of internal audit functions incorporating data analytics into the planning process successfully, but your organization may still not be ready yet to hire data analysts, rewrite existing processes, or invest in new technologies. Identifying just one or two areas where more advanced analytics could be applied allows you to test a new process and showcase real value to management before making a long term commitment. Conduct conversations with management and the board of directors to understand their objectives for the organization and risk management. Focus your pilot program in on one of the areas in which these stakeholders have an invested interest and keep your initial investment small. Be prepared to share your results and demonstrate to management and the board any cost savings, risk mitigation, operational innovation, or process improvements that the initial data analytics program was able to achieve. Demonstrating a return on the initial investment can help you win over key stakeholders to work as data analytics ambassadors as internal audit seeks to expand their program over time.
Seizing the Opportunity
There is tremendous opportunity for the internal audit function to improve efficiency, narrow scope, mitigate risk, and reduce cost by better understanding and assessing the information organizations have already collected. The biggest reward that data analytics offers to internal auditors is the ability to use diverse, new data types to better test and control actual risk, not just perceived risk. The best data analytics programs are ones that the entire organization can be excited about so it is important to involve management, the board, and key stakeholders from the beginning. Considering the objectives and pain points that these individuals have and using their feedback to adjust your approach will help you gather buy-in along the way.
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