Risk-aware digital product portfolio optimization using advanced analytics and market Intelligence

Digital firms increasingly manage portfolios of products under conditions of rapid technological change, volatile customer demand, and heightened competitive pressure. Traditional portfolio optimization approaches often emphasize financial returns while underrepresenting multidimensional risk and dynamic market intelligence. This paper proposes a risk-aware digital product portfolio optimization framework that integrates advanced analytics, machine learning, and market intelligence to support strategic decision making. Drawing on literature from portfolio theory, digital innovation, and business analytics, the study develops a structured methodology for evaluating product initiatives based on expected value, risk exposure, and market responsiveness. Using simulated multi product data reflective of digital platforms, the framework demonstrates how predictive modeling and scenario analysis can improve portfolio balance, resilience, and strategic alignment. The findings highlight the importance of embedding risk awareness and real time intelligence into portfolio governance and offer practical implications for digital leaders seeking sustainable growth.