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Delivering Internal Business Intelligence Services: How Different Strategies Allow Companies to Succeed by Failing Fast

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Aligning Business Strategies and Analytics

Part of the book series: Advances in Analytics and Data Science ((AADS,volume 1))

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Abstract

This chapter reviews opportunities and issues propelling and limiting the success of business intelligence and analytics services for a company’s internal use. We describe three strategies for providing these services internally (on-premises, cloud, and hybrid) and explore issues of importance in the shaping of current demand and of future offerings by web-based providers. It also discusses opportunities for the development of academic curricula to offer better training to graduate and improve recruiting outcomes for organizations and for the development of more relevant academic research to address topics of current and strategic importance to the firm.

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References

  • Armbrust, M., Fox, A. Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., et al. (2009, February 10). Above the clouds: A Berkeley view of cloud computing. Retrieved from https://www2.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdf

  • Arthur, W. B. (1989). Competing technologies, increasing returns, and lock-in by historical events. The Economic Journal, 99, 116.

    Article  Google Scholar 

  • Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120.

    Article  Google Scholar 

  • Berners-Lee, T., Hendler, J., & Lassila, O. (2001 May). The semantic web. Scientific American, 284(5), 34–43.

    Article  Google Scholar 

  • Carr, N. G. (2003 May). IT Doesn’t matter. Harvard Business Review. Retrieved from https://hbr.org/2003/05/it-doesnt-matter

  • Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Communications of the ACM, 54, 88–98.

    Article  Google Scholar 

  • Chen, H., Chiang, R. H., & Storey, V. C. (2012 Dec). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188.

    Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128.

    Article  Google Scholar 

  • D’Aveni, R. (1994). Hypercompetition: Managing the dynamics of strategic maneuvering. New York: Free Press.

    Google Scholar 

  • Darrow, B. (2015). Shocker! Amazon remains the top dog in cloud by far, but Microsoft, Google make strides. Fortune.com. Retrieved from http://fortune.com/2015/05/19/amazon-tops-in-cloud/

  • Davenport, T. (2013 Dec). Analytics 3.0. Harvard Business Review, 91(12).

    Google Scholar 

  • Davenport, T. H. (2006). Competing on analytics. Harvard Business Review, 84(1), 98.

    Google Scholar 

  • DeLua, J. (2008). Building a common data foundation for Enterprise Integration and Growth. Business Intelligence Journal, 13, 52–56.

    Google Scholar 

  • Devlin, B. (2010). Beyond business intelligence. Business Intelligence Journal, 15, 7–16.

    Google Scholar 

  • ElBashir, M. Z., Collier, P. A., & Sutton, S. G. (2011). The role of organizational absorptive capacity in strategic use of business intelligence to support integrated management control systems. The Accounting Review, 86, 155–184.

    Article  Google Scholar 

  • Evelson, B. (2011, March 31). Trends 2011 and beyond: Business intelligence. Forrester Research. Retrieved from https://www.forrester.com/report/Trends+2011+And+Beyond+Business+Intelligence/-/E-RES58854

  • Gartner (2013, February 19). Gartner says worldwide business intelligence software revenue to grow 7 percent in 2013. Gartner. Retrieved from https://www.gartner.com/newsroom/id/2340216

  • Goldman, S. L., Nagel, R. N., & Preiss, K. (1995). Agile competitors and virtual organizations: Strategies for enriching the customers. New York: Wiley.

    Google Scholar 

  • Heizenberg, J., Lo, T., & Chandler, N. (2017, February 14). Magic quadrant for business analytics services, Worldwide. Gartner. Retrieved from https://www.gartner.com/doc/3606022/magic-quadrant-business-analytics-services

  • International Institute for Analytics (2016). Business intelligence and analytics capabilities report. Portlan, OR (Document No. 108549_G38359.1016).

    Google Scholar 

  • James, J. (2016, February 14). Magic Quadrant for Business Analytics Services, Worldwide. Gartner. Retrieved from https://www.gartner.com/doc/3606022/magic-quMagic%20Quadrant%20for%20Business%20Analytics%20Servicesadrant-business-analytics-services

  • Jourdan, Z., Rainer, R. K., & Marshall, T. E. (2008). Business intelligence: An analysis of the literature. Information Systems Management, 25, 121–131.

    Article  Google Scholar 

  • Kappelman, L., Mclean, E., Johnson, V., Gerhart, N., Stewart, B., Peterson, B., et al. (2015). Issues, investments, concerns, and practices of organizations and their IT executives: Results and observations from the 2015 SIM IT trends study. Society for Information Management.

    Google Scholar 

  • Keen, P. G. W. (1991). Relevance and rigor in information systems research: Improving quality, confidence, cohesion and impact. Information systems research. Elsevier Science Publishers.

    Google Scholar 

  • Lang, M. (2003). Communicating academic research findings to IS professionals: An analysis of problems. Informing Science, 6, 21–29.

    Article  Google Scholar 

  • Laskowski, N. (2015). Ten analytics success stories in a nutshell. CIO decisions (CIO.com), published April 27, 2015 [Last accessed April 5, 2018], (at http://searchcio.techtarget.com/opinion/Ten-analytics-success-stories-in-a-nutshell).

  • Lee, A. S. (2010). Retrospect and prospect: Information systems research in the last and next 25 years. Journal of Information Technology, 25, 336–348.

    Article  Google Scholar 

  • Lee, H., Kim, J., & Kim, J. (2007). Determinants of success for application service provider: An empirical test in small businesses. International Journal of Human-Computer Studies, 65, 796–815.

    Article  Google Scholar 

  • LeMerle, M. (2012). It’s time for ‘Service as a Service’. Financial Times. Retrieved from https://www.ft.com/content/f88bc87a-0e4b-11e2-8b92-00144feabdc0

  • Liu, A. (2016). TOP 10 Best Cloud Providers 2016. Cloud Spectator. Retrieved from https://cloudspectator.com/best-cloud-providers-2016/

  • Lowry, P. B., Moody, G. D., Gaskin, J., Galletta, D. F., Sean, H., Barlow, J. B., & Wilson, D. (2013). Evaluating journal quality and the Association for Information Systems (AIS) senior scholars’ journal basket via bibliometric measures: Do expert journal assessments add value? MIS Quarterly, 37, 993–1012.

    Article  Google Scholar 

  • Luftman, J., & Derksen, B. (2012). Key issues for IT executives 2012: Doing more with less. MIS Quarterly Executive, 11, 207–218.

    Google Scholar 

  • Luftman, J., Kempaiah, R., & Nash, E. (2005). Key issues of IT executives. MIS Quarterly Executive., 4(2), 269–285.

    Google Scholar 

  • Luftman, J., & Mclean, E. R. (2004). Key issues for IT executives. MIS Quarterly Executive, 3, 89–104.

    Google Scholar 

  • Luftman, J., Zadeh, H. S., Derksen, B., Santana, M., Rigoni, E. H., & Huang, Z. D. (2013). Key information technology and management issues 2012-2013: An international study. Journal of Information Technology, 28, 354–366.

    Article  Google Scholar 

  • Luhn, H. P. (1958). A Business Intelligence System. IBM Journal of Research & Development, 2, 314.

    Article  Google Scholar 

  • McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90, 59–68.

    Google Scholar 

  • Mell, P., & Grance, T. (2011). The NIST definition of cloud computing. United States Department of Commerce, National Institute of Standards & Technology (NIST), Report No. 800-145.

    Google Scholar 

  • Ong, I. L., Siew, P. H., & Wong, S. F. (2011). A Five-Layered Business Intelligence Architecture. Communications of the International Business Information Management Association (IBIMA.) Retrieved from http://ibimapublishing.com/articles/CIBIMA/2011/695619/695619.pdf

  • Orlikowski, W., & Baroudi, J. J. (1991). Studying information technology in organizations: Research approaches and assumptions. Information Systems Research, 2, 1–28.

    Article  Google Scholar 

  • Orlikowski, W., & Iacono, S. (2001). Desperately seeking the IT in IT research: A call to theorizing the IT artifact. Information Systems Research., 12, 121–134.

    Article  Google Scholar 

  • Robey, D., & Markus, M. L. (1998). Beyond rigor and relevance: Producing consumable research about information systems. Information Resources Management Journal, 11, 7–15.

    Article  Google Scholar 

  • Ross, J. W. (2003). Creating a strategic IT architecture competency: Learning in stages. MIS Quarterly Executive, 2, 31–43.

    Google Scholar 

  • Sallam, R. L., Howson, C., Idoine, C. J., Oestreich, T. W., Richardson, J. L., & Tapadinhas, J. (2017). Magic quadrant for business intelligence and analytics platforms. Stamford, CT: Gartner.

    Google Scholar 

  • Sambamurthy, V., Bharadwaj, A., & Grover, V. (2003). Shaping agility through digital options: Reconceptualizing the role of information technology in contemporary firms. MIS Quarterly, 27, 237–263.

    Article  Google Scholar 

  • Shapiro, C., & Varian, H. R. (1999). Information rules: A strategic guide to the network economy. Boston: Harvard Business School Press.

    Google Scholar 

  • Shariat, M., & Hightower, R. (2007). Conceptualizing business intelligence architecture. Marketing Management Journal, 17, 40–46.

    Google Scholar 

  • Soares, S. (2015). The chief data officer handbook for data governance. Chicago: Mc Press.

    Google Scholar 

  • Song, H., Chauvel, F., Solberg, A., Foyn, B. & Yates, T. (2017). How to Support Customisation on SaaS: A Grounded Theory from Customisation Consultants. IEEE International Conference on Software Engineering. Buenos Aires, Argentina, IEEE.

    Google Scholar 

  • Tallon, P. P., Short, J. E., & Harkins, M. W. (2013). The evolution of information governance at Intel. MIS Quarterly Executive, 12, 189–198.

    Google Scholar 

  • Thompson, J. K. (2009). Business intelligence in a SaaS environment. Business Intelligence Journal, 14, 50–55.

    Google Scholar 

  • Turban, E., Sharda, R., Aronson, J. E., & King, D. (2008). Business intelligence: A managerial approach. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • van der Lans, R. (2009a, March 04). The flaws of the classic data warehouse architecture, Part 1. BeyeNetwork. Retrieved from http://www.b-eye-network.com/view/9752

  • van der Lans, R. (2009b, April 1). The flaws of the classic data warehouse architecture, Part 2. BeyeNetwork. Retrieved from http://www.b-eye-network.com/view/9960

  • van der Lans, R. (2009c, May 12). The flaws of the classic data warehouse architecture, Part 3. BeyeNetwork. Retrieved from http://www.b-eye-network.com/view/10342

  • Van Grembergen, W. (2002). Introduction to the Minitrack: IT Governance and its Mechanisms. Hawaii International Conference on System Sciences. Waikoloa, Hawaii.

    Google Scholar 

  • Vedder, R. G., Vanecek, M. T., Guynes, C. S., & Cappel, J. J. (1999). CEO and CIO perspectives on competitive intelligence. Communications of the ACM, 42, 109–116.

    Article  Google Scholar 

  • Watson, H. J. (2009). Tutorial: Business intelligence - past, present, and future. Communications of the AIS, 25, 487–510.

    Google Scholar 

  • Wixom, B., Ariyachandra, T., Douglas, D., Goul, M., Gupta, B., Iyer, L., et al. (2014). The current state of business intelligence in academia: The Arrival of Big Data. Communications of the Association for Information Systems, 34, 1–13.

    Google Scholar 

  • Wixom, B., Ariyachandra, T., Goul, M., Gray, P., Kulkarni, U., & Phillips-Wren, G. (2011). The current state of business intelligence in academia. Communications of the Association for Information Systems, 29, 299–312.

    Google Scholar 

  • Wixom, B., Yen, B., & Relich, M. (2013). Maximizing value from business analytics. MIS Quarterly Executive, 12(2), 111–123.

    Google Scholar 

  • Yeoh, W., Richards, G., & Wang, S. (2013). Linking BI competency and assimilation through absorptive capacity: A conceptual framework. In PACIS 2013: Smart, open and social information systems: Proceedings of the 17th Pacific Asia Conference on Information Systems (pp. 1–9). Association for Information Systems.

    Google Scholar 

  • Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27, 185.

    Article  Google Scholar 

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Correspondence to Rubén A. Mendoza .

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Mendoza, R.A. (2019). Delivering Internal Business Intelligence Services: How Different Strategies Allow Companies to Succeed by Failing Fast. In: Anandarajan, M., Harrison, T. (eds) Aligning Business Strategies and Analytics. Advances in Analytics and Data Science, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-93299-6_10

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