Digital transformation is reshaping the core principles of product lifecycle management (PLM) and enterprise systems at large. Among the many questions it raises, one remains timeless: What comes first, data or process? I have explored this question in my blog over the past decade, and revisiting those reflections through the lens of today’s AI-driven landscape is fascinating. Let me take you on a journey through this conundrum, blending historical insights with modern advancements in digital transformation.
Going back in history
Years ago, I wrote a blog titled “PLM: Data vs Process – Wrong Dilemma?” which became a one of my first discussions on this topic.
Jim Brown vs Chad Jackson Debates
The article I mentioned above highlighted a fascinating debate between two PLM analysts, Chad Jackson and Jim Brown, on Tech4PD (watch the video in the old article).
Their engaging exchange is fascinating and a decade history including modern perspective added even more to this conversation to demonstrate the progress we’ve made related to prioritizing data or process in PLM strategies.
Another blog of mine, “PLM Data vs. Process: A Turn Towards Linked Data,“ delved into the concept of context and the importance of linking data. This shift was very important. Three years later, it became evident to me how delivering the right data in the right context could redefine PLM’s potential. It wasn’t just about managing data or processes—it was about creating an ecosystem where they enhance each other.
The Rise of Context and Linked Data
One of the most significant advancements in this area came from the idea of “context.” To provide the right information to the right person, at the right time, requires more than just well-defined processes or robust data management. it is about contextual data processing It demands a contextual layer—a means of linking data in ways that make sense for specific tasks, roles, or decisions. Check my article – Data vs Process: turn towards linked data.
This quote encapsulates a fundamental shift: the blending of structured and unstructured data to deliver actionable insights tailored to user needs. It’s not just about having the data or the process but ensuring they work in unison to support decision-making.
The Shift to Data-First Thinking
Digital transformation fundamentally changes the relationship between processes and data. In the traditional model, processes dictated how data was structured, stored, and accessed. Digital transformation flips this paradigm, prioritizing data as the foundation of modern business operations.
Companies now focus on how to trust and manage data, recognizing that data lives longer than applications and business tools. For example, while design history can span decades, companies may switch CAD and PDM applications multiple times [this is really hard even today, but some systems can import data from old system to re-establish the history]. The same principle applies to CRM, MRP, and other systems: data records outlast processes and enterprise software.
Why is data more important than processes in a digital-first world? Here are some key reasons:
- Analytics: Data provides the foundation for real-time analytics, enabling businesses to make informed decisions quickly and respond to changing conditions.
- Process flexibility: Processes are inherently static and limited to predefined scenarios, while data enables dynamic, context-aware responses.
- Interconnected silos: By connecting data through a digital thread, businesses can ensure seamless collaboration across design, manufacturing, and operations.
- Data long term vaue: Unlike processes, which can be reengineered relatively quickly, data accumulates value over time. A robust data foundation supports innovation, automation, and strategic decision-making.
In this new paradigm, data is not merely a byproduct of processes—it is the central asset that drives innovation, efficiency, and competitive advantage. Businesses that prioritize data management are better equipped to navigate the complexities of digital transformation and achieve sustainable success.
Digital Transformation Era and AI Future
Digital transformation leads me directly to AI transformation. The integration of artificial intelligence into PLM software and enterprise systems will put the end into data vs. process debate. Everything is now data – about products, processes, the data is structured and unstructured. It covers multiple aspects of product lifecycle. Modern PLM models building product knowledge graph and transforming data into language models can learn adapt and evolve. The opportunity here is amazingly interesting and we are just scratching the surface of what is possible. Here is an opportunity I see here:
- Automate Contextualization: AI can analyze vast amounts of structured and unstructured data to deliver contextual insights (not only contextual data as before)
- Enhance Decision-Making: By identifying patterns and predicting outcomes, AI helps users make informed decisions without being bogged down by data overload.
- Redefine Processes: Processes no longer need to be rigid or static. AI enables dynamic, adaptive workflows that respond to changing conditions and new data inputs.
To echo what I’m thinking about the importance of data management and disconnecting data from applications, here is a comment Jos Voskuil left on another my article earlier this week:
Jos Voskuil’s thoughts on the matter back in that time was resonating As he stated:
“…to improve your product lifecycle management capabilities it is not about processes first – as processes will change over time. It is about real-time access to reliable data. AI can help here but it is a gradual process”
Disconnecting Data From Applications and New Paradigm
The old “data vs. process” debate has evolved into a more holistic approach where:
- Product data provides the foundation—the raw materials needed for decision-making.
- Processes offer structure—guiding how tasks are performed and decisions are made.
- AI adds intelligence—bridging gaps, contextualizing information, and automating actions.
Digital transformation has redefined the fundamentals of PLM and other business systems. What was once a debate where to start is transforming now into a new paradigm where data comes first and will be having a longer life compared to business systems.
What is my conclusion?
Reflecting on this journey, it’s clear that the “data vs. process” conundrum was never about choosing one over the other. It was about finding the balance and leveraging the technologies available to bridge gaps and create value. Today, with AI and digital transformation at the forefront, we are finally seeing the realization of this vision where data is clearly becoming a foundation.
The conclusion is that data is becoming dominant in everything we do. Capturing data about what a company does, how it performs, and what products it develops, and turning it into intelligence, is quickly becoming a universal formula for success in every business.
Just my thoughts…
Best, Oleg
Disclaimer: I’m the co-founder and CEO of OpenBOM, a digital-thread platform providing cloud-native collaborative services including PDM, PLM, and ERP capabilities. With extensive experience in federated CAD-PDM and PLM architecture, I’m advocates for agile, open product models and cloud technologies in manufacturing. My opinion can be unintentionally biased
