Complementarity as a Driver of Value in Business Intelligence and Analytics Adoption Processes

Valter Moreno, Felipe Elias Lobo Vieira da Silva, Rodrigo Ferreira, Fernando Filardi

Abstract


Objective: Investments in Business Intelligence and Analytics (BI&A) are increasingly essential to a firm’s competitiveness. Drawing on the Resource-Based View (RBV), our objective is to analyze the implementation of a BI&A system at the Brazilian National Bank of Economic and Social Development (BNDES) to assess the generation of business value for the organization.

Methodology: We collected qualitative data through interviews, participant observation, and internal documents and communications. For data analysis, we followed the general coding, aggregation and synthesis process with the use of the qualitative data analysis software Atlas.ti.

Originality: Traditional Information Technology (IT) investment evaluation frameworks, especially on BI&A systems, neglect the dynamic nature and the mutual influences of Information Systems assets and capabilities. Also, these frameworks lack studies on complementary socio-organizational capabilities in the business value generation process. Furthermore, RBV has rarely been employed in the study of the impact of BI&A in organizations.

Main results: Our results revealed the critical role played by IT and organizational resources and capacities in the BI&A adoption process, as well as the importance of the dynamics of complementarity and its positive outcomes in business.

Theoretical contribution: In our research, we provide evidence of RBV’s potential to elucidate the complexities regarding the generation of sustainable business value, and therefore to explain the distinct results obtained by organizations that adopt BI&A technologies.

 


Keywords


Business Intelligence; Information Technology Management; Resource-Based View; IT Value; Complementary Resources

References


Arvidsson, V., Holmström, J., & Lyytinen, K. (2014). Information systems use as strategy practice: A multi-dimensional view of strategic information system implementation and use. The Journal of Strategic Information Systems, 23: 45–61.

Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17 (1), 99.

Barney, J. B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view. Journal of Management, 27 (6), 643–650.

Chae, B., Olson, D., & Sheu, C. (2014). The impact of supply chain analytics on operational performance: a resource-based view. International Journal of Production Research, 52(16), 4695–4710.

Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36: 1165–1188.

Côrte-Real, N., Oliveira, T., & Ruivo, P. (2017). Assessing business value of Big Data Analytics in European firms. Journal of Business Research, 70: 379–390.

Crook, T. R., Ketchen Jr, D. J., Combs, J. G., & Todd, S. Y. (2008). Strategic resources and performance: a meta-analysis. Strategic Management Journal, 29: 1141–1154.

Dobrev, K., & Hart, M. (2015). Benefits, Justification and Implementation Planning of Real-Time Business Intelligence Systems. Electronic Journal of Information Systems Evaluation, 18(2), 104.

Fink, L., Yogev, N., & Even, A. (2017). Business intelligence and organizational learning: An empirical investigation of value creation processes. Information & Management, 54(1), 38–56. https://doi.org/10.1016/j.im.2016.03.009

Friese, S. (2014). Qualitative Data Analysis with ATLAS.ti (2nd ed.). Thousand Oaks, CA: Sage Publications.

Gartner. (2017, February 17). Analytics Trends to Be Explored at Gartner Data & Analytics Summits 2017. Retrieved September 24, 2018, from https://www.gartner.com/en/newsroom/press-releases/2017-02-17-gartner-says-worldwide-business-intelligence-and-analytics-market-to-reach-18-billion-in-2017

Hughes, D. L., Dwivedi, Y. K., Simintiras, A. C., & Rana, N. P. (2016). Project Failure and Its Contributing Factors. Success and Failure of IS/IT Projects: A State of the Art Analysis and Future Directions. New York: Springer International Publishing.

Kakhki, M. D., & Palvia, P. (2016). Effect of Business Intelligence and Analytics on Business Performance. In Proceedings of the XXII Americas Conference on Information Systems (AMCIS) (pp. 1–10). San Diego: Association for Information Systems (AIS).

Mata, F. J., Fuerst, W. L., & Barney, J. B. (1995). Information technology and sustained competitive advantage: a resource-based analysis. MIS Quarterly, 19: 487–505.

Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information Technology and Organizational Performance: An Integrative Model of IT Business Value. MIS Quarterly, 28(2), 283–322.

Miller, G. J., Bräutigam, D., & Gerlach, S. V. (2006). Business intelligence competency centers: a team approach to maximizing competitive advantage, 8. John Wiley & Sons.

Namvar, M., Cybulski, J. L., & Perera, L. (2016). Using business intelligence to support the process of organizational sensemaking. Communications of the Association for Information Systems, 38: 330–352.

Negash, S. (2004). Business Intelligence. Communications of the Associations for Information Systems, 13: 177-195.

Nevo, S., & Wade, M. (2011). Firm-level benefits of IT-enabled resources: A conceptual extension and an empirical assessment. Journal of Strategic Information Systems, 20(4), 403–418.

Nevo, S., & Wade, M. R. (2010). The Formation and Value of IT-enabled Resources: Antecedents and Consequences of Synergistic Relationships. MIS Quarterly, 34(1), 163–183.

Olszak, C. M. (2016). Toward Better Understanding and Use of Business Intelligence in Organizations. Information Systems Management, 33(2), 105–123.

Park, Y., El Sawy, O. A., & Fiss, P. C. (2017). The Role of Business Intelligence and Communication Technologies in Organizational Agility: A Configurational Approach. Journal of the Association for Information Systems, 18(9).

Popovič, A., Turk, T., & Jaklič, J. (2010). Conceptual Model of Business Value of Business Intelligence Systems. Management: Journal of Contemporary Management, 15(1), 5–29.

Ray, G., Barney, J. B., & Muhanna, W. A. (2004). Capabilities, business processes, and competitive advantage: Choosing the dependent variable in empirical tests of the resource-based view. Strategic Management Journal, 25: 23–37.

Rivard, S., Raymond, L., & Verreault, D. (2006). Resource-based view and competitive strategy: An integrated model of the contribution of information technology to firm performance. The Journal of Strategic Information Systems, 15: 29–50.

Sabherwal, R., & Jeyaraj, A. (2015). Information Technology Impacts on Firm Performance: An Extension of Kohli and Devaraj (2003). MIS Quarterly, 39: 809–836.

Sangari, M. S., & Razmi, J. (2015). Business intelligence competence, agile capabilities, and agile performance in supply chain. International Journal of Logistics Management, 26(2), 356–380.

Schmidt, J., & Keil, T. (2013). What Makes a Resource Valuable? Identifying the Drivers of Firm-Idiosyncratic Resource Value. Academy of Management Review, 38: 206–228.

Schryen, G. (2013). Revisiting IS business value research: what we already know, what we still need to know, and how we can get there. European Journal of Information Systems, 22(2), 139–169.

Seddon, P. B., Constantinidis, D., Tamm, T., & Dod, H. (2017). How does business analytics contribute to business value? Information Systems Journal, 27(3), 237–269.

Shen, J., Li, Y., Akula, V., Yan, G., Tao, R., & others. (2015). Gaining competitive intelligence from social media data. Industrial Management & Data Systems, 115(9), 1622–1636.

Torres, R., Sidorova, A., & Jones, M. C. (2018). Enabling firm performance through business intelligence and analytics: A dynamic capabilities perspective. Information & Management.

Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2), 626–639.

Wade, M., & Hulland, J. (2004). Resource-Based View and Information Systems Research: Review, Extension, and Suggestions for Future Research. MIS Quarterly, 28(1), 107–142.

Wang, Y., & Byrd, T. A. (2017). Business analytics-enabled decision-making effectiveness through knowledge absorptive capacity in health care. Journal of Knowledge Management, 21(3), 517–539.

Watson, H. J. (2009). Tutorial: Business Intelligence: Past, Present and Future. Communications of the Association for Information systems, 25, article 39.

Winter, S. G. (2003). Understanding Dynamic Capabilities. Strategic Management Journal, 24: 991–995.

Wixom, B. H., Yen, B., & Relich, M. (2013). Maximizing Value from Business Analytics. MIS Quarterly Executive, 12(2): 111–123.

Wixom, B., & Watson, H. J. (2010). The BI-based Organization. International Journal of Business Intelligence Research, 1: 13–28.

Yeoh, W., & Popovič, A. (2016). Extending the understanding of critical success factors for implementing business intelligence systems. Journal of the Association for Information Science and Technology, 67: 134–147.

Yin, R. K. (2013). Case Study Research: Design and Methods. 5th ed. Sage Publications.


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