What translates big data into business value? A meta-analysis of the impacts of business analytics on firm performance
Introduction
The disruptive impact of big data on various businesses and industries has been referred to as a “management revolution” [1] or “the next frontier” [2]. Others have even opined that “big data is possibly the most significant ‘tech’ disruption in business and academic ecosystems since the meteoric rise of the Internet and the digital economy” [3]. The advanced techniques and technologies necessary to handle big data are commonly referred to by the terms business intelligence (BI), business analytics (BA), or big data analytics (BDA) [4]. Given the enormous potential of BA to create value for business and society, an increasing number of studies from diverse research disciplines have attempted to examine the value creation mechanism of BA [5,6]. In the BA literature, technical and human resources, as well as management capabilities, are considered essential antecedents to business value creation [7.], [8.], [9.]. Moreover, a data-driven culture [6,10,11] and contextual factors such as the competitive intensity [12] and industry dynamism [13] were found to have a major impact on the value created from BA. Some studies have noted that firms can only create value from BA when they manage to combine their resources and capabilities to gain benefits [14].
Overall, numerous studies with inconsistent results have been published on the business value of BA over the past decades [7,15,16]. Although most studies report a positive relationship between BA and firm performance, for example, by demonstrating the strong impact of data analytics competency on improving firm decision-making [14] or illustrating the major role that BDA use plays in enhancing asset productivity and business growth [17], some studies present a more nuanced picture of the conditions under which BA can create value for firms. In an attempt to explain the mixed results of prior studies, IS scholars have pointed to the essential role of contextual factors, such as a firm's structural readiness, and psychological readiness factors, which are needed to create value from BA [16]. In addition, whether BA is beneficial for firms depends on the fit between different factors, such as BA tools, data, people, and tasks [18]. Some IS scholars have similarly suggested that several factors, such as the inability to capture the indirect benefits of BA use, methodological issues, and inadequate consideration of environmental factors and time lags, are the main reasons for these mixed results [15].
Although the wealth of studies on the business value of BA has undoubtedly contributed to the body of knowledge by providing valuable insights into specific aspects of the value creation mechanism, recent work has highlighted the need for a more consistent picture, especially with regard to the question on how contextual factors influence the performance outcomes due to BA [5]. To date, few research efforts, whether in IS or in other disciplines, have attempted to provide a more integrated and consistent picture on the business value of BA based on empirical findings from prior studies. We address this gap by synthesizing quantitative evidence on this research topic from the rich body of knowledge. Thus, our main research objective is to provide a comprehensive and consistent picture of the main factors that contribute to enhance the business value of BA, resolve the inconsistencies across studies, and achieve an enhanced understanding of the conditions under which BA's has varying impacts on firm performance. In doing so, we aim not only to synthesize qualitative findings from the body of knowledge but also to strive for a more valid picture of these findings based on the quantitative results of former studies. In particular, we aim to answer the following research questions (RQs):
RQ1: What are the main BA resources and capabilities as well as contextual factors that are critical to create business value from business analytics?
RQ2: To what extent do these factors contribute to enhancing firm performance and what conditions may cause business analytics to have varying impacts on firm performance?
To answer the RQs, we conduct a meta-analysis of 125 firm-level studies reported in 123 articles spanning ten years of research from across 26 countries and four continents. We consider meta-analysis to be an appropriate method for synthesizing the results of conflicting studies to resolve the inconsistencies [19] and increase the statistical power of these results [20]. The findings are expected to be of high importance for research and practice because answering the questions of how, when, and why it can create value is essential for companies to gain a competitive advantage [6,21]. For researchers, developing an enhanced understanding of the main determinants of the business value of IT would help to advance the development of theory in IS research. In business practice, such an enhanced understanding would help managers to increase the value of IT [22].
The remainder of this paper is structured as follows. In Sections 2 and 3, we explain the theoretical background concerning the business value of BA, describe the scope of our research, and develop the research framework, including identifying the dependent and independent variables of interest. In Section 4, we describe the relevant phases and activities of our meta-analysis research approach. The results of the meta-analysis are presented in Section 5. Implications for research and practice as well as the limitations of this study are described in Section 6. Finally, the concluding Section 7 presents a brief summary of this research.
Section snippets
Business value of business analytics
In the literature, the term big data is often used to describe extremely large and complex data sets drawn from various sources that require advanced techniques, such as BI, BA, or BDA, for storage, management, analysis, and visualization [4]. In this context, the “three Vs” framework is often used to highlight volume (magnitude of data), velocity (speed of data creation), and variety (structural heterogeneity of data sources) as the main characteristics of big data. Additional Vs were later
Research model
We combine the broad view of the business value term of BA proposed by Grover et al. [6] with the well-established IS business value framework [32] to examine the impact of BA on firm performance at the organizational level for several reasons. First, the IS business value framework [32] provides a sociotechnical conceptualization of IS as investments in important IS resources and capabilities such as technical assets, human resources and management capabilities, and non-IS investments (such as
Meta-analysis
We chose to conduct a meta-analysis because such a research approach facilitates the achievement of our primary goals—integrating, synthesizing, and analyzing the quantitative results of multiple individual studies to draw new conclusions from past knowledge [72]. Moreover, meta-analysis is a useful means by which to increase the statistical power of results [20]. Since being introduced in the 1970s, meta-analysis has become an important research method in multiple research disciplines of the
Results
The results of the meta-analysis of the 125 studies and 358 effect sizes are summarized in Table 6. We conducted six separate meta-analyses, each examining the relationship between an independent variable and firm performance. Each of the studies was assigned a relative weight, which is the inverse of the sum of the sampling error and the between-study variance. The relative weight for each study provides the basis for calculating the weighted mean reflected by the summary effect size [73].2
Discussion
The main research objective of our study was to integrate the empirical evidence of previous studies regarding the business value of BA to achieve a consistent and enhanced understanding of the impact of BA on firm performance. Moreover, we were interested in answering the question of under what conditions BA can create value. We found evidence that BA has an overall positive impact on organizational performance in terms of operational, financial, and market performance. In addition, we gained
Conclusion
With the primary purpose of providing a comprehensive and consistent picture of the main factors that contribute to enhancing the business value of BA, we conducted a meta-analysis of 125 studies from 123 articles to answer the questions of whether and when BA can create business value for organizations. More specifically, we examined the impact of BA resources, capabilities, and contextual factors on firm performance, as well as potential moderating effects that might account for the
CRediT authorship contribution statement
Thuy Duong Oesterreich: Conceptualization, Methodology, Investigation, Data curation, Validation, Writing – original draft, Visualization, Project administration. Eduard Anton: Investigation, Formal analysis, Validation, Writing – original draft, Visualization. Frank Teuteberg: Writing – review & editing, Supervision.
Thuy Duong Oesterreich: Thuy Duong Oesterreich is a post-doctoral researcher at the Department of Accounting and Information Systems, which is part of the Institute of Information Management and Information Systems Engineering at the Osnabrück University. She received her PhD in Information Systems at the Osnabrück University in 2019. In her research, she focusses on investigating the sociotechnical and socioeconomic issues of information technology and information systems, including big data
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Thuy Duong Oesterreich: Thuy Duong Oesterreich is a post-doctoral researcher at the Department of Accounting and Information Systems, which is part of the Institute of Information Management and Information Systems Engineering at the Osnabrück University. She received her PhD in Information Systems at the Osnabrück University in 2019. In her research, she focusses on investigating the sociotechnical and socioeconomic issues of information technology and information systems, including big data and business analytics. She has several years of industry experience in the area of management accounting and IT project management prior to her academic career. Her research was published in numerous peer-reviewed journals and conferences, including Information & Management, Technological Forecasting and Social Change, Journal of Accounting & Organizational Change, International Journal of Accounting Information Systems, Information Systems and e-Business Management, and International Conference on Information Systems (ICIS).
Eduard Anton: Eduard Anton is a research associate at the Department of Accounting and Information Systems, which is part of the Institute of Information Management and Information Systems Engineering at the Osnabrück University. He completed his master's degree in Information Systems in 2015 and subsequently worked as an IT project manager and IT consultant for several years. Currently, he is pursuing his dissertation, with a particular focus on the socioeconomic implications of business analytics and artificial intelligence. He has published journal articles and conference papers in Information & Management, International Journal of Innovation and Technology Management, and International Conference on Information Systems (ICIS).
Frank Teuteberg: Frank Teuteberg is full professor at the Osnabrück University in Germany. Since 2007 Frank Teuteberg has been head of the Department of Accounting and Information Systems, which is part of the Institute of Information Management and Information Systems Engineering at the Osnabrück University. Frank Teuteberg is spokesman of the profile line Digital Society – Innovation – Regulation and leader of several research projects (e.g., www.dorfgemeinschaft20.de). Furthermore, he is author of more than 400 papers in the field of cloud computing, industrial Internet of things, e-health, blockchain, and human–computer interaction.