To select PLM system can be a complicated project. But let’s imagine the moment you’ve made a choice and decided about PLM strategy, vendor and products. So, you might think, the tough part of the job is over. Here is the thing… You have one significant problem to overcome. Legacy data.
The problem is not specific for PLM. There are things you should not expect your computer system to do. Don’t expect computer and PLM system to clean the mess in your company. Even best data management and search technologies cannot do it. The mess must be organized before you can attempt to computerized it and bring PLM system to manage data and processes. If you don’t do it, you will wind up with “computerized mess”.
Razorleaf article The hidden cost of a free PLM migration brings excellent examples of problems you can face when migrating data between to PLM systems – wrong location of files, duplicated data, broken files, wrong indication of relationships. In the example from the article, four types of mistakes in legacy data cost $230,000 in service fees to handle during legacy data import.
The following passage is my favorite:
The fact of the matter is, the reason data loads are expensive and time consuming is not because there are no data load experts or that there are no good tools to help with data loads. The reason they are expensive and time consuming is the data is complex, sometimes inaccurate, varied and often even undiscovered. You see, if the data was 100% known, 100% consistent and 100% standard, we’d be happy to load it for free. It would probably take us an hour to setup and kick-off, and the good will that we would receive would make it worth our effort. But it never happens like this. Never.
It made me think about fundamental disconnect between PLM vendors and customers in the way technology is built and implemented. Customers are unaware about how messy is legacy data. On the other side, vendors are not paying much attention to develop tools and technologies to cope with legacy data problem. The problem is hard to solve, but I wanted to share some ides how to improve the situation.
Legacy data quality assessment tools
Imagine data assessment tool you can run to provide a quantified assessment of your existing data. To develop such tool is not easy, but doable. You will get a rank of data quality. As soon as you can get this number, you can apply it to the cost of PLM project. Better data quality can discount PLM project cost.
PLM data modeling
Most of PLM products demand data cleansing to be made before importing the data. Data storage is cheap these days. To import data and later on to clean and organize it can be an interesting alternative. It requires re-thinking of PLM system and architecture, which can be a challenge for existing systems.
What is my conclusion? Legacy data is tough and complex problem. It can easy torpedo your PLM implementation by bringing an additional cost to implementation. Planning it upfront is a good idea. To develop data quality assessment tool can be an interesting opportunity for service companies such as Razorleaf. In the future PLM architectures with flexible data organization capable to resolve data conflicts and other problems can win over older dinosaurs. Just my thoughts…
Want to learn more about PLM? Check out my new PLM Book website.
Disclaimer: I’m co-founder and CEO of openBoM developing cloud based bill of materials and inventory management tool for manufacturing companies, hardware startups and supply chain.