For my 20+ years of experience in PLM business, I can see see the age-old struggle in the world of tech: on one hand, businesses are diving into a labyrinth of growing complexity – like they’re training for a data Olympics where only the boldest and bravest survive! On the other hand, customers stand at the finish line, holding up signs that read, “Keep it stupid and simple, please!”. At the beginning of my work experience many years ago, I was asked by a customer to build “a one button application” that will always do what they need, but the user experience only has a thing called “Press Here”. In fact, the idea was not dumb at all. Google built a single “search button” universe and Apple built a user experience around single button too. Microsoft made a button “Start” in their operation system, but I don’t think it ever worked simple enough. But I digressed…
So, how do we balance the desire to build the digital universe with the demand for simplicity? Well, it’s all about finding that sweet spot where we give users the power of a spaceship with the ease of a toaster! Let’s talk about how to keep things straightforward in a world that’s anything but…
Everything is getting complex in engineering and manufacturing. As manufacturing companies today navigate a rapidly changing landscape, they face multifaceted complexities. From product sophistication to supply chain management agility, the manufacturing ecosystem has grown intricate, requiring advanced strategies and tools to stay competitive.
I’m coming to DXM 2024 next week in San Antonio, TX where among many other things, I will take a place in the panel discussion – Panel Discussion: Overcoming Complexity in a Modern Manufacturing World. So, as a preparation to this panel, I wanted to gather some of my thoughts about various levels of aspects of complexity in PLM software and engineering and manufacturing systems in general.
I’d like to explore the five core levels of complexity that are shaping the future of manufacturing: product complexity, development process intricacies, global supply chains, evolving business models, and rising customer demands.
This article explores each complexity level, as highlighted by panel experts, and examines how modern Product Lifecycle Management (PLM) systems provide the foundation for data management necessary to mitigate these challenges.
Product Complexity: Beyond Mechanical Assemblies
Modern products are far more complex than ever before. What were once primarily mechanical systems now encompass electronics, software, and interconnected subsystems. The shift toward multidisciplinary products—think smart devices, electric vehicles, or industrial IoT—demands that manufacturers manage detailed product structures that span mechanical, electrical, and software domains.
Handling such sophisticated assemblies requires PLM systems with the ability to manage multidimensional Bills of Materials (BOMs), track engineering changes across domains, and foster collaboration among specialized teams. As products evolve to include sensors, connectivity features, and even AI-powered capabilities, the challenge lies not only in developing these products but in ensuring that every component is seamlessly integrated and traceable. Modern PLM systems equipped with flexible data structures and a product knowledge graph help manufacturers navigate this complexity by creating a single source of truth for product data.
Complex Product Development Process: From Concept to Market
The journey from concept to market involves multiple stages, countless iterations, and a need for rapid adaptation. In a modern manufacturing environment, companies must manage extensive design changes, maintain regulatory compliance, and ensure strict version control. Each of these aspects introduces risk to time-to-market, innovation, and product quality.
For instance, managing regulatory requirements becomes particularly challenging when dealing with products that need certification across multiple regions. Similarly, design traceability—knowing the origin, version, and approval status of every change—becomes essential for both compliance and efficiency. Robust PLM systems are instrumental here, providing traceability that enables teams to track every decision and change throughout the product lifecycle. As a result, organizations can streamline approvals, prevent costly reworks, and move confidently from design to production.
Supply Chain Complexity: A Globalized Network
Global supply chains offer manufacturers access to a diverse set of resources and capabilities, but they also introduce substantial complexity. With multiple suppliers, deficit of raw materials and components, fluctuating costs, and varying regulatory demands across regions, companies need high levels of transparency and agility to manage the inherent risks and optimize procurement processes.
A modern PLM system enables real-time, multi-company collaboration, connecting manufacturers with suppliers and other partners in a secure, centralized platform. By aligning everyone around the same data, companies can enhance supply chain transparency, adapt more quickly to disruptions, and make informed decisions based on reliable data. Whether it’s adjusting orders based on supplier constraints or tracking shipments in real-time, an advanced PLM with data integration capabilities is critical for managing supply chain intricacies.
Evolving Business Models and the Product Lifecycle
Today’s business models are shifting from purely transactional to service-based approaches, requiring manufacturers to adapt their PLM systems accordingly. Products are no longer static; they are continuously evolving with new features, particularly in connected products that leverage IoT and embedded software. Additionally, the rise of subscription and outcome-based models is pushing manufacturers to support products well beyond their initial sale.
This shift introduces new demands on PLM systems, which must now manage not only the physical aspects of products but also their software updates, data collection, and IoT interactions. A PLM solution that supports data analytics, AI, and IoT integration can provide a holistic view of the product lifecycle, enabling manufacturers to proactively monitor product performance, predict maintenance needs, and deliver continuous value to customers.
Customer and Market Demands: High Expectations in a Rapidly Changing Market
Manufacturers today are under constant pressure to deliver personalized, high-quality products faster than ever. Customers expect rapid customization, frequent updates, and uncompromised quality—all while companies balance cost constraints. This demand for agility requires manufacturers to be exceptionally adaptable and responsive in both design and production.
Modern PLM systems play a vital role in meeting these customer expectations by supporting fast iteration cycles, flexible BOM configurations, and dynamic feedback loops. Through advanced data management and predictive analytics, manufacturers can anticipate market trends, align production schedules with demand, and deliver tailored products with minimal delay.
The Role of PLM in Overcoming Complexity
The panel discussion underscored that to tackle these levels of complexity, manufacturing companies must prioritize advanced data management strategies. Traditional systems, which often rely on outdated SQL databases and document-centric approaches, are insufficient for today’s interconnected and data-driven manufacturing environment. Here are the key characteristics that modern PLM systems must embody:
- Multi-Company Collaboration: With manufacturing ecosystems encompassing multiple players -suppliers, manufacturers, end users, and service providers – a PLM solution must facilitate seamless collaboration across this network. Current systems are more like a “database for a single company”. Modern PLM tools need to ensure that all stakeholders can securely access relevant data, promoting transparency and coordination.
- Flexible Data Management: Out of the box PLM solutions can struggle to accommodate the vast diversity within modern manufacturing environments. Companies need systems that can adapt to specific workflows, support various data structures, and evolve with changing product requirements.
- Modern Data Management Technologies: Today’s PLM systems need more than just SQL databases; they must leverage data analytics, knowledge graphs, and AI to handle complex datasets. By transitioning from static document storage to dynamic data structures, companies gain powerful insights into their processes, allowing them to manage product complexity with precision and foresight.
- Advanced Data Analytics and AI: As product and process complexities increase, the ability to analyze large datasets and make data-driven decisions becomes super critical. A PLM system that can harness data analytics, predictive modeling, machine learning and AI empowers companies to navigate uncertainties, optimize operations, and innovate continuously.
What is my conclusion?
Modern manufacturing companies demand from PLM vendors to build resilience with their platforms. Complexity in manufacturing is growing, but by embracing advanced PLM solutions, companies can turn challenges into opportunities. Whether navigating complex products, managing a fragmented supply chain, or meeting high customer demands, today’s manufacturers need systems that provide flexibility, data-driven insights, and seamless multi-company collaboration.
The paradigm shift from document management to data management is under way. 20 years ago, the backbone (PLM) of the product’s lifecycle including engineering and manufacturing was the product data management SQL database (document paradigm) with all document records responsible for check-in/out process and release workflow. But those days are over…
The future of engineering and manufacturing process (data driven) will increasingly rely on digital ecosystems where PLM platform is the backbone of the product lifecycle, to support complexity in data management, efficiency in operation, innovation in product development, and resilience overall. The resilience requires data management systems with multi-tenant data model, supporting complexity of data management using analytics, artificial intelligence, knowledge graphs, and many other advanced data management features. By investing in advanced and modern PLM platforms that support comprehensive data management, companies can ensure they’re equipped to overcome complexity, remain agile, and thrive in an ever-evolving industry.
Just my thoughts…
Best, Oleg
Disclaimer: I’m the co-founder and CEO of OpenBOM, a digital-thread platform providing cloud-native 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.
