Ensuring Successful Business Intelligence Systems Implementation: Multiple Case Studies in Engineering Asset Management Organisations

  • William Yeoh
  • Andy Koronios
  • Jing Gao


Recently heightened competition resulting from market deregulation and increased regulatory compliance requirements have demanded greater accountability for decision making in engineering asset management (EAM) organisations. However, the siloed information structure and fragmented business function of conventional EAM organisations do not support the effective extraction, analysis, and provision of actionable information to improve decision-making process. In response to this, many EAM organisations turned their efforts to implementing complex Business Intelligence (BI) systems. But how to increase the likelihood of BI systems implementation success for the diverse EAM organisations with its traditionally strong and fragmented culture? This paper investigates and discusses the critical success factors (CSFs) influencing BI systems implementation in EAM organisations. Seven in-depth case studies were conducted in EAM organisations. The empirical findings show a clear trend towards multidimensional challenges involved in such resourceful and complex undertaking. The CSFs exist in various dimensions composed of organisation, process, and technology perspectives. Nevertheless, the study reveals that a more fundamental issue concerning the business needs of BI systems may, in the end, impede BI systems success. Therefore, BI stakeholders of EAM organisations are urged to apply a business-orientation approach in tackling implementation challenges and ensuring buy-in from business stakeholders.


Business Case Successful Case Asset Management Business Intelligence Critical Success Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    IIMM (2006) International Infrastructure Management Manual. Australia New Zealand 2nd Ed, National Asset Management Steering Group, Thames.Google Scholar
  2. 2.
    IIMM (2002) International Infrastructure Management Manual. Australia New Zealand 1st Ed, National Asset Management Steering Group, Thames.Google Scholar
  3. 3.
    Steenstrup K (2004) Asset-Intensive ERP II and EAM/CMMS MQ Criteria: Gartner Research.Google Scholar
  4. 4.
    Lin S, Gao J, Koronios A & Chanana V. (2007) Developing a data quality framework for asset management in engineering organisations. International Journal of Information Quality 1(1), 100-126.CrossRefGoogle Scholar
  5. 5.
    Haider A. (2007) Information Systems Based Engineering Asset Management Evaluation: Operational Interpretations. Thesis. University of South Australia, Adelaide.Google Scholar
  6. 6.
    Woodhouse J. (2000) Key Performance Indicators, John Woodhouse Partnership, viewed 12 Feb 2008, <>Google Scholar
  7. 7.
    USDOT-FHWA December (1999) Asset Management Primer, U. S Department of Transportation, Federal Highway Administration, Office of Asset Management, FHWA Pub. No FHWA-IF-00-10.Google Scholar
  8. 8.
    Amadi-Echendu J, Willett R, Brown K, Lee J, Mathew J, Vyas N & Yang BS. (2007) 'What Is Engineering Asset Management?' paper presented at the 2nd World Congress on Engineering Asset Management, Harrogate, UK.Google Scholar
  9. 9.
    Negash S. (2004) 'Business Intelligence', Communications of the Association for Information Systems, 13, 177-195.Google Scholar
  10. 10.
    Moss L & Atre S. (2003) Business Intelligence Roadmap: The Complete Lifecycle for Decision-Support Applications. Boston, MA: Addison-Wesley.Google Scholar
  11. 11.
    Reinschmidt J & Francoise A. (2000) Business Intelligence Certification Guide, IBM, International Technical Support Organization, San Jose, CA.Google Scholar
  12. 12.
    Olszak C & Ziemba E. (2007) 'Approach to Building and Implementing Business Intelligence Systems', Interdisciplinary Journal of Information, Knowledge, and Management, 2, 135-148.Google Scholar
  13. 13.
    Gangadharan GR & Swami SN (2004), 'Business Intelligence Systems: Design and Implementation Strategies', paper presented at the 26th International Conference Information Technology Interfaces ITI.Google Scholar
  14. 14.
    Jagielska I, Darke P & Zagari G. (2003), 'Business Intelligence Systems for Decision Support: Concepts, Processes and Practice', paper presented at the 7th International Conference of the International Society for Decision Support Systems.Google Scholar
  15. 15.
    Gartner. Gartner EXP Survey of More than 1,400 CIOs Shows CIOs Must Create Leverage to Remain Relevant to the Business 2007. Retrieved May 1, 2009, from: Scholar
  16. 16.
    Gartner. Gartner EXP Worldwide Survey of 1,500 CIOs Shows 85 Percent of CIOs Expect "Significant Change" Over Next Three Years 2008 Retrieved May 1, 2009, from: Scholar
  17. 17.
    Gartner. Gartner EXP Worldwide Survey of More than 1,500 CIOs Shows IT Spending to Be Flat in 2009." Retrieved May 1, 2009, from: Scholar
  18. 18.
    Richardson J & Schlegel K. (2008) Magic Quadrant for Business Intelligence Platforms, Gartner Research.Google Scholar
  19. 19.
    Watson HJ, Fuller C & Ariyachandra T. (2004), 'Data Warehouse Governance: Best Practices at Blue Cross and Blue Shield of North Carolina', Decision Support Systems, 38(3), 435-450.CrossRefGoogle Scholar
  20. 20.
    Ang J & Teo TSH. (2000), 'Management Issues in Data Warehousing: Insights from the Housing and Development Board', Decision Support Systems, 29 (1), 11-20.CrossRefGoogle Scholar
  21. 21.
    Duncan NB. (1995) 'Capturing Flexibility of Information Technology Infrastructure: A Study of Resource Characteristics and Their Measure', Management Information Systems, 12(2) , 37-57.Google Scholar
  22. 22.
    Watson H & Haley B. (1998) 'Managerial Considerations', Communications of the ACM, 41(9), 32 - 37.CrossRefGoogle Scholar
  23. 23.
    Shin B. (2003) 'An Exploratory Investigation of System Success Factors in Data Warehousing', Journal of the Association for Information Systems, 14 (1), 141-170.Google Scholar
  24. 24.
    Watson HJ & Haley BJ. (1997) 'Data Warehousing: A Framework and Survey of Current Practices', Journal of Data Warehousing, 2(1), 10-17.Google Scholar
  25. 25.
    Friedman T. (2005) Gartner Says More Than 50 Percent of Data Warehouse Projects Will Have Limited Acceptance or Will Be Failures through 2007, Gartner Research, viewed 21 Feb 2007, <>.Google Scholar
  26. 26.
    Yeoh W, Koronios A & Gao J. (2008) Managing the Implementation of Business Intelligence Systems: A Critical Success Factors Framework, International Journal of Enterprise Information Systems, 4(3), 79-94.Google Scholar
  27. 27.
    Miles M & Huberman AM. (1994) Qualitative Data Analysis: An Expanded Sourcebook, Thousand Oaks, CA: Sage.Google Scholar
  28. 28.
    Darke P, Shanks G & Broadbent M. (1998) 'Successfully Completing Case Study Research: Combining Rigour, Relevance and Pragmatism', Information Systems Journal, 8 (4), 273-289.CrossRefGoogle Scholar
  29. 29.
    Yin R. (1994) Case Study Research, Design, and Methods, 2 edn, Newbury Park, CA: Sage.Google Scholar
  30. 30.
    Firestone W. (1993) 'Alternative Arguments for Generalizing from Data as Applied to Qualitative Research', Educational researcher, 22(4), 16-27.Google Scholar
  31. 31.
    LeMay R. (2006). Sydney Water signs business intelligence vendor. Retrieved 11 July 2008, from,130061733,139268270,00.htmGoogle Scholar
  32. 32.
    Stuart I, McCutcheon D, Handfield R, McLachlin R & Samson D. (2002) Effective Case Research in Operations Management: A Process Perspective, Operations Management, 20(5), 419-433.CrossRefGoogle Scholar
  33. 33.
    Hostmann B & Buytendijk F. (2004) Management Update-Effective BI Approaches for Today’s Business World: Gartner Research.Google Scholar
  34. 34.
    Dresner H, Linden A, Buytendijk F & Friedman T. (2002) The Business Intelligence Competency Center: An Essential Business Strategy: Gartner Research.Google Scholar
  35. 35.
    Stumpf R & Teague LC. (2005) Object-Oriented Systems Analysis and Design with UML, Upper Saddle River, NJ: Prentice Hall.Google Scholar
  36. 36.
    Fuchs G. (2006) 'The Vital BI Maintenance Process', in Business intelligence implementation: issues and perspectives, B. Sujatha (Eds). pp. 116-123. Hyderabad, India: ICFAI University Press.Google Scholar
  37. 37.
    Bates AW. (2000) Chapter Ten: Avoiding the Faustian Contract and Meeting the Technology Challenge. In T. Bates (Ed.), Managing technological change. San Francisco: Jossey-Bass.Google Scholar
  38. 38.
    Burton B. Geishecker L. & Hostmann B. (2006) Organizational Structure: Business Intelligence and Information Management: Gartner ResearchGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • William Yeoh
    • 1
    • 2
  • Andy Koronios
    • 2
    • 2
  • Jing Gao
    • 1
    • 2
  1. 1.CRC for Integrated Engineering Asset ManagementBrisbaneAustralia
  2. 2.School of Computer and Information ScienceUniversity of South AustraliaMawson LakesAustralia

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