Lectra’s white paper says that as technology adoption matures, the competitive gap in fashion will widen – not between “digital” and “non-digital” companies, but between those that operate predictively and those that remain reactive.
“The brands that turn traceability, operational data, and AI into a single, profit‑protecting system will be the ones to outpace their competition,” the study argues. “As economic uncertainty becomes the new baseline, the biggest risk for fashion brands isn’t failing to innovate – it’s operating without visibility.”
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Brands are being urged to move from bringing in more data to instead acquiring “better, more connected, decision-making data tied to the resources actually at risk.”
Lectra says the more effective fashion brands are no longer treating technology as an overlay; they are restructuring how decisions flow through their organisation.
“Technology is the key to enable that so that data is shared across design, sourcing, production and distribution. When measurements, materials, supplier capacity, and demand assumptions all live in one place, an organisation can stop questioning which set of numbers is the most accurate, and instead can start resolving issues before they become expensive.”
PLM and connected production systems deliver ROI because they can apply the same data, rules, and processes consistently across teams and seasons.
“In practice, this looks like development timelines compressing because approvals and feasibility checks move earlier. Production outcomes become more predictable because there are fewer handoffs across teams and manual reconciliations. Speed‑to‑market improves because friction is removed that used to be accepted as “this is just how we work.” For management teams, they get a single dataset to reference to help power portfolio‑level decisions,” reads the study.
The white paper also argues the benefit of traceability on operational value. When brands can see materials and components moving through suppliers and tiers – and can link that movement to SKUs and POs – they reduce uncertainty, which is the most expensive variable in fashion. For example, if a quality issue emerges at one supplier, orders can be re-routed before finished goods are impacted.
“This enables brands to meet regulatory expectations while also improving sourcing efficiency and resilience. Material substitutions can be validated against compliance and performance data, not just price. Supplier scorecards shift from anecdote to evidence. And for over‑extended leadership teams, compliance becomes a byproduct of normal operations, not a last‑minute scramble.”
Where AI is concerned, the study says its biggest benefit is predictability.
“Predictable operations yield fewer expensive buffers: less excess inventory, fewer rush orders to catch up, fewer last‑minute sourcing changes that blow up cost and disrupt timelines. The result is not just more efficiency, but stronger financial control across the value chain.
“Ultimately, AI equips brands with what they need most – the ability to see risk before it becomes costly. When every team operates from the same data foundation, and AI amplifies that visibility with stronger forecasts and smarter allocation, the entire value chain becomes more predictable and more profitable. It’s this shift from reacting to anticipating that defines the true ROI of AI in fashion.”
