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How Oil Companies Use BI to Maximize Profits

How Oil Companies Use BI to Maximize Profits

Every day, oil companies harness gushers of data to assess market conditions for a gallon of gas. Learn how they match the right tools with information to maximize profits.

In 2007, UPS piloted its telematics program on 334 delivery trucks in Georgia. Analysis of the data generated helped to cut the amount of time delivery trucks idled by 24 minutes per driver per day-for an estimated fuel savings of US$188 per driver, per year. "That adds up to a lot of wasted fuel," says Jack Levis, a manager in UPS's industrial engineering group, "and a lot of carbons being emitted into air that don't need to be." UPS has more than 90,000 US package drivers, so the potential savings could amount to millions.

In addition, many of the insights gained from the telematics system have been eye-opening and somewhat counterintuitive for the engineers in the automotive group. For example, UPS has typically scheduled fleet maintenance according to time-dependent factors. But engineers and other "data miners," as Levis calls them, discovered that UPS was replacing large components and parts on its delivery trucks when telematics showed that what actually needed to be replaced was just, say, an O-ring. "So rather than a thousand-dollar job, it was a $20 or $30 job," Levis says.

There's more to learn as operations analysts comb through the data looking for other efficiency patterns and safety trends. For instance, UPS delivery personnel may be driving unnecessary miles on their routes. "We've just scratched the surface on finding things," says Levis.

--Thomas Wailgum

Managing X-Factors

Financial markets often move on fear and uncertainty. The problem is, no one can predict which direction commodity prices will go in or how much they will gain or lose.

On April 21, news spread that unidentified attackers had punctured a Japanese oil tanker with rockets while the ship was sailing to Saudi Arabia. That same day, Royal Dutch Shell announced that African militia fighters, protesting corporate oil activity on the Niger Delta, had damaged a pipeline in Nigeria. Worried about oil supplies, traders pushed oil to US$117 per barrel, setting a new record.

Then there are less-violent but no less-volatile events. Hurricanes such as Rita and Katrina in 2005, say, or refinery explosions. Downtime at even one major refinery from a fire or explosion can drag down earnings at that company and affect the rest of the industry for years. Literally.

BP, the US$21 billion British oil company, has paid in financial terms and human lives. In 2005, explosions and fire at BP's refinery in Texas City, Texas, killed 15 people and hurt 170 others. The refinery, which by itself makes about 2.5 per cent of all the gasoline sold in the United States, had to be partially closed. Then it suffered damage from Rita and Katrina later that year and didn't reopen completely until this past February. BP's profits in the US have dropped, in part because of the Texas City disaster, from US$12.6 billion the year the refinery blew up to US$7.4 billion last year, according to BP's latest annual report.

Chevron, meanwhile, noted in its annual report that although product margins for the oil industry were generally higher for 2007, profit margins on Chevron's refined products "were negatively affected by planned and unplanned downtime at its three largest US refineries." Because of the problems, Chevron's US refineries ran at 85 per cent capacity for crude oil distillation in 2007, down from 99 per cent in 2006. Chevron's US downstream profits dipped to US$966 million from US$1.9 billion in 2006.

Smith, the EDS consultant, says competitors should have BI in place to assess an event like BP's Texas City disaster or Chevron's partial shutdowns immediately. "If I'm Shell, I should understand what's the opportunity" to fill gas orders that BP and Chevron might not be able to, he says.

The Federal Reserve Bank of Dallas has developed a model to forecast the price of gasoline that accounts for surprise events. Stephen Brown, director of energy economics and microeconomic policy analysis there, uses a combination of Excel and EViews, a Microsoft Windows-based application designed to perform regression analysis. EViews comes from Quantitative Micro Software, a privately held company in the US. Unlike most BI tools, EViews was designed specifically for analyzing time-series data. Advanced regression analysis capabilities aren't usually part of mainstream BI tools, although SAS and SPSS offer some. Universities sometimes provide such tools (for free, even), including Pennsylvania State University's EasyReg and University of Minnesota's Arc Software.

First, Brown assumes that a certain number of unpredictable events will happen in a given year. For example, some refineries will shut down for some period because of fires or hurricane damage. Brown looks at refinery histories to calculate an average outage, then sets his model to account for it. "We have said that all these unusual events that have occurred in past are going to occur on average in the future as they have in the past," he explains.

What Brown's model can't account for is politics. There's no way to calculate an average impact of country leaders acting erratic-something the US$214 billion Chevron must deal with. About 26 per cent of its proven oil reserves are in Kazakhstan, the company says. Kazakhstan isn't the most stable of countries. It broke off from Russia in 1991 and is now ruled by a president granted lifetime powers and immunity from criminal prosecution.

Chevron does not comment on the security of company personnel or operations, according to a spokesman, Sean Comey. However, in its latest annual report, Chevron lists the Kazakhstan operation under the warning "Political instability could harm Chevron's business."

From Wildcat to Datacrat

No one argues that oil isn't one heck of a lucrative industry. And all those profits don't come from good business intelligence practices alone. But it's a powerful notion to run a company with the mind-set that virtually every employee is a data analyst.

"Engineers and geoscientists and everyone have been taught BI from the start," says Lensing, the Hess CIO. Give people in any industry access to information along with tools to interpret the past, model the future and imagine different paths between the two, he says, and they can change the trajectory of companies.

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