June 23-26, 2013
INFORMS Healthcare 2013
October 6–9, 2013
2013 INFORMS Annual Meeting
June 5-6, 2013
Customer Analytics Summit 2013
June 10-14, 2013
Predictive Analytics World
September 8-14, 2013
2013 ASE/IEEE International Conference on Big Data
Special ArticlesStudy: Who can best manage ‘voice of the customer’?
Over the next three years, global organizations will make understanding and interacting with the customer their top priority. So says a new study from The Economist Intelligence Unit titled, “Voice of the customer: Whose job is it, anyway?” Yet only 56 percent of respondents to the survey, sponsored by SAS, believe their companies clearly understand the customer today.Read More
Special Articles‘Smart water’ analytics helps reduce water loss, cut costs
As water increasingly becomes one of the world’s most precious resources, IBM scientists are working with Arad Group, a world leader in reliable water meter systems, to help water companies and utilities around the globe provide more effective and efficient management of drinking water through the use of big data and advanced analytics technology.Read More
Special Articles‘Cool Vendors’ transforming how businesses operate
The converging and mutually reinforcing social, cultural and technological factors in the Nexus of Forces (cloud, mobility, social and information) are driving a radical power shift away from the culture of the enterprise and toward that of the consumer. “Cool Vendors” are exploiting this nexus to challenge long-held assumptions and affect IT investment, according to Gartner, Inc. Gartner’s 2013 Cool Vendors research series identifies the innovative companies, products and services that will shape business and consumer strategies in the future.Read More
The sport of data science
How many analysts does it take to solve a problem?
That may sound like the start of a bad joke, but no one was laughing in 2006 when Netflix offered $1 million to anyone who could come up with a collaborative filtering algorithm that improved the performance of Cinematch (Netflix’s in-house software) by at least 10 percent. Cinematch predicts which movies Netflix customers like and makes movie recommendations to customers based on those predictions. The goal: boost customer satisfaction and retention along with sales.
Three years later, after receiving several thousand entries from more than 100 countries, a winner was announced, the $1 million prize was awarded and a cottage industry – online marketplaces for business projects where companies post challenges, provide data and offer prizes for the best solutions – took off.
While Netflix reportedly performed no formal cost-benefit analysis on the Netflix Prize, the company was clearly pleased with the results. At the time, Netflix CEO Reed Hastings said, “You look at the cumulative hours and you’re getting Ph.D.’s for a dollar an hour.”
In this month’s cover story, Margit Zwemer, a data scientist and community manager at Kaggle, provides an inside look at “crowdsourcing” – the concept that turns complex analytical problems into a competitive sport open to analysts, astrophysicists or anyone else who cares to submit a solution. As Zwemer notes in her article, the concept is not new; as far back as the 18th century, the British government offered more than £100,000 in prize money to anyone who could come up with simple and practical methods for measuring longitude to assist maritime navigation.
The Netflix Prize, however, helped turn crowdsourcing into a modern-day, mainstream corporate strategy. “Data research competitions are a resource-efficient way for organizations to solve complex data problems, and they create a meritocratic market for talent that changes the way analysts work,” Zwemer writes. Kaggle, an online platform for predictive modeling and analytics competitions, was one of many companies that jumped on the “crowdsourcing” bandwagon in the aftermath of the Netflix Prize. According to Zwemer, Kaggle boasts a worldwide online community of more than 40,000 data scientists and predictive analysts, competing under the slogan “making data science a sport.”