Will Google Set Future PLM Information Standards?

Will Google Set Future PLM Information Standards?


One of the core capabilities of Product Lifecycle Management is the ability to define and manage a variety of information about product – requirements, design, engineering, manufacturing, support, supply, etc. In order to do so, PLM vendors developed data management technologies and flexible frameworks that can handle product data. You may find some of my previous posts about PLM data modeling  – PLM and Data Model Pyramid and What is the right data model for PLM?

Nowadays, Data Management is going through a cambrian explosion of database options. I touched it a bit in my writeup PLM and Data Modeling Flux. If you have few free minutes over the weekend, take a look on the presentation – PLM and Data Management in 21st century I shared on TechSoft TechTalk few weeks ago in Boston.

The biggest problem in handling product data and information is related to a growing complexity of data and dependencies. In addition to original complexity of multidisciplinary data representations (design, engineering, manufacturing), we can see a growing needs to manage customer data, supply chain, social networks, etc. I’ve been pointing on Google Knowledge Graph as one of the interesting technologies to maintain a complex set of interlinked information. Read my post – Why PLM need to learn about Google Knowledge Graph to learn more. Google is not the only vendor interested in how to maintain product data. My post – 3 things PLM can learn from UCO (Used Car Ontology) speaks about variety of technologies used to model car product information.

The following article caught my attention this morning (thanks to one of my blog readers) – Google adds car facts, prices to its Knowledge Graph. I found it very interesting and connected to my previous thoughts about how product information can be managed in the future. Here is a passage from the article:

Starting today, users can search the make, model, and year of a car to find out a variety of information, directly from the Google search page. For instance, if you search “Tesla Model S”, the Knowledge Graph will now show up and present you with the MSRP, horsepower, miles-per-gallon, make, and available trims. Different cars show a different set information, as well. Should you search “Ford Focus”, you will be presented with the MSRP, MPG, and horsepower, as well as the engine size, body styles, and other years.

I made few searches and captured following screenshots. You can see how Google Knowledge Graph semantically recognizes right information and snippets of data about vehicle.


The following set of information about Mazda6 also presents the fact GKS keeps the information about multiple models and model years (revisions?).




What is my conclusion? Most of CAD/PLM companies are very protective about data models and the ways they store, manage and share data. It can provide a potential problem in the future, which will probably will become more open and transparent. We clearly need to think what standards can support future product information modeling. Here is the thing – consumerization can come to this space exactly in the same way it came to some other domains. The future product information management standards might be developed by web giants and other companies outside of CAD/PLM space. Data architects and technologies must take a note. Just my thoughts…

Best, Oleg

*picture is courtesy of http://9to5google.com blog. 


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