PERFORMANCE IMPACTS OF BIG DATA ANALYTICS

Big Data Analytics has been a ‘hot topic’ for industry and academic during the past few years. This paper examines what constitutes Big Data Analytics (BDA) and how it relates to organizational performance. It also investigates what other factors influence this relationship, whether BDA leads to more data-driven decision-making (DDDM) and whether the latter is really superior to less informed decision-making. The study first operationalizes Big Data Analytics, and then develops a research model which manifests the direct and indirect relationships between analytic capability, DDDM, and organizational performance

Competitive advantage through big data analytics

University of Technology Sydney. Faculty of Business.‘Big Data’ has become a major topic of interest and discussion for both academics and professionals in the IT and business disciplines, and evidence from case studies suggests that companies which have invested in Big Data outperform others. It has to be noted though that ‘Bigger’ Data as such does not provide any benefits, but rather how organisations make sense of data and gain insights from analysing it. Analytic capabilities and practices are required to gain insights from Big Data, and thereby arguably improving decision-making and gaining competitive advantage. While protagonists of such Big Data Analytics (BDA) imply that those effects exist, so far they have not been confirmed by rigorous empirical research. The research questions in this thesis are: can BDA create competitive advantage, and what mechanisms drive analytic organisations to achieve competitive advantage? To explore the mechanisms, it is necessary to find out to what extent managers actually understand the implications of the analytic outputs and have capabilities and willingness to uncover and base their decisions on insights from BDA. In addition, the role of organisational culture in the context of BDA is also investigated. Data was obtained using a cross-sectional online survey which targeted Chief Information Officers and senior IT managers of medium-to-large Australian for-profit organisations. The survey yielded 163 complete responses which showed no presence of common method and non-response biases, and met the standard criteria for measurement reliability and validity. Partial least squares structural equation modelling (PLS-SEM) and multiple bootstrapping methods were used to test the hypotheses. The empirical results verify anecdotal claims made in the literature that Big Data and related analytics do actually lead to competitive advantage, partly directly and partly indirectly. The study reveals that such benefits are achieved primarily because BDA creates additional incentives for managers to base their strategic or operational decisions on analytics, and that more analytics-based decision-making actually leads to competitive advantage. Furthermore, the results also suggest that organisational culture, in contrast to BDA tools and methods, is a valuable, rare, inimitable and non-substitutable resource (as it cannot be changed easily or quickly), thereby indirectly driving and sustaining competitive advantage

Determinants of analytics-based managerial decisionmaking

This study investigates how managerial decision-making is influenced by Big Data analytics, analysts’ interaction skills and quantitative skills of senior and middle managers. The results of a cross-sectional survey of senior IT managers reveal that Big Data analytics (BDA) creates an incentive for managers to base more of their decisions on analytic insights. However, we also find that interaction skills of analysts and – even more so – managers’ quantitative skills are stronger drivers of analytics-based decision-making. Finally, our analysis reveals that, contrary to mainstream perceptions, managers in smaller organizations are more capable in terms of quantitative skills, and they are significantly more likely to base their decisions on analytics than managers in large organizations. Considering the important role of managers’ quantitative skills in leveraging analytic decision support, our findings suggest that smaller firms may owe some of their analytic advantages to the fact that they have managers who are closer to their analysts – and analytics more generally

Determinants of analytics-based managerial decision-making

This study investigates how managerial decision-making is influenced by Big Data analytics, analysts’ interaction skills and quantitative skills of senior and middle managers. The results of a cross-sectional survey of senior IT managers reveal that Big Data analytics (BDA) creates an incentive for managers to base more of their decisions on analytic insights. However, we also find that interaction skills of analysts and – even more so – managers’ quantitative skills are stronger drivers of analytics-based decision-making. Finally, our analysis reveals that, contrary to mainstream perceptions, managers in smaller organizations are more capable in terms of quantitative skills, and they are significantly more likely to base their decisions on analytics than managers in large organizations. Considering the important role of managers’ quantitative skills in leveraging analytic decision support, our findings suggest that smaller firms may owe some of their analytic advantages to the fact that they have managers who are closer to their analysts – and analytics more generally