When AVEVA talks about a “10x improvement in operational data management maturity” in this recent article, they’re pointing toward a goal many operators already recognize: operational data has to be usable, trustworthy, and shared if it’s going to drive real outcomes. That direction is right. Where most teams struggle isn’t with the vision — it’s with execution inside real, messy OT environments.

Here’s what we know from doing this work: 10x doesn’t come from a platform alone. It comes from fixing the fundamentals. Most plants are sitting on data that’s fragmented, inconsistently structured, and lightly governed at best. When that data is centralized, contextualized, and treated as operational infrastructure — not an IT science project — the improvement can be dramatic. But only if it’s tied directly to how the business actually runs.

AVEVA CONNECT fits into this picture for a reason. It provides a foundation where OT data can be aggregated, governed, and used across the enterprise — enabling analytics, AI, and optimization at scale. That’s necessary. It’s also not sufficient on its own. Between a strategy on paper and a functioning system in production is a long list of decisions that someone has to make correctly — about connectivity, security, context, ownership, and long-term maintainability.

This is where experience matters. Data without context is noise. Context without structure collapses under its own weight. Whether you call it a unified namespace or not, the work is the same: define meaning, assign ownership, and make it operational. The mistake we see over and over is trying to design perfection upfront instead of imposing order on what already exists and improving it deliberately.

The way forward is proven and repeatable. Reduce complexity instead of admiring it. Categorize assets. Standardize integration and security patterns. Connect data efforts to specific operational goals like OEE, FPY, and OTIF. This is what good systems integration actually looks like — translating modern platforms into systems that work in the real world, day after day. Do that well, and a 10x improvement isn’t aspirational. It’s achievable.