Closing the Decision Gap in Volatile Supply Chains - with & Prasad Mahajan of Optilogic and Dr. Gopalendu Pal of Target

2026-06-25 · Source: The AI in Business Podcast · Field: Business & Management — Operations & Process Management, Corporate Strategy & Leadership · Depth: Intermediate, extended

Summary

Dr. Gopalendu Pal of Target and Prasad Mahajan of Optilogic discuss how supply chain leaders can navigate increasing volatility, which has become the default operating condition. They highlight that traditional planning cycles are obsolete, requiring continuous redesign and rapid decision-making. Key challenges include outdated assumptions, siloed KPIs, and fragmented data, which impede responsiveness and create a "decision speed barrier." The experts advocate for strengthening data foundations, auditing existing constraints, and implementing scenario analysis with human-guided AI to evaluate operational options. This approach aims to shorten the cycle between sensing disruption and adjusting operations, moving from reactive mitigation to proactive preparedness. They emphasize the need for network-level goalposts to overcome conflicting departmental KPIs and foster cross-functional alignment.

Key takeaway

For supply chain leaders grappling with constant volatility, your priority must be to drastically shorten the time between detecting disruption and adjusting operations. You should audit existing constraints and data foundations, then implement human-guided AI for rapid scenario analysis. Establish network-level goalposts to align departmental KPIs, ensuring your organization proactively adapts instead of reactively mitigating.

Key insights

Volatility is the new normal, demanding continuous operational redesign and accelerated, data-driven decision-making.

Principles

• Volatility is the default operating environment.
• Shorten disruption sensing-to-adjustment cycles.
• Siloed KPIs and fragmented data impede responsiveness.

Method

Audit constraints and business rules, establish a Center of Excellence for future supply chain ownership, and implement AI-driven scenario analysis with human oversight to align data foundations.

In practice

• Use AI for rapid, multi-scenario analysis.
• Evaluate and simplify current SOPs.
• Define network-level goalposts for cross-functional alignment.

Topics

• Supply Chain Volatility
• Decision Speed
• Scenario Analysis
• Human-Guided AI
• KPI Alignment
• Data Foundations

Best for: Executive, Director of AI/ML, Operations Professional, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI in Business Podcast.