Big Data. Big Decisions
InformationWeek
Special Coverage Series


InformationWeek 500: Energy Companies And Utilities Aim To Squeeze Out More Efficiencies

With oil and gas prices down, companies are focusing on process efficiency and maximizing margins.

Oil and gas companies operate from the ocean floor to the mountaintop, while U.S.-based utilities reach virtually every household from coast to coast. The sector's IT needs are equally expansive. But there's one common thread: Falling oil and gas prices the past two years have made it imperative that companies in this industry find operational efficiencies.

They were "going flat out" when oil prices were $125 to $140 per barrel in 2008, says Curt Mortenson, a principal at Deloitte Consulting. "When everyone's making that kind of money ... cost is less of a consideration." Now, with oil hovering around $75 per barrel and natural gas prices down 60% from two years ago, companies are focusing on process efficiency and maximizing margins.

Business process innovation was cited as a focus of 75% of the industry's CIOs. An example would be deploying monitoring equipment to oil rigs to track the maintenance levels of components, to maximize rig uptime. "It's about replacing particular items based on wear indicators versus 'hot-shotting' materials out to these rigs when they go down," Mortenson says. Location data matters for those type of uses, as well as for logistics that are a key part of the business; 58% of the sector's CIOs are adopting GPS-enabled or location-aware Web apps, compared with 25% for all industries.

Doug Haugh, executive VP and CIO of Mansfield Oil, sees the combination of mobile data collection and widespread machine-to-machine connectivity as the next big force in the industry. "We're seeing every piece of physical hardware across the supply chain become intelligently connected to the network," Haugh says.

DIG DEEPER
Energy & Utilities
For full interview and in-depth look

Energy companies were focused on business process improvement before the BP spill, but the disaster will no doubt affect the demands on IT. "It's going to have an impact on how we drill, what redundancies are going to be required, and what data we need to capture," Mortenson says.


Industry Snapshot: Energy and Utilities

Return to the 2010 InformationWeek 500 homepage



Related Reading


More Insights




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.