AI in Multiparty Control Towers

Why enterprise-level AI doesn’t work in supply chain management

With the success of AI/ML in areas like image recognition, medicine, and the web, why are we only seeing incremental gains in the supply chain? What’s throttling AI’s ability to drive optimal supply chain performance?

Ranjit Notani, co-founder and CTO of One Network Enterprises, and Joe Bellini (COO), explode common myths about AI/ML and why network strategies are essential to success in Supply Chain Control Towers. Learn where AI/ML truly shine and where you should still deploy traditional algorithms.

There’s a new approach to automated decision-making and decision-support in the supply chain, that marries network learnings with the unique insights of users -- for a multiparty multi-tier process that creates optimal outcomes. After watching this webinar, you’ll understand:

• The limits of enterprise-centric technology and why you need a network-based control tower strategy
• The 5 areas in the supply chain where you can and should use network AI/ML
• The 7 Challenges in achieving the full benefit of AI in Supply Chain and how to overcome them
• How guardrails and time horizons affect the results you can obtain with AI
• How workbenches with predictive and prescriptive analytics streamline problem-solving
• Why improving forecasts is not a panacea for your supply chain. Where to focus efforts instead

Who Should Watch?

This webinar is for supply chain practitioners and executives who want to understand how AI/ML can be properly deployed to drive step-change improvements in supply network performance, and improve data quality and decision-making.