It is this time of the year again, and I want to share my thoughts about what dynamics and trends I can see in product lifecycle management (PLM) eco-system. For me it includes three different segments – industrial companies (both enterprise and SMEs), CAD/PLM vendors I’m following, and technological perspectives.
Meaning of “PLM” Name
PLM has many definitions and names. This more than 10 years old Reddit article (What is PLM) is still relevant, in my view. I gave my summary of “12 P’s of PLM” last year, so you can check. Education is a big thing in product data management, product lifecycle management, engineering related business processes and systems to support a product development process and document management.
In my writing in 2025, I plan to separate two terms – PLM software and PLM business strategy and plan to be very specific when I talk about one or another.
PLM Business Strategy Trends
Digital Thread and Digital Twin
Digital transformation will continue to lead innovation in engineering and manufacturing companies. The “links” between companies, products, and data used is leading the way to create a competitive edge for manufacturing companies. Therefore, companies are focusing on creating an unbroken digital thread, connecting all product data from concept to end-of-life. This enables better traceability, quality control, and decision-making. Simultaneously, digital twin adoption is growing, allowing organizations to simulate product performance, predict maintenance needs, and optimize designs.
Sustainability and Circular Economy
Sustainability cannot be ignored and, therefore I expect more interest to environmental considerations in PLM strategies. Companies are incorporating sustainability metrics into product design and lifecycle assessment, aligning with Industry 5.0 and Engineering 5.0 principles. It is impossible without digital thread and data connectivity and, therefore will continue to support business strategies.
Technological Advancements
I believe in technology as a key factor in PLM software innovation in 2025. As it was many times before, technology is pushing the edge of what is possible and should not be ignored.
Cloud and SaaS Adoption
There’s a broad shift towards cloud-based PLM solutions, offering scalability, accessibility, and reduced IT overhead. While cloud and SaaS is almost 25 years old (if you count from Salesforce.com foundation), the adoption of SaaS solutions will continue to grow in 2025 heavily supported by new generation of people coming to the industry. This transition is particularly beneficial for SMBs/SMEs (SaaS is a no brainer solution), but I expect enterprises to start follow and ask vendors for enterprise -grade solution with unique characteristics to fit their requirements for security, data protection, and data sharing.
AI and ML Integration
AI is being incorporated into PLM systems for predictive maintenance, design optimization, quality control automation, and supply chain optimization. Large PLM vendors are rebuilding their solutions to fully leverage AI and machine learning capabilities.
The Baukunst’s second Study Group – “Contours of CAD and AI” published in September 2024 is a good place I recommend you to check to learn about how emerging AI and machine learning technologies could revolutionize computer-aided design (CAD) across industrial design, engineering, and construction. The discussions focused on opportunities for startups to develop innovative tools and establish sustainable businesses in this evolving landscape.
IoT Connectivity
Every single piece of hardware has a way to be connected to the internet. Enhanced sensor integration and IoT capabilities are enabling real-time monitoring and data collection throughout the product lifecycle. This connectivity is crucial for building robust value chains and optimizing performance. We should see this trend broader in 2025.
Data Management and Collaboration
Data is a foundation of everything. Therefore I can see data and related development to continue its domination in PLM software and PLM strategy discussion. The main topic, in my view, is a disconnect between applications (software) and data. The later will live its own life.
Modern Data Management
Companies are prioritizing data management, preparing for AI integration, and adopting technologies like graph databases. This data-centric approach is driving more informed decision-making and enabling the way for future AI-powered PLM solutions. Data management technologies such as graph model, knowledge graphs and graph databases will bring more innovation in 2025.
Collaborative Workflows
Collaboration has two aspects – data, teams, and communication. Both are going through the process of re-imagining. On the edge of COVID, companies will be looking how to improve remote work and organize remote work and solve problems of people disconnect while working in different places
There’s a shift from document-based workflows to complex data driven collaborative workflows, incorporating various scenarios of data capture, change management and AI assistance in decision processes.
PLM vendors will put an additional focus on features that enable seamless connectivity and collaboration across different teams and organizations.
Challenges and Considerations
From the side of PLM strategies, adoption and challenges, I can see the following trends. Some of them are different in enterprise and smaller companies.
For Large Enterprises
The following aspects of PLM technology and PLM business will be more relevant and associated with larger enterprises.
- Legacy system integration, multi-SaaS, multi-cloud integrations
- Data standardization across multiple divisions
- Change management in large organizations, especially working with complex products.
- Global and local compliance with varying regulatory requirements
For SMBs/SMEs
The situation is different in small and medium size businesses. These companies are struggling with status quo, education and adoption. Here are some trends and constraints:
- Determining appropriate scope for PLM initiatives
- Vendor selection for scalable solutions
- Resource limitations balancing PLM investments
- Acquiring and retaining skilled PLM professionals
Common Challenges
At the same time, I can see some common challenges that are relevant for all organizations looking at PLM projects:
- Cybersecurity for protecting sensitive product data
- Supply chain integration with PLM systems
- Ensuring data quality and consistency
- User adoption and training for new PLM processes
What is my conclusion?
Transformation is a name of the game in both PLM strategy and PLM software/technology. I can see both PLM software and PLM business in 2025 are set for significant transformation, with a focus on:
- Greater automation of routine PLM tasks (AI agents and specific collaborative solutions can be an interesting opportunity in the industry)
- PLM won’t live in isolation. Engineering and enterprise collaboration will be in the focus. To make engineering data available for businesses and enterprise systems will be an important trend and opportunity. It will lead to enhanced integrations between PLM and other enterprise systems
- Broader adoption of PLM solutions for SMB and supply chain following the technological and business maturity of SaaS solutions and people shift to digital
- More sophisticated predictive capabilities using AI/ML. Companies will keep the focus on how to use AI tech in engineering and PLM scenarios -we will see more in this domain.
- More data availability will lead to improved sustainability tracking and optimization.
- I expect more work to be done to better support for circular economy initiatives based on the data.
As we go into 2025, I can see both industrial companies and PLM vendors looking at these evolving trends, focusing on strategic implementation, technological innovation, and addressing the unique challenges of their scale and 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
