Unnamed Global Automation Product Manufacturer

Electronics and semiconductor supply chains are among the most complex in manufacturing — characterized by long lead times, multi-tier supplier networks, and demand volatility that can cascade quickly across the entire value chain. This global automation product manufacturer faced a critical visibility gap: more than 15 separate ERP systems operated in isolated silos across the organization, each capturing only a fragment of planning data with no unified view. Demand and supply planning teams relied on manual, spreadsheet-driven processes that could not keep pace with global demand shifts. Without real-time data, decisions defaulted to opinion rather than fact — leaving inventory levels, product availability, and cost outcomes exposed to unnecessary and avoidable risk.

The company partnered with o9 Solutions to deploy the o9 Enterprise Knowledge Graph — a graph-based data architecture purpose-built for supply chain complexity — creating a true digital twin of the entire value chain. The implementation consolidated demand planning, supply planning, and scenario analysis functions onto a single platform with a unified underlying data model, replacing both Excel-based workflows and Infor ERP planning layers. The digital twin enabled real-time modeling of the full supplier network, including production capacities, component lead times, and supply parameters across all tiers. With this foundation in place, planners gained the ability to run what-if scenario analyses on live data — evaluating the downstream impact of demand shifts, supply disruptions, or capacity constraints before committing to a course of action.

The digital twin delivered end-to-end supply chain visibility across the organization for the first time, compressing response time to market shifts from weeks to hours. Key outcomes include:

• Improved product availability, directly supporting top-line sales growth
• Reduced inventory levels and lower non-standard supply chain costs
• Higher employee productivity as manual planning and data-reconciliation tasks were automated
• Sustainability benefit: reduced inventory translated into fewer transportation movements across the distribution network

Planners who previously spent cycles reconciling data across 15+ disconnected systems could redirect their effort toward value-adding analysis and exception management — a structural shift in how supply chain decisions are made.

• ERP fragmentation is a root cause, not just a symptom — unifying 15+ systems under a single data model eliminates the decision latency that comes from reconciling conflicting data sources.
• A digital twin's value compounds when it models the full network: capacities, lead times, and supply parameters must all be represented for scenario planning to reflect operational reality.
• Replacing spreadsheet-based planning with a live data model directly improves response agility — compressing reaction time from weeks to hours on demand and supply disruptions.
• Inventory reduction carries a sustainability multiplier: fewer stock buffers mean fewer transportation movements, reducing both carrying cost and carbon exposure.