Yasmina Amara , pp. 95. MAM/Sektionen för Management, 2008.
Having the right information in the right place at the right time is fundamental although not easy for the making of significant business decisions and staying competitive. Competitive Intelligence CI allows the scanning of the environment, the recognition of risks and opportunities in the competitive arena and a better understanding of today & tomorrow's information requirements with the support of Business Intelligence BI Software.
Choosing the right BI software is critical to increase productivity and effectiveness in the organization. At the same time a very elaborating and complex process due to the fact that numerous vendors exist on the market most of which are updated very rapidly besides most of BI software selection criteria already used are vague and not complete. It is also difficult to evaluate BI effectiveness as a tool in conjunction with supporting the CI cycle different phases.
The objective of this study is to develop a model and test it on a small sample of BI vendors to support organizations in selecting the BI Software that best fits their business needs as well as differentiating between different vendors in this area while developing a reliable categorization. It is the answer to the criticism of criteria selected in other BI Software evaluations today. The major criticism is that software calling themselves BI only cover parts of the Intelligence Cycle.
A comprehensive review on CI concepts, BI software functions along with previous BI software evaluations have been conducted in order to fulfill the first objective of the study (The model). Moreover, qualitative empirical study using the model developed was carried out to fulfill the other objectives by evaluating a chosen sample of BI software vendors.
The study was able to develop what has been called the Solberg Søilen Amara Vriens Model for evaluating BI software after its authors, that consists of technological variables that covers the BI function along with the variables for measuring the level of CI Cycle phases support on a (5) point Likert scale. Subsequently, it tested the model on a limited sample of BI Software vendors.
Moreover, the findings of the study also revealed that it is difficult to declare the most competitive BI software as what is good for one user might not be good for the other depending on their varied business needs. Furthermore, the study initiated a new classification of BI Software vendors depending on their support of the CI cycle phases and divided them into five categories including: Fully complete, Complete, Semi Complete, Incomplete and Insubstantial.
Finally, the SSAV Model Together with some proposed non technological variables and the classification developed can be used as a user's selection foundation when deciding upon which BI Software to pursue.