The Beginning of Crowdsourced Analytics

Despite all of the press it got, the Netflix Challenge wasn’t the first crowdsourced analytics problem. That distinction goes to the GoldCorp Challenge, which was a last ditch effort to save a gold mining company. Fortunately for the company, ownership changed in a proxy fight and an industry outsider ended up at the helm, Rob McEwen. In a true flash of genius, the new CEO crowdsourced a solution five years before Jeff Howe would coin the term in his famous Wired article. Even more intriguing, is that McEwen was inspired by the open source Linux development paradigm and asked, "How can I apply that to the mining industry?"

The Challenge

"Rob McEwen triggered the gold rush by issuing an extraordinary challenge to the world's geologists: We'll show you all of our data on the Red Lake mine online if you tell us where we're likely to find the next 6 million ounces of gold. The price: a total of $575,000, with a top award of $105,000." "The external response was immediate. More than 1,400 scientists, engineers, and geologists from 50 countries downloaded the company's data and started their virtual exploration." This opportunity did carry with it some risks though, such as a hostile take-over by a competitor using their data.

Fortune smiled on Goldcorp though, because in that group of 1,400 geologists was a high-powered Australian geological analysis firm, Fractal Analysis, that was trying to make a name for itself. They ultimately won the competition, but conceded that they lost money on the analysis in hopes that the publicity would bring them more business. An image from their winning submission is included at the right. "The worth of [the gold discovered] has so far exceeded $6 billion in value."

Quantification of Performance

Productivity and Cost Improvements: Gold production increased from 53,000 gold ounces in 1996 to 504,000 gold ounces in 2001, a 851% increase in production. Because extraction cost per ounce dropped from $360 per ounce to $59 per ounce, an 84% reduction in cost. I surmise that this reduction in extraction cost is driven by improvements in extracting more gold from the same amount of ore moved.

Accuracy: "We have drilled four of the winner's top five targets and have hit on all four."

Speed: "McEwen believes that [the challenge] cut two, maybe three years off the company's exploration time."

1,043,000% ROI: A $575,000 crowdsourcing investment yielded $6 billion in gold.

Firm Survival: The open market price for gold dropped from $400 per ounce in 1996 to $300 per ounce in 2001. Given that it cost $360 per ounce to extract the gold, Goldcorp would have shuttered the mine when the prices dropped below extraction costs. Had they NOT pursued the Goldcorp Challenge the firm would have disappeared.

Stock Growth: Now the second largest gold mining company in the world, with 27.5% CAGR in stock price since The 2001 GoldCorp Challenge

Portability of ‘deposit valuation skill’ enables acquisitions: Companies acquired since the GoldCorp challenge include Glamis Gold, Barrick Gold Trading, and Gold Eagle Mines.

Commentary

I do think that the Goldcorp challenge is a marvel, and it arose from questioning such a simple assumption, “Why should we keep the data private?” What perplexes me though is, if Goldcorp ‘struck gold’ on the five best new sites they dug, why did they ever disclose this? It may be to comply with disclosure requirements, but the larger prize was testing and knowing the efficacy of the analytical techniques.

The winning team was a small quant-geologist company in Australia. If they were the best of the bunch, why not acquire their company and use the analytical advantage to buy underperforming mines around the world?

Ok, by comparing the results Goldcorp may know that other teams submitted the same sites so the benefit could be duplicated.

Note, the firm would have closed at least temporarily, had they not found better yielding deposits to mine (which reduced their cost per ounce). But who would ever stare at an impending bankruptcy, or cessation of operations and say, “Let’s get some quant-geologists in here to save us.”

Goldcorp never ran a challenge again, because they already knew who was the best. I imagine that for every acquisition thereafter they brought in the same awardees from the original contest. Could it be that Goldcorp’s success is strictly because they used the ore targeting software when acquiring other firms, and thereby pocketed a premium on each purchase?