Drivers of the Use and Facilitators and Obstacles of the Evolution of Big Data by the Audit Profession PDF

Preview

Summary

Accounting Horizons American Accounting Association Vol. 29, No. 2 DOI: 10/acch- 2015 pp. 439–Drivers of the Use and Facilitators andObstacles of the Evolution of Big Data by theAudit ProfessionMichael G. AllesSYNOPSIS:Big Data is one of the most important developments in management practice today, ...

Description

Accounting Horizons Vol. 29, No. 2 2015 pp. 439–449

American Accounting Association DOI: 10.2308/acch-51067

Drivers of the Use and Facilitators and Obstacles of the Evolution of Big Data by the Audit Profession Michael G. Alles SYNOPSIS: Big Data is one of the most important developments in management practice today, with McKinsey Global Institute (2011) arguing that it will fundamentally change business. Forbes (2013) states that ‘‘the market for Big Data will reach $16.1 billion in 2014, growing 6 times faster than the overall information technology (IT) market.’’ Given the growing significance of Big Data as a business tool, this paper considers the extent to which Big Data will be embraced by the audit profession and how that usage will evolve over time. I put forward the hypothesis that auditors cannot stray too far from the practices of their clients since their credibility with and respect of those clients are the basis of the value added that they provide. Hence, if Big Data becomes an essential business tool, then inevitably it will have the same impact on auditing, albeit, perhaps later and with a more muted reaction. Analysis also indicates that American and international auditing standards, technological advances, and market forces are some of the facilitators and obstacles that will determine the use of Big Data by auditors and that will shape how that usage will evolve over time. Keywords: auditing; Big Data; disruptive innovation; ERP.

INTRODUCTION

M

cKinsey Global Institute (2011) states that Big Data will fundamentally change not just business, but the world. McKinsey Global Institute (2011) cautions, however, that ‘‘companies and other organizations and policy makers need to address considerable challenges if they are to capture the full potential of Big Data.’’ Given both its promise and the challenges Big Data pose to businesses in general, this paper examines the drivers of the use of Big Data by the audit profession and the facilitators and obstacles for how that use will evolve in the near future. Drivers refer to the exogenous forces that will make the use of Big Data a historical inevitability and a strategic necessity, as opposed to an entirely Michael G. Alles is an Associate Professor at Rutgers, The State University of New Jersey, Newark. I thank Eric Cohen, Miklos A. Vasarhelyi, Brad M. Tuttle (associate editor), and an anonymous referee for their comments on an earlier draft of this paper.

Submitted: January 2015 Accepted: January 2015 Published Online: February 2015 Corresponding author: Michael G. Alles Email: [email protected]

439

Alles

440

endogenous choice by auditors based on their preferences alone. Facilitators and obstacles are the factors that determine how Big Data usage will evolve in audit practice, with auditing standards identified as the most significant facilitator and the lack of trained personnel as potentially the greatest obstacle. Given the growing attention paid by the business media and the investor community to Big Data, it is important to consider to what extent the audit profession will embrace Big Data and how its usage will evolve over time. I put forward a hypothesis in this paper for why the audit profession will feel compelled to use Big Data techniques. I then show that while existing audit standards facilitate Big Data usage, auditors still face many obstacles that they will have to overcome. Outside of auditing, Big Data is seen as a tool for businesses to uncover unforeseen correlations in data that can be exploited to increase profits by, for example, developing new marketing strategies. Auditing, however, is more constrained by standards and, in the case of external auditing, focused on the specific task of attesting to management assertions. The constraints of history and legal structure that impose on auditing have to be taken into consideration when analyzing the likely evolution of Big Data in auditing. It is noteworthy, however, that the assertion that existing audit standards do not constrain the use of Big Data is a two-edged sword, as auditors are currently not exercising the full discretion that those standards allow. This raises the pertinent question of why it should be considered likely that auditors will use Big Data when they fail to make full use of the non-Big Data that they already have ready access to: for example, continuing to rely on manual confirmations, using samples when full population data are available, and basing analytic procedures on aggregates rather than the analysis of disaggregated transactional data. That is why I begin by exploring factors outside of the standards in order to understand the evolution of Big Data usage by auditors. In particular, I examine what drives auditors to utilize technology in general, and how this knowledge might inform expectations about their use of Big Data. The next section of the paper examines the drivers of Big Data usage by auditors and develops a hypothesis that, as Big Data becomes an essential component of the business of their clients, auditors will face pressure to turn to Big Data themselves. The third section analyzes the role of standards as a facilitator of the evolution of Big Data usage by auditors. The fourth section considers the impact of other market forces and technological advances as either facilitators or obstacles to the evolution of Big Data in auditing. The final section concludes. DRIVERS OF BIG DATA USAGE BY AUDITORS As far as initial usage of Big Data by auditors is concerned, there are at least two scenarios. First, one can envisage auditors embracing Big Data as fully as their clients precisely because auditors need to keep up to date technologically with their clients, and because they see themselves obtaining the same benefits from Big Data usage that their clients do. The second, less optimistic scenario is based on the historical evidence, which suggests that auditors have lagged in their adoption of technology and, hence, that the same outcome will prevail with regard to Big Data. In support of the first scenario, Littley (2012) states that Big Data has the potential to lead to better forecasts of estimates, going concern, fraud, and other such variables that are of concern to internal and external auditors: ‘‘the use of data analytic tools and techniques is helping to fundamentally transform and improve audit techniques.’’ Given the criticism that the audit profession has received over the last decade for their perceived failings ranging from Enron and WorldCom to the financial crisis (ICAEW 2010; ACCA 2011), it is conceivable that auditors may eagerly embrace Big Data as a way of increasing the effectiveness and credibility of their work products. Auditors may also potentially see Big Data as a way to reduce the costs of their audits and enhance profitability in the case of external auditors and cost effectiveness as far as internal auditors are concerned (Littley 2012). Accounting Horizons June 2015

Drivers of the Use and Facilitators and Obstacles of the Evolution of Big Data

441

The argument that auditors will readily adopt the technological advancements of their clients has been made many times before with respect to technological and analytic developments as applied to auditing (for example, Vasarhelyi and Halper [1991] in the case of continuous auditing) but often practice has failed to live up to expectations. Indeed, auditors persistently lag behind their clients in their adoption of earlier technological advances (Manson, McCartney, and Sherer 2007), such as client-server computing and the Internet, and so some may argue that auditors will also be slow in adapting audit practices to include Big Data techniques. The second scenario is given support in the recent AICPA (2012) white paper ‘‘Evolution of Auditing: From the Traditional Approach to the Future Audit’’ that states, ‘‘Auditing has made great strides in the past decade, but it has not seemingly kept pace with the real-time economy. Some auditing approaches and techniques that were valuable in the past now appear outdated.’’1 Alles, Kogan, and Vasarhelyi (2002) made the argument that the driver of continuous auditing is the demand for such a service rather than the supply of the technology, and the same may well be the case with Big Data. Consistent with Alles et al. (2002) continuous auditing has been progressively adopted largely because of the need for increased coverage of internal controls over the financial reporting process mandated by Section 404 of the Sarbanes-Oxley Act of 2002 (Alles, Kogan, and Vasarhelyi 2008). There is as yet no such obvious external driver on the horizon in the case of Big Data. And if the increased audit effectiveness promised by Big Data is not sufficient in itself to induce auditors to use Big Data techniques, the promise of lower costs may prove to be an even less convincing argument. Alles and Gray (2014) argue that auditors may find it difficult to compete for Big Data talent against competitors seeking to use Big Data for profit making rather than compliance.2 While the AICPA (2012) and others see sluggish and lagging progression in the adaptation of audit practice to technology there are, however, other perspectives. As a posting on the auditingauditors.com website states, ‘‘The increased reliance on computers and computer applications for business processes created the need for auditing to be done in a computerized environment. In fact, auditing is gradually becoming synonymous to IT auditing.’’3 One key factor that enabled and ultimately made inevitable IT-based auditing was the widespread adoption of Enterprise Resource Planning systems (ERPs) over the last two decades, accelerated by the response of businesses to the Y2K problem.4 ERPs have subsequently become widespread in all but the very smallest organizations. As Davenport (1998) stated at the beginning of the ERP revolution, ‘‘While the rise of the Internet has received most of the media attention in recent years, the business world’s embrace of enterprise systems may in fact be the most important development in the corporate use of information technology in the 1990s.’’ The relevance of this history to auditor adoption of Big Data is the explanation Davenport (1998) provides for why adoption of ERP systems had become so urgent a business priority: Of course, the long-term productivity and connectivity gains created by enterprise systems are often so compelling that not adopting one is out of the question. In the petrochemicals industry, for example, enterprise systems have improved the flow of information through the supply chain to such a degree that they have become a de facto operating standard. 1

2

3

4

Available at: http://www.aicpa.org/interestareas/frc/assuranceadvisoryservices/downloadabledocuments/whitepaper_ evolution-of-auditing.pdf As an anonymous referee pointed out, similar arguments were made in the 1970s and 1980s with regard to auditor adoption of computer technology. Available at: http://www.auditingauditors.com/auditing-through-the-computer-and-auditing-around-the-computerexplained/ Clearly there may well have been other factors that led to auditing through the computer, including audit failures from not doing so and pressure from regulators. I thank an anonymous referee for these suggestions, but it is beyond the scope of this paper to verify these historical conjectures.

Accounting Horizons June 2015

Alles

442

Because participants in the industry routinely share information electronically, it would today be hard for a company to survive in the business without an [enterprise system] . . . As the CEO of one large chemical firm says, ‘‘Competitive advantage in this industry might just come from doing the best and cheapest job at implementing SAPt.’’ In other words, competitive forces made ERPs a necessity for businesses and once ERPs became ubiquitous they ‘‘created the need for auditing to be done in a computerized environment’’ (see http://www.auditingauditors.com/auditing-through-the-computer-and-auditing-around-thecomputer-explained). It is this dynamic that I hypothesize as developing in relation to auditor adoption of Big Data. McAfee and Brynjolfsson (2012) make an argument similar to that of Davenport (1998) for why competitive pressures will necessitate the use of Big Data by business: Data-driven decisions tend to be better decisions. Leaders will either embrace this fact or be replaced by others who do. In sector after sector, companies that figure out how to combine domain expertise with data science will pull away from their rivals. I can’t say that all the winners will be harnessing Big Data to transform decision making. But the data tell us that’s the surest bet. Setty and Bakhshi (2013) make the same point: One key differentiator for enterprises is the ability to quickly yield and act promptly upon key insights gained from seemingly disparate sources of data. Companies that are able to maximize the value from all of their data (e.g., transactions, interactions, observations) and external sources of data put themselves in a position to drive more business, enhance productivity, or discover new and lucrative business opportunities. Returning to the historical experience with ERP systems: the dynamic with ERP was that as those integrated IT systems increasingly determined how businesses were run and records kept, auditors had no choice but to start auditing through those systems themselves. Unlike with PCs and other distributed IT systems, the very ubiquity of the ERP system in all aspects of the business simply made auditing around the computer infeasible. Moreover, it is the data gathering and monitoring capabilities of ERP systems that make auditing through the computer practical. Managers implemented ERP systems for their own purposes, and then auditors were able to ‘‘piggyback’’ onto that investment already in place. Eventually regulators forced auditors to fully embrace IT-based auditing. This paper posits that the most likely driver of the use of Big Data by auditors is client use of Big Data—that auditors will feel that they have no choice but to embrace Big Data if and when Big Data becomes as important to the operation of the businesses of their clients in the next decade as ERP systems proved to be in the one before. In other words, the imperative to keep up with their clients’ reliance on Big Data is the exogenous driver that will force auditors to also adopt Big Data. Consistent with Alles et al. (2002), this is a demand rather than supply side argument for why auditors will end up using Big Data—not because they necessarily value the analytical power of Big Data, but because their clients do. In proposing this hypothesis, I recognize that the analogy between ERP systems and Big Data is not an exact one. Since ERP systems are the IT infrastructure of the firm, auditors are compelled to rely on it when data are obtained and controls verified. Moreover, ERP systems provide auditors with the capability to undertake continuous auditing (Alles et al. 2008). By contrast, Big Data is a tool for the analysis of largely nonfinancial data. Nonetheless, if Big Data truly becomes a strategic necessity for businesses, then it becomes equally essential for auditors to be doing the equivalent of ‘‘auditing through’’ Big Data. Accounting Horizons June 2015

Drivers of the Use and Facilitators and Obstacles of the Evolution of Big Data

443

ISACA (2013) states: Research conducted by Erik Brynjolfsson, an economist at the Sloan School of Management at the Massachusetts Institute of Technology (U.S.), shows that companies that use ‘‘data-directed decision making’’ enjoy a 5 to 6 percent boost in productivity. Proper use of Big Data goes beyond collecting and analyzing large quantities of data; it also requires understanding how and when to use the data in making crucial decisions. Competitive advantage can be greatly improved by leveraging the right data. ISACA (2013) draws the conclusion that what is important is not just that the business can claim to be using Big Data, but that the right data are being analyzed by the firm in the right way. Internal auditors may well come to see that ensuring that the ‘‘right data are being analyzed by the firm in the right way’’ is an important way in which they can add value to the firm. The link is less direct for external auditors, but it is there nonetheless to the extent that financial statements will increasingly reflect decisions made my management on the basis of Big Data analyses, and so their verification will necessitate the auditor evaluating or independently replicating that analysis. Indeed, as Alles and Vasarhelyi (2014) argue: As audit clients increasingly rely on Big Data analyses to drive their marketing, product development, and operational strategies—and thus their estimates and income statements—auditors will face the necessity of ensuring the validity and veracity of those Big Data results in much the same way today that they examine management estimates of accruals or sales forecasts. The need for developing audit procedures for doing so will only become more essential as the material impact on the performance of firms of the use by management of Big Data increases. The dynamic underlying this hypothesis is one that accountants have faced before. Three decades ago the development of activity based costing (ABC) systems by engineers dissatisfied with traditional costing systems resulted in a crisis for the management accounting profession (Kaplan and Johnson 1987). The factors that determined the success in overcoming resistance to change by management accountants was the clear evidence that their employers were losing out to Japanese competitors due to their faulty traditional costing systems, and the truly existential threat this consequently posed to the profession. While Big Data may not be an existential threat to the auditing profession, the fact is that end-use credibility is of even greater concern in auditing than it is with management accounting. Now, assuming the eventual use of Big Data by auditors, I turn to the facilitators of how that usage will evolve, with particular emphasis on the role of audit standards. AUDIT STANDARDS AS FACILITATORS OF BIG DATA USAGE BY AUDITORS Given that auditors will use Big Data—either because they themselves see value in its capabilities or because their clients do, thus forcing auditors to follow suit—what factors will shape the evolution of that usage of Big Data by auditors? Unlike the managers of their clients who can freely experiment with Big Data in order to mine profits, audit work practices are determined in a more constrained environment, being dictated by standards in the case of external auditors, and by resource constraints as far as internal auditors are concerned. The focus in this section is on whether existing audit standards permit the use of Big Data. While standards can be changed, the application of Big Data has a greater likelihood of rapid acceptance by practitioners if it is seen as a means of more effectively or efficiently satisfying existing standards, rather than depending on new or modified standards to allow the use of Big Data. Accounting Horizons June 2015

444

Alles

Existing audit standards do not seem to constrain auditors in their use of Big Data for either financial reporting or ICFR purposes. According to paragraph A9 of AU-C 500 on audit evidence, sources of such evidence include, ‘‘Information from sources independent of the entity that the auditor may use as audit evidence include confirmations from third parties, analysts’ reports, and comparable data about competitors (benchmarking data).’’5 Audit evidence, as defined by AU-C 500, is heading in the direction of Big Data in as much as it contemplates the use of nonfinancial data from outside the client. Similarly, AU-C 315 calls on auditors to obtain evidence from both inside and outside the client when ‘‘understanding the entity and its environment and assessing the risks of ma...