Predictive data analytics in business strategy optimization: A systematic literature review
DOI:
https://doi.org/10.55873/rad.v4i1.365Keywords:
big data, business strategies, decision making, predictive analysis, resource optimizationAbstract
The article presents a systematic review on the use of predictive data analytics for optimizing business strategies, highlighting how this tool enables companies to anticipate trends, improve strategic decision-making, and enhance operational efficiency. However, the study highlights significant challenges, particularly in managing large, unstructured data sets and ensuring their seamless integration into existing business processes. The need for advanced computational resources and technical expertise is also noted as a barrier to widespread adoption. Despite these obstacles, predictive analytics remains a key tool for businesses aiming to achieve competitive advantages in an increasingly data-driven market. The review is based on a search of databases such as Scopus, Web of Science and IEEE, resulting in the selection of 15 key studies. The article concludes that, while predictive analytics holds reat potential to enhance business performance, it still faces challenges related to data integration and technological infrastructure.
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Copyright (c) 2025 Ríos-Cuadros, Marco Alejandro , Boris Jean Piere Gonzáles-Rivera , Divaldo Etsuo Medina-Coaquira , Yngue Elizabeth Ramírez-Pezo
This work is licensed under a Creative Commons Attribution 4.0 International License.
