In recent years, Business Intelligence (BI) has begun to play a critical role for businesses in terms of organizational development, helping them both to improve performance and to establish competitive advantages. However, there are many obstacles to the successful implementation of BI. This paper will discuss the challenges of BI, examining whether the reasons for failed implementation have been predominantly from BI capabilities or implementation strategy which is based on business-driven or technical. A suitable conceptual framework for the study of BI has been suggested according to set techniques and strategies which match the purpose of this research.

Business Intelligence Capabilities and Implementation Strategies

Business intelligence governance framework in a university: Universidad de la costa case study

With the start of current century, Business Intelligence (BI) has become an important and emerging tool, technique and technology in business world Organizations of all types across the globe are adopting BI for promoting business and getting advantage over competitors Business Intelligence is the processes, technologies, and tools that help organizations to change the data into information, information into knowledge and knowledge into plans that guide for better and effective decision making A Business Intelligence Competency Center (BICC) is an eternal legal unit with an organization, which encompasses dedicated members from both IT and business divisions The major reasons behind establishment of BICC are to ensure the adoption of BI at different levels of the organization by all stakeholders and to provide a platform to maintain and standardized the overall BI application Responsibilities of BICC include defining and managing the execution of the organization's BI strategy Moreover success of BI application within an organization can also be ensured through BICC In this paper, we have reviewed and analyzed BI implementations having BICC versus BI executions having no concept of BICC This study can also be used for future works like building Business Intelligence Competency Centers and/or measuring impact of Business Intelligence Competency Centers in success/failure of BI applications

Impact of business intelligence competency center in success/ failure of B.I. applications

This study examines the business value associated with business intelligence BI systems, based on the premise that business value is largely contingent on system type and its unique contribution. The study adopts a process-oriented approach to evaluating the value contribution of BI, arguing that it stems from improvements in 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 assets and capabilities that determine the impact of BI on business processes and, consequently, on organizational performance. Analysis of data collected from 159 managers and IT/BI experts, using structural equation modeling SEM techniques, shows that BI largely contributes to business value by improving both operational and strategic business processes.

How Business Intelligence Creates Value: An Empirical Investigation

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

How business intelligence creates value

The successes of organizations vary greatly from industry to industry. For every business in every industry, revenue growth remains the most fundamental indicator, and by far the most critical. Lately, marketplace realities are making revenue targets harder and harder to reach. That's why every organization must infuse strategic and tactical decisions with the knowledge necessary to maximize revenue, reduce costs, minimize risk and achieve competitive advantage. Business intelligence is defined as getting the right information to the right people at the right time. The term encompasses all the capabilities required to turn data into intelligence that everyone in an organization can trust and use for more effective decision making. BI is a sustainable competitive advantage. It allows the organization to drive revenues, manage costs, and realize consistent levels of profitability. An 'intelligent enterprise' - one that uses BI to advance its business - is better able to predict how future economic and market changes will affect its business. Such an organization is able to adapt to the new changes in order to gain. Business intelligence competency center can achieve more intelligence for organization at less cost by supporting the corporate strategy with a BI strategy on a continuous basis.

Business intelligence as a competitive differentiator

Architecture models and possible data flows for local and group datawarehouses are presented, together with some data processing models. The architecture models consists of several layers and the data flow between them. The choosen architecture of a datawarehouse depends on the data type and volumes from the source data, and inflences the analysis, data mining and reports done upon the data from DWH.

R.M. Bogza

Papers

Business intelligence as a competitive differentiator

Architecture Models and Data Flows in Local and Group Datawarehouses