A $1 Million Research Bargain for Netflix, and Maybe a Model for Others

Even the near-miss losers in the Netflix million-dollar-prize competition seemed to have few regrets.

Netflix, the movie rental company, announced on Monday that a seven-man team was the winner of its closely watched three-year contest to improve its Web site’s movie recommendation system. That was expected, but the surprise was in the nail-biter finish.

The losing team, as it turned out, precisely matched the performance of the winner, but submitted its entry 20 minutes later, just before the final deadline expired.

Under contest rules, in the event of a tie, the first team past the post was the winner. “That 20 minutes was worth a million dollars,” Reed Hastings, chief executive of Netflix, said at a news conference in New York.

Yet the scientists and engineers on the second-place team, and the employers who gave many of them the time and freedom to compete in the contest, were hardly despairing.

Arnab Gupta, chief executive of Opera Solutions, a data analytics company based in New York, took a small group of his leading researchers off other work for two years. “We’ve already had a $10 million payoff internally from what we’ve learned,” Mr. Gupta said.

Working on the contest helped the researchers come up with improved statistical analysis and predictive modeling techniques that his firm has used with clients in fields like marketing, retailing and finance, he said. “So for us, the $1 million prize was secondary, almost trivial.”

Indeed, since it began in October 2006, the Netflix contest was significant less for the prize money than as a test case for new ideas about how to efficiently foster innovation in the Internet era — notably, offering prizes as an incentive and encouraging online collaboration to tap minds worldwide.

The lessons of the Netflix contest could extend well beyond improving movie picks. The researchers from around the world were grappling with a huge data set — 100 million movie ratings — and the challenges of large-scale modeling, which can be applied across the fields of science, commerce and politics.

The prize model is increasingly being tried on work like new science and freelance projects in design and advertising. The X Prize Foundation, for example, is offering multimillion-dollar prizes for path-breaking advances in genomics, alternative energy cars and private space exploration.

InnoCentive is a marketplace for business projects, where companies post challenges — often in areas like product development or applied science — and workers or teams compete for cash payments or prizes offered by the companies. A start-up, Genius Rocket, runs a similar online marketplace mainly for marketing, advertising and design projects.

“The great advantage of the prize model is that it moves work away from the realm of the beauty contest to being performance-oriented,” said Michael Schrage, research fellow at the Center for Digital Business at the Sloan School of Management at the Massachusetts Institute of Technology. “It’s the results produced that matters.”

The emerging prize economy, according to some labor market analysts, does carry the danger of being a further shift in the balance of power toward the buyers — corporations — and away from most workers.

Thousands of teams from more than 100 nations competed in the Netflix prize contest. And it was a good deal for Netflix. “You look at the cumulative hours and you’re getting Ph.D.’s for a dollar an hour,” Mr. Hastings said in an interview.

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Tags: crowd sourcing, dollar prize, innovative problem solving, losers, losing team, movie ratings, netflix, prize competition, prize money, problem solving, recommendation system, statistical analysis, test case

This entry was posted on Tuesday, September 22nd, 2009 at 8:16 am and is filed under Consider This, Innovation, NY Times, disruptive innovation. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.