
Resilient Supply Chain Finding the One Thing That Can Break Your Supply Chain
Mar 2, 2026
Jonathan Doller, Senior Solution Consultant at Logility with ~25 years in supply chain planning and AI-enabled resilience. He discusses how AI turns data into actionable information. He talks about distinguishing correlation from causation in forecasting. He explores constrained inventory allocation, agentic AI linking demand, supply and distribution, and mapping single points of failure for resilience.
AI Snips
Chapters
Transcript
Episode notes
AI Frees Planners From Spreadsheet Work
- AI's immediate value is automating mundane, time-consuming tasks so planners stop being data wranglers.
- Planners then focus on domain expertise and final validation rather than aggregating dozens of spreadsheets.
Let Models Find Signal In Event Data
- Large AI models can distinguish correlation from causation in forecasts by evaluating event impact versus noise.
- Let models ingest many event signals instead of pre-filtering; the AI will surface meaningful relationships.
Connect Specialized AI Agents Across Planning
- Build agentic AI where specialized AI agents (demand, supply, distribution) communicate to resolve cross‑impacts.
- This lets a forecast change propagate to inventory, capacity, and distribution recommendations automatically.
