The Unseen Engine of AI: How 5 Innovation-Minded Companies Optimized for Operational Efficiency
Why does one of the AI domains with the highest ROI frequently go unnoticed in mainstream discussions about AI? Could it be that Mathematical Optimization, with its equations and complex algorithms, is too often seen as the exclusive domain of PhDs in operations research or industrial engineering? Thankfully, optimization tools and techniques are now more accessible than ever. In this session, we will explore how mathematical optimization is transforming operational decision-making. We will detail how five innovation-minded companies across diverse sectors are applying optimization techniques, often in combination with machine learning, to effectively manage their operations while balancing efficiency, service level and other KPI targets, even amidst operational disruptions and demand shifts. These case studies from recognizable brands span workforce, logistics, maintenance, and manufacturing planning and scheduling use cases. Be inspired by these real-world examples showcasing how optimization is enabling organizations to build operations that are not only more resilient and adaptable but also better positioned to thrive amidst today's unpredictable world.
Nevra Ledwon is Chief Revenue Officer at DecisionBrain, a provider of custom AI-powered decision support software solutions. Nevra brings over 20 years of experience helping organizations harness data and AI tools and technologies for better decision making. Her experience spans data integration, analytics, mathematical optimization, natural language processing and machine learning. Prior to DecisionBrain, Nevra contributed to the growth of high-growth technology companies including Databricks, RedPrairie (now BlueYonder), KXEN (now SAP), and ILOG (now IBM).