You’ve got several orders of magnitude more data coming your way, warns Google’s chief economist.
With a mission to “organize the world’s information and make it universally accessible,” Google is a central part of the current focus on huge amounts of data. Even the name Google is rooted in largeness, as it was derived from googol, an alternate term for 10100.
Hal Varian, chief economist at Google and emeritus professor at UC Berkeley, has been with Google for more than a decade and has unique insight into the past and future of data analytics.
In a conversation with Sam Ransbotham, associate professor of information systems at the Carroll School of Management at Boston College and guest editor for the MIT Sloan Management Review Data and Analytics Big Idea Initiative, Varian says that companies need to beef up their systems to function within an overwhelming data flow — including new voice-command system data and other computer-mediated transactions.
Thank you for taking the time to talk with us. Can you tell us a bit about your background at Google?
When I stepped down from being dean at Berkeley, I ran into Eric Schmidt, who told me he had joined this cute little company down in the Valley, and asked if I could come down and help them out. So I went down in May of 2002, and met everybody. There were maybe 200 people there, located in one building — Building Zero. I had so much fun during that year that I stuck around and consulted for Google when I returned to Berkeley. And then later, as the company grew so rapidly and there were so many demands on my time, I shifted over to a full-time position in 2007.
When I got there, I said, “Eric, what do you want me to work on?” He said, “Why don’t you take a look at this ad auction. I think it might make us a little money.” They had implemented this novel method for selling ads, namely the AdWords auction. That had been rolled out in February of 2002. When I got there, I took a look at it and ended up constructing an economic model, doing some fairly detailed empirical analysis, trying to understand its properties and how it should evolve and so on.