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If you want to deepen the quality of insights you get from the routine data you collect in an audit, data analytics is often the key. But to maximize the value, users need to be able to interpret results, translate that information into business outcomes, and then communicate the findings to other people in ways they can use and understand.
Simply analyzing the data is not enough — organizations must also use it to make people’s jobs easier and help their teams operate more effectively. Data analytics in an audit might sound cold and austere at first, but when companies identify key use cases and put data analytics into practice correctly, they can enhance the human element of an organization. Essentially, a data-driven culture is people-focused at heart. It’s about using the benefits of big data to make small differences in your auditors’ jobs and free up your team to do what they do best.
Most auditors and analysts are busy people. The time it takes out of their days to crunch the numbers and investigate the data can be daunting. Three primary error types can occur on spreadsheets generated by human effort: mechanical (inputting, typing, copy/paste errors), logical (inappropriate or incorrect formulas and algorithms leading to flawed calculations) and omission (data simply unincorporated). Though the errors in isolation can appear small, they are not insignificant. For example, an annual audit of the state of Oregon’s financial statements and programs found $6.4 billion in unintentional accounting errors over the course of 2020.
A Harvard Business Review study noted that only 3% of organizations’ data meets basic data quality standards, and 47% of newly created data records have at least one critical error. This means that the number of bad data records can rapidly increase when a company creates millions of records every day.
However, when you use tools that incorporate the most advanced methods available, you can slash the time it takes to perform analytics while also enabling your organization to respond to emerging risks and get insights faster.
For example, a process that uses automated workflows to book, obtain approval and upload journal entries can pull in the appropriate information to reconcile accounts daily rather than waiting until the end of the month. Data automation aids in eliminating stressful and time-consuming month-, quarter-, and year-end accounting processes. Busy auditors can then spend more time on the complex processes that require their professional judgment and develop new service lines and projects to grow the business.
Furthermore, when you use automation in your digital workforce transformation, you can quickly and accurately interpret all the company’s data, which leads to stronger decision-making within the finance department and the board. Good communication and data sharing can also help auditors identify financial reporting issues faster before the end of the year, which helps your company stay aware of accounting missteps.
In a data-driven culture, you not only rely on data from within, but also combine it with datasets from other sources. For instance, satellite images of parking lots outside retail stores can gauge customer volume and inventory turnover, and product reviews can forecast sales or even potential recalls. These are nontraditional data points, but your company can still use them to gain timely insights that help your key people do their jobs more effectively.
Your data transformation helps you learn where you’re going and understand where you’ve been. It can help identify emerging risks so auditors can target responses effectively. Data transformation can also create predictive analysis and help you understand historical data to either create budgets or identify outliers in the current year that require additional investigation.
The key tool for this is visual data. When auditors visualize data, either through charts or complete dashboards, it helps communicate risks and results to clients so they can understand findings more effectively and realistically. By using client dashboards, auditors can understand your clients’ needs and identify high-risk areas to focus on right away instead of spending valuable time hunting down and analyzing the correct information.
Data visualization software complements Excel and other auditing applications and helps companies with risk assessment, substantive testing and client communication in turn. Connecting to the data is quick and easy, and you can update the process quarterly or annually.
When your culture is driven by data, audit teams can tap into the power of that data to analyze business processes, test internal controls and identify risks in real time. This is the kind of auditing that promotes high-quality financial reporting, gives investors trust and confidence in markets, and promotes satisfaction and well-being for your employees by saving them time and energy.
Beverley McCarthy is a CPA and program manager for strategic insights at MindBridge, where she brings a data-driven mindset to enhance how the company leverages AI.
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