Intelligence in Medium-sized companies: experience from successful Bi4dynamics solution projects 9.1 Overview Business Intelligence (BI), a concept which emerged in the 1990s, became over the years more mature, elaborated, but also diversified. Derived from the basic concepts of Management Information Systems (MIS) and combined with Decision Supports Systems (DSS), it appeared for a short period of time as the Executive Information Systems (EIS) [1]. When the concept of data warehouses (DW) were developed and on-line analytical concepts (OLAP) became popular, the domain of BI gained importance. BI has, as do all information systems, two sides. One of them is technology side which defines the structure and technologies used. It deals with the data warehouse as the central point of BI to which data have to be collected through sophisticated processes of ETL (Extraction Transformation- Loading) which connects business information solutions at an operational level with the data warehouse. This transfer of data in the past was very batch-oriented with certain delays; it became faster with less delays than recently and is nearly on-line or even fully on-line in some solutions. Once data are in the data warehouse, they have to be formatted and disseminated to managers. At this point, companies can use different technologies from the broad group of OLAP tools. All this technological diversity has to be integrated by the company that wants to build such a system. BI also has another side. Because BI is about reporting, analysis and decision support, it can be also observed from the user side from the business side. At the beginning, these viewpoints have been somewhat neglected and the technology side was more important. But when BI became mature, in-depth research on its quality of support that was provided for managers emerged. Questions about the Business Value of BI occur more and more often. Howson defines seven areas of the Business Value of BI [2]: - BI for management and control; - BI for improving business performance; - Operational BI; - BI for process improvement; - BI for improve customer service; - BI for discovering new business opportunities; - BI for government and public services. This definition implies that BI became, even if the same technologies are used, more diversified and elaborated. The term BI maturity, the research area of several researchers [3], is explained in the literature by several models. It is very often used in the Six-stage BI maturity model by TDWI [4] which delimits six stages and defines for each one its own structural characteristics, analytics ability and focus of the stage. According to that model an up-to-date BI system is in its Adult (fifth) stage, and where the Enterprise DW is used, dashboards and cascading scorecards are implemented; the focus of the BI systems is not only in insight but more in support for action. BI systems are moving toward six stages of the aforementioned model where structure can be described as analytical services and as imbedded BI. When a system is mature, leveraging the system becomes a crucial question for an organization. So it is not surprising that more and more research on BI is recently focused on the acceptance of BI by its users (namely managers). The Technology Acceptance Model (TAM). (original abstract)
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