An Exploratory Investigation of System Success Factors in Data Warehousing

Despite the increasing role of the data warehouse as a strategic information source for decision makers, academic research has been lacking, especially from an organizational perspective. An exploratory study was conducted to improve general understanding of data warehousing issues from the perspective of IS success. For this, the effect of variables pertaining to system quality, information quality, and service quality on user satisfaction for the data warehouse was studied. Additional characterization was made on data warehouse users, their organizational tasks, and data warehouse usage. Empirical data were gathered at a large enterprise from three different information sources: a survey, unstructured group interviews with end-users, and informal interviews with an IT manager who was in charge of the data warehouse. Data analysis showed that user satisfaction with the data warehouse was significantly affected by such system quality factors as data quality, data locatability, and system throughput. Interviews also supported the existence of system design and management issues that have to be addressed to optimize the utility of the data warehouse as an effective decision support environment. In the meantime, data analysis indicated that first-line (or lower) and middle managers were the main users of the system. Managers and knowledge workers were taking advantage of the system to perform complex tasks, to support decision making, and to seek information critical for enhanced productivity. The group interviews revealed additional benefits of the data warehouse and major roadblocks in its successful usage

Business intelligence usage determinants: an assessment of factors influencing indivdual intentions to use a business intelligence system within a financial firm in South Africa

Although studies are conducted on economical gains due to BI system adoption, limited knowledge is available on factors which influence BI system usage. Identifying these factors is necessary for organisations because this may enable the design of effective BI systems, thus increasing the chance of firms adopting them to realise the actual value inherent in the exploitation of BI systems. The purpose of this study is, therefore, to investigate factors which influence BI system usage. The investigation employed constructs derived from three theoretical frameworks, namely technology acceptance model (TAM), task-technology fit (TTF) and social cognitive theory (SCT) as follows: intention to use, perceived usefulness, perceived ease use, task characteristics, technology characteristics, task-technology fit and computer self-efficacy. To test the hypotheses, data was collected by administering the study to 682 BI system users in a South African financial institution, SA-Bank, wherein 193 usable responses were received. The findings of the study with partial least squares (PLS) analysis indicated support for the joint use of constructs from the three theoretical frameworks, explaining 65% of BI system usage variance. Furthermore, the perceived usefulness of a BI system reflected a stronger influence as a factor of BI system usage over the beliefs that the system was easy to use, and the belief that it was aligned to the performance of business tasks. An unusual outcome in this study was the lack of influence of computer self-efficacy on BI system usage. Nonetheless, the study extended validation of the use of constructs derived from the three theoretical frameworks for a BI technology in the context of SA-Bank, thereby contributing to theory. Finally, the results of hypothesis testing suggested a starting point for practitioners towards designing BI systems, and recommendations and suggestions are included in this report

Factors Influencing BI Data Collection Strategies: An Empirical Investigation

The purpose of this dissertation is to examine the external factors that influence an organizations' business intelligence (BI) data collection strategy when mediated by BI attributes. In this dissertation, data warehousing strategies are used as the basis on which to frame the exploration of BI data collection strategies. The attributes include BI insightfulness, BI consistency, and the organizational transformation attribute of BI. The research population consisted of IT professionals and top level managers involved in developing and managing BI. Data was collected from a range of industries and organizations within the United States. An online survey was used to collect the data to empirically test the proposed relationships. Data was analyzed using partial least square path modeling (PLS). The results of this study suggest that there exists a positive relationship between institutional isomorphism and BI consistency. The results also indicate that there exists a positive relationship between BI consistency and BI comprehensive data collection strategy, and the organizational transformation attribute of BI and BI comprehensive data collection strategy. These findings provide a theoretical lens to better understand the motivators and the success factors related to collecting the huge amounts of data required for BI. This study also provides managers with a mental model on which to base decisions about the data required to accomplish their goals for BI

The Role of Business Intelligence in Organizational Decision-making

This Ph.D. thesis is concerned with the role of the business intelligence (BI) output in organizational decision-making processes. The primary focus of this thesis is to investigate how this BI output is employed and deployed by decision-makers to shape collective judgement and to reach organizational decisions. Concerning the role of the BI output in decision-making the BI literature is characterized by normative ideas of how the BI output should be used in decision-making and how it can enable people to make better decisions. Most previous work has concerned methods and technologies to collect, store and analyze BI. It has also, assumed a rational approach to decision making where data from information systems are used to inform decisions either by reducing uncertainty, ambiguity or complexity. This study attempts to establish knowledge about the role of the BI output in the IT project prioritization process of the Group IT of the Danske Bank Group. Hence, the starting point of this thesis is a 16-month long interpretive study from March 2010 till July 2011 during which I observed the prioritization process and collected various forms of data. I use a rich dataset built from this longitudinal study of the IT project prioritization process in Group IT where thematic analysis is used to analyze the data. Overall, the study operates under the interpretive paradigm, which assumes that the world and knowledge are socially constructed