New developments in information technology
A call for action
Introduction
Much has been claimed about the strategic promise of new information technologies over the years. Back in the 1980s, McFarlan (1984) argued that, “Information Technology Changes the Way You Compete”, while Porter and Millar (1985) provided guidance as to “How Information Gives You Competitive Advantage”. In the following decade, Business Process Re-engineering (BPR) was all the rage with, for example, Davenport and Short (1990) promoting “The New Industrial Engineering” and Hammer (1990) calling for the “obliteration” of existing business processes, rather than mere “automation”, in order to get order of magnitude improvements in business performance on the back of BPR and associated enterprise systems (e.g., Davenport, 2000; Kalling, 2003). More recently, similar hyperbole has been associated with so-called business intelligence systems with, for example, a Gartner press release in 2006 claiming that the “Business Intelligence Software Market [would] reach $3 Billion in 2009” (see Chee et al., 2009 for a review). More recently still, Big Data has taken centre stage (e.g., Chen et al., 2012; McAfee and Brynjolfsson, 2012).
Having said all this, there have been more critical stances taken. For example, Clemons (1986) questioned the sustainability of the competitive advantage to be gained from information technology, while others have critically reflected on business process re-engineering (e.g., Davenport, 1996; Galliers, 1997; Galliers and Swan, 1999; Land, 1996). Indeed, Galliers (2006) confronts “some of the common myths of IS strategy discourse” in his reflection on strategic alignment, competitive advantage and knowledge management, while Robey and Boudreau (1996) consider some of the contradictory consequences associated with information technology implementations. Additionally, focus has shifted from strategy to strategising (e.g., Galliers, 2004, 2011; Jarzabkowski and Spee, 2009; Whittington, 2006), with emphasis being placed on the actual practices and capabilities of organisational actors (e.g., Karpovsky and Galliers, 2015; Marabelli and Galliers, 2016; Peppard and Ward, 2004; Whittington et al., 2006), and the impacts of social media in this regard (Baptista et al., 2017; Huang et al., 2013).
In this chapter, we consider the major investments taking place in new information technologies such as Enterprise Resource Planning (ERP) systems and the more recent hyperbole surrounding Big Data. We also consider the implications of such investments, in terms of organisational capabilities (cf. Peppard and Ward, 2004), with particular reference to the accounting and finance professions. We commence with a reflection on Enterprise Resource Planning systems as a potential strategic asset and then consider Big Data in a similar light. Implications for accounting practice and for accounting and finance professionals are then considered.
Information as a strategic asset: Enterprise Resource Planning systems
ERP systems are typically the largest and most complex information systems implemented by organisations. Furthermore, ERP systems often represent one of the most significant capital investments that an organisation will make towards its information technology/systems infrastructure. Despite their complexity and cost, research has indicated that ERP systems have the potential to be used as a strategic asset and thereby enhance an organisation’s competitive advantage (see for example, Hunton et al., 2003; Poston and Grabski, 2001). Additionally, a growing body of research has also reported that ERP systems have the potential to transform the accounting profession and the role of the management accountant in particular from one of controller or scorekeeper to that of a strategic business advisor (see for example Burns and Vaivio, 2001; Byrne and Pierce, 2007; Grabski et al., 2011; Rom and Rhode, 2007; Sayed, 2006; Caglio, 2003; Scapens and Jazayeri, 2003). The strategic role that ERP systems have played within organisations has undoubtedly been instrumental in changing the role of the management accountant function, or what has been termed “hybridisation” in the literature.
Given their scale, it is therefore hardly surprising that ERP systems have dominated much academic and practitioner research activity for the last two decades. Reflecting this in a relatively recent literature review, Grabski et al. (2011) identified a significant body of research which has investigated three major ERP research areas: the critical success factors of ERP; the organisational impact of ERP; and the economic impact of ERP. From their review, Grabski et al. (2011) summarise what is known about ERP systems in the context of accounting. First, the literature has identified a number of critical success factors of ERP systems. Second, ERP systems have the capability to provide a competitive advantage; however, this is short-lived. Third, the success of ERP is dependent on the extent to which the system is aligned with an organisation’s culture (both internal and external to the organisation). Fourth, employees have an impact on ERP systems in sometimes unpredictable ways. Fifth, ERP systems evolve over time with extensions taking “the form of business intelligence (BI) applications, inter-organisational value-chain integration enhancements, or focus on security, auditability and reporting, among other functions” (Grabski et al., 2011, p. 64).
Whilst Grabski et al. (2011) acknowledge that more research is needed in the area of ERP systems, more recently there is evidence from both the practitioner and academic literatures that research efforts are shifting their focus from ERP systems to issues related to “Big Data”, given its potential for use as a strategic asset and the significant opportunities and challenges it poses to the accounting and finance professions, and more widely, for example, in terms of the societal and ethical issues involved (e.g., Galliers et al., 2015).
Information as a strategic asset: Big Data
Big Data refers to “datasets that are too large and complex to manipulate or interrogate with standard methods or tools” (Cao et al., 2015, p. 423). According to Warren et al., (2015), Big Data consists of both structured and unstructured data, with the latter including data derived from sources such as social media postings, email messages, customer loyalty cards, website traffic, WiFi sensors, electronic tags and video streams. Five characteristics of Big Data have been identified in the literature (e.g., McAfee and Brynjolfsson, 2012; Elragal, 2014; Zhang et al., 2015):
• Volume refers to the enormous volumes of data associated with Big Data;
• Velocity represents the speed of data creation;
• Variety refers to the variety of data sources;
• Veracity is concerned with the accuracy and credibility of the underlying data sources; and
• Value refers to the value associated with Big Data sources when aligned with organisational objectives.
The scale of Big Data applications and their importance as a source of competitive advantage has been reported in a number of studies. For example, in a recent survey conducted in China, France, Germany, India, South Africa, the United Kingdom and the United States of America (Accenture, 2014), 73% of the companies taking part indicated that they were already investing more than 20% of their total technology budget on Big Data analytics. In addition, some three quarters of the executives surveyed expected spending to increase on Big Data in the year following the study. Furthermore, it was reported that 80–90% of the companies taking part in the study indicated that Big Data is either their organisation’s top priority or in its top three priorities.
Although research on Big Data is still at an early stage, numerous examples already exist where organisations have embraced the opportunities afforded by this relatively new technology. For example, Schneider (2013) provides examples of organisations in the financial services industry (Morgan Stanley), the automotive industry (Ford), supply chain, logistics and industrial engineering (Union Pacific Railroad), retail (Walmart, Sears and Kmart, Amazon) and entertainment (Time Warner, Cablevision) sectors who are using Big Data to gain competitive advantage. More recently, Bloom (2015) provides examples of companies who are “moving beyond the hype” and are reaping the benefits of their investment in Big Data. Examples include Southwest and Delta who are using Big Data to understand customer behaviours and enable customers to better track their luggage. Other success stories exist in the media sector where the Huffington Post and FT.com have reportedly successfully used Big Data to improve the user experience and to increase the relevance of their communications respectively.
As illustrated above, examples are beginning to emerge in the popular media and the professional press regarding the strategic benefits of Big Data. However, research regarding the implications of Big Data for accounting practice and the role of accounting and finance professionals in particular is still at an early stage. For example, Suddaby et al. (2015) is one of the few papers to explore Big Data and social media but, as is often the case, tend to treat the technology as a “black box”. In the next section of this chapter, the academic and practitioner research that has investigated the role of Big Data and its impact on accounting will be summarised.
Implications of Big Data for accounting practice
Given the increasing importance and use of Big Data within organisations, a number of academic articles and professional reports have addressed its implications for various aspects of accounting practice. For example, in a recent commentary for a special issue dedicated to the importance of Big Data for accounting and auditing, Griffin and Wright (2015) argue that it represents a significant challenge to the accounting profession. They further suggest that Big Data “by its very nature … cannot avoid running head-on into the traditional systems of accounting and auditing that have served our profession so well in the past” (p. 377). Supporting this view, Vasarhelyi et al. (2015) suggest that, “although changes in accounting practices and standards in response to Big Data have yet to happen, Big Data has the potential to cause a paradigm shift allowing economic transactions to be traced and measured earlier and deeper” (p. 384).
Reflecting its potential impact on accounting practice, a number of studies have considered the implications of Big Data on the audit function in particular. For example, Cao et al. (2015) identified a number of challenges facing the auditing profession as a result of Big Data. They include the need for auditors to make a paradigm shift away from a focus on the use of “small clean databases … [to] large relatively messy datasets” (p. 427) and the computational challenges of using Big Data. Cao et al. (2015) also identified a number of other issues, which auditors will have to address in a Big Data context. These include the need for auditors to develop expertise in data analytics and the difficulties associated with access to suitable hardware and software to conduct data analytics. In another study, Yoon et al. (2015) argue that Big Data has the potential to enrich the audit function in terms of complementing traditional data and enhancing the reliability and relevance of audit evidence. However, that said, the authors also identify a number of critical challenges which potentially face the audit function. These include issues around the integration of Big Data with traditional audit evidence, the need for auditors to consider how Big Data might be weighted when compared to traditional data sources, and difficulties associated with Big Data privacy issues. In yet another study conducted by Brown-Liburd et al. (2015), the behavioural implications of Big Data on the auditing profession are identified. These include the potential for information overload to occur when dealing with Big Data, the difficulties associated with identifying relevant, as opposed to irrelevant, information and the potential for the characteristics of Big Data to create ambiguity for the auditor. In addition, Brown-Liburd et al. (2015) argue that, historically, auditors have not been particularly skilful in terms of identifying patterns in financial and non-financial data (see for example Asare et al., 2000; Bedard and Biggs, 1991). This deficiency in skills has obvious implications for the analyses of Big Data.
While earlier studies have generally adopted the perspective that the auditing function will embrace Big Data, Alles (2015) suggests two alternative scenarios in this regard. First, in line with their clients, auditors will fully embrace the Big Data revolution. Alternatively, based on historical evidence, auditors will lag in their analysis of Big Data. Drawing on the analogy of ERP systems and the subsequent need for computerised auditing which accompanied them, Alles (2015) goes on to posit that the most likely driver for use of Big Data within the auditing function will be that of client use where auditors will have no choice but to incorporate the analysis of Big Data into their practices. Alles (2015) concludes by stating that “the lesson of history is the seeming slowness of the profession [auditing] in adapting to previous technological changes … [and that] auditor use of Big Data will likely not happen unless the failure to adopt Big Data is perceived by the audit profession as a serious threat” (p. 447). Interestingly, Alles’s (2015) perspective on the future of Big Data in auditing is in contrast to that of the Federation of European Accountants1 who recently issued a discussion document on the future of audit and assurance, which suggested that the impact of Big Data technologies is likely to be “revolutionary for the audit profession” (FEE, February 2014, p. 8).
In addition to the research summarised above, some limited research has also considered how Big Data is likely to influence management accounting practices. For example, Warren et al. (2015) suggest that Big Data can play a significant role in the operation of management control systems (MCS) (Chenhall, 2003) and budgeting processes. With respect to the former, Warren et al. (2015) suggest that the analysis of Big Data has the potential to assist organisations identify which performance measures should be incorporated into MCSs and how these will motivate employees to behave in a manner which is consistent with the achievement of an organisation’s strategic objectives. However, Warren et al. (2015) argue that management accountants will only be able to use Big Data effectively where they are supported by those with the expertise to understand, mine, transform and analyse Big Data.
Implications of Big Data on the role of the accounting and finance professions
While the extant academic literature has tended to focus on the implications of Big Data for specific accounting functions (e.g., auditing, managerial accounting), more recently a number of professional reports have investigated how Big Data is likely to shape the future of the accounting and finance professions. In particular, the Association of Certified Accountants (ACCA) and the Institute of Management Accountants (IMA) appear to be taking a lead in this regard. For example, a relatively recent ACCA and IMA (2013a) report investigated the ten top technology trends, which have the potential to fundamentally alter the accounting and finance professions. Drawing on data collected from interviews, email consultations, a series of events and a survey of over 2,100 ACCA and IMA members worldwide, the report identified Big Data as the second most important technology (rated after mobile technologies and ahead of other technologies such as cloud computing, artificial intelligence, robotics and digital service delivery). According to the ACCA and IMA (2013a) report, “accountants and finance professionals have a significant role to play in the increasingly connected and interconnected ecosystem that will emerge as the 10 technologies [e.g., mobile, Big Data, artificial intelligence and robotics, cybersecurity] … come together to create the ‘new normal’” (p. 12)2. In another ground-breaking report, ACCA and IMA (2013b) argue that the role of accounting and finance professionals will change as businesses are transformed by the Big Data “revolution”. According to the authors, accounting and finance professionals can respond to Big Data in one of two ways: they can “do nothing and watch as advances in technology commoditise their skills and downgrade their role” (p. 25). Alternatively, they can “adapt to the new environment and increase their influence and the value they add to organisations” (p. 25). However, to do this, accounting and finance professionals will need to reinvent themselves.
The authors of the ACCA and IMA (2013b) report also argue that the increasing use of Big Data within organisations presents both opportunities and challenges for accounting and finance professionals over the next five to ten years. In terms of the former, it is argued that Big Data presents an opportunity for finance professionals to “move ‘upstream’, shifting to a more strategic decision-making role within businesses” (p. 5). With respect to the challenges, Big Data will also present new problems for accounting and finance professionals over the next decade. For example, new standards for measuring and valuing Big Data will need to be developed, and issues around ethics and privacy of data in the context of Big Data will need to be addressed. Such concerns are echoed in the information systems literature. For example, Newell and Marabelli (2015) raised a number of major concerns regarding society’s increasing reliance on what they term “algorithmic decision-making”. As a result, “they made an urgent call for action for research by IS scholars that would critically assess society’s apparent taken-for-granted and unknowing acquiescence to this increasingly prevalent phenomenon” (Galliers et al., 2015, p. I).
Taken together, the opportunities and challenges identified by ACCA and IMA (2013b) suggest a new professional agenda for accounting and finance professionals – one that comprises three imperatives, which should be addressed over the next five to ten years. The first of these imperatives is concerned with the need to develop new metrics and standards to understand and derive the financial value of Big Data as an intangible asset. This would include for example, a consideration of the rate of obsolescence of Big Data and how this can be reflected through appropriate depreciation of the intangible asset. Accounting and finance professionals will also need to develop new metrics through the collection of unstructured data to be combined and integrated with other datasets for the purposes of assessing organisational performance. The second imperative identified by ACCA and IMA is the need for accounting and finance professionals to develop analytical skills to bridge the gap between “data science and data art, combining analytical skills and sophisticated models developed by mathematicians and statisticians with the skills of data art and data ‘storytelling’” (2013b, p. 7). The final imperative is the requirement for accounting and finance professionals to engage in creating a visual language of data “art” whereby “telling the story” of Big Data will be increasingly important. To that end, ACCA and IMA (2013b) suggest that there will be a growing need for accounting and finance professions to have the capability to integrate statistical and analytical skills with storytelling which can be used in performance management “dashboards” or “cockpits”. However, despite the challenges and imperatives of engaging with Big Data, ACCA argue that, “accountants and finance professionals are well placed to take an active role in Big Data by providing a new and critical service: ‘distilling’ vast amounts of information into actionable insights” (ACCA and IMA, 2013b, p. 5).
The implications of Big Data (among other things) as a driver of change within the accounting and finance professions, is given further consideration in a very recent report published by ACCA (2016). Using data collected from over 2,000 professional accountants and C-suite executives3 employed worldwide, the authors of the report argue that its findings provide a “fresh perspective on the outlook for professional accountants and their role in society in 2025” (p. 18). To that end, it specifically discusses the technical, ethical and interpersonal skills and the competencies which will be required of professional accountants in the future. In particular, the report identifies that emerging technologies, including Big Data, will impact the skills of the accountant in a number of areas: namely, audit and assurance, corporate reporting, strategic planning and performance management and tax. For example, accountants will need to develop the following skills to effectively deal with Big Data: IT knowledge, the ability to find, analyse and present data in an accessible and meaningful way, the ability to use analytics to unlock value in both financial and non-financial data to provide insights and future predictions. The ACCA (2016) report, concludes by stating that “vital knowledge of and skills with digital technologies appear to be lacking, but all accountants need to be aware of and able to apply a range of emerging technologies; many will need to be expert users of predictive analytics, Big Data and smart software” (p. 62).
Concluding remarks
In this chapter, we have primarily considered the potential impact of Big Data for accounting practice and accounting and finance professions. We acknowledge the clear potential that ERP and more recently Big Data have had – and are continuing to have – on organisations, but we have also tried to take a balanced approach in that we avoid much of the hyperbole that often goes hand-in-hand with the IT industry. History is replete with examples of so-called IT “solutions” that are purveyed as “the” answer to the question of the strategic use of information. What we have tried to do here is to demonstrate that it is the skilled use and understanding of these technologies that is paramount. As an illustration, following (and indeed during) his promotion of BPR, Davenport (1996) reminded us why “Why Re-engineering Failed”, given that it was “the fad that forgot people”.
Thus, we argue that the accounting and finance professions should be very much aware of the impacts, risks, challenges and opportunities arising from the use of new technologies in organisations, such as Big Data, drawing on lessons that should have been learned from the impacts – expected and unexpected (cf. Robey and Boudreau, 1996) – of prior technological developments, such as ERP systems. In particular, the accounting and finance professions need to urgently consider how best to address the numerous challenges associated with Big Data identified in this chapter: the need to develop new standards and metrics, issues around ethics and privacy, the need to develop appropriate expertise towards more effective Big Data analyses and storytelling, the need to understand how Big Data complements traditional accounting data and an understanding of how to deal with information overload and ambiguity associated with Big Data usage.
We recognise, too, that much research is required to be done in this sphere. We would advocate trans-disciplinary (cf. Whittington, 2014; Galliers, 1995, 2003) and in situ qualitative research that takes a practice perspective (cf. Peppard et al., 2014; Jarzabkowski and Spee, 2009) – this, with a view to uncovering the actual practices of individuals in decision-making that not just impacts but creates strategy. A range of skills and competencies will be required, which will require accounting and finance professionals (academics and practitioners) to develop new competencies and partner with colleagues in the strategic management and IS/IT communities in order to avoid being left behind but, more importantly, to contribute actively in understanding the multifaceted and complex nature of these emerging phenomena. After all, Big Data is just one in a long line of new technologies that have – and will continue to have – profound effects on work life, organisations and society. A proactive, forward-looking stance on the part of the accounting and finance professions is therefore called for. In other words, this chapter is a call for action in this regard.
Notes
1 The Federation of European Accountants (FEE) is the voice of the European accounting professions. It has a membership of approximately 800,000 professional accountants who are employed in private practice (small, medium and large accountancy firms), government and education.
2 Similar views have been expressed in a report published by the Chartered Institute of Management Accountants (CIMA) (2013).
3 “C-suite executive” is a widely-used “slang” term which is used to collectively refer to an organisation’s most senior executives.
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