In the last few weeks, I published articles to share with you the retrospective of PLM architecture – system, data, and selection process with the current systems available in the market. As we move forward in 2021, I want to come with a series of articles to share what I can see as a trend moving forward related to PLM and data management.
Back in 2013, I shared my Future of PLM Data Management in the 21st century. The idea of using multiple databases is still novel for many PLM developers that grew up using SQL foundation, but it just means that it requires more education to understand what is the next step in PLM and data architectures.
Today, I want to talk about 3 major trends I can see in data management that will impact PLM development in the next several years.
1- Data Is A New Software
Data is a source of unlimited innovation in every field we touch these days. Whatever product you touch today, you realize the potential of data and how it can impact the future development of the systems and services. Every manufacturing company understands it, but they don’t have the tools to turn data into a source of business and intelligence. Artificial intelligence and machine learning supplements the traditional systems we are all familiar with the enterprise. The rise of data development will change the role of PLM systems, but only these systems will change their paradigm and turn from a source of data control to a source of data intelligence. It might sound strange, but data is the most underrated tool in enterprise software and PLM specifically.
2- Cloud-Native Data Lakes
For quite a long time, the PLM industry was talking about master data management and later about data lakes. Master data management, data warehousing, or lakehousing is an interesting topic because it brings a question of breaking data silos and connecting pieces of information. However, for a long time, it was a privilege of large companies with massive data infrastructure. Not anymore. Earlier systems like ERP or CRM hold the status of the organizational data records. Not anymore. The data lakes are now much better places where employees can access the data they can trust. Data analytics and data cloud data lakes will be fast becoming a source of data in virtual organizations. Delivering the data will become a critical part of enterprise systems including PLM.
3- Virtual Experts and Networks
Analytic workflows are growing and will be dominating the single source of truth. AI and machine learning turned software into a virtual source of knowledge that can be used for the expertise and decision support. With a lot of data available, the software will become an expert. What is the right contractor, what is the right price? AI can capture and sort the knowledge of the network of experts and engineers and everyone will be able to access the knowledge closing the gap between our desire to build intelligence from the data and actually doing so.
What is my conclusion?
Data is a source of intelligence in a new network of manufacturing companies. PLM was before the source of data management routines to store and retrieve data. Novel platforms to manage information and product intelligence will be replacing old fashion enterprise PLM and switching into a new sort of network platforms. Just my thoughts…
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.