Business intelligence (BI) can be described as a “managerial concept” or “process.” It is used to assist organisations to manage business information and information technology to make effective decisions. Measuring both tangible and intangible benefits of BI projects remains a significant challenge for South African banking institutions. The output of BI projects is intelligence, which makes the assessment of value difficult. The aim of this study was to gain an understanding as to what are the benefits of implementing BI solutions for a single South African banking institution, Absa. A phenomenological research methodology was used to collect, analyse and interpret the data. A combination of questionnaires and semi structured interviews was used for data collection purposes. The research gauged the BI users’ perceptions of what are the benefits associated with various BI solutions and how they could be measured. Results showed that Absa uses numerous approaches to calculate the benefits of its BI implementations. The research also identified various tangible and intangible benefits of BI solutions in Absa. Furthermore results suggested that there was a genuine need to capture and measure these benefits however, users of these BI solutions required assistance in the form of a guideline or tools to calculate them. Financial metrics such as ROI, was only partially serving this purpose for Absa. These findings together with insights gleaned from the literature review were then be used to suggest a process for the measurement and identification of BI benefits in Absa. Further recommendations and suggestions for future study are stated in the concluding chapter of the research. / Dissertation (MBA)--University of Pretoria, 2010. / Gordon Institute of Business Science (GIBS) / unrestricted

M.Comm. / It is critical for companies in today's competitive business environment to understand the impact and influence competitors and the external environment have on the success of their strategies and competitive advantage. Business must therefore comprehend how the strategies of competitors and forces of the external environment may affect the competitive advantage of the business. Businesses require actionable intelligence to enable them to monitor, analyse and determine the impact from external environmental forces and actions from competitors. Businesses have to develop appropriate strategies to achieve competitive advantage over competitors in their industry. The question which this study addresses, is whether businesses are able to monitor the strategies and influences from the external environment effectively. This is needed to gain a competitive advantage, and is accomplished by producing actionable intelligence utilising the competitive intelligence cycle. The purpose of the study is to determine how a business can utilise competitive intelligence in order to determine the potential strategies of competitors. To achieve these objectives, a literature study was completed on the subject matter. This study has established that the competitive intelligence function consists of tour distinct phases. Phase one determines the intelligence requirements of the end users of the intelligence. Phase two involves the collection of information. Phase three involves the analysis of the information in order to produce intelligence. Phase four disseminates the intelligence to the end users (those who requested the intelligence). Each of the four phases of the competitive intelligence cycle have been examined and discussed. Special reference and attention has been paid to the analytical techniques and tools - phase three - that id used to produce actionable intelligence.

Background: Business intelligence (BI) is regarded as a key practice to invest into and adopt. This is due to the benefits that can be realized from BI. Critical success factors (CSFs) need to be managed appropriately for organizations to realize maximum benefit from their BI investments. Objective: The objective of this study is to measure the influence of BI CSFs on BI net benefits. In addition, the interrelationships between these CSFs will be measured, the effect of moderating variables will be determined and the reasons why these CSFs are important will be explored. Method: A deductive approach was followed. A conceptual model was derived from literature. This model was used to construct an online survey. The data gathered from the survey was analysed using statistical techniques. The results from the statistical analysis were validated and expanded on by conducting semi-structured interviews with participants who completed the online survey. Results: The results found that top management support, alignment between BI and business objectives and BI technology fit for the business were determined to be the most influential BI CSFs to realize BI net benefits. Top management support was shown to have a relationship with all other CSFs. Well-defined user requirements and user participation did not have a relationship with BI net benefits. Industry and size moderated a small portion of the relationships between BI CSFs and BI net benefits. Conclusion: Organizations need to prioritize top management support, alignment between BI and business objectives, BI technology fit for the business, incremental project management methodology and adequate team skills, to realize BI net benefits. Special attention should be given to top management support as it influences all other BI CSFs.

The thesis is focused on the area of Business Intelligence Governance that seeks to management BI as a complex environment in an organization. The goal of this thesis is to create comprehensive BIG framework that will help to understand and lead BI, to support business strategy execution. The fist part of this thesis is introduction to the area of BIG. It contains definition of the term BI, description of trends in BI, definition of the term BIG and the answer on question Why do we need to governance BI. The second part focuses on description and evaluation of existing BIG instruments. The third part handles about new BIG framework and authorities. It describes particular building blocks of the framework and discovers structure of BIG authorities.

When the data warehouse concept was first introduced by IBM as a part of their new information system in 1988, the first step in the field of modern decision support systems or business intelligence was taken. Since then, academics, practitioners and solution developers have put a considerable effort in introducing new trends of these systems. Each new trend has roots in what enterprises demand from these systems. The advances in Web technologies and social media, has led to introduction of new trends such as Cloud BI and Big Data which are both cost-effective and also have the potential to take advantage of semi-structured and unstructured data within organizations. This paper deals with these new trends and the influences of organizational demands and new technologies and tools on them. A deep literature review deals with four major BI trends in detail. (Data warehouse, Business Performance Management (BPM), Cloud BI and Big Data). Two case studies from local Business intelligence developers are carried out in order to explore the influences mentioned above. As the result of this study, a model is proposed that addresses the elements that affect the BI trends, both in organizational and technological perspectives. It is observed that despite the fact that lots of new trends have been introduced in the past years (e.g. Cloud BI and Big Data), it does not necessarily mean that older trends are becoming obsolete. Data warehouses and BPM systems are still being used vastly in the industry. However, the later trends can be offered to clients that have the demand for them. The results imply that Cloud BI is mainly suitable for companies with low initial budgets and Big Data can be adopted by organizations that want to exploit their social data sources. The mere fact that both implied trends are built upon their preceding ones, has transformed data warehouses and BPM approach the ground work for any new trends to come.

Zugl.: Bochum, Univ., Diss., 2009

Diss. St. Gallen, 2008 ; no. 3399. / Literaturverz.

Business Intelligence (BI) is the set of methodologies, practices and capacities focused on information management that allows companies to make better decisions. The practice of BI is developed through IT systems and an in-depth knowledge of the company’s “core business”. This article seeks to make an assessment of the difficulties, costs and benefits that are taken into account before acquiring a BI tool.Among the difficulties is the adaptation of complex information, the deficient data entry, the privacy problems. Related to costs, the costs of licensing and acquiring a tool are developed, as well as those derived from the adaptation of personnel to these solutions. Likewise, regarding the main benefits, the control of the activities, the improvement in the productivity of the collaborators, the technological support to reach the objectives, the promotion of a data-oriented culture and the improvement in the decision-making are exposed. In this way, it shows the challenge that companies in the information age, where knowledge has become a source of competitive advantage for the market and in which people are prepared to achieve success. / El Business Intelligence (BI) es el conjunto de metodologías, prácticas y capacidades enfocadas al manejo de información que permite tomar mejores decisiones a las empresas. La práctica del BI se logra desarrollar a través de sistemas de tecnologías de la información y de un conocimiento profundo del core business de la empresa. El presente artículo busca hacer una evaluación de las dificultades, costos y beneficios que se toman en cuenta antes de adquirir una herramienta de BI.Entre las dificultades se plantea la adaptación de información compleja, el deficiente ingreso de datos, los problemas de privacidad. Respecto a los costos, se identifica los costos de licenciamiento y adquisición de una herramienta, así como los derivados de la adaptación del personal a estas soluciones. Asimismo, en cuanto a los principales beneficios se expone el control de las actividades, la mejora en la productividad de los colaboradores, el soporte tecnológico para alcanzar los objetivos, el impulsar una cultura orientada a datos y la mejora en la toma de decisiones. De esta manera, se muestra el desafío que enfrentan las empresas en la era de la información, donde el conocimiento se ha convertido en una fuente de ventaja competitiva para destacar en el mercado y que solo aquellas que estén adecuadamente preparadas podrán lograr resultados superiores.

Success is something different for every organisation and Business Intelligence can be a tool to achieve success. Today big data is everywhere and organisations are starting to use these data and transform it to information. Information has always been valuable and from an organisational view now more than ever. Transforming data into information is critical, due to the fact that it’s a lot of data to consider. To acquire information, visualization of data may be useful. Dashboards can help in the process but it isn’t an easy task.  Instead of putting focus on the problem and the underlying factors, this study intends to investigate the success factors that can be the base for the use of a successful dashboard as a Business Intelligence tool. Previous research shows that there is no legitimate framework for success factors in Business Intelligence tools and dashboards. Through a qualitative approach and semi-structured interviews, we examine what users perceive as the most important factors for a successful dashboard. This is done with a Business Intelligence focus. The study shows that the major success factors when using a dashboard is purpose, data quality, organisational knowledge and context. These factors will hopefully lead to success when using a dashboard.

Thesis (MBA)--Stellenbosch University, 2013. / ENGLISH ABSTRACT:The research answered the primary research question by defining what business intelligence (BI) platform must be included in Pragma’s asset care centre (ACC) model. Pragma delivers physical asset management services and products with the aim of improving performance of physical assets. These services and products are contained in the ACC model, which is based on Pragma’s AMIP asset management maturity assessment methodology. The current BI platform in the ACC Pack cannot deliver information management to a mature asset management organisation as set out in the AMIP methodology. The research used a questionnaire, based on an extensive literature review, to determine the need for BI within the current user base, and to determine the ideal BI functionality profile delivered inside the ACC model. This proved to be valuable input in defining the BI platform by evaluating the features and capabilities of BI vendors. The quality of information findings highlighted the inadequacy of the current BI platform. The current platform consists of SSRS reports executing directly on the database of the business application, On Key. The concern is that the reports do not conform to the specification. This highlights a misalignment between what the SSRS reports deliver, and what the user expects. The platform is not sufficiently dynamic to allow tailored reports or data analysis to overcome this. Another key finding was that the platform is not delivering the service that the consumer expects. The current platform favours operational users over managerial users. Most of the information quality weaknesses are due to the current platform’s functionality that is stretched beyond its intended purpose. The research found that the current platform is delivering the two main capabilities required from the BI platform, i.e. reporting and MS Office integration. However, this is insufficient because SSRS is unable to deliver on any of the other capabilities present in the BI model. Capabilities like dashboards, collaboration and ad hoc query are key capabilities required by Pragma’s user base. Users require an online platform where they can perform analysis originating from multiple sources. The users responsible for implementing and maintaining the platform must have the functionality to make minor adjustments to the standard reports and the ability to add objects unique to the business environment. The research recommends a hybrid BI platform consisting of SSRS for activity reports, and QlikView for analysis models and adding the complete set of BI capabilities not present in the current platform. QlikTech’s QlikView, one of the leading data discovery tools in the industry, is the BI tool best suited to Pragma’s needs due to its user-friendliness and self-service BI capabilities. This will require an original equipment manufacturers (OEM) partnership between Pragma and QlikTech, with QlikView embedded into On Key as its BI capability. Another recommendation is that Pragma include a data warehouse as part of the On Key deployment. This will allow for analysis across multiple sources and enable completeness of information.