This is the last blog this year and I’d like to finish it by discussing what the PLM selection process will look like in 2021. It is the 3rd and final article in my end of the year series of articles I used to explain the evolution of PLM system architecture, PLM data architecture evaluation, and now speak about what can help manufacturing companies to select the right path for their PLM decisions in 2021.
In my view, every engineering team or manufacturing company will be going through the two processes in parallel – (1) PLM Maturity Process; (2) Cloud/SaaS Maturity Process. These two processes are independent and connected at the same time. Let me talk about both.
1- Cloud / SaaS Maturity
Cloud / SaaS is the fundamental and the most transformative technological change that is happening in the industry. It changes the way we think about software architecture, the way we develop and consume software. It brings changes in the way systems are built and impact all aspects from core IT to applications and systems. It allows us to rethink the way we manage data and consume information. It brings new functions and opens new horizons in the way decision processes can be supported. This is not something you can ignore. SaaS/Cloud will change everything. For manufacturing companies it is not a question of “why”, but it is the question of “when” and “how”. What happened over the last few decades can be described in 4 phases – (1) Files/Networks; (2) Databases; (3) Hosted Systems; (4) SaaS Applications and Global data. Decades of CAD, PDM, and PLM development are going to be transformed and it won’t happen overnight. But if you’re responsible for IT strategy, you certainly don’t want to miss that.
2- PLM Maturity
PLM system architecture, data management, and tools have their own evolutionary path. New technologies in 3D modeling, CAD systems, later in data and process management allowed companies to manage information about the products, support changes, and decisions making. Documents were a core conceptual model from the early beginning. The data was managed in documents and later documents were managed using database records. More advanced data management architecture allowed more flexible data management and an additional type of information to be managed. These models evolved and started to cover even more information, which brings a question about new modeling and data engineering techniques. A data-driven approach, System engineering, Network architecture are clearly opening the way for PLM systems to support even more complex processes, products, and company organizations. It comes together with the maturity of manufacturing organizations, their understanding of processes, expansion in lifecycle, data, and communication models.
The picture below shows you my one slide perspective on how an engineering team or manufacturing company should approach the PLM selection process.
Once you understand where you are in these two maturity processes – “SaaS/Cloud” and “PLM”, think about what you have now and plan the next steps.
1- No-Risk Mature Legacy
The ground floor for everyone is existing mature desktop CAD systems, maybe local PDM, and tons of Excels. You might be choosing on-premise PLM if your company or industry is super-conservative and PLM strategy development is at its very beginning. This strategy will come with low risk and plenty of software and application to choose from from existing vendors. Your money will be well spent, but you might feel like a person who is buying a flip phone at the time everyone else is using smartphones.
2- Advanced PLM Development, No Cloud
For companies using PLM for a long time, who spent tons of resources and time to plan PLM strategy, but at the same time not very much advancing in the adoption of the cloud system, the goal should be to focus on the data and advanced PLM modeling, move away from documents and focus on a data-driven approach. Enterprise PLM systems, Federated data, System engineering, advanced integrations – this is a shortlist of what you should do. Mature PLM platforms can help you and they have a lot to offer.
3- Connected Systems and Teams
If your strategy is how to connect teams and companies, to organize data, and to create a foundation for data management, using cloud-hosted or SaaS PLM is the right way to go. These systems can be lacking some advanced PLM features, but these systems will create a healthy foundation and ROI for your money. SaaS systems development is fast. These are not your “grandfather 2 years for each release” PLM systems. SaaS tools can provide 10-12 releases in a year and bring advanced features when you’re ready for them without disrupting anything you already achieved.
4- Connected Value Chain and Data
For companies that want to explore the cutting edge of both PLM and Cloud/SaaS trends, the strategy should be to select systems and think about connecting data and processes alongside planning a global value chain – engineering, manufacturing, suppliers, and customers. In my view, this is where the future will go. Such systems can provide enormous value in the future. This is not something you can buy today out of the box. But you can identify vendors, technologies, and people that can build it. This is a place where everyone will be coming in the next 5-10 years.
What is my conclusion?
You probably noticed that I didn’t mention the names of the vendors and products in my article. My goal was to give you a foundation for a thought process to support your strategy and decision process. PLM is a journey – technological, product, and process-oriented. Only by understanding all elements of this journey, you will be able to make the right choice. The coming years will be amazing from both standpoints – understanding the value of new technologies and maturity of PLM business and strategy development. Just my thoughts…
PS. Stay tuned for new blogs in 2021. Happy New Year!
Disclaimer: I’m co-founder and CEO of OpenBOM developing a digital network-based platform that manages product data and connects manufacturers and their supply chain networks. My opinion can be unintentionally biased.