Key Success Factors in Business Intelligence

Szymon Adamala, Linus Cidrin


Business Intelligence can bring critical capabilities to an organization, but the implementation of such capabilities is often plagued with problems. Why is it that certain projects fail, while others succeed? The aim of this article is to identify the factors that are present in successful Business Intelligence projects and to organize them into a framework of critical success factors. A survey was conducted during the spring of 2011 to collect primary data on Business Intelligence projects. Findings confirm that Business Intelligence projects are wrestling with both technological and non-technological problems, but the non-technological problems are found to be harder to solve as well as more time consuming than their counterparts. The study also shows that critical success factors for Business Intelligence projects are different from success factors for Information Systems projects in general. Business Intelligences projects have critical success factors that are unique to the subject matter. Major differences can be found primarily among non-technological factors, such as the presence of a specific business need and a clear vision to guide the project. Success depends on types of project funding, the business value provided by each iteration in the project and the alignment of the project to a strategic vision for Business Intelligence at large. Furthermore, the study provides a framework for critical success factors that, explains sixty-one percent of variability of success for projects. Areas which should be given special attention include making sure that the Business Intelligence solution is built with the end users in mind, that the Business Intelligence solution is closely tied to the company’s strategic vision and that the project is properly scoped and prioritized to concentrate on the best opportunities first.


Business Intelligence, Data Warehouse, Critical Success Factors, Enterprise Data Warehouse, Success Factors Framework, project risk management

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Adelman, S. 2003. Impossible Data Warehouse Situations. Solutions from the Experts. Boston, MA: Pearson Education.

Adèr, & Mellenbergh, G. 2011. Advising on Research Methods: A consultant's companion. 3rd ed. Huizen, The Netherlands: Johannes van Kessel Publishing.

Ariyachandra, T., & Watson, H. 2006. Which Data Warehouse Architecture Is Most Successful? Business Intelligence Journal , 11 (1).

Babbie, E. 2009. The Practice of Social Research. Wadsworth Publishing.

Beal, B. 2005. Report: Half of data warehouse projects to fail. Retrieved May 22, 2011, from Search CRM:

Chen, L., Soliman, K., Mao, E., & Frolick, M. 2000. Measuring user satisfaction with data warehouses: An exploratory study. Information & Management , 37 (3), 103-110.

Daniel, D. 1961. Management Information Crisis. Harvard Business Review.

Delone, W., & McLean, E. 1992. Information Systems Success: The Quest for the Dependent Variable. Journal of Information System Research, 3 (1), 60-95.

Delone, W., & McLean, E. 2003. The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems , 19 (4), 9-30.

Duncan, W. 1996. A Guide to the Project Management Body of Knowledge. Sylva, North Carolina: PMI Publishing.

Ellison, R., & Moore, A. 2003. Trustworthy Refinement Through Intrusion-Aware Design. Carnegie Mellon Software Engineering Institute.

Garthwaite, P. 1994. An Interpretation of Partial Least Squares. Journal of the American Statistical Association , 89 (425), 122-127.

Hwang, M., & Xu, H. 2008. A Structural Model of Data Warehousing Success. Journal of Computer Information Systems , 48-56.

Inmon, W. H. 2002. Building the Data Warehouse, 3rd ed. New York, NY: John Wiley & Sons.

Jamieson, S. 2004. Likert scales: how to (ab)use them. Medical Education, 1217-1218.

Kimball, R., & Ross, M. 2002. The data warehouse Toolkit, 2 ed. New York, NY: John Wiley and Sons, Inc.

Kimball, R., Ross, M., Thornthwaite, W., Mondy, J., & Becker, B. 2008. The Data Warehouse Lifecycle Toolkit, 2nd ed. Indianapolis, IN: Wiley Publishing.

Laskowski, N. 2001. Gartner BI Summit: Business intelligence benefits lie in orchestration. Retrieved May 22, 2011, from

Legodi, I., & Barry, M.-L. 2010. The current challenges and status of risk management in enterprise data warehouse projects in South Africa. PICMET 2010 Technology Management for Global Economic Growth.

Linstone, H. A., & Turoff, M. 2002. The Delphi Method Techniques and Applications.

Markarian, J., Brobst, S., & Bedell, J. 2007. Critical Success Factors Deploying Pervasive BI.

Meehan, P. 2011. Patrick Meehan speech during Gartner Business Intelligence Summit 2011. London, UK. Retrieved from

Merriam-Webster Dictionary. 2011. Retrieved May 24, 2011, from

Numminen, E. (2010). On the Economic Return of a Software Investment omManaging Cost, PhD Dissertation.

Pirouz, D. 2006. An Overview of Partial Least Squares. Retrieved May 27, 2011, from Social Science Research Network:

Pisello, T. 2001. IT Value Chain Management rom Social Science Research Network: htt Alinean, LLC.

Popovic, A., & Jaklic, J. 2010. Benefits of Business Intelligence System Implementation: An Empirical Analysis of the Impact of Business Intelligence System Maturity on Information Quality.

Ringle, C., Wende, S., & Will, S. 2005. SmartPLS 2.0 (M3) Beta. Hamburg.

Shin, B. 2003. An Exploratory Investigation of System Success Factors in Data Warehousing. Communications of the Association for Information Systems , 6 (4), 141-170.

Solberg Søilen, K., & Hasslinger, A. 2009. How application integration, security issues and pricing strategies in business intelligence shape vendor differentiation. ECIS 2009: THIRD EUROPEAN COMPETITIVE INTELLIGENCE SYMPOSIUM, (pp. 252-260). Stockholm.

Walton, E. J., & Dawson, S. 2001. Managers J., & Dawson, S. MPETITIVE INTELLIGENCE SYMPOSIUMtrategiesJournal of Management Studies, 173-179.

Watson, H., Annino, D., Wixom, B., Avery, L., & Rutherford, M. 2001. Current Practices in Data Warehousing. Information Systems Management, 18 (1), 47-55.

Wixom, B., & Watson, H. 2001. An Empirical Investigation of the Factors Affecting Data Warehousing Success. MIS Quarterly , 25 (1), 17-41.

Yeoh, W., & Koronios, A. 2010. Critical Success Factors for Business Intelligence Systems. Journal of Computer Information Systems, 50 (3), 23-32.

Yeoh, W., Gao, J., & Koronios, A. 2007. Towards a CSF Framework for Implementation of Business Intelligence Systems: A Delphi Study in Engineering Asset Management Organisations. Research and Practical Issues of Enterprise Information Systems II. Beijing, PRC.



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