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Business Intelligence Maturity Models: Information Management Perspective

  • Alaskar Thamir
  • Babis Theodoulidis
Part of the Communications in Computer and Information Science book series (CCIS, volume 403)

Abstract

While Business Intelligence (BI) plays a critical role for businesses in terms of organizational development and creating competitive advantages, many BI projects fail to fully deliver the features and benefits that could help organizations in their decision-making. Rather than depending on software, BI success relies on the capabilities of sensing for appropriate information, data collection, extraction, organization, analysis, and retention of information due to the large volume of information that exists.

Therefore, this paper presents a comprehensive review of existing BI maturity models and elaborates their methodical and conceptual characteristics to determine their gaps in addressing the information life-cycle concept in terms of sensing, collecting, organizing, processing, and maintaining activities. As a result, a conceptual framework is proposed from the literature analysis. The intentions are to build a BI maturity model that can be used to increase the success of BI implementation by basing it on Information Management Practice (IMP), which a model built on the information life-cycle concept.

Keywords

Business Intelligence Maturity Model Information Life-Cycle Information Management Practise Literature Review 

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References

  1. 1.
    Aho, M.: A Capability Maturity Model for Corporate Performance Management, an Empirical Study in Large Finnish Manufacturing Companies. In: Proceedings from the eBRF 2009. Presented in the eBRF 2009 - A Research Forum to Understand Business in Knowledge Society in Jyväskylä, Finland (2009)Google Scholar
  2. 2.
    AlFedaghi, S.: Information Management and Valuation. International Journal of Engineering Business Management (2013)Google Scholar
  3. 3.
    Bach, J.: The immaturity of CMM. American Programmer 7(9), 13–18 (1994)Google Scholar
  4. 4.
    Biberoglu, E., Haddad, H.: A Survey of Industrial Experiences with CMM and the Teaching of CMM Practices. Journal of Computing Sciences in Colleges, S.143–S.152 (2002)Google Scholar
  5. 5.
    Brunelli, M.: BI, ERP top 2007’s IT spending list (2006), http://searchoracletechtarget.com/originalContent/0,289142,sid41gci1233170,00.html (accessed May 2013)
  6. 6.
    Bramer, M.: Artificial Intelligence: An International Perspective. LNCS, vol. 5640. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    King, W.R., Thompson, T.S.H.: Integration Between Business Systems Planning: Validating a Stage Hypothesis. Decision Sciences 28(2), 279–308 (1979)CrossRefGoogle Scholar
  8. 8.
    Cackett, D., Bond, A., Gouk, J.: Information Management and Big Data A Reference Architecture. Oracle Corporation (2013), http://www.oracle.com/technetwork/topics/entarch/articles/info-mgmt-big-data-ref-arch-1902853.pdf (accessed February 2013)
  9. 9.
    Cates, J.E., Gill, S.S., Zeituny, N.: The Ladder of Business Intelligence. Happy About Info. CA (2007)Google Scholar
  10. 10.
    Chamoni, P., Gluchowski, P.: Integration trends in business intelligence systems - An empirical study based on the business intelligence maturity model. Wirtschaftsinformatik 46(2), 119–128 (2004)CrossRefGoogle Scholar
  11. 11.
    Chee, T., Chan, L.-K., Chuah, M.-H., Tan, C.-S., Wong, S.-F., Yeoh, W.: Business Intelligence Systems: State-of-the-art Review and Contemporary Applications. Paper presented at the Symposium on Progress in Information and Technology (2009)Google Scholar
  12. 12.
    Chen, H., Chiang, R., Storey, V.: Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly 36(4), 1165–1188 (2012)Google Scholar
  13. 13.
    Chen, X.: Impact of Business Intelligence and IT Infrastructure Flexibility on Competitive Advantage: An Organizational Agility Perspective. Dissertations and Theses from the College of Business Administration. University of Nebraska (2012)Google Scholar
  14. 14.
    Choo, C.W.: Information management for the intelligent organization: The art of scanning the environment. Information Today, Medford (1998)Google Scholar
  15. 15.
    Choo, C.W.: Information Management for the Intelligent Organization: The Art of Scanning the Environment, 3rd edn. Information Today, Inc., Medford (2002)Google Scholar
  16. 16.
    Chuah, M., Wong, K.: A review of business intelligence and its maturity models. African Journal of Business Management 5(9), 3424–3428 (2011)Google Scholar
  17. 17.
    Davenport, T., Prusak, L.: Information ecology: Mastering the information and knowledge environment. Oxford University Press, New York (1997)Google Scholar
  18. 18.
    David, R., Felix, W., Robert, W.: Situational Business Intelligence Maturity Models: An Exploratory Analysis. In: HICSS 2013, pp. 3797–3806 (2013)Google Scholar
  19. 19.
    Deng, R.: Business Intelligence Maturity Hierarchy: A New Perspective from Knowledge Management. Information Management (2007), http://www.informationmanagement.com/infodirect/20070323/1079089-1.html
  20. 20.
    Eckerson, W.: Predictive Analytics. Extending the Value of Your Data Warehousing Investment. The Data Warehousing Institute (2007), https://www.tdwi.org/publications/whatworks/display.aspx?id=8452 (retrieved January 2012)
  21. 21.
    Ferris, J.: How to Compete on Analytics. The Analytical Center of Excellence. SAS Institute Inc. (2008)Google Scholar
  22. 22.
    Fisher, T.: How Mature Is Your Data Management Environment? Business Intelligence Journal 10(3), 20–26 (2005)Google Scholar
  23. 23.
    Fisher, T.: How Mature Is Your Data Management Environment (2007), http://www.tdan.com/view-articles/5831 (accessed February 2013)
  24. 24.
    Frates, J., Sharp, S.: Using business intelligence to discover new market opportunities. Journal of Competitive Intelligence and Management 3, 15–26 (2005)Google Scholar
  25. 25.
    Gable, G., Sedera, D., Chan, T.: Re-conceptualizing Information System Success: The IS-Impact Measurement Model. Journal of the Association for Information Systems 9(7), S.377–S.408 (2008)Google Scholar
  26. 26.
    Gartner Press Release. Gartner EXP survey of more than 1,400 CIOs shows CIOs must create leverage to remain relevant to the business (2007), http://www.gartner.com/itpage.jsp?id=501189/page.jsp?id=501189 (January 25, 2013 ) (retrieved) (accessed May 2013)
  27. 27.
    Gartner Press Release, Get Smarter Business Intelligence: Should You Create a BI Competency Center (2013), http://www.gartner.com/technology/cio-priorities/
  28. 28.
    Gilad, B.: Early Warning: Using Competitive Intelligence to Anticipate Market Shifts, Control Risk, and Create Powerful Strategies. American Management Association, New York (2004)Google Scholar
  29. 29.
    Grof, A.: Only the Paranoid Survive How to Exploit the Crisis Points that Challenge Every Company, 1st edn. Bantam books (1999)Google Scholar
  30. 30.
    Groom, J.R., David, F.R.: Competitive intelligence activity among small firms. SAM Advanced Management Journal, 12–20 (Winter 2001)Google Scholar
  31. 31.
    Hagerty, J.: AMR Research’s Business Intelligence/ Performance Management Maturity Model, Version 2 (2006), www.eurim.org.uk/.../ig/.../AMR_Researchs_Business_Intelligence.p (Accessed February 2013)
  32. 32.
    Hatcher, D., Prentice, B.: The Evolution of Information Management: A model for enabling companies to get maximum results from existing information (2004), http://www.ewsolutions.com/resource-center/rwds_folder/rwds-archives/rwds-2004-04/evolution-of-information-mgt (Accessed February 2013)
  33. 33.
    Hawking, P., Jovanovic, R., Sellitto, C.: Business Intelligence Maturity in Australia. Victoria University ERP Research Group (2010)Google Scholar
  34. 34.
    Henschen, D.: 2012 BI and Information Management Trends. Information week report (2011), http://www.umsl.edu/~sauterv/DSS/research-2012-bi-and-informationmanagement_9951311.pdf (Accessed May 2013)
  35. 35.
    Hewlett Packard (HP). “The HP Business Intelligence Maturity Model: De-scribing the BI journey”. Hewlett-Packard Development Company, L.P. (2009), http://www.computerwoche.de/fileserver/idgwpcw/files/1935.pdf (accessed February 2013)
  36. 36.
    Hostmann, B., et al.: Gartner’s Business Intelligence and Performance Management Framework. Gartner Inc. (2006), http://www.gartner.com (accessed May 2013)
  37. 37.
    Kasabian, D.: ‘I Can See Clearly Now’, Business Trends Quarterly (2007), http://www.btquarterly.com (viewed on May 16, 2009) (accessed May 2013)
  38. 38.
    Kasnik, A.: ‘Model optimization infrastructure’, Internal material of ZRSZ, Ljubljana (2008)Google Scholar
  39. 39.
    Kettinger, W.J., Marchand, D.A.: Information Management Practices (IMP) from the Senior Manager’s Perspective: An Investigation of the IMP Construct and Its Measurement. Information Systems Journal 21(5), 385–406 (2011)CrossRefGoogle Scholar
  40. 40.
    Koh, C.E., Watson, H.J.: Data management in executive information systems. Information and Management 33, 301–312 (1998)CrossRefGoogle Scholar
  41. 41.
    Lahrmann, G., et al.: Business Intelligence Maturity Models: An Overview. In: itAIS 2010. Springer, Naples (2010)Google Scholar
  42. 42.
    Lahrmann, G., Marx, F., Winter, R., Wortmann, F.: Business Intelligence Maturity: Development and Evaluation of a Theoretical Model. In: Proceedings of the 44th Hawaii International Conference on System Sciences (2011)Google Scholar
  43. 43.
    Manyika, J., Chui, M., Bughin, J., Brown, B., Dobbs, R., Roxburgh, C., Byers, A.H.: Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute (2011), http://www.mckinsey.com/mgi/publications/big_data/pdfs/MGI_big_data_full_report.pdf (accessed May 2013)
  44. 44.
    Marchand, D.A., Kettinger, W.J., Rollins, J.O.: Information orientation: The link to business performance. Oxford University Press, Oxford (2002)CrossRefGoogle Scholar
  45. 45.
    McGovern, J., Ambler, S.W., Stevens, M.E., Linn, J., Sharan, V., Jo, E.K.: A Practical Guide to Enterprise Architecture. Prentice Hall PTR (2004)Google Scholar
  46. 46.
    Microsoft. Business Productivity Infrastructure Optimization Campaign (2007), http://download.microsoft.com/.../BPIO_Module_25_Summary.ppt (accessed February 2013)
  47. 47.
    Miller, L., Schiller, D., Rhone, M.: DataWarehouse Maturity Assessment Service Lance (2009), http://www.teradata.com/.../Data-Warehouse-Maturity-Assessment-Service- (accessed February 2013)
  48. 48.
    Myllarniemi, J., Okkonen, J., Karkkainen, H.: Utilizing Business Intelligence Framework For Leveraging Products Lifecycle Management. In: The 9th International Conference on Electronic Business, Macau (2009)Google Scholar
  49. 49.
    Pawar, S.P., Sharda, R.: Obtaining business intelligence on the Internet. Long Range Planning 30(1), 110–121 (1997)CrossRefGoogle Scholar
  50. 50.
    Raber, D., Wortmann, F., Winter, R.: Situational Business Intelligence Maturity Models: An Exploratory Analysis. In: 46th Hawaii International Conference on System Sciences (2013)Google Scholar
  51. 51.
    Rajteric, I.: Overview of Business Intelligence Maturity Models. Int. J. Hum. Sci. 15(1), 47–67 (2010)Google Scholar
  52. 52.
    Rayner, N., Schlegel, K.: Maturity Model Overview for Business Intelligence and Performance Management, Gartner, Stamford (2008)Google Scholar
  53. 53.
    Riordan, P.: The CIO: MIS Makes its Move into the Executive Suite. Journal of Information Systems Management 4(3), 54–56 (1987)CrossRefGoogle Scholar
  54. 54.
    Rouibah, K., Ould-Ali, S.: PUZZLE: A concept and prototype for linking business intelligence to business strategy. Journal of Strategic Information System 11(2), 111–130 (2002)Google Scholar
  55. 55.
    Sacu, C., Spruit, M.: BIDM: The Business Intelligence development model. Technical report UU-CS-2010-010, Department of Information and Computing Sciences, Utrecht University (2010)Google Scholar
  56. 56.
    SAS. Information Evolution Model (2009), http://www.sas.com/software/iem (accessed February 2013)
  57. 57.
    Schulze, K.-D., Besbak, U., Dinter, B., Overmeyer, A., Schulz-Sacharow, C., Stenzel, E.: Business Intelligence-Studie, Steria Mummert Consulting AG, Hamburg (2009)Google Scholar
  58. 58.
    Sen, A., Sinha, A., Ramamurthy, K.: Data Warehousing Process Maturity: An Exploratory Study of Factors Influencing User Perceptions. IEEE Transactions on Engineering Management 53(3), S.440–S.455 (2006)Google Scholar
  59. 59.
    Short, J.: Information Lifecycle Management: An Analysis of End User Perspectives (2006)Google Scholar
  60. 60.
    SMC. Steria Mummert Consulting AG (2009), http://www.nomina.de/cognos/pdf/1s017_co.pdf (accessed February 2013)
  61. 61.
    Stock, P.: The Business Intelligence Maturity Model: describing the BI journey. YoungBlood (2013), http://www.young-blood.co.za/index.php/2013-02-10-10-55-36/mining-and-operations/item/20-bi-maturity-model (accessed May 2013)
  62. 62.
    Stone, P.J., et al.: The General Inquirer: A Computer Approach to Content Analysis. MIT Press, Cambridge (1966)Google Scholar
  63. 63.
    Swoyer, S.: Come Together: Business Intelligence and Enterprise Content Man-agement Bleed into Each Other. TDWI (2010), http://tdwi.org/Articles/2010/01/06/Come-Together-BI-and-ECM-Bleed-into-Each-Other.aspx?Page=1 (accessed February 2013)
  64. 64.
    Turban, E., Aronson, J.E., Liang, T.-P., Sharda, R.: Decision Support and Business Intelligence Systems, 8th edn. Pearson Education International, New Jersey (2007)Google Scholar
  65. 65.
    Yeoh, W., Koronios, A.: Critical Success Factors for Business Intelligence Systems. Journal of Computer Information Systems 50(3), 23–32 (2010)Google Scholar
  66. 66.
    Yeoh, W., Gao, J., Koronios, A.: Empirical Investigation of CSFs for Implementing Business Intelligence Systems in Multiple Engineering Asset Management Organisations. In: Cater-Steel, A., Al-Hakim, L. (eds.) Information Systems Research Methods, Epistemology, and Applications, pp. 247–271. IGI Global, Pennsylvania (2009)Google Scholar
  67. 67.
    Vitt, E., Luckevich, M., Misner, S.: Business Intelligence, Making Better Decisions Faster. Microsoft Press (2002)Google Scholar
  68. 68.
    Wang, R.Y., Lee, Y.W., Pipino, L.L., Strong, D.M.: Manage your Information as a Product. Sloan Management Review 39(4), 95–105 (1998)Google Scholar
  69. 69.
    Watson, H.J., Ariyachandra, T., Matyska, R.J.: Data warehousing stages of growth. Information Systems Management 18(3), 42–50 (2001)CrossRefGoogle Scholar
  70. 70.
    Wells, D.: Business analytics—Getting the point (2008), http://b-eye-network.com/view/7133 (accessed May 2013) (retrieved)
  71. 71.
    Whitehorn, M., Whitehorn, M.: Business Intelligence: The IBM Solution Data warehousing and OLAP. Springer, NY (1999)Google Scholar
  72. 72.
    William, S., William, N.: The Profit Impact of Business Intelligence. Morgan Kaufmann Publishers, San Francisco (2007)Google Scholar
  73. 73.
    William, N., Thomann, J.: ‘BI Maturity and ROI: How Does Your Organization Measure Up?’ (2003), http://www.decisionpath.com/docs_downloads/TDWI%20Flash%20%20BI%20Maturity%20and%20ROI%20110703.pdf (accessed January 2013)
  74. 74.
    Wright, S.: The CI marketing interface. Journal of Competitive Intelligence and Management 3(2), 3–7 (2005)Google Scholar
  75. 75.
    Zeid, A.: Driving Innovation – The Information Evolution Model. In: Statistics Canada Information Technology Conference (2009), http://www.statcan.gc.ca/conferences/it-ti2009/ppt/session15-aiman-fra.ppt (accessed February 2013)

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alaskar Thamir
    • 1
  • Babis Theodoulidis
    • 1
  1. 1.Manchester Business SchoolUniversity of ManchesterManchesterUK

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