by French Caldwell | January 9, 2013 | Comments Off on Will It Be Big Data or Big Oil That Saves America?
It could be awfully confusing to try to make sense out of today’s FT. A front page article highlights that the US is headed toward energy independence, which is a boon to energy intensive industries — heavy manufacturing, high tech manufacturing, petrochemicals, and even IT services. On the other hand, a lead opinion piece touts Big Data, not Big Oil, as the salvation of American manufacturing.
So, which is it? It really depends on what you might see as the fundamental economic problem facing the US. Stratfor’s CEO George Friedman published a heartfelt piece yesterday on the crisis of the American middle class. In it he clearly differentiates between economic gains, which the FT piece on Big Data highlights, and the prosperity or lack of it for the middle class. Friedman convincingly illustrates that what’s good for the economy is not necessarily good for middle class workers and families.
The application of Big Data to manufacturing and supply chains can help to make American manufacturing more competitive, mostly through ongoing gains in productivity. For workers who keep their jobs in the next Big Data led productivity push, that’s great, but productivity gains often lead many to lose their jobs. And it may even help to bring some manufacturing back on shore, which is good for the economy, but as highly automated as repatriated manufacturing can be, it is not necessarily a big job booster.
On the other hand, lower and more stable energy costs have a direct impact on the bottom line irrespective of productivity. Bringing supply chains closer to home and low emission, low cost natural gas energy sources will enable gains in well-paid manufacturing employment as well in sustainability performance. My colleague Stephen Stokes predicts: “By 2016, 60% of global manufacturers will focus on the upstream supply chain for sustainability reporting, analysis and performance improvement.”
And new jobs start with the exploration and production of natural gas and oil in regions like the great plains and the mid west that were hit hard by economic shifts over the last several decades. With lower energy costs, and sources of energy close to traditional centers of manufacturing, the US middle class will indubitably benefit, starting at the pump and continuing with gains in employment.
Big Oil trumps Big Data, right? Not quite. With lower energy costs, US CIOs will see the economics of off shoring shift as well. Off shoring has already been hit by higher wages in developing economies, and now with the US having a competitive differentiator on energy costs, data processing and storage could shift back to the US as well. While there is not a lot of correlation between the location of data centers and the analysis and application of big data, off shore centers enable developing economies to develop higher value IT services like Big Data analytics. Lower energy cost in the US could slow that trend enabling the US to maintain a significant lead in the analysis and application of Big Data.
Within manufacturing sectors, we could see the development of a synergistic relationship between Big Oil and Big Data — the former lowering the cost of doing business in the US and re-invigorating the middle class, and the latter driving ongoing gains in productivity and innovation enabling ongoing economic gains — a virtuous circle of Big Oil and Big Data.
Read Complimentary Relevant Research
Predicts 2017: Artificial Intelligence
Artificial intelligence is changing the way in which organizations innovate and communicate their processes, products and services. Practical...
View Relevant Webinars
How to Live Without Mobile Device Management
This webinar addresses the growing trend of users refusing to have enterprise management of their mobile devices due to privacy concerns....
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.