Data-driven manufacturing management: strategic production planning with a results-oriented focus

This article explores Data-Driven Manufacturing Management (DDMM) as a strategic model for production planning in the United States. The research analyzes real-world case studies from companies such as General Electric, Procter & Gamble, BMW, and Ford, demonstrating how the use of digital technologies, predictive analytics, and data integration significantly improves operational efficiency, reduces costs, and strengthens the alignment between production and organizational goals. The study concludes that adopting DDMM is no longer optional but essential for industrial competitiveness in the Industry 4.0 era. It also suggests that future research should investigate the role of emerging technologies such as artificial intelligence and edge computing in the evolution of autonomous planning.