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Boom Times for Mining Giant Signal Deep Changes in Sector

Wall Street Journal Original article ›

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BHP Billiton was known as Broken Hill Proprietary in the 1990's. The largest Australian mining company, it was based in Melbourne and simply known as the Big Australian. It had huge losses in that period - $3 billion in 1998-1999. The turnaround at BHP Billiton comes as a remarkable turnaround for the whole mining sector. BHP made $6.5 billion in profit in the year ending June 2005. Its not just rising Chinese demand that has made this possible. Billiton has taken steps to avoid past boom bust cycles in mining by taking a conservative approach to investing in new mines that might create an oversupply in the market. The company is run buy a banker. CEO Charles Goodyear avoids taking on large risky projects and has announced plans to return $2 billion to shareholders in stock buybacks. Even with this discipline compared to the past, some mining analysts believe the boom bust cycle will occur over time. HP has $10 billion worth of projects in different stages of development. One advantage the mining companies enjoy is the concentration of mining in a few companies- BHP, Rio Tinto, Xstrata PLC. This makes it possible to price aggressively for the nickel, copper, iron ore, and other metals. A 72% price increase was negotiated with steelmakers in 2005. Another part of the transformation is the use of risk-analysis tools. BHP uses "Monte Carlo analysis" to check all potential outcomes once a range of parameters- commodity prices, currency vales, interest rate scenarios- are entered that affect financial performance of a new mine or a new investment. Goodyear came in as CFO under a new team led by Paul Anderson, a former executive of Duke Energy Corporation, after the huge losses in failed copper mining investments in the late 1990's. Even with the recent success and the careful investing discipline there is a sense that things could change quickly if rising demand slows in China and other developing countries. And in that situation this discipline may prove insufficient and the models may only be good as the assumptions and information entered.

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