Great post Bill. Note that the 3Vs as I first defined them over 13 years ago (ref: http://goo.gl/wH3qG) were meant only to define the challenges and opportunities of Big Data. Value is important of course (along with a dozen other dimensions Gartner has identified), but it is not a defining characteristic of Big Data. That is, you can have Big Data but not be generating value from it. "Value" also is a vague, slipery word that's thrown around too casually: enterprise assets that are unutilized have probable value recorded on balance sheets, and deployed assets have realized value recorded in income statements. And "benefits" are often an unfortunate, insufficient proxy for actual value. Notwithstanding the fact that accounting principles *still* do not allow for information assets to be recognized, they meet all the criteria. Recognizing this and information's growing economic importance, I developed and have been teaching information economics (infonomics), including information valuation methods for some years (ref: http://en.wikipedia.org/wiki/Infonomics). Happy to connect on this w you.
Also, it's great that you point out the importance of "new data". This is one of the fallacies/limitations of Moneyball that people don't realize: new statistics were developed using old measurements. New ways of measuring player performance (e.g. Sportsvision's Field/fx system of capturing 2M datapoints per game) and similarly corporate/individual/process/machine performance are critical.
Doug Laney, VP Research, Gartner, @doug_laney