Archives For Critical success factors

CSFs for implementing BI systems

Wednesday, December 23, 2015

There is a new publication in January 2016 issue of Journal of the Association for Information Science and Technology on the topic of business intelligence systems implementation, co-authored with W. Yeoh: Extending the understanding of critical success factors for implementing business intelligence systems. It is an important step in extending our understanding of critical success factors for implementing business intelligence systems. Here is the abstract:

Extant studies suggest implementing a business intelligence (BI) system is a costly, resource-intensive and complex undertaking. Literature draws attention to the critical success factors (CSFs) for implementation of BI systems. Leveraging case studies of seven large organizations and blending them with Yeoh and Koronios’s (2010) BI CSFs framework, our empirical study gives evidence to support this notion of CSFs and provides better contextual understanding of the CSFs in BI implementation domain. Cross-case analysis suggests that organizational factors play the most crucial role in determining the success of a BI system implementation. Hence, BI stakeholders should prioritize on the organizational dimension ahead of other factors. Our findings allow BI stakeholders to holistically understand the CSFs and the associated contextual issues that impact on implementation of BI systems.

Embryonic data mining success

Wednesday, April 22, 2015

A study exploring the critical success factors of embryonic data mining implementation, co-authored with U. Bole, J. Žabkar, G. Papa, and J. Jaklič, has appeared in April 2015 issue of International Journal of Information Management. In the work titled A case analysis of embryonic data mining success we propose and validate, through a series of cases, a conceptual framework to guide practitioners’ adoption of data mining practices. Abstract:

Within highly competitive business environments, data mining (DM) is viewed as a significant technology to enhance decision-making processes by transforming data into valuable and actionable information to gain competitive advantage. There appears, however, to be a dearth of empirical case studies which consider in detail the initial stages in DM management to enable apt foundation for its later successful implementation. Our research applied a multi-method strategy to determine the critical success factors of embryonic DM implementation. We propose and validate, through a series of cases, a conceptual framework to guide practitioners’ adoption of DM. Our findings reveal additional issues for applied decision making in the context of DM success.