A HYBRID STRATEGIC PROBABILISTIC FRAMEWORK FOR FUNCTIONAL ASSESSMENT AND RISK CONTROL IN INDUSTRIAL SYSTEMS: A CASE STUDY

ABSTRACT: This study proposes a strategic management methodology for evaluating risk variables in industrial systems through the development of a hybrid decision-support dashboard. The framework integrates the Balanced Scorecard (BSC), the OFAI method (Objectives, Key Success Factors, Actions, Indicators), and Bayesian Networks (BN), with the addition of a fifth axis that focuses on environmental factors. A review of existing literature highlights the lack of integrated approaches that combine probabilistic reasoning with strategic performance frameworks, underlining the novelty and scientific relevance of this contribution. The methodology is validated through a real-world case study in a textile manufacturing company. Using expert knowledge and historical data, the Bayesian model allows for the simulation of various risk scenarios. Results indicate a notable improvement in profitability and key performance indicators under optimized strategic scenarios. These findings validate the model's ability to support risk-informed decision-making and strategic adaptability in complex, dynamic industrial environments.