Ashley Greuel

Special Guest Blog Post written by Jeff Echel and Steve Lykken with e2open   Supply chain planners in high-tech don’t just manage shipments; they’re crisis managers, data detectives, and sometimes, referees in a high-stakes game of inventory tug-of-war. Why do these planners find themselves huddled in “war rooms,” surrounded by spreadsheets and urgent emails? It starts with relentless pressure: customers expect rapid, reliable service, but the reality is a maze of long lead times, outsourced manufacturing, and unpredictable global logistics. Securing critical components can take months, and a single misstep, like overstocking or missing a shipment, can ripple through the business, impacting revenue and margins. The chaos: War rooms and spreadsheet battles Add to that, the complexity of forecasting demand. Planners reconcile noisy, inconsistent data from retailers and distributors, often with little visibility, into . Forecasts are built, torn down, and rebuilt, sometimes manually, as teams try to align bottom-up channel data with top-down financial targets. Meanwhile, supply plans are constantly threatened by shortages, excess inventory, and last-minute changes. When demand surges or supply is disrupted, channels compete for limited stock, sometimes “stealing” from each other, and sometimes winning simply by being the loudest voice in the room. All of…

Supply chains are more volatile and interconnected than ever, but many planning processes still rely on disconnected systems, manual analysis, and spreadsheet-based interventions. This white paper explores how network optimization, supported by advances in optimization technology, workflow design, cloud computing, and AI, can help planning teams evaluate cross-functional trade-offs, respond faster to change, and move from static plans to continuous, decision-driven supply chain planning. Inside the White Paper: – Why traditional planning systems and network optimization evolved separately, and why that separation limits decision quality in today’s supply chains. – How network optimization helps evaluate cross-functional trade-offs across sourcing, production, inventory, transportation, fulfillment, service, cost, and capacity. – Why continuous network optimization is different from one-time strategic modeling, and how it can support recurring tactical and operational planning decisions. – How AI and configurable workflows can make optimization more usable for planners without requiring them to become modeling experts. – How planning systems and network optimization can work together in a feedback loop that improves decisions over time. Click here to download