The idea of product lifecycle management (PLM) is alluring—faster time to market, enhanced product quality, increased collaboration, accelerated deliveries, and more. However, a full understanding of this offering will help reduce risk.
A PLM is the software solution that manages your product throughout every phase of ideation, development, implementation, and retirement. PLM is used extensively by engineers creating your products, and the information that is contained within can be used to inform the data within your other key systems.
Captivating, right? Unfortunately, it’s not always that simple—especially with the roadblocks your company could run into that would instantly devalue your PLM investment.
Continue reading to discover five of the most common mistakes we see when it comes to PLM implementation.
1. Selecting the Wrong PLM Solution
Many technical data companies have the same goal in mind—to find the ideal PLM solution and provider that is unique to their business requirements. However, a lack of experience and little-to-no insight into market complexities can make the journey to find the perfect PLM a complete doozy.
We’ve seen companies pay the hefty price of either inefficiently implementing their PLM solution or selecting the wrong solution to begin with. Which—you guessed it—means they’ve had to replace their PLM a few years later.
Not to mention when your team members refuse to use your new PLM solution, you’re going to lose support and decrease ROI—something no company wants.
Let’s fix it!
Right off the bat, it’s important to realize that while your team can conduct its own market research, a scientific approach (e.g. requesting demos or talking with technical data experts) will truly help weed out providers not fit for your company. From there, you’ll already be starting off on a better foot—and minimizing the risk of choosing the wrong PLM solution.
2. New and Existing System Mix-Ups
Your product data is spread across different platforms. This causes a lack of clarity about how to properly manage that data—especially after a recent PLM implementation.
Not only that, some systems you already have in place offer extremely similar functionality as your new PLM solution. And when your teams aren’t communicating on how to manage these systems alongside one another, it won’t be long before everyone is turning against PLM.
Let’s fix it!
At the end of the day, it’s all about outlining system responsibilities:
- Who does what?
- Where do you need to manage product data?
- Is more than one system needed to release parts to production?
- Where do you do what?
When bringing a new solution on board, you’ll often need to compromise with your existing team and systems. Implementing a data governance strategy that defines the system roles and PLM functions will slowly build relationships between your PLM, its users, and counterparts.
3. Poor Integration of PLM Solution
Not properly integrating your solution with other key systems (e.g. ERP, CRM, SCM, etc.) is one of the biggest and most costly mistakes companies can make when it comes to a PLM. For example, if there’s a hiccup in the development of a product and it doesn’t reach the marketing team on time, you’re going to be launching a faulty product too soon, which ultimately is a waste of your team’s time and resources.
Properly storing data and migrating it among teams is key—which is why a PLM is so beneficial. This solution gives you the ability to store data in a centralized location, making it easy to access for all involved.
Let’s fix it!
To ensure a successful PLM integration, make sure your new solution is seamlessly receiving information from other systems within your organization. Keep in mind, as technology continues to evolve, you may have to do some extra work behind the scenes to integrate systems from different generations.
4. Getting Stuck In the Past
It’s human nature for people to resist change—and a new PLM is no exception. While management may be inducing the change, end users also have a great influence on implementation.
Those working in management shouldn’t expect their employees to make change at the flip of a coin. But end-users also can’t expect to “stick to the status quo” forever.
Let’s fix it!
It’s crucial all projects work collaboratively and all groups are brought into the mix early on. To ensure a seamless transition and maximize your PLM’s potential, integrate your new system into every applicable department of your organization. This will avoid the risk of your investment becoming an underutilized product.
5. Moving Too Fast
Moving too fast with PLM implementation can cause more problems for you in the long run. Although getting your new system set up quickly seems ideal to keep everything moving in your organization, the quick ROI you’re looking for is going to be nonexistent if you keep moving at such a fast pace.
It’s going to take time to get your PLM solution working at the same pace and in correspondence with your existing systems.
Let’s fix it!
New PLMs take time to develop. Your team needs to become familiar with the new system and the system needs to become familiar with your team’s processes. Establishing a long-term roadmap is key before you can expect to see any ROI.
6. Migrating Dirty Data
Importing dirty data and duplicate parts is the fastest way to devalue your PLM investment. If you’re just starting out or in the process of migrating your data into a new system, make sure you are only importing clean data into the system. After all, cleaner data does drive better results.
Let’s fix it!
Convergence Data helps its customers collect, humanize and validate their data by eliminating clutter to optimize their engineering and marketing outreach. We recommend consolidating your disorganized or siloed data to store it in a classification database. From there, you will easily be able to validate and publish your cleansed data.
Ready for an Improved PLM?
If you’re looking to capitalize on the capabilities a new PLM has to offer, you’ve come to the right place. Convergence Data can help by classifying your parts, normalizing your data, and standardizing the clean data—in a way that makes sense for your business. Contact us today to get started.
