How Mainstream PLM and Old Habits Can Slow Down Your Digital Transformation Process

How Mainstream PLM and Old Habits Can Slow Down Your Digital Transformation Process

Manufacturing companies are under pressure to transform their operations to stay competitive. It includes changes in business models, turning data into a competitive advantage, and figuring out how to manage global product development. While most manufacturing companies clearly understand the challenges, many are struggling to do so due to the many limitations in their IT infrastructure and organization of business software. The limitations of PLM software are one of the biggest elements of enterprise software failure to provide manufacturing companies with the system foundation to manage product development in the 21st century.

Existing PLM software is experiencing many challenges and is unable to handle the scale and complexity of modern manufacturing businesses, which is preventing them from achieving digital transformation. In order to overcome these limitations, manufacturers need to find alternative ways to develop their IT and PLM strategies as well as to find better PLM technologies and products compared to mainstream PLM software, which is responsible for more than 90% of current PLM business today.

The conversation about digital transformation and what is missed is bigger than one blog article. In my blog today, I want to focus first on the biggest 3 limitations that slow down PLM transformation.

Legacy Platforms and Data Silos

Each company operates with a humongous amount of legacy data sources. Pick any department in a manufacturing company of any range and you will find many islands of data. Excels, legacy database, multiple systems working together and sending product information and all what is needed between accounts. Yet, doesn’t provide a strong data foundation.

Legacy data and solutions (including legacy PLM solutions) are a block to create a foundation for digital transformation and PLM software to expand. Almost all existing mainstream systems have a hard time acquiring legacy data or just managing this data.

A typical legacy data set contains main three elements:

  • Old PLM and ERP software platforms
  • Databases (usually Access, but not only) that are used to maintain the current processes.
  • Tons of legacy (and not only) spreadsheets

The challenge for mainstream PLM systems is to acquire the data and re-establish the processes. This leads to my next question – old paradigm and database thinking. Let’s talk about it for the moment.

Old Paradigms and Habits

Multiple generations of business systems and data management strategies established a set of paradigms that dominated the engineering, manufacturing, and PLM software world. The foundation of these paradigms is documents, folders, and document management software. Most design software used in production is still desktop and file-based. Files are a foundation of design storage, managed in folders and it is very hard to break from this paradigm.

What cannot be managed using files and folders, eventually ends up with Excels (or other forms of spreadsheets). Engineering people like it because of its simplicity, flexibility, and portability. However, most companies understand that spreadsheets create an immense level of struggle that inevitably come and must be managed in a better way than we do it now.

You can ask me – what about databases? Your right and this is the last paradigm that dominated in PLM world – it is a single database. Remember this picture I brought up a few years ago – 1/ Look like data – SQL database; 2/ use like files – Office.

Database decision process

Single Database Thinking

For years in product lifecycle management (PLM) software, the magic word was “single source of truth”, which was directly connected to the architecture of a single database system behind the scene. The magic performance of any mainstream PLM system is “to put all data into a database” and then we can figure out everything else. The architecture of a single database was going back to the time when enterprise PLM deployment was dependent on IT (hence database system must be approved by IT) and many customizations were done using direct database operations. The amount of SQL-based customization in PLM implementations using the old platform is huge and within time, these customizations made companies locked in the existing PLM systems without any chance to upgrade to new systems to improve their processes.

A digital transformation of the product development process and thinking about information flow in the entire product lifecycle is the first step to move from legacy “database thinking” and focus the business strategy on the information flow when implementing PLM. A single database thinking doesn’t stop here. I can see future attempts to bring “a better database” to solve all problems. I will talk about it in my next article.


Product lifecycle management is the foundation of the digital transformation strategy. It is a technology that consolidates multiple business systems using digital technology to turn company data into digital data, streamline business processes, organize the digital thread of product information, optimize supply chain management, organize manufacturing process and product data management across multiple stages of the product lifecycle. This is a super ambition goal and it requires new digital technologies and new digital transformation strategies to create new PLM solutions. A digital transformation in PLM software means first to find a way to leverage a massive amount of legacy data and legacy systems without disrupting processes and existing PLM investments. Re-using existing data and applying new paradigms to manage product lifecycle management will unlock the opportunities for new business processes using data as a foundation of the business (unlike existing PLM software focusing mostly on how to control data access and changes). Digital transformation strategy also means to bring new data management platforms using PLM software using polyglot persistence data strategy as a foundational element of new product lifecycle management technologies switching off the traditional single database-driven PLM software. Removing these limitations will bring a new type of product lifecycle management software with a focus on an entire digital thread of information. Just my thoughts…

PS. This article will be continued. Stay tuned.

Best, Oleg

Disclaimer: I’m co-founder and CEO of OpenBOM developing a digital cloud-native PLM platform that manages product data and connects manufacturers, construction companies, and their supply chain networksMy opinion can be unintentionally biased.


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