A Guide to Successful PLM Implementation
Blog Article | June 8, 2023
Product lifecycle management (PLM) platforms are seeing increased adoption across a wide range of organizations. According to Transparency Market Research, the global PLM market is expected to see a compound annual growth rate of 5 percent through 2030. The use of Internet of Things (IoT) devices in next-generation smart factories is helping to drive this growth.
PLM systems help organizations streamline the design and production process by taking full advantage of the data collected by smart devices. PLM can also maximize the benefits of digital twins, artificial intelligence, and other advanced technologies. However, PLM implementations are complex, and many projects fail.
This guide is designed to help you better understand the potential pitfalls and drive your implementation project to a successful conclusion.
Tackle the Most Difficult Product Lifecycle Management Projects With Teamcenter PLM
With Teamcenter you can enjoy higher returns on your product lifecycle management system.
What is PLM?
As the name implies, PLM is the management of a product at every stage, from concept to design, manufacturing, sales, services, and retirement. PLM also refers to a suite of software tools that facilitate this process by tracking data and making it easier to share that data throughout the value chain.
The PLM concept has its roots in paper-based configuration management systems introduced by the Defense Department in the 1950s. It was further refined in standards developed by the military for government contractors. Computerization began in the early 1960s with the first CAD products, followed in the late 1960s with CAM. Product data management (PDM) systems were introduced in the 1980s to centralize documentation.
A PLM system was first used by American Motors Corp. in the mid-1980s to streamline vehicle production. By using CAD tools instead of traditional drafting techniques, AMC was able to increase consistency and accuracy in the design process. Storing CAD drawings and their associated documentation in a central repository simplified engineering changes and the correction of design errors.
Today, PLM tools are tightly integrated applications that focus on the customer and supply chain rather than CAD file management. Many leading solutions are cloud-based and have the ability to connect people, factories, IoT devices and digital twins.
How Does PLM Work?
In 1965, German economist Theodore Levitt introduced his product lifecycle model in a Harvard Business Review article. Levitt’s lifecycle comprises five phases: development, introduction, growth, maturity, and decline. The product lifecycle model is designed to help marketers understand the distinct opportunities, costs, and risks of each stage so they can make strategic decisions.
In the PLM context, the product development lifecycle can also be broken down into five phases:
CONCEPT
Product developers begin to define product requirements based on market forces such as customer needs and competition.
DESIGN AND DEVELOPMENT
In this phase, a detailed design is created, and the product analyzed and validated. Prototyping and piloting are also done during this phase.
PRODUCTION
Data and feedback gathered during the design and development phase are used to fine-tune the product and begin full-scale production for launch into the marketplace.
SERVICE AND SUPPORT
Once the product becomes available, the organization must be prepared to offer customers service and support.
RETIREMENT
The company must manage the product’s withdrawal from the marketplace at the end of its lifecycle.
What Are the Benefits of PLM?
PLM systems link CAD data with other sources of information across the enterprise, giving designers and engineers access to the data they need to manage products throughout their lifecycle. PLM also serves as a “single source of truth” for the business and its suppliers and partners. Key benefits include:
GREATER EFFICIENCY
PLM breaks down information silos, enabling design and engineering teams to share data and collaborate more effectively.
HIGHER QUALITY
Integrating data from multiple sources enables designers and engineers to better understand product requirements and make more effective decisions.
IMPROVED PROJECT MANAGEMENT
Advanced workflow capabilities streamline the transition from design to engineering to manufacturing and facilitate change management.
REDUCED COST AND WASTE
By enabling engineers to resolve design and production issues early, PLM helps reduce costs and manufacturing waste.
FASTER TIME-TO-MARKET
Because PLM serves as a single source of truth, project managers have greater control over the design and production timeline.
GREATER SCALABILITY
PLM optimizes the production process and streamlines the supply chain, making it easier to ramp up volume to meet demand.
What Are the Steps of PLM Implementation?
PLM systems are complex, and integrating them with other applications and data sources can be difficult. To be successful, PLM implementation should include several key steps:
1
DEFINE BUSINESS GOALS
To maximize the value of PLM, you have to choose the right solution. Establishing clear business goals and the PLM features needed to achieve them will make the selection process easier. It may be necessary to review existing processes to gain an understanding of what steps can be streamlined and what data will need to be transferred to the new system.
2
CHOOSE THE PLM SOLUTION
Stakeholders should narrow the field to those options that meet the established objectives, then conduct an in-depth analysis of their strengths and weaknesses. It’s important to find a solution that can scale to meet growing needs and a vendor with a well-defined technology roadmap. The vendor should be financially stable and able to provide technical personnel to assist with configuration and implementation.
3
ASSEMBLE AN IMPLEMENTATION TEAM
The team should include key stakeholders involved in the product lifecycle and an IT manager authorized to coordinate with the software vendor. An experienced project manager should oversee deadlines and tasks.
4
DEVELOP AN IMPLEMENTATION AND ROLLOUT PLAN
Working from a formal implementation plan helps ensure that the process proceeds efficiently, and any roadblocks are addressed promptly. The plan should also define whether it’s a phased or full-scale rollout, how data will be transferred to the new system, and how users will be trained.
5
TAKE STEPS TO FACILITATE ADOPTION
Many people will stick with the old way of doing things even if the new way is better. Successful implementation ultimately depends on user adoption, which requires training early in the process and having a team on hand to answer questions and help facilitate the transition.
6
GET READY TO GO LIVE
Implementation team members should be tasked with testing the interface, features, use cases and collaboration scenarios to identify any problems or areas where more training may be needed. Once they provide positive feedback, it’s ready to launch.
7
MEASURE SUCCESS
Use the goals identified in the first step to establish key performance indicators (KPIs) for the solution. Immediately begin tracking and measuring the solution against the KPIs.
How Can You Future-Proof the PLM Implementation?
Many organizations struggle with legacy PLM platforms that no longer meet their business needs. Because they don’t want the cost and disruption of migration, they put up with limited functionality and an inability to integrate the PLM system with newer technologies.
In order to avoid that scenario when implementing a new PLM system, organizations should select a solution that has the flexibility to adapt to changing requirements. It should be stable yet adaptable and easy to maintain and upgrade. Other factors to consider include:
Open, standards-based platforms that interoperate seamlessly with other software.
Solutions that allow users to access data and full application functionality from any location or device.
The ability to add functionality, updates, or new integrations without having to upgrade the entire platform.
Solutions that can readily scale in terms of the number of users, devices, and locations.
How Do You Avoid PLM Implementation Challenges?
Any complex implementation is fraught with challenges, and PLM is no exception. The following are examples of common roadblocks and ways to avoid them.
CHOOSING THE WRONG PLATFORM
In their haste to begin the PLM implementation, organizations may shortchange the step of defining their business goals. Sufficient time should be allotted to identifying needs and evaluating solutions.
MISALIGNED OBJECTIVES
If various teams are unaware of the impact of PLM and don’t fully understand their role in PLM implementation, the project will not be successful. Stakeholders throughout the organization should have input into the implementation process.
FAILURE TO IDENTIFY DATA SOURCES
Existing data must be imported into the PLM platform, which in turn disseminates that data across other applications. Often, there is insufficient understanding of what data should be imported and whether that data needs to be cleaned up before import. Performing a thorough assessment before implementation begins can minimize delays and avoid the unnecessary transfer and cleanup of data.
DATA QUALITY AND FORMATTING PROBLEMS
In many organizations, various teams have different methods and formats for capturing data. Because data is shared across systems with PLM, all stakeholders need to understand the changes to their data formats and that any data quality problems will be replicated across the environment.
BREAKING OLD HABITS
Users who don’t understand the PLM system may be inclined to stick with old spreadsheet-based processes. Training should be conducted as soon as possible during the implementation process to ensure a smooth transition to the new system. Third-party sales, service and distribution partners should be trained as appropriate.
Conclusion
Upfront planning is the key to successful PLM implementation. Organizations should devote adequate time to understanding their needs and objectives, assessing their existing processes and datasets, and obtaining input from stakeholders across the product lifecycle. Training should be conducted to ensure adoption and minimize miscommunication and data problems. Once the solution is in place, organizations should measure performance against established KPIs to help ensure that the PLM platform delivers maximum value.