Decision-making under Uncertainty in Supply Chain (with Dr. Meinolf Sellmann) - Ep 162 скачать в хорошем качестве

Decision-making under Uncertainty in Supply Chain (with Dr. Meinolf Sellmann) - Ep 162

Full transcript available: https://www.lokad.com/tv/2024/5/22/de... About the guest Dr. Meinolf Sellmann is founder and CTO at InsideOpt, a US-based startup that produces general-purpose software for automating decision-making under uncertainty. He is the former Director for Network Optimization at Shopify, Lab Director for the Machine Learning and Knowledge Representation Labs at General Electric's Global Research Center, Senior Manager for Cognitive Computing at IBM Research, and Assistant Professor for Computer Science at Brown University. Meinolf architected systems like the trade-settlement system of the ECB, which handles over 1 trillion Euros per night, has published over 80 articles in international conferences and journals, holds six patents, and has won over 22 first prizes at international programming competitions. Summary In a recent LokadTV interview, Conor Doherty, Joannes Vermorel, and guest Meinolf Sellmann discussed the role of stochastic optimization in supply chain management. They highlighted the importance of considering variability and uncertainty in decision-making processes. Traditional deterministic methods often fall short in real-world scenarios, leading to over-optimistic optimization plans. Both Vermorel and Sellmann criticized the "predict then optimize" approach, suggesting that companies can achieve better results by accounting for forecast variability during optimization. They emphasized the need for executable plans and measurable effectiveness in any optimization model. 00:00:00: Introduction of the interview 00:00:42: Meinolf Sellman's career and InsideOpt's decision-making 00:03:47: Disruptions and over-optimism in optimization 00:06:18: Vermorel's stochastic optimization discovery and influences 00:08:10: E-commerce fulfillment and supply chain forecasting 00:09:56: 'Predict then optimize' approach and consequences 00:11:41: Operational results improvement and business costs 00:14:08: Unpredictability and chaos in supply chain 00:16:16: Appeal of forecasting and rational decision making 00:18:43: Rational decision making and overbooking game 00:21:55: Supermarket product example and supply availability 00:24:27: Stochastic optimization and seasonal sales variability 00:28:53: Price changes impact and joint posterior distribution 00:30:39: Problem-solving heuristics and tackling complexity 00:33:10: Challenges with perishable goods and posterior distribution 00:36:01: Reasoning difficulties and creating solution awareness 00:38:40: Coffee Roastery problem and production planning 00:42:20: Business modelization and complex variables reality 00:45:34: Ignored concerns in optimization and silver bullet seeking 00:49:00: CEO advice and understanding business processes 00:51:58: Warehouse capacity and supplier delivery uncertainty 00:54:38: Perception of service level and briefing exercise 00:57:33: Airlines' financial losses and technology adoption 01:00:10: AI-based search benefits and hardware compatibility 01:03:05: Convexity in optimization and usefulness over proof 01:06:06: Convergence of machine learning with optimization techniques 01:09:34: Runtime features and broadening search horizon 01:12:22: Micro adjustments and warehouse operation risks 01:16:09: Finding good compromise and insurance against uncertainty 01:19:11: Expected profit rise with stochastic optimization 01:22:23: Aerospace industry example 01:24:30: Accepting good decisions and damage control 01:25:19: Supply chain efficiency 01:26:22: Client feedback and importance of technology 01:26:56: End of interview ****** Check out our website: https://www.lokad.com/ Follow us on LinkedIn:   / lokad   ******