Meaningful Part Numbers vs Rich Attributes in PLM Systems: Striking the Balance in a Hybrid World

In today’s data-driven landscape, organizations face the challenge of managing vast amounts of information efficiently. When it comes to CAD, PDM, PLM, and ERP systems, one critical aspect is how to include all corresponding attributes and align the data management systems and strategy with Part Numbers. Traditionally, part numbers have been used solely to identify components (parts) with their appropriate configurations, sometimes also documents and used much beyond the scope of a single data management system. This is the reason for the discussion about efficient data management and the definition of Part Numbers for this purpose. You can catch up on some of my recent publications about part numbers, best practices, and challenges here and here.

History and Digital Transformation

Data organizations was quite simple before digital transformation and data management systems. In a pure “analog world”, Part Number is a core element of part classification and the center of gravity that connects all information about each part in a single string. As we move to a digital world and with the emergence of intelligent systems, flexible data management systems, and rich semantic attribute sets, the debate arises: Should organizations continue their reliance on meaningful part numbers or adopt a more data management-specific attribute-focused approach? You can jump fast to a conclusion and decide to abandon old meaningful part number best practices and transform into a purely digital world with semantic flexible data management systems, AR, and glasses that can “see” information. But, our legacy is much stronger than we think. Therefore, companies are often forced to keep old approaches and think about co-existing multiple ways to manage data.

So, there are two approaches in product lifecycle management regarding definitions of part numbers and how they can be used in the product development process, product data management, computer-aided design, and supply chain management. What is important is to realize what support from PLM software and other software you can get to maintain these approaches.

1. Use meaningful (sometimes called intelligent) part numbers
2. Use number or simple combinations of text+number to identify all parts together with a rich set of data attributes.

This article explores the key differences between these two approaches and the implications they have in a hybrid data world.

The Need for Hybrid Data Management:

In the era of digital transformation, it is important to acknowledge that the world is not entirely digital. Many organizations still operate in hybrid environments where physical and digital assets coexist. This reality brings a data management approach that can support both fully digital and hybrid contexts. While the digital world is predominantly ruled by databases, the concept of part numbers provides a familiar and efficient way to identify and reference items in both situations when you have access to a data management system and when the system is out of reach because of different reasons. The second use case provides huge support to all people looking at how to identify a part outside of the data management system and digital environment.

Meaningful Part Numbers and Their Utility

One significant advantage of meaningful part numbers is their usability beyond the confines of a specific data management system. These identifiers can be easily communicated and understood by various stakeholders, facilitating seamless interactions across organizational boundaries. They serve as a common language and allow for efficient collaboration with partners, suppliers, and customers. However, incorporating rich attribute sets alongside meaningful part numbers can enhance their usefulness. Specific functions within the data management system can generate and attach attributes during the export process, bridging the gap between the system’s internal structure and the external usability of part numbers.

Supporters of structured data management will define an appropriate set of attributes that can be used to describe all characteristics, codes, and parameters in the data management systems. So, a part in this case is described by a set of attributes and not a single meaningfully defined alpha numerical number. Even so, modern PLM software can give you a combination of both worlds and construct a meaningful part number from a set of attributes using data management tools. It can help companies to live in both “digital” and “analog” worlds.

Complexity and Business Logic Challenges

Creating meaningful part numbers often involves embedding additional complexity and business logic within the identifier itself. While this can provide valuable information and context about the item, it can also introduce many challenges. As the business evolves and new requirements arise, modifying the underlying logic within part numbers can become cumbersome. Furthermore, maintaining consistency and ensuring the uniqueness of part numbers can be intricate when complex rules govern their creation. Organizations must carefully balance the benefits of rich information encapsulated within the part number against the potential complexity it introduces.

Conclusion:

Finding the Balance: In the pursuit of efficient data management, organizations should strive to strike a balance between meaningful part numbers and rich attribute sets. By leveraging intelligent systems and database capabilities, it is possible to combine the benefits of both approaches. Intelligent algorithms can derive part numbers from a collection of relevant attributes, preserving the usability and external communication aspects. Simultaneously, rich attribute sets can enhance the part number by providing additional context, enabling comprehensive data analysis, and facilitating integration with various systems.

In a world that operates in a hybrid state, the decision regarding part numbers in data management systems is crucial. While meaningful part numbers offer external usability and ease of communication, they should be complemented with rich attribute sets to ensure comprehensive data management. Striking the right balance allows organizations to leverage the advantages of both approaches, ensuring efficient collaboration, seamless data integration, and effective decision-making across the hybrid data landscape.

OpenBOM gives you both of both worlds. A flexible data management system allows you the creation and maintenance of a set of attributes to define parts. At the same time, OpenBOM accepts any part number format, which can be used by apologetics in old fashion way.

REGISTER FOR FREE and check how OpenBOM can help you.

Best, Oleg