Over the past decade, data driven techniques have been steadily gaining ground over more intuitive approaches. Marriott’s Courtyard brand was born from the results of a conjoint analysis, not a light bulb going off at an executive retreat. And the crisp metrics generated by online advertising campaigns are placing intense pressure on legacy “I waste half of my budget, but don’t know which half” advertising models.

It's particularly interesting when quantitative methods are applied to former bastions of intuition. Moneyball is a memorable account of how a professional baseball team used statistical techniques rather than talent scouts to identify undervalued players. And Epagogix has sophisticated algorithms that can allegedly predict a movie’s box office takings based on the script alone.

It doesn't take an education in music to observe the similarity between musical and mathematical notation. Just as algebraic chess notation is used to describe the moves in a game of chess, I wonder if a piece of music can be expressed in some standard schema that makes it amenable to quantitative analysis. That will open the door for analyzing the entire musical corpus, and perhaps distilling the essence of what it is that makes a piece of music “good”.

The obvious near-term application of data driven musical analytics is to predict whether a new song is going to be a hit – companies such as Platinum Blue and Polyphonic HMI already have some traction. I wonder when we will have the ability to build the musical equivalent of IBM’s Deep Blue–a system which can write original music just as well as the world’s leading composers, and the impact that will have on the world’s music ecosystem.