In this episode, we dive into the critical role of data integrity by design in enabling the future of smart manufacturing in the life sciences industry. As Pharma 4.0 initiatives gain traction, leading organizations are shifting from reactive compliance to proactive data governance strategies that embed quality, traceability, and trust directly into their digital systems.

Our expert guests will explore how companies are operationalizing ALCOA+ principles—ensuring data is Attributable, Legible, Contemporaneous, Original, Accurate, and more—and aligning with the FAIR principles (Findable, Accessible, Interoperable, Reusable) to future-proof their digital infrastructure. We'll discuss real-world strategiesfor building data integrity into system design, enabling seamless regulatory readiness and supporting the ethical, effective deployment of AI in regulated environments.

Whether you're a digital transformation leader, a quality professional, or an AI innovator in life sciences, this episode will offer insights into how your organization can design for trust—right from the start.

In this episode, we sit down with manufacturers and supply chain experts to explore how today’svolatile trade environment is forcing a strategic rethink across the industry. From shifting sourcing decisions and rising costs to accelerating reshoring and digital investments, we unpack how tariffs and uncertainty are no longer just a policy issue — they’re an operational reality. I am joined by several members of our Knowledge Committee as well as special guest Robert Cohen, Senior Fellow at the Economic Strategy Institute.   Our guests share real-world stories of how they’re adapting:

• Rethinking just-in-time vs. just-in-case inventory
• Using digital twins and simulation to plan around disruption
• Adjusting capital investment to favor agility and automation
• Navigating compliance across borders while lobbying for clarity at home
• 
  

We also dig into the role of predictive analytics, supply chain visibility, and policy advocacy —and what forward-looking manufacturers are doing now to prepare for what’s next.  Whether you're navigating sourcing headaches, retooling your production strategy, or trying to future-proof your business model, this episode delivers insight you won’t want to miss.

What’s really driving success with analytics and AI in manufacturing? In this episode, we dive into the latest industry survey results with Julie Fraser of Tech-Clarity to uncover what’s working, what’s not, and what leading manufacturers are doing differently. Don’t miss this data-driven conversation that puts real-world insight behind the buzz. This full survey report is available from MESA. It represents the next installment in the biennial survey that MESA has been creating for 2 decades now. There is a wealth to learn from our history of these surveys, from both current state as well as the trends that we can observe through the 21st century.

Following on the heels of a great community discussion, I have Joanne Friedmann and Khris Kammer discuss the elevation of data to the forefront of IT/OT architecture. Embedded in that is a thinking about the value of data and how it be measured, your Return on Data. Smart manufacturing and the MESA model place data at the foundation of any effective architecture. There is a significant shift in IT/OT where data is becoming the core driver of architecture decisions, rather than just an afterthought. Traditional IT/OT architectures were built around applications, with data being managed as a byproduct. Now, data-first architectures ensure that storage, processing, and movement of data are optimized for real-time decision-making, analytics, and AI-driven automation. AI and machine learning models thrive on high-quality, well-structured data. Data must be easily accessible across different systems (ERP, MES, SCADA, etc.). Organizations are implementing unified data governance frameworks to ensure consistency, security, and compliance. Modern architectures use event-driven models to react in real-time, which is critical for smart manufacturing and predictive maintenance. Manufacturing execution system (MES) platforms will evolve to be data-first, prioritizing real-time analytics. AI-driven decision-making will require IT systems to be built around data streams, not just applications. Data interoperability between legacy and modern systems will be crucial.

The pace of technology change in manufacturing can be dizzying. Some of our listeners to this podcast have asked us to take a step back from some of our deeper investigative topics and simply review the current state of technologies applied to analytics in smart manufacturing. We call this episode "Back to the Basics". I am joined by an all-star group of MESA experts to define what is artificial intelligence and machine learning and how they are being applied across all facets of manufacturing.

How is Artificial Intelligence Changing Industrial Analytics?

From the Smart Manufacturing Now event and a tumultuous year of technology change, it's clear

The practice of MRO (Maintenance, Repair, and Operations) has been with us as long as the first industrial revolution and today is as critical as ever. But Smart Manufacturing has had major impacts on MRO. Our group has assembled to discuss the impact of Smart Manufacturing on MRO. Smart Manufacturing technologies and operations enable more accurate predictive maintenance, better tracking of equipment conditions, and more efficient planning of maintenance activities, leading to further improvements in operational efficiency and cost savings.

The large language model (think Chat GPT) made quite a splash at the end of 2023. This class of technologies can be applied to many real-world challenges that face industrial enterprises. But what problems are practical to be solved today by the application of LLM technology? The MESA Analytics Working Group discusses the challenges and opportunities that LLM bring to manufacturing. Join us, its a great discussion filled with possibilities for a promising new technology.

The digital twin may be the ultimate expression of digital transformation. The concept of a Digital Twin has evolved and expanded over the years, but at its core, it generally refers to a virtual representation of a physical asset or process that can accurately represent and simulate its equivalent physical asset or process. Digital twins in manufacturing have been

Knowing where you are on your digital transformation journey is the key to setting goals and identifying and celebrating the wins. But is it healthy to obsess about this score? And whats behind this single number that is expected to define your level of readiness? And compared to whom? In this episode the analytics working group from MESA International will try to unpack all this and get to the root of the value of a digital maturity assessment.