One size doesn’t fit all. It is very true when it comes to anything related to manufacturing and engineering. Every manufacturing company believes that they are unique and all attempts of PLM vendors to convince them in opposite failed. Out of the box products, business practices, template, etc… you name it. Companies are always looking how to adjust, configure, tailor and change what product can do.
My hunch, most of people in PLM industry and manufacturing companies will agree with me. However, the define the problem is hard. My attention was caught by Engineering.com article – PLM THIS WEEK: New Solutions from Siemens and Mentor, Big PLM Contracts for Aras and Dassault. My favorite passage is about Unclear data structures.
Unclear Data Structure. The Aeronamics Production Manager adds that one of the company’s problems was its unclear data structure. “Over time, it became more difficult for me and my colleagues to maintain a good overview of documentation, staff and other data sets. For instance, we had an Excel file with a list of people that are qualified to do a certain job. We managed our EBOM in an Access database, and our MRO records in another Access database. I can name a lot of similar examples, but the idea is that these systems were not connected but were containing identical information.”
It made me think about trajectory of data management and PLM. Most of PLM systems came to manufacturing systems as an extension of CAD data management. To manage CATIA, NX or Pro-E was the first goal. With the expansion of PLM vision and boundary, the demand of PLM companies to govern a wider scope of data failed on unprepared and limited platforms capable only to manage CAD data. It became unfortunate for PLM vendors that variety of data in a company such as zillions of Excel files, Access databases and other enterprise data management were not covered by PLM platform capabilities. It created a huge demand for flexibility and expandability of PLM platforms.
PLM vendors are facing huge challenge of digital transformation coming from outside of PLM domain. One of the major analyst and consulting company in PLM domain. CIMdata defined digital transformation as PLM outside view. This outside view is going to dictate some rules of digital transformation to PLM vendors and it will come in a form of data management challenge – to transform large amount of enterprise data into structured, connected and manageable data sets.
What is my conclusion? Manufacturing companies are facing data management challenges these days. These challenges are coming on the edge of digital transformation trend and it is coming from outside of PLM domain. PLM vendors seem not to have much control and will have to react by adapting and expanding their platforms with flexible data management tools capable to get zillion of Excels and legacy databases under control. Who is up to these challenge in PLM world? This is a good question to ask analysts, manufacturing companies, vendors and all PLM pundits. Just my thoughts…
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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. My opinion can be unintentionally biased.
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