Schneider Electric

Schneider Electric, a global industrial technology leader serving buildings, data centers, industry, and infrastructure customers across more than 100 countries, had built its supply chain around traditional efficiency metrics: on-time delivery percentages, leadtime variances, and backlog reports. As post-pandemic volatility became the norm in energy and automation markets, those metrics masked a deeper problem. During a strategic review with a key OEM customer in Europe, the company heard a pointed critique: "We just don't know what to expect. It's the uncertainty that hurts us the most." The issue was not delivery rates — it was predictability and agency. Customers needed commitments they could plan against and early warnings when commitments were at risk. The absence of proactive communication was eroding trust and generating costly escalations that reactive OTD scores did nothing to prevent.

To close the confidence gap, Schneider Electric built an end-to-end supply chain control tower as a unified digital backbone, integrating event-level data streams across its global logistics and fulfillment network. Machine learning and predictive analytics were applied to this signal fabric to detect exceptions in real time, analyze root causes, and recommend resolution options with explicit cost and service trade-offs — automating routine decisions so teams could focus on high-value exception management. Three foundational practices governed the build: ensuring data quality at capture so models learn from accurate inputs; consistently time-stamping every event to enable AI detection of ETA drift and emerging bottlenecks; and designing explainability into every alert so teams received not just "ETA moved" but the reason and a recommended action. The operating model was restructured around three customer communication horizons — Now (live disruptions), Near (anticipated ETA shifts), and Next (proactive allocation and commitment) — embedding proactive outreach into standard workflows rather than treating it as after-sales care.

Customer satisfaction on delivery recovered more than 60 points from its 2022 low, one of the most significant recoveries in the company's recent supply chain history. Net Promoter Score on Delivery (NPSoD) rose by double digits, widening the performance gap with competitors. The Net Satisfaction Score (NSS) trended consistently upward, signaling restored trust across the customer base. Critical-part escalations fell sharply as risks were surfaced and communicated before customers needed to intervene — the clearest sign that the shift from reactive to proactive was taking hold. Schneider Electric has held the #1 ranking in Gartner's Supply Chain Top 25 for three consecutive years, a recognition that reflects both operational excellence and the customer experience improvements anchored by this initiative.

• 60+ point recovery in customer satisfaction on delivery (from 2022 low)
• Double-digit increase in Net Promoter Score on Delivery
• #1 Gartner Supply Chain Top 25, three consecutive years

• Customer experience metrics like NPSoD and NSS are lead indicators of loyalty and future revenue — treat them as north star metrics alongside cost and speed, not soft scores.
• AI is only as reliable as the signal fabric beneath it: data quality at capture and consistent event time-stamping are prerequisites, not afterthoughts.
• Proactive communication tailored to customer type — OEMs needing explainable ETAs, distributors expecting notifications before they ask, VIP accounts requiring prioritized allocation — builds more trust than generic outreach.
• Track how many issues are resolved before the customer asks; that metric reveals supply chain health more clearly than OTD alone.
• Consolidate around a common signal fabric rather than layering dashboards; overlapping systems amplify noise and slow the decisions that matter most.