Complex manufacturing sectors - healthcare equipment, electronics, pharma, aerospace, and many others - have increased pressure from world health events for real-time analytics and visibility of the full supply chain. The view of complex dependencies, make-cut-move decisions, and time to delivery has never been more important for all executives and supply chain practitioners alike. The focus of this webinar is to identify how Graph and Machine Learning can directly increase accuracy and output of supply chain material flow.
The event is designed as a 'Speed Dating' format with focus on key topics for under 15 minutes in order to maximize the insights. During this online meetup, you'll learn from our experts on how Expero and TigerGraph technology can unlock the potential in your organization. We will feature unique TigerGraph and Expero technology lightning talks, followed by a short Q&A session.
What You'll Learn:
What can we we learn from new technology and real time technology systems - why SQL and current predictive approaches are falling short. Highlights on why Graph is uniquely qualified for Material Flow in equipment manufacturing, including Medical Devices and key Healthcare Equipment.
- Cut costs by more than 10% by revealing upstream and downstream issues and risk in advance.
- Increase accuracy of parts supply and demand determinations by 20%
- Use Graph & ML to unify data for Preventive & Predictive analytics
- Use Graph & ML for 'What If' for alternative paths, dependencies, and avoiding compounding downstream effects
