3 reasons why big data is a big challenge for PLM

3 reasons why big data is a big challenge for PLM

big-data-plm-challenge

Data was always a core part of what manufacturing does. Manufacturing companies have lots of data. According to Joanna Schloss of Dell Software, manufacturers are literally sitting on big data dynamite of potential revenues and opportunities driven by data initiatives. Joanna Schloss is  subject matter expert on business intelligence and analytics; data warehousing, & big data analytics. Her recent article – On the cusp of a Big Data boom caught my attention this morning. According to her, there are several reasons that manufacturers can become a primary beneficiary of big data boom. The following passage can give you an idea why manufacturing can leverage big data:

Relative to other vertical markets, manufacturers enjoy three primary advantages that leave them uniquely positioned to benefit from big data. First and foremost, every industry and individual is touched by manufacturing in some way. You’re either doing business directly with a manufacturer, or purchasing something that at some point or another emanated from one.

In addition, because manufacturers were among the first to make widespread data collection a standard practice, they can quickly and easily scale their data collection efforts. Put more simply, a manufacturing company can track virtually everything much faster than most other companies can.

Lastly, manufacturers typically don’t face the data collection barriers that many other companies encounter. Whether they know it or not, many consumers readily provide valuable data to manufacturers on a daily basis.

The opportunity driven by big data can include improving product quality, help to discover new design for existing products and find new product opportunities. I agree with author – big data sounds like a gold mine for manufacturing companies.

It made me think how to bring these opportunity into reality. Do you think PLM vendors and platforms are in the position to make a play around big data opportunities? Manufacturing companies are sitting on piles of data. Existing business intelligence software was able to get this data, but wasn’t able to crank it until new big data technologies became available.  I touched big data opportunity several times on my blog earlier – Will PLM vendors dig into big data? How PLM can ride big data trend in 2015; PLM… wait, Big data 2.0 is coming.

Big data solutions are quite unique in the way companies are implementing them. In my past publications, I was looking for examples of Big Data usage in product design, engineering and manufacturing. One of them was company True & Co that is using customer data to improve product design – PLM and big data driven design. Another example, I captured last month, is related to Siemens PLM big data projects based on Omneo platform. Read more about it here – Siemens PLM: cloud services and big data.

I’ve been thinking about the potential of CAD and PLM companies to leverage big data trend. My conclusion is that most of big data use cases are representing a big challenge for existing CAD/PLM vendors. Here is the summary of my thoughts. I can identify 3 main reasons for that.

1- Existing CAD / PLM systems are built on top of 15-20 years old RDBMS technologies. These platforms are providing limited capabilities to capture the amount and diversity of new data insight. Modern web and big data platforms are leveraging polyglot persistence principle that allows to use different database models to solve complex problems.

2- PLM platforms are built around the concept of closed world assumption (opposite to open world assumption)  where all data models are predefined by a platform. Under open world assumption the data and statements about knowledge that are not included in or inferred from the knowledge explicitly recorded in the system may be considered unknown, rather than wrong or false. Existing PLM platforms have a big challenge to handle “unknown data” and be flexible enough to discover new data patterns.

3- The openness of PLM platforms are improving these days. A good example of that is Codex of PLM Openness focusing on how to establish data transparency between vendors, customers and services providers. Unfortunately, for most of PLM vendors, openness is reflected as an ability to export data from PLM system via predefined APIs. At the same time, it is hard to make design and PLM systems to be driven by the data coming from an outside world.

What is my conclusion? I think, big data is a big challenge for PLM vendors. Most of big data solutions are using platforms that are different and disconnected from existing PLM platforms built on older RDBMS technologies. Existing PLM platforms are suffering from limited ability to manage meaningful connections with big data platforms and are not capable to provide a platform to leverage big data insight and analysis. PLM vendors should discover how to apply modern data management principles to improve their ability to leverage piles of data and transform their solution from traditional data recording into data driven discovery and decision. Just my thoughts…

Best, Oleg

Image courtesy of jesadaphorn at FreeDigitalPhotos.net

 

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  • Selva Kumaresan Ramakrishnan

    It is interesting view. Thanks Oleg.

    As rightly pointed out PLM system are gathering vital information of Product (BOM, CAD Model, Drawing, Engineering Change Management) . After year of implementation, data size is growing beyond management of RDBMS with file system. Always questions is RDBMS right choice for Bill of Material? Since BOM is more Graph.

    I also following closely following Omneo Solution (Big Data) of Siemens PLM. In my opinion, PLM Vendor will move to BigData/Cloud/Mobile/Social based Technology, like what they did from traditional client/sever to web based System. However they have huge legacy of closed data model, they need to figure it out with standards. These new technology also gives great opportunity to define what will be next generation of Engineering, Manufacturing and Service (PLM, MES, EAM) say 2020 with wealth of legacy data that to create enhance/new customer experience and business model.

    I also see the same issue with ERP/CRM vendors also..

  • beyondplm

    Selva Kumaresan, thanks for your comment! Indeed, many PLM/BOM models don’t fit well RDBM models. Therefore all PLM platforms are creating flexible object modeling schemas. As you rightly mentioned all of them are based on closed data modeling paradigm and might not scale in the future big data /cloud / social. It would be interesting to see what tech PLM vendors will chose for the future platforms. You might be interested to read the following post

    The foundation for the next PLM platforms:
    http://beyondplm.com/2014/08/29/the-foundation-for-next-plm-platforms/

    Best, Oleg

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