How do top- and bottom-performing companies differ in using business analytics?

Purpose Business analytics (BA) has attracted growing attention mainly due to the phenomena of big data. While studies suggest that BA positively affects organizational performance, there is a lack of academic research. The purpose of this paper, therefore, is to examine the extent to which top- and bottom-performing companies differ regarding their use and organizational facilitation of BA. Design/methodology/approach Hypotheses are developed drawing on the information processing view and contingency theory, and tested using multivariate analysis of variance to analyze data collected from 117 UK manufacture companies. Findings Top- and bottom-performing companies differ significantly in their use of BA, data-driven environment, and level of fit between BA and data-drain environment. Practical implications Extensive use of BA and data-driven decisions will lead to superior firm performance. Companies wishing to use BA to improve decision making and performance need to develop relevant analytical strategy to guide BA activities and design its structure and business processes to embed BA activities. Originality/value This study provides useful management insights into the effective use of BA for improving organizational performance

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

ORGANISATIONAL FACTORS AND THEIR ROLES IN CREATING IT BUSINESS VALUE

Research on business value of information technology (IT) has recognised that organisational factors play critical roles in affecting how IT impacts on firm performance. However, the conceptualisation of organisational factors and their relationship with IT and firm performance has not been extensively developed in the literature. There is neither a coherent way of specifying organisational factors nor a consensus on how IT and organisational factors interact to affect IT business value. This paper, based on a change management perspective, understands IT adoption as a change that is likely to trigger significant changes in organisational factors, which in turn may affect IT business value either positively or negatively. Building on previous work in IT business value and change management, this paper presents a cross-disciplinary study of the relationship between IT and organisational factors. It adopts a classification of organisational change and maps organisational factors identified in the IT business value studies into four categories for the purpose of knowledge accumulation. Based on the analysis, this paper offers an explanation of how IT and organisational factors interact to affect business value and concludes with a discussion of the findings and future research

Systemic capabilities: the source of IT business value

Purpose – The purpose of this paper is to develop, and explicate the significance of the need for a systemic conceptual framework for understanding IT business value. Design/methodology/approach – Embracing a systems perspective, this paper examines the interrelationship between IT and other organisational factors at the organisational level and its impact on the business value of IT. As a result, a systemic conceptual framework for understanding IT business value is developed. An example of enhancing IT business value through developing systemic capabilities is then used to test and demonstrate the value of this framework. Findings – The findings suggest that IT business value would be significantly enhanced when systemic capabilities are generated from the synergistic interrelations among IT and other organisational factors at the systems level, while the system’s human agents play a critical role in developing systemic capabilities by purposely configuring and reconfiguring organisational factors. Practical implications – The conceptual framework advanced provides the means to recognise the significance of the need for understanding IT business value systemically and dynamically. It encourages an organisation to focus on developing systemic capabilities by ensuring that IT and other organisational factors work together as a synergistic whole, better managing the role its human agents play in shaping the systems interrelations, and developing and redeveloping systemic capabilities by configuring its subsystems purposely with the changing business environment. Originality/value – This paper reveals the nature of systemic capabilities underpinned by a systems perspective. The resultant systemic conceptual framework for understanding IT business value can help us move away from pairwise resource complementarity to focusing on the whole system and its interrelations while responding to the changing business environment. It is hoped that the framework can help organisations delineate important IT investment considerations and the priorities that they must adopt to create superior IT business value

Intelligent student engagement management : applying business intelligence in higher education

Advances in emerging ICT have enabled organisations to develop innovative ways to intelligently collect data that may not be possible before. However, this leads to the explosion of data and unprecedented challenges in making strategic and effective use of available data. This research-in-progress paper presents an action research focusing on applying business intelligence (BI) in a UK higher education institution that has developed a student engagement tracking system (SES) for student engagement management. The current system serves merely as a data collection and processing system, which needs significant enhancement for better decision support. This action research aims to enhance the current SETS with BI solutions and explore its strategic use. The research attempts to follow socio-technical approach in its effort to make the BI application a success. Progress and experience so far has revealed interesting findings on advancing our understanding and research in organisation-wide BI for better decision-making

Big data in higher education: an action research on managing student engagement with business intelligence

This research aims to explore the value of Big Data in student engagement management. It presents an action research on applying BI in a UK higher education institution that has developed and implemented a student engagement tracking system (SES) for better student engagement management. The SES collects data from various sources, including RFID tracking devices across many locations in the campus and student online activities. This public funded research project has enhanced the current SES with BI solutions and raised awareness on the value of the Big Data in improving student experience. The action research concerns with the organizational wide development and deployment of Intelligent Student Engagement System involving a diverse range of stakeholders. The activities undertaken to date have revealed interesting findings and implications for advancing our understanding and research in leveraging the benefit of the Big Data in Higher Education from a socio-technical perspective

Do Top-Performing Companies Use Business Analytics Differently And Why?

It is suggested that companies that use business analytics perform better than those that do not in making strategic decisions and creating business value. However, little academic research based on theories exists to examine the extent to which companies differ in using business analytics and why this difference may contribute to company performance difference. To reduce this knowledge gap, this paper investigates the extent to which top and bottom performing companies differ in using business analytics by means of analysis of variance based on 232 responses collected from UK manufacturers, and seeks to explain how this use difference may be linked to performance difference drawing on the information processing view and path dependence theory. The research findings indicate that top-performing companies are three times more likely than bottom-performing companies to use business analytics and develop a data-driven environment simultaneously; and that the company differences regarding the use of business analytics and the resultant performance may be due to path dependence and how relevant organisational factors are designed. The study contributes to business analytics literature by providing empirical evidences and offering a theoretical-based understanding of business analytics, providing a foundation for future research. This study also has important managerial implications by demonstrating how business analytics can be used to improve performance

Understanding the Impact of Business Analytics on Innovation

The advances in Big Data and Business Analytics (BA) have provided unprecedented opportunities for organizations to innovate. With new and unique insights gained from BA, companies are able to develop new or improve existing products/services. However, few studies have investigated the mechanism through which BA contributes to a firm’s innovation success. This research aims to address this gap. From an information processing and use perspective, a research model is proposed and empirically validated with data collected from a survey with UK businesses. The evidence from the survey of 296 respondents supports the research model that provides a focused and validated view on BA’s contribution to innovation. The key findings suggest that BA directly improves environmental scanning which in turn helps to enhance a company’s innovation in terms of new product novelty and meaningfulness. However, the effect of BA’s contribution would be increased through the mediation role of data-driven culture in the organization. Data-driven culture directly impacts on new product novelty, but indirectly on product meaningfulness through environmental scanning. The findings also confirm that environmental scanning directly contributes to new product novelty and meaningfulness which in turn enhance competitive advantage. The model testing results also reveal that innovation success can be influenced by many other factors which should be addressed alongside the BA applications

The link between information processing capability and competitive advantage mediated through decision-making effectiveness

While research underpinned by the resource-based view (RBV) appears to suggest that IT-enabled capabilities are positively linked to competitive advantage, such a link is often seen as a black box as the processes through which competitive advantage can be gained appears unclear. In particular, research appears to suggest that information processing capability is linked to decision-making effectiveness and competitive advantage; however little research appears to examine the interrelationship among them. This study, drawing on the RBV, develops a mediation model to examine the link between competitive advantage and the key tenets of value, rarity, inimitability and non-substitutability of information processing capability in the context of business analytics; and whether this link is mediated through decision-making effectiveness. Based on data collected from 633 UK companies, this study shows that there is a positive link between the value, rarity and inimitability characteristics of information processing capability and competitive advantage, which is partially mediated by decision-making effectiveness. The findings contribute to the theoretical development of the RBV by developing a mediation model that looks inside the black box. They also contribute to managers’ knowledge and understanding of the mechanism through which the strategic value of information processing capability can be maximized

Impact of recent and anticipated change in oil price on global logistics and supply chain activities - a survey of practitioner and educator opinions

Purpose: This research investigated the views of logistics and supply chain (SC) managers, and also those of educators teaching these disciplines, of the impact of the recent fall in oil price, and also anticipated future oil prices, on global logistics and SC activities. In terms of future prices, this work has sought to understand how these professionals see the oil price as evolving in the near term (3-years) and medium term (10-years), and hence understand the impacts they foresee for logistics and SC activities. Research Approach: The research is empirical, with semi-structured questionnaires being handed out and collected at a recent industry logistic and supply chain event in the UK, at a corresponding conference in the UK, and likewise at an international conference in the US. This approach ensured that only the target audience - middle and senior managers in companies, and lecturers and above in universities - were surveyed, and that a high response rate was achieved. The questionnaire was kept short and anonymous to assist this high take-up rate. A total of 31 valid questionnaires were returned, and these were analysed using both qualitative and quantitative (SPSS) methods.   Findings and Originality: This research is recent and original. One key and perhaps surprising finding is that about half of respondents thought that the recent fall in oil price had had no significant impact on logistics and supply chain activities, while the other half thought there had been an impact, classing this as ‘medium’, and identifying the nature of these impacts. A second key finding was the very wide range of expectations, from both managers and educators, of the future price of oil; with estimates for the expected oil price 10 years hence ranging from below $30/bbl to over$120/bbl.   Research and Practical Impacts: The survey showed that the risk of a significant medium-term constraint to global oil supply, sufficient to raise the oil price to above $90/bbl, was thought unlikely by nearly two-thirds of those that responded to the questionnaire. In terms of research impact, it is hoped that this paper will help raise awareness of this future price risk, both for practitioners within the logistics and SC industry, and for those that teach these topics within academia.