Analyzing the Utilization of Data Analytics in Supply Chain Decision-Making among Small and Medium Enterprises in Lusaka, Zambia
Main Article Content
Abstract
Data analytics has become a crucial tool for businesses, allowing them to uncover valuable insights from large datasets and enhance their operational efficiency. For Small and Medium Enterprises (SMEs), which are the foundation of many economies, effective supply chain management is essential for staying competitive and sustainable. This study investigated the utilization of data analytics in supply chain decision-making among SMEs in manufacturing, agribusiness, and retail and wholesale trade in Lusaka, Zambia. Employing a quantitative research approach, this study collected and analyzed data from a representative sample of 220 SMEs in Lusaka. The findings revealed that several intertwined factors contribute significantly to the lack of big data analytics use in supply chain decision-making among SMEs in Lusaka with many SMEs acknowledging gaps in expertise and uneven distribution of skills. Additionally, the findings suggested a significant gap in data analytics knowledge and application within the company's supply chain management. Based on these findings the study recommends that SMEs invest in data infrastructure and prioritize data analytics training to enhance the utilization of data analytics in the supply chain. In the same vein, the study recommends that policymakers develop policies such as tax incentives, grants, and subsidies that encourage the adoption of data analytics among SMEs in Lusaka.
Article Details
Copyright (c) 2025 Leah Butala, Bupe Getrude Mwanza (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abrol, S. & Gupta, M., 2023. ROLE OF BIG DATA ANALYTICS IN FINANCIAL FRAUD DETECTION-A BIBLIOMETRIC ANALYSIS. Corporate Governance Insight, 5(1).
https://doi.org/10.58426/cgi.v5.i1.2023.86-115 DOI: https://doi.org/10.58426/cgi.v5.i1.2023.86-115
African Development Bank, 2023. African Economic Outlook 2023, s.l.: African Development Bank.
Alharthi, A., Krotov, V. & Bowman, M., 2017. Addressing barriers to data. Business Horizons, 60(3), pp. 285292.
https://doi.org/10.1016/j.bushor.2017.01.002 DOI: https://doi.org/10.1016/j.bushor.2017.01.002
Alp, K., 2018. Challenges of Big Data Adoption in Turkish SMEs: A Case Study, London: Brunel University London.
Arunachalam, D., Kumar, N., Kawalek, J., 2017. Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice. Transportation Research Part E: Logistics and Transportation Review, Volume 114, pp 416-436
https://doi.org/10.1016/j.tre.2017.04.001 DOI: https://doi.org/10.1016/j.tre.2017.04.001
Asiri, A. M., Al-Somali, S. A. & Maghrabi, R. O., 2024. The Integration of Sustainable Technology and Big Data Analytics in Saudi Arabian SMEs: A Path to Improved Business Performance. Sustainability, 16(8).
https://doi.org/10.3390/su16083209 DOI: https://doi.org/10.3390/su16083209
Bach, M. P., Bertoncel, T., Mesko, M. & Vugec, D. S., 2020. Big Data Usage in European Countries: Cluster Analysis Approach. Data, 5(1).
https://doi.org/10.3390/data5010025 DOI: https://doi.org/10.3390/data5010025
Bhardwaj, S., 2022. Data Analytics in Small and Medium Enterprises (SME): A Systematic Review and Future Research Directions. Information Resources Management Journal, 35(2).
https://doi.org/10.4018/IRMJ.291691 DOI: https://doi.org/10.4018/IRMJ.291691
Bouwman, H., Nikou, S., Molina-Castillo, F. J. & Reuver, d. M., 2018. "The impact of digitalization on business models
https://doi.org/10.1108/DPRG-07-2017-0039 DOI: https://doi.org/10.1108/DPRG-07-2017-0039
Centre International Trade, 2015. SME Competitiveness Outlook.
Chellah, R. C. & Kaunda, D., 2021. An assessment of factors that affect the implementation of big data analytics in the Zambian health sector for strategic planning and predictive analysis: a case of Copperbelt province. International Journal of Electronic Health, 9(2).
https://doi.org/10.1504/IJEH.2020.113196 DOI: https://doi.org/10.1504/IJEH.2020.113196
Chen, Y. & Zhang, C., 2019. Big data analytics for supply chain decision-making: A review and future research directions. Journal of Big Data, 6(1).
Chilembo, T., 2021. A Study of the Factors Affecting Small and Medium Enterprises (SMEs) Access to Finance. A Case of Lusaka Based SMEs. American Journal of Industrial and Business Management, 11(05).
https://doi.org/10.4236/ajibm.2021.115028 DOI: https://doi.org/10.4236/ajibm.2021.115028
Coleman, S., Göb, R., Manco, G., Pievatolo, A., Tort-Martorell, X., & Reis, M. S. (2016). How Can SMEs Benefit from Big Data? Challenges and a Path Forward. Quality and Reliability Engineering International, 32,2151-2164.
https://doi.org/10.1002/qre.2008 DOI: https://doi.org/10.1002/qre.2008
Dat, D. T., 2018. ADOPTION OF SUPPLY CHAIN ANALYTICS IN SMEs, s.l.: Mikkel Campus.
Davenport, T., 2014. Big data at work: Dispelling the myths, uncovering the opportunities. [Online] Available at: https://hbr.org/2014/03/big-data-at-work-dispelling-the-myths-uncovering-the-opportunities [Accessed 10 April 2024].
Davenport, T. & Harris, G. J., 2007. Data to Knowledge to Results: Building an Analytic Capability.
Es, K. V., 2022. Netflix & Big Data: The Strategic Ambivalence of an Entertainment Company. Television & New Media, 24(5).
https://doi.org/10.1177/15274764221125745 DOI: https://doi.org/10.1177/15274764221125745
FSD Zambia, 2017. Access to Finance: SME perceptions of Financial Service.
Grand View Research, 2023. Market Analysis Report, Grand View Research.
IBM, 2024. What is Data Quality. [Online] Available at: https://www.ibm.com/topics/data-quality#:~:text=IBM-,What%20is%20data%20quality%3F,governance%20initiatives%20within%20an%20organization. [Accessed 31 July 2024].
Invest, Z., 2017. Zambia to Set Entrepreneurial Fund for SMEs
Iqbal, M. et al., 2018. A study of big data for business growth in SMEs: Opportunities & challenges. [Online] Available at: https://ieeexplore.ieee.org/abstract/document/8346368/authors [Accessed 2 July 2024].
Karki, R., 2024. Data analytics to enhance supply chain decision-making, inventory management, and logistic optimization.
Kelley, K. (2024, November 30). SQL for Data Analysis: Unlocking Insights from Data. Retrieved from SQL for Data Analysis: Unlocking Insights from Data: https://pg-p.ctme.caltech.edu/blog/data-analytics/sql-for-data-analysis#:~:text=SQL%20(Structured%20Query%20Language)%20is,making%20it%20accessible%20for%20analysis [Accessed 8 January 2025].
Kot, S., Goldbach, I. R. & Ślusarczyk, B., 2018. Supply chain management in SMEs-Polish and Romanian approach. Economics & Sociology, p. 11.
https://doi.org/10.14254/2071-789X.2018/11-4/9 DOI: https://doi.org/10.14254/2071-789X.2018/11-4/9
Lee, I. & Mangalaraj, G., 2022. Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions. Big Data and Cognitive Computing, 6(1).
https://doi.org/10.3390/bdcc6010017 DOI: https://doi.org/10.3390/bdcc6010017
Lutfi, A. et al., 2022. Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs. Sustainability, 14(3).
https://doi.org/10.3390/su14031802 DOI: https://doi.org/10.3390/su14031802
Mahardhani, A. J. (2023). The Role of Public Policy in Fostering Technological Innovation and Sustainability. Journal of Contemporary Administration and Management, 47-53.
https://doi.org/10.61100/adman.v1i2.22 DOI: https://doi.org/10.61100/adman.v1i2.22
Maroufkhani, P., Iranmanesh, M. & Ghobakhloo, M., 2022. Determinants of big data analytics adoption in small and medium- sized enterprises (SMEs). Industrial Management & Data Systems, 123(1), pp. 278-301.
https://doi.org/10.1108/IMDS-11-2021-0695 DOI: https://doi.org/10.1108/IMDS-11-2021-0695
McAfee, A. & Brynjolfsson, E., 2012. Harvard Business Review. [Online] Available at: https://hbr.org/2012/10/big-data-the-management-revolution [Accessed 10 April 2024].
Ministry of Technology and Science, 2023. [Online]
Available at: https://www.mots.gov.zm/wp-content/uploads/2023/10/National-Digital-Transformation-Strategy.pdf [Accessed 26 June 2024].
Mohamed, A., Pranav, K., Rachit, B. & Aniket, M., 2018. Big Data Analytics in Supply Chain: A Literature Review. Washington DC, USA, University at Buffalo.
Ogbuokiri, b., Udanor, C. & Agu, M., 2015. Implementing bigdata analytics for small and medium enterprise (SME) regional growth. Journal of Computer Engineering, 17(6), pp. 35-43.
Policy Monitoring Research Centre, 2021. Policy Monitoring Research Centre. [Online]
Available at: https://pmrczambia.com/blog-agriculture-mining-manufacturing-and-tourism-four-keyeconomic-sectors-to-drive-zambias-economic-stabilisation-agenda/ [Accessed 10 April 2024].
Proventa International. (2023). The Impact of Data Analytics on Supply Chain Decision Making. Retrieved from https://proventainternational.com/the-impact-of-data-analytics-on-supply-chain-decision-making/
Telukdarie, A., Philbin, S., Mwanza, B. G., & Munsamy, M. (2022). Digital Platforms for SMME Enablement. Procedia Computer Science, 811-819.
https://doi.org/10.1016/j.procs.2022.01.278 DOI: https://doi.org/10.1016/j.procs.2022.01.278
Rahman, S., Pabmann, J. & Srai, J., 2017. Big data analytics in supply chain management: Trends and related research. Supply Chain Forum: An International Journal, 18(4).
Rozak, I. R., Johari, R. J., Hairudin, N. A. M. & Hussin, S. A. H. S., 2022. Detecting and preventing fraud with big data analytics: Auditing perspective. Journal of Governance and Regulation, 11(4).
https://doi.org/10.22495/jgrv11i4art1 DOI: https://doi.org/10.22495/jgrv11i4art1
Selamat, S. A. M., Prakoonwit, S., Sahandi, R. & Khan, W., 2018. Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(2).
https://doi.org/10.1002/widm.1238 DOI: https://doi.org/10.1002/widm.1238
Seseni, L. & Mbohwa, C., 2021. The Significance of Big Data in the Success of SMEs in Emerging Markets: A Case of South Africa. Singapore, 11th Annual International Conference on Industrial Engineering and Operations Management.
https://doi.org/10.46254/AN11.20210376 DOI: https://doi.org/10.46254/AN11.20210376
Shahid, N. U. & Sheikh, N. J., 2021. Impact of Big Data on Innovation, Competitive Advantage, Productivity, and Decision Making: Literature Review. Journal of Business and Management, 9(2).
Siedlecki, S., 2020. Siedlecki, S.L., 2020. Understanding descriptive research designs and methods. Clinical Nurse Specialist, 34(1), pp. 8-12.
https://doi.org/10.1097/NUR.0000000000000493 DOI: https://doi.org/10.1097/NUR.0000000000000493
Suresh, S., 2016. Big Data and Predictive Analytics. Pediatric Clinics of North America, 63(2).
https://doi.org/10.1016/S0031-3955(16)00015-8 DOI: https://doi.org/10.1016/S0031-3955(16)00015-8
Tan, K. H. & Zhan, y., 2017. Improving new product development using big data: a case study of an electronics company.
Udeh , C. A., Orieno, O. H., Daraojimba, O. D. & Ndubuisi, N. L., 2024. BIG DATA ANALYTICS: A REVIEW OF ITS TRANSFORMATIVE ROLE IN MODERN BUSINESS INTELLIGENCE. Computer Science & IT Research Journal, 5(1).
https://doi.org/10.51594/csitrj.v5i1.718 DOI: https://doi.org/10.51594/csitrj.v5i1.718
UN Global Pulse, 2012. Big Data for Development: Challenges & Opportunities, New York: Global Pulse.
Velthuijsen, J., Yıldırım, B., Kramer, G. & Schmidl, R., 2018. "Innovation and Digital Transformation: How do European SMEs, Belgium: OECD, Data for Belgium.
Wamba, S. F., Akter, S., Edwards, A. J. & Chopin, G., 2014. How 'big data' can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics.
Willetts, M., Atkins A, S. & Stanier, A. C., 2020. A Strategic Big Data Analytics Framework to Provide Opportunities for SMEs," in 14th International Technology, Education and Development, s.l.: s.n.
https://doi.org/10.21125/inted.2020.0893 DOI: https://doi.org/10.21125/inted.2020.0893
Yoshikuni, A. C., Dwivedi, R., Zhou, D. & Wamba, S. F., 2023. Big data and business analytics enabled innovation and dynamic capabilities in organizations: Developing and validating scale. International Journal of Information Management Data Insights, 3(2).
https://doi.org/10.1016/j.jjimei.2023.100206 DOI: https://doi.org/10.1016/j.jjimei.2023.100206
Article Sidebar
