Big data and decision quality: the role of management accountants’ data analytics skills

Abstract

Purpose Existing research on the relationship between big data and organizational decision quality is still few and far between, and what does exist often assumes direct effects of big data on decision quality. More recent research indicates that such direct effects may be too simplistic, and in particular, an organization’s overall human skills are often not considered sufficiently. Inspired by the knowledge-based view, we therefore propose that interactions between three aspects of big data usage and management accountants’ data analytics skills may be key to reaching high-quality decisions. The purpose of this study is to test these predictions based on a survey of US firms. Design/methodology/approach The authors draw on survey data from 140 US firms. This survey has been conducted via MTurk in 2020. Findings The results of the study show that the quality of big data sources is associated with higher perceived levels of decision quality. However, according to the results, the breadth of big data sources and a data-driven culture only improve decision quality if management accountants’ data analytics skills are highly developed. These results point to the important, but so far unexamined role of an organization’s management accountants and their skills for translating big data into high-quality decisions. Practical implications The present study highlights the importance of an organization’s human skills in creating value out of big data. In particular, the findings imply that management accountants may need to increasingly draw on data analytics skills to make the most out of big data for their employers. Originality/value This study is among the first, to the best of the authors’ knowledge, to provide empirical proof of the relevance of an organization’s management accountants and their data analytics skills for reaching desirable firm-level outcomes. In addition, this study thus adds to the further advancement of the knowledge-based view by providing evidence that in contemporary big-data environments, interactions between tacit and explicit knowledge seem crucial for driving desirable firm-level outcomes.

Information systems quality in management accounting and management control effectiveness

“…The CFA resulted in factor loadings >0.7 for all six items (Table 2), which is well above the recommended threshold of 0.4 according to Field (2018). Thus, the six items loaded onto one factor.…”

“…First, we tested whether the variables are normally distributed using a Shapiro-Wilk test and a Kolmogorov-Smirnov test. For the variables, Past Performance and Management Control Effectiveness, the Shapiro-Wilk test was not significant, as the p-value was greater than 0.05, indicating that the two variables were normally distributed (Field, 2018). The remaining variables were not normally distributed.…”

“…However, automation not only leads to the avoidance or reduction of control problems but also enables the creation and use of real-time data. In the context of the implementation of modern production equipment and digitalization of industry, there are increasingly new possibilities for automated data collection and analysis, as often argued in the literature on big data (Bhimani and Willcocks, 2014;Franke and Hiebl, 2023;Gärtner and Hiebl, 2018;Hedman et al, 2016;Vasarhelyi et al, 2015;Warren et al, 2015;). Smarter manufacturing JAOC 20,3 plants in the course of Industry 4.0, which are characterized by features, such as artificial intelligence, Internet of Things and cyber-physical systems (Kamble et al, 2020), will lead to management accounting being able to access enhanced data thanks to automation.…”

Digital technologies and the evolution of the management accounting profession: a grounded theory literature review

“…To that end, it has been acknowledged that big data analytics is strongly extending MAs' skills toward IT (Payne, 2014;Pilipczuk, 2020). MAs need a solid understanding of aspects such as data structures, data accuracy, data management, data security and data cleansing (Franke and Hiebl, 2023;Kokina et al, 2021;Möller et al, 2020) or even programming (Richins et al, 2017). In addition, intermediate (Wadan and Teuteberg, 2019) or advanced statistical knowledge (Nielsen, 2018) should be added to the competence portfolios of MAs for them to operate at a highly analytical level.…”

“…On the one hand, researchers have emphasized that digital technologies represent a paradigmatic shift for the management accounting profession. These scholars argue that to remain relevant, MAs must develop specialized ICT competences that will enable them not only to use but also to design new technologies (Franke and Hiebl, 2023; Kokina et al. , 2021; Nielsen, 2018; Payne, 2014).…”