Integrating Business Intelligence and Analytics in Managing Public Sector Performance: An Empirical Study

Nur Hani Zulkifli Abai, Jamaiah Yahaya, Aziz Deraman, Abdul Razak Hamdan, Zulkefli Mansor, Yusmadi Yah Jusoh


Business intelligence and analytics (BIA) is emerging as a critical area to boost organizational performance. Nowadays, data is not only important and valuable to the organization but recognized as necessary to spike the organization performance and success. As a result, many organizations spend a considerable amount of investment toward obtaining faster accurate information on a real-time basis. The previous study revealed that even though many organizations use business intelligence technologies for obtaining information, yet they still lack analytics implementation. Therefore, this study aims to discover the integrated implementation factors of business intelligence and analytics in managing organizational performance, particularly for organizations of the public sector. In achieving this, a depth literature review was carried out to identify the influential factors in the implementation of business intelligence, business analytics, and performance management. The subject matter experts in Business Intelligence (BI), Business Analytics (BA) and Organisational Performance Management (OPM) were invited to participate in this empirical study, which was conducted in Malaysia. The study was carried out through interviewing experts, in order to identify the essential factors for business intelligence and data analytics implementation. Twenty essential factors and sixty-four sub-factors were identified and analyzed to construct the integrated factors in BIA and OPM implementation. The result of the study revealed four integrated factors of the BIA and OPM implementation, such as skill, documentation, visualization, and work culture. Finance, data management, software, strategic planning, and decision-making are other factors integrated with BI, BA, and OPM respectively. Finally, this study illustrates the integrated factors in a visual form.


business intelligence; business analytics; organisational performance management; public sector; implementation factor.

Full Text:



C. Pollitt, “The logics of performance management,” Evaluation, vol. 19, no. 4, pp. 346–363, 2013.

C. Holsapple, A. Lee-Post, and R. Pakath, “A unified foundation for business analytics,” Decis. Support Syst., vol. 64, pp. 130–141, Aug. 2014.

T. Klatt, M. Schlaefke and K. Moeller, “Integrating business analytics into strategic planning for better performance,” J. Bus. Strategy, vol. 32, no. 6, pp. 30–39, 2011.

H. Chen, R. H. L. Chiang, V. C. Storey, R. H. L. Chiang, and V. C. Storey, “Business intelligence and analytics : from big data to big ompact,” MIS Q. Spec. Ed. Bus. Intell. Res., vol. 36, no. 4, pp. 1165–1188, Dec. 2012.

A. Martin, T. Miranda Lakshmi, and V. P. Venkatesan, “A business intelligence framework for business performance using data mining techniques,” 2012 Int. Conf. Emerg. Trends Sci. Eng. Technol., Dec. 2012. pp. 373–380.

T. Alaskar, P. Efthimios, “Business intelligence capabilities and implementation strategies” International Journal of Global Business, vol. 8, no. 1, pp. 34-45, June 2015.

A. Audzeyeva and R.Hudson, “How to get the most from a business intelligence application during the post implementation phase? Deep structure transformation at a U.K. retail bank”, European Journal of Information Systems, vol. 25, no. 1, pp. 29–46, 2016.

N. H. Zulkifli Abai, J. H. Yahaya and A. Deraman, "The determinants of integrated business intelligence and analytics in organisational performance process," The 6th International Conference on Electrical Engineering and Informatics (ICEEI), Langkawi, Nov 2017, pp. 1-6., (2018) Business Intelligence, [Online]. Available:

M. Obeidat, M. North, R. Richardson, V. Rattanak and S. North, "Business intelligence technology, applications and trends", International Management Review, vol. 11, no. 2, 2015, pp. 47-56.

V. L. Sauter, Decision Support Systems for Business Intelligence. New Jersey: Wiley, 2010.

C. Elena, “Business intelligence,” J. Knowl. Manag. Econ. Inf. Technol., vol. 1, p. 101, 2011.

W. H. Inmon, Building the data warehouse, 5th Edition, John Wiley & Sons, 2005.

S. Jou and R. Ng, "Introduction and the changing landscape of business intelligence,” in Perspectives on Business Intelligence, Morgan & Claypool Publishers, pp. 1–3, 2013.

W. Grossmann and S. Rinderle-Ma, Fundamentals of Business intelligence, Springer, 2015.

B. Gupta, M. Goul and B. Dinter, "Business intelligence and big data in higher education: status of a multi-year model curriculum development effort for business school undergraduates, MS graduates, and MBAs", Communications of the Association for Information Systems, vol 36, article 23, 2015.

L. Serbanescu, “Necessity to Implement a Business Intelligence Solution for the Management Optimization of a Company,” USV Ann. Econ. Public Adm., vol. 12, no. 2, pp. 114–123, 2012.

S. Moro, P. Cortez, and P. Rita, "Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation", Expert Systems with Applications,vol. 42, no. 3, pp. 1314-1324, 15 Feb. 2015.

M. Zamani, Maeen and M. Haghparast, “Ïmplemenatation of business intelligence to increase the effectiveness of decision making process of managers in companies providing payment services,” Journal of Internet Banking and Commerce, vol. 22, no. S8, pp 1-24, 2017.

C. Loebbecke and A. Picot, "Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda", The Journal of Strategic Information Systems, vol. 24, no. 3, pp. 149-157, Sept. 2015.

Y. Jarrar. (2017) "What is the role of Government in the digital age?" World Economic Forum, [Online] available from

C. M. Olszak, “Business Intelligence and Analytics in Organizations,” in Advances in ICT for Business, Industry and Public Sector, vol. 579, 2015.

G.H.N. Laursen and J Thorlund, Business Analytics for Managers: Taking Business Intelligence Beyond Reporting, second edition, Wiley 2017.

R Fitriana, J Saragih and N Luthfiana “Model business intelligence system design of quality products by using data mining in R Bakery Company”, IOP Conference Series: Materials Science and Engineering, vol. 277, conference 1, 2017, pp. 1-8.

A. Mutanga, "A Context-based Business Intelligence Solution for South African Higher Education", Journal of Industrial and Intelligent Information, vol. 3, no. 2, pp. 119-125, June 2015.

CRISP-DM, “Cross-Industry Standard Process for Data Mining (CRISP-DM),” 2013.

W. Albright, Business Analytics : Data Analysis and Decision Making. Cengage Learning, 2015.

M. Tavana & K. Puranam, Handbook of Research on Organizational transformation through Big Data Analytics. IGI Global, Hershey PA, 2015.

The BPM Standard Group. (2005) “Business Performance Managenent : Industry Framework Document,” [Online] Available from

N. Mirsepasi, A. Faghihi, and M. R. Babaei, “Design a system model for performance management in the public sector,” Arab. J. Bus. Manag. Rev., vol. 1, no. 4, pp. 23–32, 2013.

M. Tresnadi, I. Primiana, and D. Wibisono, “Analyzing mainstreams in current performance management studies and its relationship with HR and other practices : A literature review,” Sains Humanika, vol. 2, pp. 41–51, 2016.

P. I. Bogdana, A. Felicia, and B. Delia, “The role of business intelligence in business performance management,” Ann. Fac. Econ., vol. 4, no. 1, pp. 1025–1029, 2009.

M. Bronzo, P. T. V. de Resende, M. P. V. de Oliveira, K. P. McCormack, P. R. de Sousa, and R. L. Ferreira, “Improving performance aligning business analytics with process orientation,” Int. J. Inf. Manage., vol. 33, no. 2, pp. 300–307, Apr. 2013.

R. S. Kaplan, “Strategic performance measurement and management in nonprofit organizations,” Nonprofit Manag. Leadersh., vol. 11, no. 3, pp. 353–370, 2001.

N. Chandler, B. Hostmann, N. Rayne and G. Herschel, "Gartner Business Analytics Framework", Gartner Report G00219420, 2011.

H. Baars and J. Ereth, "From data warehouses to analytical atoms - the Internet of things as a centrifugal force in business intelligence and analytics", Twenty-Fourth European Conference on Information Systems (ECIS), İstanbul,Turkey, 2016.

G. S. Richards, W. Yeoh, A. Chong and A. Popovic,"Business intelligence effectiveness and corporate performance management: an empirical analysis", Journal of Computer Information Systems, July 2017.

M. I. M. Nofal and Z. M. Yusof, "Conceptual model of enterprise resource planning and business intelligence systems usage," International Journal Business Information Systems, vol. 21, no. 2, pp. 178-194, 2016

J.-Y, Wu, "Computational intelligence -based intelligent business intelligence system: concept and framework," 2010 Second International Conference on Computer and Network Technology, 2010, pp. 334-338,

R. Cosic, G. Shanks and S. Maynard "A business analytics capability framework," Australian Journal of Information Systems, vol. 19, pp. 5-19, 2015.

P. Eachempati and P.R, Srivastava "Systematic literature review of big data analytics", SIGMIS-CPR 2017 - Proceedings of the 2017 ACM SIGMIS Conference on Computers and People Research 21 June 2017, pp. 177-178.

N. Rayner and K. Schlegel, Maturity Model Overview for Business Intelligence and Performance Management, Gartner, Stamford, 2008.

P.P. Dooley, Y. Levy, R.A. Hackney and J.L. Parrish, "Critical value factors in business intelligence systems implementations," In: Deokar A., Gupta A., Iyer L., Jones M. (eds) Analytics and Data Science. Annals of Information Systems. Springer, Cham, pp. 55-78, 2018.

P. Brooks, O. El-Gayar and S. Sarnikar, "A framework for developing a domain specific business intelligence maturity model: Application to healthcare", International Journal of Information Management, vol. 35, no. 3, pp. 337-345, 2015

Sacu, C. and Spruit, M. "BIDM: The business intelligence development model," Technical Report, Institute of Information and Computing Sciences, Utrecht University, 3508 TC, Utrecht, The Netherlands, 2010.

LaValle, S. "Breaking away with business analytics and optimization," IBM Global Business Services, Executive Report, 2009.

E. Bjarnason, K. Wnuk, and B. Regnell, “A case study on benefits and side effects of Agile practices in large scale requirements engineering,” Agile Requirement Engineering, 2011, pp. 3–7.

P. Wimpenny and J. Gass, “Interviewing in phenomenology and grounded theory: is there a difference?,” J. Adv. Nurs., vol. 31, no. 6, pp. 1485–1492, 2000.

R. K. Gupta and R. Awasthy , Qualitative Research in Management: Method and Experience, Sage, 2015.

J. Laforest, Guide to Organizing Semi-Structured Interviews with Key Informant, vol. 11, Canada:Quebec, 2009.

M. Mason, "Sample size and saturation in PhD studies using qualitative interviews. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, vol. 11, no.3, 2010.

G. Guest, A. Bunce and L. Johnson, "How many interviews are enaough?:An experiment with data saturation and variability," Field Methods, vol. 18, no. 1, pp.59-82, 2006.

Zulkifli Abai, N. H, Yahaya, J.H. and Deraman, A. "An integrated framework of business intelligence and analytic with performance management system: a conceptual framework," Science and Information Conference, London, 2015, pp. 452-456.

F.A. Mohammad, and K. Ahmad, "Business intelligence model for unstructured data management", The 5th International Conference on Electrical Engineering and Informatics 2015, August 10-11, Bali, Indonesia, 2015, pp. 473-477.



  • There are currently no refbacks.

Published by INSIGHT - Indonesian Society for Knowledge and Human Development