How does business analytics contribute to organisational performance and business value? A resource-based view

YesPurpose – The purpose of this article is to identify how the organisations are able to improve their business value through acquisition of business analytics capabilities and by improving their performance. Design/Methodology/Approach – With the help of literature survey, along with standard resource-based view framework, a conceptual model has been developed. These have been statistically tested by collecting the data using the survey questionnaire from 306 selected respondents from various service sector and product based organisations in India. To analyse the data we have used partial least square based structural equation modelling. Findings – The study highlights that by the help of data acquisition and tool acquisition as two vital components, the acquisition of business analytics capabilities could improve the business value of the organisation by strengthening its organisational performance. The findings of this research also indicated that acquisition of business analytics capabilities has a significant influence on organisation’s business process performance and business decision, which in turn significantly influence organisational performance. And, organisational performance eventually positively influences its business value. The model was found to provide an explanative power of 71%. Research Implication – The proposed research model can provide effective recommendations to the management of the organisations to realise the importance of acquisition of effective business analytics capabilities to eventually improve the business value of the organisation. Originality/Value – No specific studies, as yet, have analysed the effects of acquisition of business analytics capabilities for improving organisational performance mediated through business process performance and business decision. Therefore, this research has explored the distinctive effort to empirically validate this understanding

Linking Big Data and Business: Design Parameters of Data-Driven Organizations

Big data analytics is accepted to be an important driver of business value. However, this value does not come without a cost. Becoming a data-driven organization (DDO) necessitates a substantial transformation along the components structure, actors, task, and technology. Moreover, as successfully generating value from big data requires the utilization of data insights in business, attention needs to be assigned to the different actors from the data and business side, and their interrelation and collaboration. By taking a socio-technical systems perspective and utilizing a multi-case research approach, we developed a taxonomy to structure insights about different design parameters of a DDO. Thus, we contribute to the information systems literature by proposing a holistic design framework for DDOs paying tribute to its high collaboration requirements, and offer a compendium for managers with pathways how to design a DDO

Business Intelligence & Analytics and Decision Quality - Insights on Analytics Specialization and Information Processing Modes

Leveraging the benefits of business intelligence and analytics (BI&A) and improving decision quality does not only depend on establishing BI&A technology, but also on the organization and characteristics of decision processes. This research investigates new perspectives on these decision processes and establishes a link between characteristics of BI&A support and decision makers’ modes of information processing behavior, and how these ultimately contribute to the quality of decision outcomes. We build on the heuristic–systematic model (HSM) of information processing, as a central explanatory mechanism for linking BI&A support and decision quality. This allows us examining the effects of decision makers’ systematic and heuristic modes of information processing behavior in decision making processes. We further elucidate the role of analytics experts in influencing decision makers’ utilization of analytic advice. The analysis of data from 136 BI&A-supported decisions reveals how high levels of analytics elaboration can have a negative effect on decision makers’ information processing behavior. We further show how decision makers’ systematic processing contributes to decision quality and how heuristic processing restrains it. In this context we also find that trustworthiness in the analytics expert plays an important role for the adoption of analytic advice

Overcoming Barriers in Supply Chain Analytics—Investigating Measures in LSCM Organizations

While supply chain analytics shows promise regarding value, benefits, and increase in performance for logistics and supply chain management (LSCM) organizations, those organizations are often either reluctant to invest or unable to achieve the returns they aspire to. This article systematically explores the barriers LSCM organizations experience in employing supply chain analytics that contribute to such reluctance and unachieved returns and measures to overcome these barriers. This article therefore aims to systemize the barriers and measures and allocate measures to barriers in order to provide organizations with directions on how to cope with their individual barriers. By using Grounded Theory through 12 in-depth interviews and Q-Methodology to synthesize the intended results, this article derives core categories for the barriers and measures, and their impacts and relationships are mapped based on empirical evidence from various actors along the supply chain. Resultingly, the article presents the core categories of barriers and measures, including their effect on different phases of the analytics solutions life cycle, the explanation of these effects, and accompanying examples. Finally, to address the intended aim of providing directions to organizations, the article provides recommendations for overcoming the identified barriers in organizations

Linking business analytics to decision making effectiveness: a path model analysis

While business analytics is being increasingly used to gain data-driven insights to support decision making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness (DME) at the organizational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organizational DME. The research model is tested using structural equation modeling based on 740 responses collected from U.K. businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capability, which in turn has a positive effect on DME. The findings also demonstrate that the paths from business analytics to DME have no statistical differences between large and medium companies, but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision making. They also contribute to manager's knowledge and understanding by demonstrating how business analytics should be implemented to improve DM

Essential Micro-foundations for Contemporary Business Operations: Top Management Tangible Competencies, Relationship-based Business Networks and Environmental Sustainability

Although various studies have emphasized linkages between firm competencies, networks and sustainability at organizational level, the links between top management tangible competencies (e.g., contemporary relevant quantitative-focused education such as big data analytics and data-driven applications linked with the internet of things, relevant experience and analytical business applications), relationship-based business networks (RBNs) and environmental sustainability have not been well established at micro-level, and there is a literature gap in terms of investigating these relationships. This study examines these links based on the unique data collected from 175 top management representatives (chief executive officers and managing directors) working in food import and export firms headquartered in the UK and New Zealand. Our results from structural equation modelling indicate that top management tangible competencies (TMTCs) are the key determinants for building RBNs, mediating the correlation between TMTCs and environmental sustainability. Directly, the competencies also play a vital role towards environmental practices. The findings further depict that relationship-oriented firms perform better compared to those which focus less on such networks. Consequently, our findings provide a deeper understanding of the micro-foundations of environmental sustainability based on TMTCs rooted in the resource-based view and RBNs entrenched in the social network theory. We discuss the theoretical and practical implications of our findings, and we provide suggestions for future research

Actionable Supply Chain Management Insights for 2016 and Beyond

The summit World Class Supply Chain 2016: Critical to Prosperity , contributed to addressing a need that the Supply Chain Management (SCM) field’s current discourse has deemed as critical: that need is for more academia-­‐industry collaboration to develop the field’s body of actionable knowledge. Held on May 4th, 2016 in Milton, Ontario, the summit addressed that need in a way that proved to be both effective and distinctive in the Canadian SCM environment. The summit, convened in partnership between Wilfrid Laurier University’s Lazaridis School of Business & Economics and CN Rail, focused on building actionable SCM knowledge to address three core questions: What are the most significant SCM issues to be confronted now and beyond 2016? What SCM practices are imperative now and beyond 2016? What are optimal ways of ensuring that (a) issues of interest to SCM practitioners inform the scholarly activities of research and teaching and (b) the knowledge generated from those scholarly activities reciprocally guide SCM practice? These are important questions for supply chain professionals in their efforts to make sense of today’s business environment that is appropriately viewed as volatile, uncertain, complex, and ambiguous. The structure of the deliberations to address these questions comprised two keynote presentations and three panel discussions, all of which were designed to leverage the collective wisdom that comes from genuine peer-­‐to-­‐peer dialogue between the SCM practitioners and SCM scholars. Specifically, the structure aimed for a balanced blend of industry and academic input and for coverage of the SCM issues of greatest interest to attendees (as determined through a pre-­‐summit survey of attendees). The structure produced impressively wide-­‐ranging deliberations on the aforementioned questions. The essence of the resulting findings from the summit can be distilled into three messages: Given today’s globally significant trends such as changes in population demographics, four highly impactful levers that SCM executives must expertly handle to attain excellence are: collaboration; information; technology; and talent Government policy, especially for infrastructure, is a significant determinant of SCM excellence There is tremendous potential for mutually beneficial industry-academia knowledge co-creation/sharing aimed at research and student training This white paper reports on those findings as well as on the summit’s success in realizing its vision of fostering mutually beneficial industry-academia dialogue. The paper also documents what emerged as matters that are inadequately understood and should therefore be targeted in the ongoing quest for deeper understanding of actionable SCM insights. Deliberations throughout the day on May 4th, 2016 and the encouraging results from the pre-­‐summit and post-­‐summit surveys have provided much inspiration to enthusiastically undertake that quest. The undertaking will be through initiatives that include future research projects as well as next year’s summit–World Class Supply Chain 2017

Privacy, Public Goods, and the Tragedy of the Trust Commons: A Response to Professors Fairfield and Engel

User trust is an essential resource for the information economy. Without it, users would not provide their personal information and digital businesses could not operate. Digital companies do not protect this trust sufficiently. Instead, many take advantage of it for short-term gain. They act in ways that, over time, will undermine user trust. In so doing, they act against their own best interest. This Article shows that companies behave this way because they face a tragedy of the commons. When a company takes advantage of user trust for profit, it appropriates the full benefit of this action. However, it shares the cost with all other companies that rely on the wellspring of user trust. Each company, acting rationally, has an incentive to appropriate as much of the trust resource as it can. That is why such companies collect, analyze, and “monetize” our personal information in such an unrestrained way. This behavior poses a longer term risk. User trust is like a fishery. It can withstand a certain level of exploitation and renew itself. But over-exploitation can cause it to collapse. Were digital companies collectively to undermine user trust this would not only hurt the users, it would damage the companies themselves. This Article explores commons-management theory for potential solutions to this impending tragedy of the trust commons