Sales Planning Based on Fuzzy Logic: An Alternative for Decision-Making in Cuban State-Owned Enterprises

Strategic planning remains a core component within any enterprise due to its influence on economic profitability. In recent years, the advancement of technology, artificial intelligence, and digital information systems has allowed decision-making in competitive organizations to incorporate statistical models that account for uncertainty. These models have enhanced both efficiency and effectiveness, thereby strengthening market positioning. In the specific context of Cuba, where state-owned enterprises play a crucial role in achieving economic and social objectives, no empirically validated and clearly structured approach currently addresses this need. This study aims to develop a sales planning procedure grounded in fuzzy logic principles, while integrating traditional methods such as exponential smoothing. The company Cariflor, part of the PALCO business group, served as the case study. The methodology was applied to Cariflor using historical sales data and expert judgment to estimate demand. Results revealed that the model produced forecasts with low error margins (1.5%–2.8%), indicating high accuracy and practical relevance for decision-making in business environments with limited information. This research offers an innovative contribution to Cuban business management by delivering a replicable, adaptable tool capable of minimizing subjectivity in critical planning processes.