Business Intelligence Center Concepts

The approach of Business Intelligence (BI) as a support function for management decisions is established in practice and theory. BI can not just be considered as a simple sequence of isolated single projects. Its coordination requires permanent efforts to keep the BI function and the business organization in alignment. In the context of the present empirical study, BI organizations have been analyzed for the diffusion of BI units and their distinct characteristics. Furthermore these organizations have been classified in different types of BI centers based on development and operational tasks. The results indicate a wide spread implementation of BI units in companies with a multifaceted range of duty. Thereby conclusions for the practical constitution of BI centers are deduced from the results

THE ROLE OF BUSINESS INTELLIGENCE (BI) IN SERVICE INNOVATION: AN AMBIDEXTERITY PERSPECTIVE

Advancement in information and communication technologies has been a key driver of the transition from a goods-basedeconomy to a services-based economy where significant changes are occurring in the way that services are produced andconsumed. There is tremendous opportunity to realize business value from service innovation by using the knowledge aboutservices to develop and deliver new information services and business services. Organizations can seize this opportunity touse service innovation initiatives to set themselves apart from competitors. One of the means for organizations to achieveservice innovation is to incorporate business intelligence (BI) both at the strategic and operational levels. A review of extantIS literature on service innovation and BI revealed that the strategic and operational role of BI in fostering service innovationfrom an organizational ambidexterity perspective is one that has not been explored. We address this gap in research bydeveloping a theoretical model and hypotheses to examine the role of BI in service innovation. Our literature review revealedthat firms use BI strategically and operationally for exploration and exploitation respectively to create opportunities forservice innovations which have the potential to impact organizational performance

USING THE MUTUAL INFORMATION METRIC TO IMPROVE ACCESSIBILITY AND UNDERSTANDABILITY IN BUSINESS INTELLIGENCE TOOLS

The rapidly-growing organizational data resources introduce a growing difficulty to locate and understand the relevant data subsets within large datasets – what can be seen as a severe information quality issue in today\u27s decision-support environments. The study proposes a quantitative methodology, based on the mutual-information metric, for assessing the relative importance of different data subsets within a large dataset. Such assessments can grant the end-user with faster access to relevant subsets within a large dataset, the ability to better understandits contents, and gain deeper insights from analyzing it – e.g., when such a dataset is being used for Business Intelligence (BI) applications. This manuscript provides the background and the motivation for integrating the proposed assessments of relative importance. It then defines the calculations behind the mutualinformation metric, and demonstrates their applications using illustrative examples

Using Interest Graphs to Predict Rich-Media Diffusion in Content-Based Online Social Networks

Rich-media, pictures, and videos, are becoming an increasingly important aspect of online social networks. Unlike social networks, where users are connected primarily because of being friends, peers, or co-workers, content-based networks build connections between individuals founded on a shared interest in rich-media content. In this study, “interest-graphs” comprised of these content-based connections were examined. As shown, interest graph analysis provides important advantages over traditional social network analysis to identify valuable network members and predicting rich-media diffusion

HOW BUSINESS INTELLIGENCE CREATES VALUE

Assessing IT business value has long been recognized as a major challenge, stemming largely from the considerable variability in the role and contribution of IT. This study examines the business value associated with business intelligence (BI) systems, suggesting that business value assessment is largely contingent on system type and should consider its unique contribution. The study adopts a process-oriented approach to evaluating the value contribution of BI, arguing that it stems from the improvement of business processes. The study develops and tests a research model that explains the unique mechanisms through which BI creates business value. The model draws on the resource-based view to identify key resources and capabilities that determine the impact of BI on business processes and, consequently, on organizational performance. Furthermore, the research model seeks to analyse the manner in which the organizational approach to innovation moderates the business value of BI. Analysis of data collected from 159 managers and IT/BI experts, using Structural Equations Modelling (SEM) techniques, shows that BI largely contributes to business value by improving both operational and strategic business processes. Further, it highlights the effect of the organizational approach toward exploration on transforming BI resources into capabilities and further into business value

Assessing Supply Chain Performance through Applying the SCOR Model

In recent years, supply chain performance measurement has received much attention from researchers and practitioners. Effective supply chain performance through supply chain antecedents such as business analytics has become a potentially valuable way of securing competitive advantage and improving supply chain performance. This study addressed the lack of the empirical studies by developing a comprehensive model to examine the effect of business analytics on supply chain performance. A quantitative methodology using a cross-sectional survey method was used to investigate the relationship between variables. Data were collected from automotive companies in Iran. The relationships between variables were examined using structural equation modelling (SEM) technique and partial least squares (PLS) software was used. The results revealed there is a significant positive relationship between business analytics and supply chain performance. The study combined resource- based theory, resource dependence theories to develop a new theoretical framework to demonstrate the importance of businesses analytics; in improving supply chain performance

Assessing Supply Chain Performance through Applying the SCOR Model

In recent years, supply chain performance measurement has received much attention from researchers and practitioners. Effective supply chain performance through supply chain antecedents such as business analytics has become a potentially valuable way of securing competitive advantage and improving supply chain performance. This study addressed the lack of the empirical studies by developing a comprehensive model to examine the effect of business analytics on supply chain performance. A quantitative methodology using a cross-sectional survey method was used to investigate the relationship between variables. Data were collected from automotive companies in Iran. The relationships between variables were examined using structural equation modelling (SEM) technique and partial least squares (PLS) software was used. The results revealed there is a significant positive relationship between business analytics and supply chain performance. The study combined resource- based theory, resource dependence theories to develop a new theoretical framework to demonstrate the importance of businesses analytics; in improving supply chain performance

The Impact of Business Intelligence Tools on Performance: A User Satisfaction Paradox?

While Business Intelligence (BI) initiatives have been a top-priority of CIOs around the worldfor several years, accounting for billions of USD of IT investments per annum (IDC), academicresearch on the actual benefits derived from BI tools and the drivers of these benefits remainsparse.This paper reports the findings of an exploratory, cross-sectional field study investigatingthe factors that define and drive benefits associated with the deployment of dedicated BI tools.BI is broadly defined as an analytical process which transforms fragmented data ofenterprises and markets into action-oriented information or knowledge about objectives,opportunities and positions of an organization; BI tools are software products primarilydesigned and deployed to support this analytical process (e.g. data warehouse software, datamining software, digital dashboards applications).Building upon DeLoneand McLean’s (1992; 2002; 2003) information systems successmodel, we develop, test and refine a BI quality and performance model adapted for the specificpurpose, application, user group and technology of BI tools. The ultimate performancepredictors in this model are user satisfaction and the impact of BI tools on managerial decisionquality, both of which are determined by data quality.Partial Least Square (PLS) modeling is used to analyze data collected in a surveyadministered to IT executives of large Australian Stock Exchange (ASX) listed companies.The results confirm some of the theoretical relationships established in – especially theoriginal – DeLone-McLean model in the specific context of BI. More importantly, the resultsalso confirm the important role of explicit BI management as antecedent of benefits derived fromBI tools, and the key impact of data quality on managerial decision making and organizationalperformance.However, the results also reveal a ‘user satisfaction paradox’: In contrast to thepredictions derived from the DeLone-McLean model, organizational performance is negativelyassociated with user satisfaction with BI tools. Financial performance data collected for ex-post verification of this unexpected result confirm this paradox. We discuss BI-specificinterpretations of these unexpected findings and provide avenues for future research