Posted: August 28, 2026

Insights from the “Data Infrastructure in Life Sciences” webinar series – episode one

For life sciences manufacturing operations, a data historian is one of the first investments in the digital GAMP roadmap. But all too often when evaluating historians, companies fail to anticipate what’s needed in later stages of their digital journey.

And that’s where AVEVA™ PI System™ rises above other historians. It provides a comprehensive data infrastructure for real-time operational information management.

“Infrastructure,” though, can seem to be an ambiguous term.  So, our first episode sets out to explain it using the analogy of city planning. Planning for the future needs of digital infrastructure and planning for the future needs of a city share the same set of structural challenges.

• Scale uncertainty. Both have to serve immediate needs while anticipating future demand that isn't yet visible.
• Invisible foundations. Both rely on hidden elements– pipes, cables, data pipelines – that nobody notices until they fail.
• Retrofit cost. Both are exponentially more expensive to fix than to build correctly from the start.
• Standards as enablers. Both depend on standards – zoning codes, building codes, data standards – to ensure interoperability across the whole system.
• Multi-stakeholder coordination. Both require aligned decisions across stakeholders with different priorities and time horizons.

This analogy is useful because it helps to shift the conversation from reactive to proactive: A city planner isn't asked simply to fix today’s problems. They are asked to design for the city ten and twenty years from now, while also keeping the present city running smoothly.

When you’re designing data infrastructure, you also need to plan for the present and the future—especially   considering management’s expectations of AI’s promise. AVEVA PI System enables companies to build the right data foundation to deliver results right now and for the future, with its promise of enterprise-wide, scalable AI.

AI models are the ultimate infrastructure stress test. They will expose the differences between a simple historian and data infrastructure.

AI models demand data at a scale, quality, and contextual richness that exposes every shortcut taken in the previous decade. Organizations that were collecting data reactively, capturing only what was needed for immediate compliance, may now find themselves boxed in by their data foundation limitations.

"Too many clients are looking to do predictive models based on data that doesn't exist... If they thought a bit more like a city planner, we would have definitely seen some people being able to act on their AI more effectively right now."
— Rory Sheehan

Finally, the right infrastructure must also enable flexibility. City planners don't know exactly where the population will be in 20 years. They design flexible, extensible, standards-compliant infrastructure so that when the future arrives in an unexpected form, it can be accommodated without tearing down what was previously built. This is the kind of mindset you need too when you’re planning your data infrastructure.

Do you want to know what’s next?

Watch the second episode and discover the journey toward transforming operations in your company.