Everything About Product Data Management

Product Data Management (PDM) is an integrated system streamlining data across a product's lifecycle, enhancing collaboration, ensuring accuracy, and facilitating informed decision-making across diverse industries. So if you are wondering how it works, this blog will help you with some insights. 

How Do Product Data Management Systems Work?

PDM or product data management systems work as a repository for secure data access and retrieval. Any user in an enterprise or a stakeholder who is authorised to a PDM system can access, use and update data present on it. However, an administrator is responsible for choosing who can use the data at a specific workflow stage. 

To simplify it further...

Imagine a company's 'digital vault' – that's what a Product Data Management (PDM) system resembles. Just like a vault secures valuable items, a PDM system safeguards crucial product information. Employees or authorised personnel have 'digital keys' to access, use, and update data stored within it. Yet, similar to a vault's manager, an administrator oversees and decides who gets access to specific data at different stages of work.

Why Product Data Management is Beneficial For Enterprises Going Through Digital Transformation?

Although a PDM system is generally considered for an engineering department, it also benefits businesses in various ways. Let’s take a look at a simple example of a product data management system in an online business.

PDM systems store various product-related data pertaining to a business. Such type of information can broadly include descriptions about the product, inventory status, supplier product information, and so on. 

For e-retailers, such a system allows syncing and automation of the item listing information. When customers buy the product from the item list, the synced data can be automated the moment the current listing goes below a certain threshold. As the product descriptions are already present in the PDM system, the new items will appear automatically. This removes manual work and potential risks of putting out incorrect information on a company’s website.

As information from suppliers is sourced, recorded and maintained by respective teams, coming up with new product descriptions with new listings on the brand website are done accurately. Accurate product data and timely listing help make the customer journey smooth. In short, it reduces the time-to-market factor. 

Components of Product Data Management Systems

The scope of a product data management system can be understood with some of the key components and how they are used. See below. 

Bill of Materials (BOM)

All raw materials and different parts required for product development constitute Bill of Materials. Instructions to assemble a product are also stored inside it. These data sources are automatically aligned and completely visible to users in a PDM system during all product cycle phases from as-designed to as-maintained. 

Engineering Change Order (ECO)

It is a document comprising specific product details and the list of engineering-related changes required for the product. It is required when there is a design defect or requirement for a product redesign from the manufacturing unit. 

ECOs are required by the design, supply chain, manufacturing and engineering team as well as the main stakeholders. 

Common Capabilities of Product Data Management Systems

Without a PDM system, workflow management is limited to handling static business processes. That is, if there is any modification in the product, the workflow needs to be determined again from the beginning. Check below to see the common dynamic tasks of PDM systems. 

• Product Classification – PDM systems can easily categorise separately collected products into groups or ranges.  
• Product Structuring – It is convenient to handle individual parts or product assemblies and different lists inside PDM systems. Once data is collected it is rearranged by comparing to a similar process. 
• Product Authorisation – Product changes cannot be done unless an authoriser provides it. This makes PDM systems secure. 
• Product Versions – PDM systems keep real-time information, even on minute product changes. Authorised users can check the version history of the product. Any design reiteration in the product can be controlled with CAD file management tools available in different PDM systems.  

Product Data Management in Diverse Industries

Let's find out the role of PDM across different industries. 

Industry	Sub-Industry	Example Companies
Manufacturing	Aerospace & Defense	Boeing, Lockheed Martin, Airbus
	Automotive	Ford, General Motors, Toyota
	Electronics	Samsung, LG, Apple
	Medical Devices	Medtronic, Johnson & Johnson, Stryker
Consumer Goods	Food & Beverage	Nestle, Unilever, PepsiCo
	Apparel & Footwear	Nike, Adidas, Puma
	Furniture & Home Furnishings	IKEA, Ashley Furniture, Ethan Allen
High Tech	Software	Microsoft, IBM, Oracle
	Semiconductors	Intel, Samsung, TSMC
	Telecommunications	Ericsson, Nokia, Huawei
Other Industries	Construction	Skanska, Bechtel, Turner Construction
	Marine	Fincantieri, Damen Shipyards, Meyer Werft
	Oil & Gas	ExxonMobil, Shell, Chevron

The Future of PDM: How AI, ML, and Cloud are Reshaping the Landscape

Let's delve into the cutting-edge advancements today. The integration of AI, machine learning (ML), and cloud-based solutions is fundamentally changing how companies manage product data, and the future holds immense potential.

AI and ML are transforming PDM in several key ways.

• Automated data entry and classification: AI can extract product information from documents, emails, and images, reducing manual effort and errors. ML algorithms can then automatically classify and categorize products, making data retrieval and analysis much faster.
• Predictive insights and recommendations: AI and ML, by analysing historical data, identify patterns, becoming helpful for predict future trends, such as demand forecasting, stock levels, and potential product issues. This enables proactive decision-making and optimizes resource allocation.
• Personalisation and customisation: AI-powered product configurators allow customers to personalize products based on their preferences and needs. This enhances customer experience and drives sales growth.
• Virtual prototyping and testing: They empower virtual product prototypes. That significantly reduces the need for physical prototypes and accelerating the development process. This saves time and costs while improving product quality.

Cloud-based PDM solutions offer several advantages:

• Scalability and accessibility: These platforms are easily scalable to accommodate growing data volumes and user bases. They also offer remote access, enabling teams to collaborate on product data from anywhere.
• Cost-effectiveness: Cloud PDM eliminates the need for expensive on-premise hardware and software, reducing upfront costs and ongoing maintenance expenses.
• Improved collaboration and communication: Cloud platforms facilitate real-time collaboration between different departments, such as engineering, design, and marketing, streamlining product development workflows.
• Continuous updates and innovation: Cloud providers continuously update their PDM platforms with new features and functionalities. The latest technologies can be accessed without the need for manual upgrades.

Learning Product Data Management

If you are planning to enhance your career with product data management, it is recommended to gain a deeper knowledge of product management. You can also pursue a relevant postgraduate course such as IIM Lucknow & Wiley – Executive Program in Data-Driven Product Management.