Big Data: Is the Energy Industry Starting to See Real Applications?

This is an excerpt of the original article. It was written for the January-February 2015 edition of Supply Chain Management Review. The full article is available to current subscribers.

January-February 2015

As long as there have been boats and beasts of burden, intrepid business professionals, governments, and marauders have sought fame, fortune, wealth, and value by going global. Think the Phoenicians, Marco Polo, and the Vikings in days of old. Or in contemporary times, think of China, BRIC, EMEA, and other emerging markets. One could argue that outsourcing to China a few decades ago gave birth to supply chain management as we think of it today. This month we’re including an online bonus column from APQC. While this issue focuses on global management, we didn’t want to miss out on the column.

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Imagine a scenario where a category manager could connect field valve, combustor, or artificial lift failure rates across a variety of operating environments to specific brands and models of equipment. Or imagine another scenario where a supply chain professional could more precisely predict necessary replacement parts usage by understanding the level of experience of the service crews maintaining the equipment. These are increasingly real applications of Big Data across the manufacturing space. Procurement organizations are at the nerve center of this data and have the ability to significantly impact operational performance, costs, and project performance metrics by using data that has historically been available but hard to access.

We will specifically explore the applications to the oil and gas industry (O&G) in this article, but these applications are relevant across multiple industries.

The oil and gas industry operates at the forefront of technology applied to exploration and production. High performance clusters, large reservoir models, seismic models, and large volumes of production data are regularly analyzed. Working with large data sets and advanced analytic modeling (Big Data), therefore, is not a new concept.

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