Business analytics and decision science: A review of techniques in strategic business decision-making.
By Abdul-Yekeen, A. M., & Ekezie, M. N.
Abdul-Yekeen, A. M., & Ekezie, M. N. (2024). Business analytics and decision science: A review of techniques in strategic business decision-making. Research Inventy: International Journal of Engineering and Science, 14(7), 17–25. https://researchinventy.com/papers/v14i7/E14702170225.pdf
Abdul-Yekeen and Ekezie (2024) provide a detailed review of the intersection between business analytics and decision science within the context of strategic business management. The authors argue that in an increasingly data-intensive global market, the integration of quantitative techniques and predictive modeling is vital for maintaining a competitive advantage. The article examines various methodologies, including descriptive, diagnostic, predictive, and prescriptive analytics, evaluating how each contributes to the quality of organizational decisions. It highlights the transition from traditional intuition-based management to evidence-based practices facilitated by advanced computational tools. The study also discusses the challenges associated with data quality, organizational culture, and the technical skills required to implement these analytical frameworks effectively. Ultimately, the paper serves as a theoretical and practical bridge, demonstrating how mathematical rigor applied to business data leads to more accurate forecasting, optimized resource allocation, and enhanced long-term strategic planning for modern enterprises across diverse industries.