Five Key Takeaways from Day 2 at Gartner Supply Chain Symposium

1) Proverbial duck paddling—or musicians on the Titanic?        

One of the most surprising aspects of Day 2 was the relative silence on tariffs. Given the scale of potential disruptions, I expected a Defcon 1-level focus from supply chain leaders. Instead, discussions around tariffs were muted, confined to a few sessions.

Why the disconnect? Perhaps it's because the attendee base skewed toward tactical planners rather than day-to-day logistics professionals. The folks watching vessel movements and managing port delays—amid a 60% drop in volumes—would be sounding alarms. Procurement professionals purchasing direct materials would be shouting from roof tops.

2) Gartner Lifecycle Model: Implications for Supply Chain Design        

Gartner's lifecycle framework outlines four phases—Startup, Growth, Peak, and Decline—that most supply chains evolve through. The strategic opportunity lies in the “Sweet Spot of Optionality” during the Growth phase. This is the window to redesign supply chains before reaching peak performance and risking decline. The message is clear: redesign before disruption, not during crisis.

3) Focus on the Day After Tomorrow        

A powerful keynote emphasized shifting resources—time, attention, budget, and talent—from the “Garbage of Yesterday” to building adaptive, future-ready capabilities.

• “Today” represents current operations and firefighting.
• “Tomorrow” is about incremental improvements.
• “Day After Tomorrow” is where organizations build structural resilience and strategic reinvention.

Outdated systems and thinking (the “Garbage of Yesterday”) drain resources and limit adaptability. The real transformation lies in scenario-based design and digital twin-led planning.

Garbage of Yesterday

• Focus Area: Strategic drag, legacy systems
• Supply Chain Design Action: Sunset outdated tools, break silos, shift away from cost-only metrics
• Use Case Example: Decommission legacy excel based supply chain design tools

Today

• Focus Area: Execution, firefighting
• Supply Chain Design Action: Automate alerts, streamline flows, improve visibility
• Use Case Example: PO Collaboration provides data for rapid redesign of supply and transportation routes

Tomorrow

• Focus Area: Incremental improvements
• Supply Chain Design Action: Run what-if scenarios, shift sourcing, improve collaboration
• Use Case Example: Reconfigure distribution based on port and geopolitical risk from third party supplier data

Day After Tomorrow

• Focus Area: Strategic resilience & reinvention
• Supply Chain Design Action: Invest in digital twins, model disruptions, redesign network
• Use Case Example: Shift sourcing from China to LATAM

4. Everything Is an Agent Now        

“Agent-washing” was rampant—every interface suddenly rebranded as an "agent." I remain skeptical. Declaring 100s of agents without tangible outcomes isn’t innovation. Real AI impact lies in data quality, data engineering, and meaningful applications.

At Coupa, we believe in quality over quantity. Our advantage isn’t just in the number of agents—it’s the underlying data network and decisioning architecture that connects supply chain design to execution. We are excited to showcase agentic AI capabilities at Inspire 2025 (May 12-15 2025 at Las Vegas - next week !)

5. Decisioning Systems: The New Supply Chain Framework        

Arthur Mesher and Amber Salley's session, “Is Supply Chain Planning SaaS Dead?”, was a highlight. Art's thesis: the future lies not in monolithic platforms, but in modular, outcome-driven Decisioning Services.

Traditional planning systems—designed around process automation and long deployment cycles—are being replaced by high-fidelity, context-aware systems driven by operations research, data science, and distributed computing.

Here’s how this shift applies to supply chain design:

Tools & Approach

• Traditional Model: Static models, centralized execution
• Decisioning Model Impact: AI agents for dynamic design iteration
• Strategic SC Design Use Case: AI-driven platform evaluates tariff shifts for continuous nearshoring assessment

Optimization

• Traditional Model: Global, uniform strategies
• Decisioning Model Impact: Localized, domain-specific optimization
• Strategic SC Design Use Case: Segment network by product type and geography for optimized flows

Flexibility

• Traditional Model: Rigid, fixed processes
• Decisioning Model Impact: Modular, plug-and-play components
• Strategic SC Design Use Case: Pilot carbon-aware sourcing in LATAM before scaling globally

Design Philosophy

• Traditional Model: Designed in isolation
• Decisioning Model Impact: Embedded intelligence in every step
• Strategic SC Design Use Case: Integrate disruption signals (e.g., port delays) directly into sourcing model

Outcome Orientation

• Traditional Model: Efficiency-focused (process adherence)
• Decisioning Model Impact: Outcome-focused (resilience, scalability, fidelity)
• Strategic SC Design Use Case: Redesign DCs to reduce geopolitical exposure across East Asia

Customization

• Traditional Model: Made-to-stock configurations
• Decisioning Model Impact: Engineered-to-order decisioning
• Strategic SC Design Use Case: Run SKU-specific simulations for seasonal launch fulfillment in different markets

Final Thoughts        

There were some standout insights, but also notable absences. The looming chaos around tariffs received relatively little airtime. AI was everywhere—sometimes meaningfully, often superficially.

But one thing stood out clearly: Coupa is leading in real AI, not because of how many agents we have, but because of our data moat and the tight integration of design (SCDP) with execution (S2P).

“Design to Pay” is emerging as a powerful category—and one that may just reshape how supply chains are built and run.