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Business intelligence and analytics (BIA) initiatives are costly, complex and experience high failure rates. Organizations require effective approaches to evaluate their BIA capabilities in order to develop strategies for their evolution. In this paper, we employ a design science paradigm to develop a comprehensive BIA effectiveness diagnostic (BIAED) framework that can be easily operationalized. We propose that a useful BIAED framework must assess the correct factors, should be deployed in the proper process context and acquire the appropriate input from different constituencies within an organization. Drawing on the BIAED framework, we further develop an online diagnostic toolkit that includes a comprehensive survey instrument. We subsequently deploy the diagnostic mechanism within three large organizations in North America (involving over 1500 participants) and use the results to inform BIA strategy formulation. Feedback from participating organizations indicates that BIA diagnostic toolkit provides insights that are essential inputs to strategy development. This work addresses a significant research gap in the area of BIA effectiveness assessment.
Business Intelligence (BI) applications are strategic decision support systems that are significantly underutilized in many organizations. We propose that adoption and use can be improved by designing BI applications that provide users with high-quality metadata (i.e. information about the meaning, quality, location, and lineage of decision support data). Metadata's value is that it positively influences user attitudes towards data as measured by cognition and affect.
There are several sociotechnical themes and associated issues that need to be considered prior to implementing HIT in rural HPC settings. Proactive evaluation of these issues can enhance HIT implementation and also help to make ethical aspects of HIT design more explicit.
Modern organizations rely on Business Intelligence (BI) systems to provide the information needed to support a wide array of decisions, many of which have significant financial and strategic consequences. As such, information quality is critically important but is also highly contextual, meaning that information that is of sufficient quality for one purpose may not be so for others. The implication of this fact is that users must have the ability to assess information for its fitness to specific purposes. The authors submit that metadata provides this capability. Metadata is information that serves to provide insight into the meaning, quality, location, and lineage of information resources (for example, data elements, queries, and reports) provided by BI systems. In this chapter, they describe how organizations can increase the levels of use of their BI systems by providing the right metadata to users. The authors propose a conceptual model that describes how metadata contributes to the level of BI system use by creating positive attitudes toward the information available. They validate the model through consultation with experts in the fields of BI, information quality, and metadata management as well as through a survey of over 250 BI practitioners.
Effectively managing information resources is an important activity contributing to the competitive advantage of modern organizations. Organizational knowledge workers must be able to search for pertinent information quickly and effectively. This research identifies the relative usefulness of the metadata elements associated with the Dublin Core metadata standard for the effective retrieval of three different information resources – structured business intelligence reports, structured spreadsheet reports, and unstructured reports in formats such as Word and PowerPoint. A survey of knowledge workers was conducted to determine the relative usefulness of the metadata elements for each of the three information resources and to develop a framework outlining where metadata tag requirements differ between such resources. Overall, the study and resulting framework emphasize the need for system developers and database management personnel to be cognizant of the type of information resources being used, and ensure that search metadata elements that are appropriate for these specific resources are in place.
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