How oil companies use BI to maximize profits

Gas tops US$4 per gallon. Crude is trading at all-time highs-above $125 a barrel. And oil and gas companies are booking fat profits. In May, Exxon Mobil reported $10.9 billion in profits for its latest quarter, just short of its record-breaking $11.7 billion the quarter before.

It's tempting-and politically expedient-to explain such astounding numbers by saying that greedy oil companies are taking advantage of market fears, making money on the bent backs of corporate and individual consumers. So many of us, after all, have no choice but to buy fuel. We fill our cars to drive to work, where buildings must be heated in winter, supplies must be shipped, products trucked and executives jetted hither and yon.

Yet economists will counter that taking advantage-spotting a revenue opportunity and moving on it-is exactly what companies should do: That's capitalism. Oil companies excel at identifying where their profit advantage lies. And they obtain that advantage through sophisticated business intelligence systems.

Without good BI, oil companies risk their livelihoods, says David Knapp, a senior editor at the Energy Intelligence Group, an information provider for the oil industry. "Those that have lagged in understanding have lagged in performance," Knapp says. And BI is all about understanding what makes your company-and your industry-thrive. Mortgage lenders, for example, are going under in part because they didn't analyze enough of the right customer data and signed up risky borrowers. Retailers in trouble are studying financial intelligence to determine whether they should seek loans to stay afloat, like Borders Group, or, like RedEnvelope and Lillian Vernon, file Chapter 11.

Oil companies have always lived and died on BI, says Gary Lensing, VP and CIO for global exploration and production at the $32 billion Hess. "Data drives what we do, always quantifying where that value is."

Hess and its competitors harvest data from inside and outside their four walls, plus they factor in wild cards such as war, weather and global politics. BI in oil and gas isn't a simple matter of buying a set of analysis tools and feeding data into them. Oil companies pass information through multiple layers of software, with nearly every employee focused on collecting and storing some kind of data. Exxon, for example, wants its geophysicists to know Fortran, C and Java so they can code their own, quick analyses. When Hess drills a well, Lensing says, engineers collect status data every 15 seconds.

Typically, specialized applications for oil and gas-such as Geolog from Paradigm Geotechnology (to find patterns in seismic measures) or PDI FocalPoint from Professional DataSolutions (to track gas station store sales in a dashboard)-have their own analysis capabilities. But to get a global view of company performance, that data must be fed into off-the-shelf BI analysis and reporting packages familiar to most CIOs, such as those from Cognos or SAS Institute. Then the companies add supply-chain information. SAP for Oil & Gas modules manages the supply chains at companies like Hess and Valero. Those companies also use at least some of SAP's analysis and storage applications, including Business Warehouse. Oil companies store data in both common databases, such as Oracle, and specialized ones for the oil industry, such as OpenWorks or StratWorks from Halliburton.

When it comes to BI, Big Oil has a big view. "We're not as transactionally driven as other industries," Lensing says. "Are you trying to gain operational efficiencies by squeezing pennies out of transactions, or are you looking at core assets and trying to extract additional value?"

Examine how oil companies approach BI and you will uncover valuable lessons for improving your own BI efforts, whether you're trying to optimize profits or uncover untapped markets.

Factors in the Price of Gas

Old-timers called oil "Texas Tea," but the U.S. oil industry really started in Pennsylvania, with the 1859 discovery of light crude burbling between rocks in a farmer's creek. People at first used it to grease machinery and light lamps. Fifty years later, rigs pumped black gold from wells across the country and fortunes were made. Now, as then, oilmen cagey about their claims don't say much about what they know. But some will talk about how they know it.

In an industry where the top five oil companies last year booked $1.5 trillion in sales, thieves target that intelligence. In February, for example, Petrobras, the $112 billion state-owned oil giant in Brazil, had four laptops and two hard drives stolen. They contained "secret and important information," the company told Brazilian news outlets, about an ocean reservoir that in the next few years could produce up to 8 billion barrels of oil. Brazilian police are said to be investigating. Geologic information like the sort believed to have been stolen from Petrobras is one piece of the "upstream" part of the business, where companies and countries explore and drill for oil deposits deep in the earth. Analysts combine geologic and seismic data with what-if engineering models showing how best to get the oil out and the projected costs of such a multiyear project, explains Louie Ehrlich, CIO and president of Chevron Information Technology.

Then there is the "downstream" work of refining crude oil into something usable, such as gasoline or diesel, and of getting those products sold and delivered. Those jobs generate information on refinery capacity and throughput, for example, and the cost of marketing and distribution.

Exxon and Chevron, the biggest oil companies in the United States, are known as "integrated," meaning they work both the upstream and downstream ends of the business. Petrobras does, too, though Ehrlich points out that no company is perfectly integrated, meaning that what it finds in the ground always ends up in its own refineries. Chevron might find crude that its refineries don't handle, he says. "Some types of oil require more complex refining capability to process." Chevron produces about 2 million barrels of oil per day and only refines about 15 percent in its own refineries.

Others focus on just one end or the other. Valero, for example, is the biggest U.S. refiner, concentrating on the downstream work of turning oil into other things to sell.

Upstream usually costs more than downstream. Exxon, for example, spent $15.7 billion on upstream jobs in 2007. Chevron, $15.5 billion. But downstream costs stack up, too. Exxon's were $1.1 billion and Chevron's $3.4 billion.

Prices at the pump reflect these expenses. The cost of crude oil constitutes most of the price of gas, accounting for 73 percent of today's $4-plus figure, according to the U.S. Department of Energy. Refining, meanwhile, is 8 percent; so is distribution and marketing. The remaining 12 percent goes to state and federal taxes. Each oil company analyzes its costs and potential income, says David Smith, an IT consultant to the oil industry at Electronic Data Systems, trying to profit at each step (except for taxes, which are fixed).

Traditional economic principles of supply and demand alone fall short when you try to forecast prices, Smith says. "With political instability, fear about Iran and Iraq-those have ripple effects and an emotional response at the pump," he says.

"You have to blend that volatility with real-time market data and factors you can't predict."

Big Oil's Big Picture

After oil, the best kind of gusher to discover and manage these days is data, and therefore profits, in real time. Or close to it. That's what Hess is after.

For the past four years, the $32 billion integrated oil company has been building BI systems to trace and interpret data from start to finish along the exploration and production value chain in as close to real time as possible, says Lensing. The idea is to be able to see activity at all its assets in Norway, Denmark, the U.K., the U.S., Thailand and Africa. Are its four fields in Equatorial Guinea producing as expected today? Is the refinery in New Jersey running at capacity, or can it take in more barrels of oil before the end of the month? What have sales at its 1,370 gas stations been since last Saturday at noon?

No one business intelligence product can do it all, though. For financial analysis, Hess mainly uses tools from Hyperion, which Oracle bought last year. To estimate how much oil or natural gas its wells can produce, the company develops a model of the reservoir terrain based in part on readings from bouncing seismic waves in the area. For a look at patterns in well production, Hess runs a tool popular among pharmaceutical firms called Spotfire, from Tibco. Spotfire lets analysts visualize data by producing graphs, charts and other pictures, into which users can drill down with queries.

The company is also installing OSIsoft performance management software-in part to collect operations data-to measure, for example, how efficiently platforms and storage tanks are running. That project isn't finished yet. Meanwhile, Hess receives daily uploads about the performance of its joint ventures, such as one with Shell in the Gulf of Mexico, via secured FTP transfers.

One of the real-time parts of this BI chain is well data. An engineer in Houston can monitor drilling activity in West Africa, see an anomaly in how the drill bit sinks into the ocean floor and can send that data over satellite to a geoscientist in Houston, who can view the visualization and e-mail a recommendation on how to adjust the machines, Lensing says.

"The ability for people on a platform to communicate with people in the home office and work on the same set of data means we can get more production done faster and more accurately," he says. "How you choose to analyze the data and the decisions you make-there's your competitive advantage."

More production faster means Hess could, in theory, sell more crude or refined products sooner while market prices are high, as they are now.

The Cost of New Business

For Petrobras, an oil field discovered off the coast of Brazil could become the world's third biggest, after one in Saudi Arabia and another in Kuwait. The potential bounty: 33 billion barrels.

That's an unofficial estimate attributed in April to Brazil's National Petroleum Agency. Petrobras officials decline to confirm it, insisting that more testing must be done. Olinto Gomes de Souza Jr., a senior geologist there, is helping analyze some of the test data.

After four years of exploration and computerized modeling, the company last November announced that it had hit oil 6,500 feet beneath the ocean surface and another 16,000 feet into the ocean floor. Now proof drilling continues, boring through rock and salt layers atop the oil. At each centimeter, Petrobras looks at 10 to 12 variables, including temperature, pressure, and weight of rock and sediment. Stored in an Oracle database, the information is queried with analytics software from SAS Institute.

After geologists assess the information, it's sliced and diced against financial realities. "The amount of money we spend is very high-$100 million for a well alone," de Souza says. "We want to get it right."

To reach its goal of becoming one of the five biggest oil companies in the world by 2020, Petrobras has to take some calculated risks. Recovering oil from this find will be expensive partly because it's so far down in the earth. "No company has tried to explore under it," he says. But promising data has triggered major staffing decisions: Petrobras has created a new group of senior managers to oversee exploration of this area and plans to hire 14,000 drillers, geologists and engineers. It takes years to go from initial exploration to crude oil production and sales of finished gasoline, so companies have to model markets five, 10, 15 years out. They use a mix of their own intelligence and public data, such as from the Energy Information Administration (EIA), says researcher Knapp.

For example, automakers continue to improve the fuel efficiency of their cars and light trucks, as well as to build electric-gas hybrids. By 2030, the average light-duty vehicle will get 27.9 miles per gallon, 40 percent more than in 2006, according to the EIA. A highly simplified analysis suggests that if people use less gasoline, gas prices should drop, which makes expensive drilling less profitable, Knapp explains.

Although demand for gas is growing in China and India, so far it's not enough to offset the expected drop in U.S. demand. New well and rig technologies could take some of the cost out of drilling, but no one knows exactly when or by how much. There is no shortage of data points; the value is in interpretation. "It's about filtering rather than finding a piece of information," he says. "Understanding what this whole pile of stuff can do for you is the key."

Adjusting to Change in Real Time

Every Wednesday morning, the shouts and hand gestures that make the Nymex trading floor in New York frantic begin to calm. Petroleum traders are waiting for the release of data from the U.S. Energy Information Administration (EIA) on countries' inventories of crude oil and gasoline, as well as world crude prices.

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