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Last week, I followed Gilbane Conference Boston online. Navigate here to dig for more info. Gilbane conference focus is content, web and mobile. My primary interest was about content. Let me say differently – growing content in organization and online. This is not a surprising topic these days. You can see many charts these days online presenting a growing content online and in enterprise organizations. Another trending word is “big data”. I’m sure you’ve heard this buzzword before. Nevertheless, here is Wikipedia definition from this article.

In information technology, big data[1][2] is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools. The challenges include capture, curation, storage,[3] search, sharing, analysis,[4] and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to “spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions.”[5][6][7]

One of Gilbane’s presentations about big data caught my attention - Big Data for Enterprise and Marketing Applications — Three Views. CMS article Big Data Explosion Offers Value provide a good write up of this presentation. What was interesting to me is to see how the value of Big Data presented beyond the point of Twitter data analyzes and other web-oriented application. The following paragraph focuses on Big Data and Industrial view by GE’s GM Brian Courteny:

Brian Courtney, GM of Industrial Data Intelligence for GE, discussed a critical but less-publicized aspect of Big Data — its role in automating the monitoring and analysis of industrial data. He said GE uses both batch processing, the offline analysis of “massive repositories of data for patterns and insights,” and stream processing, the real-time analysis of “web-scale data to identify trends and anomalies as or before they occur,” to determine data patterns that indicate likely failures in GE technology such as electricity-generating turbines and airplane engines and then monitor equipment for those patterns in real time.

Another article GE, Industrial Internet and radical efficiency is providing more examples about how GE is planning to leverage Big Data technology to improve their products. Here is my favorite passage:

Something important is going on here. GE’s new focus is about “the convergence of the global industrial system with the power of advanced computing, analytics, low-cost sensing and new levels of connectivity permitted by the Internet.” It’s about how “the deeper meshing of the digital world with the world of machines holds the potential to bring about profound transformation to global industry, and in turn to many aspects of daily life, including the way many of us do our jobs.”

The examples above make a lot of sense to me in the connection to PLM, product development and manufacturing. Monitoring of products in a real life becomes an interesting and fascinating topic. It can provide significant impact of design improvements and help manufacturers to innovate. Sounds like a primary role for PLM these days – to boost innovation among manufacturing companies. Think about data trend analyzes that can prevent potential failure of systems in a car that can alert customer to approach server center. Dream? I’m not sure and think we will see it soon.

What is my conclusion? Monitoring products in a real life is a interesting topic. However, most of the limitations today are related to inability to analyze a massive amount of data produced during the monitoring. Relational databases used by majority of PLM platforms cannot scale. BigData technologies can change it. It is an interesting application of tech originally developed in a consumer space. Just my thoughts…

Best, Oleg

pic is courtesy GreenBiz article.

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