PLM, BigData and Importance of Information Lifecycle

PLM, BigData and Importance of Information Lifecycle

BigData is trending these days. It goes everywhere. Marketing people are in love with this name. It brings such a good taste of “big something”. It might be $$ or amount of problems it supposed to solve. It can be potentially related to big value proposition. Net-net, the amount of people and articles around you referring to the opportunity related to big data is probably skyrocketing. If you want to read more about big data, navigate to the following Wikipedia article – it is a good starting point.

CIMdata, well-known PLM advisory outfit, recently published an interesting paper about PLM and BigData. Navigate to this link, download research paper (it requires registration) and have a read. I’d say, this is the best reference about intersection of PLM and Big Data worlds. Here is what is the document about:

This paper focuses on the intersection of PLM and what has come to be known as “Big Data.” The increasing volume and growth rate of data applicable to PLM is requiring companies to seek new methods to turn that data into actionable intelligence that can enhance business performance. The paper describes methods, including search-based techniques, that show promise to help address this problem.

Search and analytic is one of the ways to dig into big data problem. Last year, I wrote about why PLM vendors need to dig into Big Data. Here is the link to my post – Will PLM vendors dig into Big Data?. I believe, BigData can provide a huge value to organization. To unlock this value is extremely important. However, looking on BigData hype these days, I got a feeling of wrong priorities and some gaps between vision of BigData and reality of PLM implementations.

I’ve been reading an ITBusinessEdge article – Three Reasons Why Life Cycle Management Matters More with Big Data. The main thing I learned in this article – even big data is going to change a lot, it won’t change some fundamental data management laws. Data lifecycle is one of them. Here is my favorite passage:

With Big Data, which can be unpredictable and come in many different sizes and formats, the process isn’t so easy,” writes Mary Shacklett, president of technology research and market development firm Transworld Data. “Yet if we don’t start thinking about how we are going to manage this incoming mass of unstructured and semi-structured data in our data centers.

It means a lot in the context of PLM systems. This is where I can see the biggest gap between BigData and PLM. It is easy to collect data from multiple sources. That’s what everybody speaks about. However, big data needs to be managed as well together with other information managed by PLM. Big Data is coming through the lifecycle of processing, classification, indexing and annotation. To connect pieces and to related big data pieces of information to PLM system – significant problem to think about. Engineers and other people in the company probably won’t be interested to access data itself, but analytics, insight and recommendation.

What is my conclusion? The value behind big data is huge. It can improve decision making, quality of service, suppliers bids and lot of other things. However, it creates a huge pressure on IT and organization in terms of resources, data organization and data infrastructure. PLM systems won’t be able to start with big data overnight. Whoever, will tell you “now we support big data” is probably too marketing oriented. PLM will have to focus on data lifecycle to bring a realistic big data implementation plans to organization. Just my thoughts…

Best, Oleg


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