Earlier this week, I read an article by Josef Schöttner discussing PLM software Integration Solutions. You can find the article [here].
The article speaks about modern PLM software and how modern PLM solutions can organize different data silos and integrate between them. The article emphasizes that true Product Lifecycle Management (PLM) must encompass all product and process-related data across a product’s lifecycle, integrating technical, logistical, organizational, and business data from systems like PDM, PLM, CRM, SCM, MES, and CRM. Those are multiple business systems focusing on document management, software development, supply chain, quality management, project management and many others. The systems connected and need to share the information.
The article critiques the mislabeling of PDM systems as PLM, highlighting that a single system cannot seamlessly manage all lifecycle data. Instead, PLM should represent an integrated solution enabling complete, consistent, and up-to-date data management across all value-added processes. This holistic approach is crucial for achieving digital factory objectives and competitive Smart Factory outcomes.
My favorite passage is as follows:
“During further value-added processes, certain technical product data (part master records, parts lists, drawings, etc.) is transferred to ERP/SCM, MES, and CRM with appropriate approvals as required. By applying the relevant business applications, planning, procurement, and cost/price calculation data, production and quality data, as well as sales and distribution data, are created. Thus, the process-related description of a product includes not only technical but also logistical, organizational, and business data.”
The question the article left me with is how to organize this desired data integration solution.
Integration of Multiple Systems
This earlier statement raises an essential question: how can we address integrations effectively? How to get always up to date information to cover the entire lifecycle. While the picture in the article makes total sense, achieving the status of data that is seamlessly integrate is complex. Some PLM people now say now – this is where digital thread begins. Even so, how to do so?
This problem is not new and has existed in the industry for over 25 years. I recall PLM vendors frequently discussing PLM-ERP (and other) integrations. Here are my thoughts on three possible approaches:
(1) Build one system for everything. In my view, the industry has tried this approach for the past 30 years, and it has proven ineffective.
(2) Sync data between systems. This is the current standard among PLM/ERP vendors and service providers. While it is often inefficient and laborious, it delivers results. The sheer number of “sync projects” in the industry is enormous. Essentially, the industry continues to “pump” data from one CRUD database to another.
(3) Adopt an integrated data layer with a flexible data model and collaborative tools (e.g., collaborative workspace). The goal is to develop a data model that can interface with all systems. Whether it involves a knowledge graph, large language models (LLMs), or another technology, time will tell.
What is my conclusion?
Data represents the biggest asset in each manufacturing company we misuse the most. We do care of physical parts design, we concerned about supply chain efficiency and shopfloor operation planning. But we fundamentally misuse the data. The current paradigm of data used in PLM system is wrong because it focuses on the document management and data ownership first. The data accumulated in multiple systems remain scattered and not used. Infinite number of “syncs” pumping data between systems. PLM industry has no business model how to use the data, there is only a model to own the data. This is how the business of largest PLM vendors work.
Manufacturing businesses face widespread challenges with data management. Data often resides in multiple systems, is poorly managed, and is frequently misinterpreted. For 25 years, the industry has sought a better way to align this data and make it more accessible – essentially the “holy grail” of PLM. Escaping the current paradigms of data management (SQL databases + PLM object modeling + data synchronization across multiple systems) remains a challenge but is becoming increasingly achievable.
If you work in a manufacturing company, ask yourself: How can we get smarter with data? There are countless technologies available, yet many manufacturing companies remain trapped in the “Excel paradigm” and continue buying from major PLM vendors.
Just my thoughts.
Best, Oleg
Disclaimer: I am the co-founder and CEO of OpenBOM, a digital-thread platform that offers cloud-native collaborative services, including PDM, PLM, and ERP capabilities. With extensive experience in federated CAD-PDM and PLM architecture, I advocate for agile approaches, open product models, and the adoption of cloud technologies in manufacturing. Please note that my opinions may reflect my work at OpenBOM and could be unintentionally biased.
