Enhancing Strategic Decision-Making in Malaysian Public Organizations: The Role of Big Data Analytics and Continuous Improvement
DOI:
https://doi.org/10.24191/jikm.v15iSI2.7172Abstract
Organizations must look for ways to enhance decision-making processes due to advancements in public administration and increasing demands. This study explores the integration of Continuous Improvement (CI) and Big Data Analytics (BDA) within Malaysian public organizations, proposing a novel framework aimed at enhancing strategic decision-making. The framework comprises five interconnected components: Organizational Readiness Assessment, Analytical and Improvement Capabilities Development, Data Governance and Quality Management, Performance Measurement and Feedback Loops, and Continuous Learning and Adaptation. By addressing challenges such as resistance to change and ethical concerns, the framework offers a pathway to better governance and service delivery. Practical implications include guidelines for fostering a data-driven culture and achieving sustainable development goals. Key findings include the need for leadership commitment, robust data governance, and the cultivation of a data-driven culture. Practical and pathways for empirical testing are provided.
References
Abhari, K., Davis, D., Ness, H., Pagador, J., Parsons, M., & Brodskiy, R. (2022). Data swagger: a systemic
approach to train, motivate and engage data savvy employees.. https://doi.org/10.24251/hicss.2022.742
Alieva, Jamila & von Haartman, Robin. (2020). Digital Muda - The New Form of Waste by Industry 4.0. Operations and Supply Chain Management: An International Journal. 269-278. 10.31387/oscm0420268.
AnandaRao, A., Reddy, G., & T.V, R. (2015). Text clustering using incremental frequent pattern mining approach. International Journal of Data Mining & Knowledge Management Process, 5(6), 53-65. https://doi.org/10.5121/ijdkp.2015.5605
Baschung, L. (2023). Conditions for effective implementation of quality management systems in public administration. Hrvatska I Komparativna Javna Uprava, 23(3), 365-386. https://doi.org/10.31297/hkju.23.3.6
Belsvik, M. R. , Lædre, O. & Hjelseth, E. 2019. Metrics in VDC Projects, Proc. 27th Annual Conference of the International Group for Lean Construction (IGLC) , 1129-1140. doi.org/10.24928/2019/0167
Bondarenko, S., Liganenko, I., & Mykytenko, D. (2020). Transformation of public administration in digital conditions: world experience, prospects of ukraine. Journal of Scientific Papers Social Development & Security, 10(2), 76-89. https://doi.org/10.33445/sds.2020.10.2.9
Brynjolfsson, E. and McElheran, K. (2016). The rapid adoption of data-driven decision-making. American Economic Review, 106(5), 133-139. https://doi.org/10.1257/aer.p20161016
Carlson, V., Chilton, M., Corso, L., & Beitsch, L. (2015). Defining the functions of public health governance. American Journal of Public Health, 105(S2), S159-S166. https://doi.org/10.2105/ajph.2014.302198
Dubey, R., Gunasekaran, A., & Childe, S. (2019). Big data analytics capability in supply chain agility. Management Decision, 57(8), 2092-2112. https://doi.org/10.1108/md-01-2018-0119
Dubey, R., et. al. (2019). Can big data and predictive analytics improve social and environmental sustainability?. Technological Forecasting and Social Change, 144, 534-545. https://doi.org/10.1016/j.techfore.2017.06.020
Duong, L., Wood, L., & Wang, W. (2018). A review and reflection on inventory management of perishable products in a single-echelon model. International Journal of Operational Research, 31(3), 313. https://doi.org/10.1504/ijor.2018.089734
Džinić, J. (2017). Effective implementation of a quality management policy in public administration: Experiences from Spain and lessons for Croatia. Hrvatska i komparativna javna uprava: časopis za teoriju i praksu javne uprave, 17(4), 639-664.
Fant, G. (2023). Technical review: key concepts of health database management for public health workforce development in resource-limited settings. International Journal of Science and Research Archive, 9(2), 222-230. https://doi.org/10.30574/ijsra.2023.9.2.0526
Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2019). Big data analytics capabilities and knowledge management: impact on firm performance. Management Decision, 57(8), 1923-1936. https://doi.org/10.1108/md-07-2018-0825
Handfield, R., Jeong, S., & Choi, T. (2019). Emerging procurement technology: data analytics and cognitive analytics. International Journal of Physical Distribution & Logistics Management, 49(10), 972-1002. https://doi.org/10.1108/ijpdlm-11-2017-0348
Ichdan, D. (2023). Participation in decision-making, career development, and organizational commitment. Jurnal Ilmiah Akuntansi Dan Bisnis, 18(2), 342. https://doi.org/10.24843/jiab.2023.v18.i02.p10
Intezari, A. and Gressel, S. (2017). Information and reformation in km systems: big data and strategic decision-making. Journal of Knowledge Management, 21(1), 71-91. https://doi.org/10.1108/jkm-07-2015-0293
Khan, S., Kaviani, M., Galli, B., & Ishtiaq, P. (2019). Application of continuous improvement techniques to improve organization performance. International Journal of Lean Six Sigma, 10(2), 542-565. https://doi.org/10.1108/ijlss-05-2017-0048
Lan, C., Bellemare, M., & Castro, P. (2021). Metrics and continuity in reinforcement learning. Proceedings of the AAAI Conference on Artificial Intelligence, 35(9), 8261-8269. https://doi.org/10.1609/aaai.v35i9.17005
Lundkvist, A. and Gustavsson, M. (2018). Learning conditions for continuous improvement in a public service organization. Journal of Workplace Learning, 30(8), 578-591. https://doi.org/10.1108/jwl-03-2018-0049
Мандал, С. (2019). The influence of big data analytics management capabilities on supply chain preparedness, alertness and agility. Information Technology and People, 32(2), 297-318. https://doi.org/10.1108/itp-11-2017-0386
Miah, S., Vu, H., Gammack, J., & McGrath, G. (2017). A big data analytics method for tourist behaviour analysis. Information & Management, 54(6), 771-785. https://doi.org/10.1016/j.im.2016.11.011
Monko, M. (2023). The role of computer literacy familiarity in the adoption of e-government by public sector workers in local government authorities: a case of Kigamboni municipal council. European Journal of Theoretical and Applied Sciences, 1(6), 776-786. https://doi.org/10.59324/ejtas.2023.1(6).77
Nugroho, D. (2024). The impact of social media analytics on sme strategic decision making. Iaic Transactions on Sustainable Digital Innovation (Itsdi), 5(2), 169-178. https://doi.org/10.34306/itsdi.v5i2.664
Oh, S. (2024). Community-based learning and data literacy: the role of the public library. Information and Learning Sciences, 125(7/8), 456-474. https://doi.org/10.1108/ils-06-2023-0078
Olaniyi, O. (2023). Utilizing big data analytics and business intelligence for improved decision-making at leading fortune company. Journal of Scientific Research and Reports, 29(9), 64-72. https://doi.org/10.9734/jsrr/2023/v29i91785
Ongena, G. and Davids, A. (2023). Big data analytics capability and governmental performance. International Journal of Electronic Government Research, 19(1), 1-18. https://doi.org/10.4018/ijegr.321638
Rodgers, B., & Antony, J. (2019). Lean and Six Sigma practices in the public sector: A review. International Journal of Quality & Reliability Management, 36(3), 437-455. https://doi.org/10.1108/ijqrm-02-2018-0057.
Rogge, N., et al. "Big data and the measurement of public organizations’ performance and efficiency: The state-of-the-art" Public Policy and Administration (2017) doi:10.1177/0952076716687355.
Rossi, E., Rubattino, C., & Viscusi, G. (2019). Big data use and challenges: insights from two internet-mediated surveys. Computers, 8(4), 73. https://doi.org/10.3390/computers8040073
Rukanova, B., et. al (2019). Value of big data analytics for customs supervision in e-commerce., 288-300. https://doi.org/10.1007/978-3-030-27325-5_22
Saravanabhavan, C., et. al (2021). Data Mining Model for Chronic Kidney Risks Prediction Based on Using NB-CbH. In 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1023-1026). IEEE.
Senavirathne, R. (2022). Application of big data analytics in telecommunication sector company in Sri Lanka: with reference to marketing perspective. Sri Lanka Journal of Marketing, 8(3), 114-140. https://doi.org/10.4038/sljmuok.v8i3.114
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2025 Mohd Hazly Mazly, Mad Khir Johari Abdullah Sani , Nora’ayu Ahmad Uzir

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright of articles that appear in the journal belongs exclusively to Faculty of Information Science, Universiti Teknologi MARA (Publisher). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions or any other reproductions of similar nature.







