Whether one is auditing a rapidly transforming organization, executing audits of emerging technologies, mentoring new auditors or guiding experienced auditors, an element shaping the 21st century business environment is an increased emphasis on data analytics. The convergence of several global aspects has made it possible to work with and scrutinize large sets of data.
The South African chairman of the International Integrated Reporting Council wrote:
The megatrends the world is facing, including climate change, the fourth industrial revolution, globalization and artificial intelligence, demand a modern audit profession capable of attracting the skilled professionals to provide the assurances services needed by 21st century businesses. The risks and opportunities facing the global economy 20 years from today will require a profession that is flexible, agile and responsive to remain relevant and avoid the risk of extinction.1
Additionally, accounting and finance leaders in public practice, industry and government have witnessed the benefits of bringing data analytics to areas such as compliance and risk management, internal and external auditing, financial statement preparation, and fraud identification.
There are several environmental factors contributing to the more widespread adoption of data analytics in business, accounting and auditing. It is important to identify competencies needed by auditors to ready themselves for work with data analytics tools and techniques.
The Data Analytics Explosion
What has created the business case for data analytics? There are three reasons why data analytics has garnered increased attention and use:2 First, tools used in analytics are more powerful and sophisticated. Second, the unstructured and structured data used in data analytics have grown in volume. Finally, businesspeople have become more focused on basing decisions on quantifiable data. It has been observed that in a “data-driven decision making culture, there is opportunity for accountants to move beyond optimizing the accounting function to transforming the enterprise.”3
More Powerful and Sophisticated Data Analytics Tools
A survey of more than 740 business executives around the world conducted in October and November 2017 found that three aspects of data analytics technology have led to its more widespread use: data visualization, social media analytics and statistical analysis.4 Data analytics’ use in the continuous monitoring of business transactions has become common in large organizations. Particularly in the areas of risk management and compliance, data analytics techniques such as real-time examination of all transactions can speed up discovery of fraudulent or inappropriate activity by comparing each transaction to typical patterns of data behavior. This alters the perspective of auditors who previously relied on a manual examination of statistical samples of transactions—now they use technology to examine every transaction as it happens.
Growth in Data Volume
The term "big data" refers to data characterized by their tremendous volume, velocity and variety (called the three Vs). These three characteristics have not changed in the years since big data and data analytics rose in prominence, but the extent to which such data are available has. There are more data coming at business users faster and in formats and from sources that were not considered mainstream even several years ago. Managing ever-expanding volumes of information is a strategic problem identified by 300 C-suite executives from 16 countries interviewed in 2015.5 One of the panelists on a March 2018 webcast shared comments from C-suite executives, saying, “All of a sudden, data that was buried in a grave somewhere is coming to life. We have to make sense of it and use it as an asset.”6
Data-Driven Perspective
Changing habits of the mind can be difficult and demand a shift in how the corporate culture values decision-making driven by data. In business environments characterized by emergent situations, complexity, randomness and experimentation, an analytic mind-set is required to make the most of the data to which employees have access.7 Challenging managers and employees alike is the increased use of predictive analytics and its capacity to alter how organizations undertake forecasting tasks that range from creating annual budgets to determining strategic merger and acquisition activity.
A partner at PricewaterhouseCoopers, Singapore, comments that data analytics has the capability to transform auditing from a profession working with data from the past to one that adds value and helps enterprises anticipate the future. Although his comments specifically focus on the internal audit function, they can be extended to audit and accounting practitioners generally. He suggests that:
...those that can adjust in more real-time and establish an end to end data driven Internal Audit model, will elevate their relevancy and allow them to move from simply auditing around historic risks to monitoring and pivoting based upon prospective risks.8
How do auditors and accountants move to this data-focused approach? Many of these skills can be gained through self study, while others, such as identifying key data trends, can be gained through work experience. Accounting professionals can participate in data analytics-related webinars provided by public accounting firms or IT consultancies. For more casual learning approaches, there are online videos prepared and uploaded by individuals or organizations.
Data-Analytics-Related Competencies for Auditors
Effective work with data analytics demands that auditors have a broad range of competencies that cut across liberal arts, business, information technology and communication fields. These competencies vary in importance and frequency of use depending on employment setting, position and career stage. Figure 1 presents a list of competencies for success in working with data analytics.
How Organizations Are Leveraging Data Analytics
The treasurer of a global heavy industrial manufacturer observes that her:
...Accounting department is much more efficient and proactive in management decisions with the increased help of data analytics. By saving time completing tasks, [data analytics] allows more human brain time for process improvement decisions for the business.9
Her staff uses Microsoft Excel for analytics tasks.
The director of internal audit of a US national fast-food restaurant chain notes that all aspects of internal auditing are touched by data analytics. She explains that data analytics are incorporated into every stage of financial, operational and compliance audits.
We use it in planning to know where to look for deeper analysis, like the sales compensation audit. We ran it during planning and identified some outliers where there were an abnormal number of salespeople on smaller contracts or fewer salespeople on larger contracts. During the actual testing and execution phase we use it to run for compliance testing—SOX for example and for testing any big swings in balances outside of normal, testing all journal entry transactions to see if any did not have proper approval, etc. And then we also use [it] at the end of an audit for continuous monitoring to watch real time if something is an anomaly.10
She says analytics tools employed in her workplace depend on the type of tasks, but ACL, Tableau and Excel are the most commonly used applications.
A typical accounting or IT graduate likely will not come to an entry-level auditing position fully versed in data analytics methods and tools. New entrants to the profession need mentoring, self-study programs and experience on the job to understand how the technology is applied in the workplace. At the same time, these less-proficient auditors must work on enhancing their business acumen and exercising creative and critical-thinking abilities as they try to interpret and work with the results of analyses.
For more seasoned audit professionals, their extensive understanding of the organization’s internal controls and business processes enhances their ability to choose data for analysis and interpret risk inherent in the results. For example, in internal audit, the staff uses data analytics for audit planning to know where to look for deeper analysis such as for the sales compensation audit. Internal auditors run analytics during planning and identify outliers where there are an abnormal number of salespeople on smaller contracts or fewer salespeople on larger contracts. This internal audit department also runs analytics during the actual testing and execution phase for US Sarbanes-Oxley Act 2002 (SOX) compliance testing. At the conclusion of an audit, analytics allow for continuous monitoring to watch in real time if something is an anomaly.
No matter the auditor’s career stage, a tale relayed by one organization offers cautionary advice. With the increased capabilities of artificial intelligence, robotics and other data-analytics-related software, the advisory role of certified public accountants (CPAs) may decline. Therefore, “accountants or financial specialists who want to maintain a competitive advantage over other professionals need to get involved in the rise of big data.”11
The Next Generation of Auditors: Data Analytics Ready
Workplace expectations for data analytics’ readiness continue to rise. Some employers may have training available for their current staff and new hires. But for those that do not, new entrants to the auditing and accounting workforce and experienced professionals alike should consider self-study of these subjects outside of work hours. Data analytics competencies—and their related hard and soft skills—can no longer be viewed as optional. They are necessary for audit, accounting and business professionals at all stages of their careers.
Author’s Note
The author wishes to gratefully acknowledge feedback given on drafts of this article from her faculty colleagues Bev Hogue, Michael Morgan, Harrison Potter and Bob Van Camp.
Endnotes
1 King, M.; “Where Is the Audit Profession Going?” Accounting Today, 18 July 2018, https://www.accountingtoday.com/opinion/where-is-the-audit-profession-going
2 Pan, G.; S. Sun; C. Chan; L. Yeong; “From Data Analysis to Intelligent Accounting: Impact of Analytics on Accounting Function,” Analytics and Cybersecurity: The Shape of Things to Come, Singapore, 2015
3 Ibid.
4 EY, Global Forensic Data Analytics Survey 2018, www.ey.com/Publication/vwLUAssets/ey-how-can-you-disrupt-risk-in-an-era-of-digital-transformation/$FILE/ey-how-can-you-disrupt-risk-in-an-era-of-digital-transformation.pdf
5 Chartered Institute of Management Accountants, Joining the Dots: Decision Making for a New Era, 2016, https://www.cgma.org/resources/reports/joining-the-dots.html
6 Deloitte, “Digitizing the Core: Transforming the Business Behind the Business,” Dbriefs Driving Enterprise Value Series Webinar, 21 March 2018, https://www2.deloitte.com/us/en/pages/dbriefs-webcasts/resources/dbriefs-program-guide.html?id=us:2em:3db:feremind:awa
7 Lyytinen, K.; V. Grover; “Management Misinformation Systems: A Time to Revisit?” Journal of the Association for Information Systems, 2017, vol. 18, no. 3
8 Ye, T.; “Internal Audit Analytics,” Analytics and Cybersecurity: The Shape of Things to Come, Singapore, 2015
9 Nelson, S.; email correspondence, 9 March 2018
10 Huff, M.; email correspondence, 6 June 2018
11 CPA Ireland; “Big Data—The Role of the Accountant,” UHY Global Trend Series: Issues Affecting Accountants, 2017
Grace Johnson, CPA
Is the lead instructor for the accounting and public accounting majors at Marietta College (Ohio, USA). She is responsible for courses in financial accounting, accounting information systems, accounting research, business ethics and international business. Johnson has taught in Brazil, China and South Korea. Her current research projects include studies of business ethics pedagogy, corporate financial reporting and internal control.