While substantial business investment in business intelligence systems (BIS) is continuing to accelerate, there is an urgent need of specific and rigorous methods to assess their performance and ...effectiveness. There are some scholars that have handled the measurement of Business Intelligence (BI) from a value perspective; others have chosen to assess the BI process, while some have tried to rather evaluate the performance of BI systems. However, there are practically no empirical research papers at hand concerning the measurement of BI systems seen from a product perspective. Therefore, we propose in this paper a product oriented evaluation of two major aspects of BIS: end user satisfaction with the intelligence produced by BIS and the quality of the data conveyed to end users. By exploiting the lessons learned from prior attempts to measure those two dimensions in information systems, we present a new evaluation model that is based on an understanding of the characteristics and the intelligence produced by BIS. We then propose a list of dimensions to be assessed in an examination of the relationship between end user's satisfaction and the quality of data conveyed to them. In this paper, multiple definitions of business intelligence in the literature are presented; besides, business intelligence systems measurement from different points of view is addressed. The purpose of this paper is to present an assessment model of end user satisfaction and data quality in BIS that participates towards the development of an evaluation approach of business intelligence systems seen from a product perspective.
Today the strategic significance of information is fundamental to any organization. With the intensification of competition between companies in open markets and often saturated, companies must learn ...to know themselves and to the market through the collection and analysis of quality information. The strategic information is seen as a key resource for success in the business, which is provided by Business Intelligence systems. A successful business strategy requires an awareness of the surrounding (internal and external) environment of organizations, including customers, competitors, industry structure and competitive forces. Managing the future means not only is able to anticipate what will happen outside the organization, but also be able to represent the events through their own actions timely. To make it possible, Pervasive Business Intelligence arises as a natural evolution of business intelligence applications in organizations, allowing to companies achieve and maintain a sustainable competitive advantage.
Purpose: To better understand the impact of Business Intelligence systems on organizations’ effectiveness.Methodology: Critical and descriptive literature review.Findings: On the basis of numerous ...case studies described in literature and pertaining to various types of enterprises, different industries and countries, the paper confirms the positive impact of the implementation of Business Intelligence systems on organizations’ effectiveness.Research implications: The paper provides insights that can fuel future in-depth research aimed at the development of objective methods for measuring the impact of the implementation of Business Intelligence systems on organizational effectiveness, as well as further quantitative research.Practical implications: Results of the majority of studies indicate that the implementation of Business Intelligence systems brings tangible benefits to organizations. The implementation should, however, be appropriate and adequate, adjusted to each organization’s resources.Originality: The paper organizes and systematizes knowledge about the impact of BI implementation on organisation’s efficiency.
Organizations nowadays invest heavily in business intelligence (BI) systems to get insights from their increasingly large volumes of complex data, support decision making and achieve competitive ...advantages. The visualization capability of a BI system in terms of developing effective visualizations for addressing business problems is crucial to the success of BI. With the rapid advances achieved in the domain of information visualization, many existing visualization techniques/applications can provide reasonable support for particular paradigms, problem domains, and data types. However, they are still weak for supporting multi-paradigm, multi-domain problems and maintaining visualization effectiveness under dynamic contexts. BI systems need to include visualization subsystems or be used together with separate visualization systems that offer flexible support for creating, manipulating and transforming visualization solutions. In this paper, we discuss business visualization context and propose and implement a context adaptive visualization framework. Furthermore, we demonstrate the framework implementation through a sequence of context-driven illustrations.
With advances in the business intelligence area, there is an increasing interest for the introduction of business intelligence systems into organizations. Although the opinion about business ...intelligence and its creation of business value is generally accepted, economic justification of investments into business intelligence systems is not always clear. Measuring the business value of business intelligence in practice is often not carried out due to the lack of measurement methods and resources. Even though the perceived benefits from business intelligence systems, in terms of better information quality or achievement of information quality improvement goals, are far from being neglected, these are only indirect business benefits or the business value of such systems. The true business value of business intelligence systems hides in improved business processes and thus in improved business performance. The aim of the paper is to propose a conceptual model to assess business value of business intelligence systems that was developed on extensive literature review, in-depth interviews, and case study analysis for researching business intelligence systems’ absorbability capabilities or key factors facilitating usage of quality information provided by such systems respectively.
Several arguments can be found in business intelligence literature that the use of business intelligence systems can bring multiple benefits, for example, via faster and easier access to information, ...savings in information technology (‘IT’) and greater customer satisfaction all the way through to the improved competitiveness of enterprises. Yet, most of these benefits are often very difficult to measure because of their indirect and delayed effects on business success. On top of the difficulties in justifying investments in information technology (‘IT’), particularly business intelligence (‘BI’), business executives generally want to know whether the investment is worth the money and if it can be economically justified. In looking for an answer to this question, various methods of evaluating investments can be employed. We can use the classic return on investment (‘ROI’) calculation, cost-benefit analysis, the net present value (‘NPV’) method, the internal rate of return (‘IRR’) and others. However, it often appears in business practice that the use of these methods alone is inappropriate, insufficient or unfeasible for evaluating an investment in business intelligence systems. Therefore, for this purpose, more appropriate methods are those based mainly on a qualitative approach, such as case studies, empirical analyses, user satisfaction analyses, and others that can be employed independently or can help us complete the whole picture in conjunction with the previously mentioned methods. Since there is no universal approach to the evaluation of an investment in information technology and business intelligence, it is necessary to approach each case in a different way based on the specific circumstances and purpose of the evaluation. This paper presents a case study in which the evaluation of an investment in on-line analytical processing (‘OLAP’) technology in the company Melamin was made through an analysis of users' opinions along with a strategic analysis based on identifying a cause-and-effect relationship between the benefits of OLAP technology and the company’s strategic goals.
This paper analyzes the current situation of business environment and business intelligence systems integration at first. Accrediting to the frame of RosettaNet, the trend of business process ...integration is analyzed. Then discusses the integration of business intelligence systems based on RosettaNet frame. The conceptual development and implementation a RosettaNet frame work for business intelligence systems, a novel concept for the realization of optimize business processes. A generic conceptual framework will be developed and a prototype implementation of the generic concepts will be benchmarked in system design of business intelligence systems. It can help confirm the keystone of the construction of business intelligence systems and the direction of system integration.
W artykule przedstawiono najważniejsze elementy Inteligentnego Kokpitu Menedżerskiego InKoM. System InKoM został zaprojektowany, wykonany i zaimplementowany w środowisku TETA BI jako podstawowy ...produkt projektu1, którego fazy badawczą i komercjalizacji zrealizowano w latach 2012-2014. Innowacyjny Inteligentny Kokpit Menedżerski stanowi z jednej strony uzupełnienie, z drugiej rozwinięcie systemu TETA BI, a więc zestawu rozwiązań klasy business intelligence oferowanych na rynku przez UNIT4 TETA BI Center. Innowacyjność systemu InKoM polega m.in. na bardzo szerokim zastosowaniu metod, technik i narzędzi wizualnej eksploracji danych w obszarze wiedzy ekonomicznej i finansowej. Zdaniem jego twórców, zastosowane podejście oraz stworzone rozwiązania dostarczają menedżerom małych i średnich obiektów gospodarczych niedostępne dotąd dla nich zaawansowane funkcje analityczne i informacyjne, podnosząc jakość, skuteczność i efektywność procesów podejmowania decyzji. Należy dodać, że projekt InKoM i wykonany w jego ramach system są przykładem współpracy i transferu wiedzy między jednostką naukowo-badawczą, komercyjnym wytwórcą oprogramowania i praktykami gospodarczymi, bez której nie jest możliwe tworzenie innowacyjnych rozwiązań wspomagających zarządzanie. (abstrakt oryginalny)
The article presents the most important elements of the InKoM Intelligent Management Cookpit. The InKoM system was designed, executed and implemented in the TETA BI environment as the basic product of project1, the research and commercialization phases of which were carried out in 2012-2014. On the one hand, the innovative Intelligent Managing Cockpit complements the development of TETA BI, on the other hand, a set of business intelligence class solutions offered on the market by UNIT4 TETA BI Center. InKoM system innovation includes use of methods, techniques, and tools of visual data mining in the area of economic and financial knowledge. According to its creators, the approach used and the solutions created provide managers with small and medium-sized economic facilities that have not yet been available to them advanced analytical and information functions, improving the quality, effectiveness and effectiveness of decision-making processes. It should be added that the project of InKoM and its system are an example of cooperation and knowledge transfer between a scientific research unit, a commercial software manufacturer and economic practices, without which it is not possible to create innovative management solutions. (original abstract)
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