2012, Product Data and the next big thing

2011 is coming to a close. This is usually the time when the blogosphere is awash with “predictions” for the New Year. Curiously enough, I just typed “product data 2012 predictions” in Google and didn’t find anything relevant. Hmmmm. However, I did come across an article by Forbes / O’Reily on the five big data predicitons for 2012. Have a read and tell me what you think. My favorite quote from the article is:

Your own data can become that much more potent when mixed with other datasets. For instance, add in weather conditions to your customer data, and discover if there are weather related patterns to your customers’ purchasing patterns. Acquiring these datasets can be a pain, especially if you want to do it outside of the IT department, and with some exactness. The value of data marketplaces is in providing a directory to this data, as well as streamlined, standardized methods of delivering it.

How would these “data marketplaces” apply, I wonder, to “product data” in manufacturing companies? And what does it actually mean in practice? Cross referencing weather conditions with your customer data can be interesting. But what if the weather stays at -20C from Nov to March (as in the place I am just returning from)? Of what use is that to someone in manufacturing? Let’s now shifts gears. I found a couple of interesting articles, courtesy of the Beyond Search blog. Go here and here to see the articles. Here’s a passage, from the first article, that caught my eye:

The maximal information coefficient (MIC) is a measure of two-variable dependence designed specifically for rapid exploration of many-dimensional data sets. MIC is part of a larger family of maximal information-based nonparametric exploration (MINE) statistics, which can be used not only to identify important relationships in data sets but also to characterize them.

These articles resonate with what Inforbix views as the next “big thing” that will impact product data in 2012 and beyond. Okay, so here’s my prediction relating to the future of product data:

Identifying and connecting together disparate sources of product data in useful ways will become the most effective means manufacturing companies improve innovation and productivity.

Large CAD and PLM vendors are moving towards scalable and agile implementations. Apropos, the latest Autodesk PLM announcement made it clear that Autodesk wants to help their customers connect proceses and workflows across multiple (or all) departments and organizations. Autodesk is deploying cloud oriented applications that may make it possible for processes and workflows to extend beyond a company to include their suppliers and partners.

In my view, connecting multiple islands of data together will soon become more important than ever. Vendors capable of offering customers’ easy, flexible, granular, and affordable means of achieving this will best be able to address their customers’ changing product data requirements. I’d be interested to have your take on my views. What’s your prediction with regards to product data?

Best, Oleg

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