A Comprehensive Study on the Adoption of Predictive Analysis in Small and Medium-Scale Enterprises (SMEs)

Abstract

This study explores the plausible role of predictive analytics in empowering Small and Medium Enterprises (SMEs) in India. Predictive analytics, characterized by statistical algorithms and machine learning techniques, offers SMEs the capability to analyze historical and real-time data, make accurate predictions, and derive actionable insights. With a sample size of 150 respondents representing a diverse range of SMEs, this study delves into Research Questions encompassing adoption dynamics, barriers and enablers, impact on business performance, implementation frameworks, policy and strategy contributions, business and academic understanding, and the foundation for future research.
Key findings suggest that predictive analytics plays a crucial role in demand forecasting, inventory management, customer segmentation, and personalization, enhancing operational efficiency and customer satisfaction. Moreover, predictive analytics contributes significantly to risk management and fraud detection, helping SMEs mitigate risks and ensure regulatory compliance. Additionally, predictive analytics aids SMEs in optimizing resource allocation, streamlining operations, and improving productivity.
The study emphasizes the need for SMEs to invest in technology infrastructure, data analytics capabilities, and talent development to fully leverage the benefits of predictive analytics and gain a competitive edge in the market. Overall, the adoption of predictive analytics holds immense promise for SMEs in India, enabling data-driven decision-making, enhancing customer experiences, and driving sustainable business growth.
Keywords: Predictive analytics, SMEs, India, data-driven decision-making, competitive edge