Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I have over 15 years of experience across industrial manufacturing, mining, engineering, and consumer packaging supply chains, spanning demand planning, inventory optimization, and end-to-end planning transformation. My work has combined hands-on operational roles with global consulting and SME responsibilities, particularly around SAP IBP, PPDS, and advanced planning design. I’ve led full-cycle planning implementations, supported complex aftermarket and make-to-order environments, and advised leadership teams on balancing service, cost, and resilience. What differentiates my experience is operating at the intersection of planning theory, system execution, and real-world constraints.

Q2. What is the one shift in industrial supply chains that most changes planning decisions today, and why does it matter more now than two years ago? 

The biggest shift is the move from cost-optimized, forecast-driven planning to resilience-aware, scenario-driven decision-making. Two years ago, volatility was treated as an exception; today, it is the baseline assumption. This matters because planning decisions now need to price risk explicitly, not just efficiency. Lead times, sourcing strategies, and inventory buffers are increasingly strategic levers rather than purely operational ones.

Q3. Where do advanced planning tools or AI genuinely improve forecasting and inventory outcomes, and where do they fail to deliver measurable ROI? 

Advanced planning tools and AI add the most value in demand sensing, exception management, and multi-echelon inventory optimization, where data quality is strong, and decisions are repeatable. They struggle when the underlying master data is weak, demand is structurally intermittent, or organizations expect automation to replace governance. ROI fails when tools are implemented as technology upgrades rather than decision redesign initiatives. The gains come from better decisions, not better algorithms alone.

Q4. Where do ESG requirements materially constrain sourcing flexibility, cost, or margins in industrial supply chains, and how do leading firms manage the trade-off? 

ESG requirements most often constrain sourcing flexibility through supplier qualification limits, regional sourcing mandates, and higher compliance-driven input costs. These constraints directly affect margins in commodity-heavy, energy-intensive industries. Leading firms manage the trade-off by segmenting products and customers, applying ESG rigor where it matters most commercially or regulatorily, rather than uniformly. They also invest early in supplier transparency to avoid late-stage cost shocks.

Q5. What risk is most underestimated in current supply chain resilience planning, and how does it typically surface? 

The most underestimated risk is planning-system fragility under stress, not physical supply disruption. When volatility spikes, many organizations discover that their planning logic, parameters, and decision rights cannot adapt fast enough. This typically surfaces as overreaction: excess inventory in some nodes and critical shortages in others. The issue is less about data availability and more about decision latency.

Q6. Which geography or customer segment looks attractive in demand data but is operationally hardest to scale profitably, and why? 

Aftermarket and emerging-market demand often looks attractive in topline data but is operationally difficult to scale profitably. High SKU proliferation, erratic order patterns, and service-level expectations drive disproportionate complexity. Without differentiated planning policies and service segmentation, margins erode quickly. Growth is real, but only disciplined execution sustains it.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

 
I would ask: which planning decisions in your organization are still driven by intuition or manual workarounds, and why? The answer reveals far more about scalability and resilience than any KPI dashboard. Companies that can clearly articulate how they make decisions under stress tend to outperform during disruptions. Those who cannot are usually one shock away from value erosion.