This story first appeared in the November/December issue of Supply Chain Xchange, a journal of thought leadership for the supply chain management profession and a sister publication to AGiLE Business Media & Events’ DC Velocity.
For decades, supply chains have been focused on efficiency—moving goods faster, cheaper, and more reliably. But as a supply chain executive at Schneider Electric, I have seen customer expectations change, particularly as volatility has become the norm.
Schneider Electric is a technology company that delivers energy and automation digital solutions to drive efficiency and sustainability for customers worldwide. We serve four key end markets: buildings, data centers, industry, and infrastructure. Our supply chain is designed with the customer at its core—ensuring responsiveness, resilience, and innovation at every step. We also have the distinction of being ranked first in the analyst firm Gartner’s annual “Supply Chain Top 25” for the past three consecutive years.
Recently we have seen customers assess us not just on what we deliver but also on how they experienced that delivery: Were promises clear? Were risks explained before they asked? Did they have choices when things went wrong?
The shift in focus—from fulfillment to experience—has had profound implications. It means supply chains are judged as much on trust as on cost or speed. And trust must be designed in from the start. This change required that we refocus our logistics and fulfillment operations and metrics around the customer experience. We needed to better understand what our customers’ expectations were and then better communicate how well we were meeting those expectations.
THE MOMENT OF REALIZATION
The impetus for this change came a few years ago, during a review with one of our key customers, an original equipment manufacturer (OEM) in Europe. We were reviewing data that would be familiar to any logistics manager—on-time delivery (OTD) percentages, leadtime variances, and backlog reports—but the conversation kept circling back to one simple frustration that the customer had:
“We just don’t know what to expect. It’s the uncertainty that hurts us the most.”
That was the turning point. The issue wasn’t whether we hit 90% or 95% OTD. The issue was confidence. Customers wanted commitments they could plan against and early warnings when those commitments were at risk. One truth became clear: Customers don’t expect flawlessness, but they do expect honesty and agency. They weren’t asking for perfection—they were asking for reliability they could understand.
CUSTOMER EXPERIENCE AS A “NORTH STAR”
That insight reframed our approach. Instead of treating customer experience as a by-product of operations, we began treating it as a “north star metric,” one that captures the core value that we aim to deliver to our customers and a chief indicator of our long-term success.
Part of this approach involves realizing that different customers will have different priorities:
- OEMs want estimated times of arrival (ETAs) to be not just visible but also explainable.
- Distributors want delivery notifications to arrive before they ask.
- VIP customers running multimillion-dollar, time-critical projects want commitments to be safeguarded with prioritized allocation and to receive proactive communication when risks emerge.
When the customer’s experience becomes the main focus, operational performance is evaluated differently. You don’t ask, “Is the shipment on time?” You ask, “Will the customer feel informed and in control?” In practice, we wanted to track how many issues are resolved before the customer asks—a metric that resonates more than OTD alone.
As a result, we began to build customer communication into the operating model, not as after-sales care but as a proactive capability. These communications involved three key elements:
- Predictive notifications when risks emerge.
- Clear explanations of any exceptions or risks tied to root causes.
- Options for customers to choose their mitigation path.
We also realized that we could not build that feeling of trust and agency in a single moment. Instead we needed to create and sustain it across three horizons:
- Now—by stabilizing live disruptions quickly and consistently.
- Near—by anticipating tomorrow’s ETA drifts or capacity mismatches before they surprise the customer.
- Next—by shaping commitments and allocating constrained parts based on customer criticality.
The orchestration of communication across these horizons matters as much as the analytics. It ensures that each decision—whether made by a planner or a care agent—directly supports customer confidence.
USING TECHNOLOGY TO UNLOCK FORESIGHT
As we worked to improve communication, we knew that more tools or more metrics don’t necessarily create more trust. In fact, overlapping systems often make signals and alerts noisier and decisions slower. What mattered was not adding another dashboard, but simplifying the technology landscape around a common signal fabric.
To enhance real-time visibility across our supply chain, we invested in integrating event-level data to build a comprehensive end-to-end control tower. This digital backbone enables us to sense and respond with agility.
By applying AI (artificial intelligence) and predictive analytics, we transformed this rich fabric of signals into actionable foresight. Today, we can detect and monitor exceptions in real time, analyze root causes, recommend resolution options with clear cost and service implications, and automate routine tasks. All of this allows our teams to focus on what truly matters: managing exceptions and driving value.
As we worked to create this foresight, three practices proved essential:
1. Data quality at capture: By making sure that our data was accurate at the source, we can ensure that our predictive models are learning from the right inputs.
2. Time-stamped events: Every event and data signal needs to be time-stamped consistently and accurately. This practice allows AI to detect patterns like ETA drift or bottlenecks.
3. Explainability by design: All analytics need to be combined with a narrative context. The information and insight provided can’t just be “ETA moved”; it also needs to explain why the ETA moved and what action to take.
With this foundation, predictive engines could flag risks days earlier, recommend reallocations, and help teams simulate alternatives. In short, AI became useful not as a standalone tool but as a layer that made the signal fabric proactive rather than reactive.
Technology optimization, in this sense, isn’t about deploying the newest platform—it’s about ensuring that every tool is tied directly to a decision that customers feel. That focus allowed us to amplify the role of predictive analytics and AI, not as “shiny” add-ons, but as practical enablers of confidence.
CHANGES IN OUTCOMES
The results validated the approach:
- Net promoter score on delivery (NPSoD) rose by double digits, widening the performance gap with competitors.
- Customer satisfaction on delivery recovered more than 60 points from its low in 2022.
- OTD improved, but more importantly, confidence in commitments increased.
- Critical-part escalations fell dramatically as risks were surfaced earlier.
- Net satisfaction score (NSS) trended upward, signaling restored trust.
The real breakthrough was cultural: Teams stopped celebrating only when a shipment was “on time.” They began celebrating when a customer’s confidence was protected—even if that meant a tough conversation and a revised plan.
TRUST AS DIFFERENTIATOR
Customer experience is not the only measure of supply chain success—but it is one of the most powerful. Cost competitiveness, resilience, sustainability, and innovation still remain critical levers. But when volatility disrupts even the best-laid plans, it is the experience of clarity, anticipation, and choice that keeps customers loyal.
That balance matters: Efficiency moves goods, sustainability secures the future, but experience sustains trust in the present. The supply chains that win will be those that integrate all of these drivers into a coherent model.
Reflecting on this journey, three lessons stand out:
1. Experience is measurable. NSS and NPSoD are not soft scores; they are lead indicators of loyalty and growth.
2. Signals matter more than screens. Reliable, explainable data is the foundation for foresight.
3. Communication is strategy. A proactive message with options can transform a disruption into a trust-building moment.
In today’s environment, customers aren’t buying only products. They are buying **ital{confidence}—the assurance that plans can be made and promises will be kept. The future of supply chain leadership lies in designing for that confidence: treating experience as the company’s north star, wiring decisions with living data, and empowering teams to act with clarity.
Efficiency moves goods. Experience builds trust. And trust, in volatile times, is the ultimate differentiator.
