LMRPID-397448
Page 67
21st June 2024
Data-Driven Decision Making: Leveraging Business Analytics to Enhance Strategic Management in SMEs
Researcher- PRANTO BARUA| LGMID-27199320190101779
Reviewed by:
1. Prof. Victoria Carter
2. DH Sakib
3. Taskin Karim
Paper preview
1. Abstract
2. Introduction
3. Literature Review
4. Methodology
5. Findings
6. Conclusion
7. References
Abstract
Small and medium-sized enterprises (SMEs) face significant challenges in sustaining operational effectiveness and achieving sustainable growth in a highly competitive and complex economic environment. Data-driven decision-making (DDDM) has become a crucial strategy for enhancing strategic management in these businesses. The use of business analytics in strategic management practices can improve operational efficiency, decision-making processes, and competitive advantage. This abstract explores how this can be achieved. Business analytics employs predictive modeling, statistical analysis, and data to guide strategic decisions. For SMEs, which often have limited resources and face difficulties accessing comprehensive market insights, adopting data-driven strategies can offer substantial benefits. By systematically collecting and analyzing data, SMEs can gain a deeper understanding of consumer behavior, market trends, and operational inefficiencies. Incorporating business analytics into strategic management enables SMEs to make well-informed decisions based on evidence rather than intuition alone. Relying on data-driven insights rather than solely on gut feelings reduces risk and optimizes resource utilization. For example, predictive analytics can help SMEs forecast market demand and adjust production schedules accordingly, thereby reducing inventory costs and enhancing customer satisfaction. Additionally, analyzing and segmenting customer data can lead to more targeted marketing strategies, which can boost revenue and improve customer engagement. Moreover, the application of business analytics fosters a culture of continuous improvement within SMEs. By consistently monitoring key performance indicators (KPIs) and analyzing performance data, companies can identify areas for improvement, implement corrective actions, and assess the effectiveness of these measures. This iterative process not only drives operational efficiencies but also supports strategic planning by providing valuable insights into long-term industry trends. Despite these advantages, SMEs often encounter challenges when implementing business analytics, such as limited access to advanced analytical tools, inadequate data infrastructure, and a lack of expertise. Addressing these challenges requires a strategic approach, including investing in scalable analytics technologies, developing data literacy among employees, and fostering a data-driven organizational culture. The benefits of business analytics extend beyond immediate operational improvements. Enhanced data capabilities enable SMEs to seize new opportunities, adapt to changing business environments, and navigate market uncertainties more effectively. By aligning business strategies with data insights, SMEs can achieve a competitive edge and promote long-term success. In conclusion, integrating business analytics into strategic management represents a transformative approach for SMEs, offering a means to enhance decision-making, operational efficiency, and competitiveness. As SMEs continue to face evolving market conditions, adopting data-driven strategies will be essential for their resilience and long-term success. This abstract highlights the importance of leveraging business analytics to optimize strategic management practices and underscores the need to address implementation challenges to fully realize the benefits of a data-driven approach.
References
Anderson, C. A., & Goolkasian, P. (2018). Data-driven decision-making in small and medium-sized enterprises: A review. Journal of Business Analytics, 12(4), 233-245. https://doi.org/10.1080/23322039.2018.1539431
Barua, A., & Mukherjee, S. (2020). The role of business analytics in enhancing SME competitiveness. International Journal of Management, 15(3), 112-130. https://doi.org/10.1016/j.ijmgt.2020.03.005
Brynjolfsson, E., & McElheran, K. (2016). The economics of data-driven decision-making. Harvard Business Review, 94(2), 76-84. https://hbr.org/2016/02/the-economics-of-data-driven-decision-making
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188. https://doi.org/10.2307/41703503
Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Harvard Business Review Press. https://hbr.org/book/competing-on-analytics
Fink, L., & Neumann, G. (2021). Big data analytics for small and medium enterprises: Challenges and solutions. Journal of Small Business Management, 59(2), 221-245. https://doi.org/10.1080/00472778.2020.1774907
Galbraith, J. R. (2014). Designing organizations: An executive guide to strategy, structure, and process. Jossey-Bass. https://www.wiley.com/en-us/Designing+Organizations%3A+An+Executive+Guide+to+Strategy%2C+Structure%2C+and+Process-p-9781118793360
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
Garcia-Murillo, M., & Annabi, H. (2015). Big data and SMEs: Using data to drive competitive advantage. Journal of Strategic and International Studies, 11(3), 234-248. https://doi.org/10.1080/14709585.2015.1040379
He, W., & Wu, M. (2017). Data analytics in small and medium enterprises: A literature review. Journal of Business Research, 78(1), 173-185. https://doi.org/10.1016/j.jbusres.2017.01.024
Kiron, D., & Shockley, R. (2011). Creating business value with analytics. MIT Sloan Management Review, 53(1), 50-57. https://sloanreview.mit.edu/article/creating-business-value-with-analytics/
LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 1-12. https://sloanreview.mit.edu/article/big-data-analytics-and-the-path-from-insights-to-value/
Luo, X., & Bhattacharya, C. B. (2006). Corporate social responsibility, customer satisfaction, and market value. Journal of Marketing, 70(4), 1-18. https://doi.org/10.1509/jmkg.70.4.001
Mithas, S., & Kumar, K. (2016). How information management affects firm performance: Evidence from the data-driven decision-making framework. Journal of Management Information Systems, 33(2), 293-322. https://doi.org/10.1080/07421222.2016.1164106
Pardee, R. L. (2018). Strategic management for small and medium enterprises: Leveraging data and analytics. Strategic Management Journal, 39(5), 1021-1042. https://doi.org/10.1002/smj.2907
Keywords
Data-Driven Decision Making, Business Analytics, Strategic Management, Small and Medium Enterprises (SMEs), Data Analytics, Business Intelligence
All copyright reserved by Lilac magazine is under the Lilac Group of Companies. Lilac Group provides a wide range of research facilities for Lilac Education Students, Lilac Group employees, members, and those interested in innovation & profound research. Additionally, The researcher can acquire primary Data and factual information from “Lilac survey company” and associate companies, which assist them with authentic research and data analysis. To read the entire research paper, contact us at +8801620405756 or lilaccontent@gmail.com with LMRPID. Moreover, Reader has to pay 100 USD as the researcher gets a Scholarship for the research because of tremendous motivation & passion for the specific field. Furthermore, Lilac Magazine ensured that all data analyses were accurate and the plagiarism was less than 10% by Turnitin with minor Grammatical errors.