[...] The discontinuity emerges from the vast breadth and scope of data that a Merck, a GE, an Airbus, a Wal-Mart, or a GM can reliably generate. There's an extraordinary clash and convergence of opportunity and intent. On the one hand, innovators are seeking laserlike precision in the focus and specificity of their innovation initiatives. On the other, it's become so cheap and easy to collect data on every aspect of an experiment's progress that the question has become, Why not? Data diversity that would once have been dismissed as chaotic noise is now understood to contain meaningful signals. Correlation becomes the crucible for innovation and insight.

[...]

So Merck and Wal-Mart won't merely explore provocative correlations; they'll be exploring the provocative correlations of correlations. These meta-analyses will become how prepared minds cultivate chance as well as exploit it. Innovators will spend less time designing clever experiments to generate data and more time scouring the data to generate hypotheses.

Exploring correlation and causality between multiple monitoring modes should spawn even greater opportunities. [...]

Of course, correlation isn’t causality.