Mastering Decision Intelligence in Volatile Supply Chains | Andy Kohm, SCIP at Manifest 2026
Why It Matters
Consolidated, high‑quality supply‑chain data unlocks reliable AI‑driven decisions, safeguarding margins and operational resilience in increasingly volatile markets.
Key Takeaways
- •Data silos hinder end-to-end supply-chain decision making effectively.
- •Skip unifies ERP, PLM, S&OP data into a single platform.
- •AI amplifies need for clean, consolidated, high-quality data across operations.
- •Poor data quality causes AI hallucinations and misleading business insights.
- •Integrated intelligence lets firms trace margin impacts from sourcing to sales.
Summary
Andy Kohm, CEO and co‑founder of Skip, opened the session by framing decision intelligence as the missing link in today’s volatile supply chains. He described Skip as a supply‑chain intelligence platform that overlays existing legacy systems—ERP, PLM, S&OP—and aggregates every data source into a single, AI‑ready repository. The core argument centered on three pain points: data silos, fragmentation, and deteriorating data health. Kohm explained that while many vendors target a single supply‑chain function, only a holistic view can reveal how a downstream price change ripples through margins. With AI’s rise, the platform not only pulls data but also automates cleaning and maintenance, tasks that are impractical to perform manually. He warned that “if you roll out an AI system and it gives you strange answers, either the AI is hallucinating or the data it’s using is wrong,” underscoring the direct link between data quality and model reliability. Real‑world examples included tracing a component‑cost shift to its impact on end‑customer profitability, a calculation impossible without unified, trustworthy data. The implication for executives is clear: investing in a unified data layer is no longer optional but a prerequisite for extracting value from AI. Companies that secure data integrity and accessibility will gain faster, more accurate insights, protect margins, and build resilience against supply‑chain disruptions, while laggards risk costly AI missteps.
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