A PLM system serves as a central hub that connects teams and organizes product data throughout a product’s lifecycle. It begins with the initial concept and design phase, where teams collaborate on requirements and create digital models. As the product moves into development and manufacturing, the PLM system ensures that engineering changes and compliance requirements remain aligned. For software products, the PLM process connects development, testing, release management, and ongoing updates. Version control, user feedback, and compliance with security or privacy standards are tracked throughout the lifecycle. 

Modern PLM solutions leverage cloud computing, automation, and data integration to enhance visibility. Digital threads connect real-time information across engineering and supply chain operations, allowing companies to respond to market demands more effectively. Built-in workflow automation enforces structured approval processes, while integrations with enterprise systems such as ERP and MES ensure seamless data flow across the organization. Through these capabilities, PLM enables businesses to optimize product development and drive continuous innovation. 

Organizations tend to tailor their approaches to product lifecycle management to their own specific needs. Even so, most follow a fairly structured process. Regardless of what they are producing, PLM must coordinate design, production, distribution, and any other relevant departments while maintaining compliance and controlling costs.

While the following lifecycle stages are typical for hardware products, similar principles apply to software development. In software, concepts like BOMs or production may translate to package dependencies or release pipelines. 

Stage 1. Design

The design phase begins with defining a product’s purpose and technical requirements. Engineers and designers create initial concepts, often using CAD software to develop digital models. Prototypes and simulations help test functionality and identify necessary refinements. This phase is highly iterative, with adjustments based on testing and regulatory feedback. PLM enables concurrent engineering, allowing different teams to work together and refine designs in parallel.

Stage 2. Bill of materials management

Once the product design is finalized, teams create a bill of materials. This serves as the complete list of components, subassemblies, and raw materials required for production. Each part must be documented with sourcing information, cost details, and compliance data to ensure smooth procurement and manufacturing. BOM management within PLM allows teams to track revisions and maintain version control as designs evolve.  

Stage 3. Engineer-to-order

For highly customized products, the engineer-to-order (ETO) stage allows companies to modify designs based on customer specifications. Unlike standard production, ETO requires close collaboration between sales and engineering teams to refine requirements and validate feasibility. PLM ensures that design iterations remain well-documented and accessible throughout the process. 

Stage 4. Production

Once designs and materials are finalized, manufacturing begins. This stage requires careful coordination of schedules and quality control measures. Manufacturing execution systems (MES) may integrate with PLM to ensure production follows the latest specifications. Any design changes must be communicated quickly to prevent disruptions. 

Stage 5. Distribution and service

After production, companies focus on delivering products to customers and supporting them post-sale. The distribution process includes inventory oversight and logistics planning. Service teams track maintenance requirements and customer feedback to address issues as they arise. 

Stage 6. Retirement

As market demands shift and newer products replace older ones, companies must manage the transition of products out of circulation. The retirement phase involves final inventory management and discontinuation planning, as well as environmental considerations for disposal or recycling. Companies may choose to repurpose components from these retired designs and should analyze any available data to help develop new offerings based on past product performance.  

A PLM solution must support a wide range of functions to ensure that products are manufactured and maintained efficiently. To do this, the best PLM systems include several essential capabilities. These include:

Collaborative product development 

Developing a product requires input from multiple teams, often working across various locations and disciplines. PLM provides a shared workspace where engineers, designers, suppliers, and other stakeholders can contribute, reviewing and refining product data in real time. Collaboration tools help manage workflows, control document access, and synchronize updates to prevent conflicting changes. 

Engineering change management 

Whether due to design improvements, regulatory updates, supply chain constraints or other factors, every product goes through at least some revisions. Without a structured approach to managing these changes, errors can disrupt production. PLM systems enforce governance by maintaining detailed records of modifications and dependencies. Change requests follow a defined process, ensuring that updates are reviewed by the appropriate teams before implementation.  

IP security

Protecting intellectual property is essential, particularly for companies that collaborate with external partners or operate in highly competitive markets. PLM systems include cyber-security measures designed to safeguard sensitive product data. These protections ensure that proprietary designs and manufacturing details are shared only with authorized personnel.

Product configuration management 

Many products are offered in multiple configurations, requiring companies to track variations in design, materials, and assembly processes. PLM provides a structured framework for managing these differences, ensuring that each configuration is documented correctly and tied to the appropriate manufacturing and service requirements.

Product data management 

A PLM system acts as the backbone of an organization’s product data, ensuring that all relevant information is stored in a centralized, secure environment. By maintaining strict access controls and data integrity, PLM prevents unauthorized modifications or conflicting updates. This structure also eliminates version control issues by integrating with CAD and other engineering tools, ensuring that teams always work with the latest information. 

Product variability management 

For companies that manufacture different versions of a product, PLM helps organize and control product variability. Instead of duplicating work for each variation, teams can define configurable elements within a single framework.

Quality management 

Maintaining high product quality requires more than just a detailed final inspection—quality assurance must be embedded throughout the entire lifecycle. PLM integrates quality management processes by capturing data from design, manufacturing, and field performance, giving teams everything they need to identify and address issues early. By linking quality metrics with engineering and production data, companies can implement corrective actions before issues escalate into costly problems. 

Service process management 

Once a product reaches customers, companies must support it with accurate service information and maintenance resources. PLM systems store service manuals, repair instructions, and historical performance data in a single repository, making it easy for field technicians and customer support teams to access what they need, when they need it. In software, this could include patching, updates, customer issue tracking, and ongoing DevOps support. 

Supply chain collaboration 

Modern supply chains involve multiple stakeholders—suppliers, contract manufacturers, logistics providers, etc., all of whom need access to accurate product information. PLM facilitates supplier collaboration by providing controlled access to design specifications, material requirements, and production schedules. This ensures that external partners are fully on board with internal teams, reducing delays and improving overall supply chain efficiency. 

PLM directly impacts how efficiently teams work, how quickly products reach the market, and how well companies adapt to change. By standardizing processes and improving visibility, PLM helps organizations navigate these challenges while maintaining total control over every stage of the product journey. This delivers several important business advantages: 

• Reduced siloing  

PLM breaks down barriers between departments by providing a single source of truth for product data. With all teams working from the same platform, information flows more freely, reducing inefficiencies caused by isolated workflows. 

• Optimal collaboration  

By promoting real-time data sharing and structured workflows, PLM ensures that everyone involved on every level (internal and otherwise) can operate together without friction. This level of coordination improves decision-making and accelerates product development. 

• Fewer errors  

Errors in product design and manufacturing can be costly and time-consuming to fix. PLM enforces version control, approval processes, and traceability, helping teams catch and correct mistakes early on. 

• Enhanced efficiency  

Centralized data management allows organizations to streamline processes and reduce manual workloads. By minimizing time spent searching for information or resolving inconsistencies, teams can focus more of their time and energy on strategically relevant tasks.

• Faster time to market  

PLM helps teams manage overlapping development timelines, keeping projects moving forward without delays. Real-time visibility allows companies to anticipate and resolve bottlenecks before they start to negatively impact deadlines. 

• Improved project delivery  

With better control over workflows and product data, organizations can more effectively manage design handovers, production planning, and cost estimation. PLM reduces the risk of last-minute surprises, so projects remain on track. 

• Higher quality  

Capturing and analyzing performance data at every stage of the product lifecycle helps teams to make informed improvements. PLM integrates quality management into development, supporting organizations as they build reliable, well-designed products.

While PLM offers some major advantages, its effectiveness depends on how well it is implemented and integrated into an organization’s workflows. Addressing the following challenges requires strategic investments in technology and process improvements: 

• Less visibility of product lifecycle  

Many organizations lack full visibility into the entire design-to-delivery process, making it difficult to track product performance and respond to market demands. This challenge is especially significant for teams working in iterative development models, such as Agile, where products evolve rapidly across multiple cycles. Without centralized tracking, frequent updates and shifting priorities can create blind spots and disconnect stakeholders from real-time product status. Adopting Industry 4.0 technologies—such as IoT sensors and predictive analytics—enhances real-time monitoring and ensures that decision-makers have access to accurate, actionable insights. 

• Limited usability for non-engineers  

In many companies, PLM is seen as an engineering tool instead of a platform created to be used by an entire organization. Departments like sales, marketing, and supply chain management may struggle to extract value from the system due to complex interfaces or limited data accessibility. Integrating built-in AI can help bridge this gap by automating data analysis, providing user-friendly direction, and making relevant product information more accessible across teams.

Product lifecycle management and product data management are often discussed together, but they serve different purposes within an organization. While both systems manage product-related information, their scope and impact vary significantly: 

• PLM provides a comprehensive framework that manages a product’s entire lifecycle, from initial concept to retirement. It integrates people, processes, and enterprise systems to ensure seamless collaboration across design, manufacturing, supply chain, and service operations. By offering end-to-end visibility, PLM supports better decision-making and enables organizations to optimize every stage of a product’s journey. 
• PDM is focused specifically on managing and organizing design and engineering data. It centralizes CAD files, documentation, and BOMs to ensure that teams work with accurate and up-to-date information. While PDM plays a critical role in product development, it primarily serves engineers and designers rather than the broader enterprise. 

To put it simply, PLM is a company-wide strategy for managing the full product lifecycle, while PDM is a specialized tool for handling design and engineering data within that broader framework.

Successfully implementing PLM requires more than just selecting the right software—it involves aligning the system with business processes, ensuring adoption across teams, and continuously optimizing performance. A well-planned approach helps companies avoid common pitfalls, such as poor user adoption or data inconsistencies, while maximizing the value of the PLM system. The following best practices provide a structured approach to deploying PLM effectively. 

Assemble the team

A successful PLM implementation starts with assembling the right team. This group should include representatives from key departments such as engineering, manufacturing, IT, supply chain, and leadership. Each member should have a clear role in defining requirements, overseeing implementation, and ensuring adoption. Engaging cross-functional stakeholders early in the process helps keep expectations consistent and secures buy-in early from those who will be using the system. 

Map the production data and business processes 

Before integrating a PLM system, organizations must evaluate their existing workflows and data management practices. This means mapping out how product-related data moves through the company, from design to manufacturing to after-sales support. Identifying inefficiencies and bottlenecks at this stage ensures that the PLM system is configured to improve operations (rather than reinforce outdated processes). Likewise, teams should assess data quality to prevent inconsistencies and migration issues in the new system. 

Settle on the ideal PLM solution 

Selecting the right PLM solution requires careful evaluation—companies should research vendors, compare features, and assess how well each system fits their specific goals. How accessible is the PLM system going to be for non-technical users? Will it be able to integrate data with existing enterprise systems? How much customization will be needed for it to meet the company’s unique needs? Organizations should also consider long-term factors, such as vendor support, data-privacy, and ongoing support, to ensure the solution remains viable even as the business evolves. 

Shape the selected PLM 

Once a PLM system is chosen, it must be tailored to fit the company’s requirements. Some organizations may need additional customization to match the system to specialized processes or industry regulations. Collaborating with the PLM vendor during this phase ensures that the platform will be optimized for current needs—and that it can be further adjusted to address changing needs in the future. 

Train the stakeholders 

Even the most advanced PLM system will fail if users do not know how to use it effectively. Training should be tailored to distinct roles, ensuring that engineers, project managers, and executives understand the features that are relevant to their responsibilities. Beyond initial training sessions, companies should provide ongoing support and refresher courses to reinforce adoption. Encouraging feedback and addressing user concerns early can help increase long-term engagement with the system. 

Developing, delivering, and maintaining products is a more complex process than it has ever been, but the correct approach to PLM keeps teams aligned and operations running efficiently. ServiceNow and the Now Platform^® provide a unified system of action, giving organizations total visibility across the product lifecycle. Break down silos, connect teams, and ensure that every decision is backed by real-time insights.

Use Predictive Intelligence to anticipate risks, Process Mining to streamline workflows, and Performance Analytics to track progress and optimize strategies. ServiceNow equips organizations with AI-powered tools that drive efficiency and help teams move from planning to execution without disruption. 

For increased support, consider Strategic Portfolio Management (SPM). Prioritize resources effectively with Demand Management and track project performance with Project Portfolio Management. Empower teams with Collaborative Work Management, so product managers, engineers, and stakeholders can plan, visualize, and execute seamlessly. Drive faster innovation and smarter decision-making with AI automation, eliminating bottlenecks that slow progress. ServiceNow makes it all possible, delivering a fully connected PLM solution to help your business and your customers get the most out of your product lifecycle. 

Request a demo today!