Achieving Efficient Business Performance through Implementation of Business Intelligence Analytics
Abstract
This study investigates the impact of Business Intelligence (BI) and Business Analytics (BA) on business
performance. Using a sample of 383 respondents, data were collected on demographic characteristics and levels of exposure
to BI and BA tools. The study employed independent t-test analysis to examine two hypotheses: the effect of BI on business
performance and the effect of BA on business performance. Results showed statistically significant differences between
groups with high and low engagement in both BI and BA. Specifically, respondents with higher exposure to BI and BA
reported significantly better performance outcomes compared to those with lower exposure. These findings suggest that BI
and BA are critical drivers of organizational productivity and effectiveness. The study concludes that organizations aiming
to enhance business performance should invest in BI and BA capabilities, integrate them into their strategic processes, and
provide continuous training to employees. Recommendations include fostering a data-driven culture, aligning BI/BA
initiatives with business goals, and adopting continuous performance evaluation systems.
References
Agrawal et al., 2001). Why is business intelligence (BI) important to your company? Retrieved on 29th July, 2018.
Allen, R., and Meyers, G., (1990). The role of business intelligence tools in the decision making process. International Journal of
Computer Applications, 7 (3), 16-31.
Anandarajan, W., Srinivasan, C., and Anandarajan, N., (2004). Business models and technological innovation. Long range
planning, 4 (6), 419-426.
Atkinson et al. (1997). Antecedents and enablers of supply chain agility and its effect on performance: a dynamic capabilities
perspective. International Journal of Production Research, 5 (1), 1295-1318
Atkinson, F., Waterhouse, R., and Wells, K., (2009). The third international conference on business intelligence and
technology, 21-26. Analysis of interaction between business intelligence and SMEs: learn from each other.
Baars, O., & Kemper, D., (2008). Application of decision-making techniques in supplier, selection: A systematic review of
literature. Expert Systems with Applications, (40), 3872–3885. European Journal of Business and Innovation Research Vol.7,
No.2, pp.1-21, March 2019
___Published by the European Centre for Research Training and Development UK (www.eajournals.org) 20
Dr. Duezeh, Emmanuel Afamefuna ( American Journal of Business Practice)
American Journal of Business Practice 203
Bose, B., (2006). The role of competitive intelligence in strategic purchasing decisions and its influence on suppliers’ resource
allocation. Unpublished Master's dissertation, Technical University of Berlin.
Chen, F., & Siau, S., (2012). Competitive intelligence systems: relationships to strategic orientation and perceived usefulness.
Journal of Managerial Issues, 7 (4), 420-434. Competitive Intelligence and Management 3 (4) ,15–35.
Clark et al. (2007). Benefits of ontologies in real time data access. Digital Ecosystems and Technologies Conference, DEST '1 (7),
392-397.
Implementation of public hospitals data. 3 (1), 23-67.
Dinter, C., (2012). Implementation of a data-based medical event reporting system in the US department of defense. 3rd
editors. Advances in Patient Safety: From Research to Implementation (Rockville
(MD): Agency for Healthcare Research and Quality (US).
Elbashir et al. (2008). Five elements of organizational success. Retrieved on 6th July, 2018 from <
https://www.elementalpartners.net >
Frolick, E., & Ariyachandra, M., (2006). Causes of E-Government success and failure homepage of IDPM, University of
Manchester. Retrieved on 29th July, 2018 from http://www.edevexchange.org/eGov/causefactor.htm.
Frolick, H., Thilini, C., and Ariyachandra, M., (2012). Business intelligence: Overview and Case Reports. Professional MBA
Program IS 6800.
Graham, F., (2009) Introduction to Business Intelligence. A Publication of IBM Software Group I
Han, S., and Kamber, A., (2000). Strategic intelligence and knowledge management: How Organizations can improve their
Decision-making Process Published by University of Khaje Nasir.
Kaplan, U., and Norton, J., (2010). Competitive intelligence: Bridging organizational boundaries. "Information Management Journal
2 (1), 46-55.
Lahrmann et al. (2011). Introduction to the SAS 9 business intelligence platform: A Tutorial. Retrieved from on 29th July, 2018 <
http://www.thowave, com >
Laura, G., Shawnee, E., and Cornelia, P., (2009). Business intelligence systems in holistic infrastructure development support
decision-making in organizations. Interdisciplinary Journal of Information, Knowledge, and Management, 1 (1), 47-57. European
Journal of Business and Innovation Research Vol.7, No.2, pp.1-21, March 2019
___Published by the European Centre for Research Training and Development UK (www.eajournals.org) 21
Likert, W., (1932). The information systems age. Retrieved on 29th July, 2018 from
www.the age.com.au/articles
Mann, B., and Kehoe, K., (2009). Business intelligence: Concepts, components, techniques and benefits. Journal of Theoretical
and Applied Information Technology 1 (9), 060–070.
Maskell, C., (2012).. Diffusion of Innovations (1st ed.). The Free Press, New York.
Mooney et al. (1996).Africa's survival plan for meeting the challenges of information technology in the 1990s and beyond.
Libri, 44 (1), 77-94.
Müller et al. (2010). Oracle data warehousing and business intelligence solutions. Wiley Publishing, Inc, Indianapolis.
Dr. Duezeh, Emmanuel Afamefuna ( American Journal of Business Practice)
American Journal of Business Practice 204
Negash, B., (2004). Difference between efficiency and effectiveness. Retrieved on 6th July, 2018 from < https://www. >
keydifference .com
Ranjan, D., (2009). Identified key success factors for developing competitive intelligence in an organization. American Journal
of Business and Management, 2 (3), 239-244.
Sahay, F., & Ranjan, D., (2008).Techniques, process, and enterprise
solutions of business intelligence ’, Conference on Systems, Man, and Cybernetics October 8-11, 2006, Taipei, Taiwan, 2 (6), 47-56
Slater, V., Olson, H., and Reddy, W., (2012). An empirical assessment of the "fit" between strategy and management
information design. Accounting and Finance, 34, 49-66.
Teseema, G., and Socters, I., (2006). A stakeholder approach to strategic
performance measurement. Sloan Management Review, 39 (3), 25-37.
Unyimadu, S., (2005). Management support with structured and unstructured data: an integrated business intelligence
framework. Information Systems Management, 25 (2), 132-148.
Uzoagulu, K., (1998). Understanding management data systems for enterprise performance management. Industrial
Management and Data Systems, 106 (1), 132-148.
Vander, Y., Meer et al., 2012). Performance effects of using the balanced scorecard: A note on the Dutch experience. Long
Range Planning, 37, 335-349.
Watson, J., & Wixom, O., (2007). Performance consequences of Balanced Scorecard adoptions: claim for large-scale evidence
and propositions for future research. In M.J. Epstein, J.F. Manzoni & A. Davila (Eds.). Performance Measurement and
Management Control: Innovative Concepts and
Practices. Emerald Group Publishing: Bingley, UK, 345-361
Wixom, et al. (2008). Business intelligence and Analytics: From big data to
big impact. MIS Quarterly, 36 (4), 1165-1188.
Wixom, W., & Watson, K., (2010). The Impact of Business Intelligence and Flexibility in IT Infrastructure on Organizational
AgilityThirty Third International Conference on Information Systems. Orlando.
Wood, S., (2006). The dynamic structure of management support
systems: Theory development, research focus and direction. MIS Quarterly, 579-615.
Yeoh, R., & Koronios, I., (2010). Competing on analytics. Harvard Business Review, 2-10.
