Predictive Datasets & “Self-Exciting” Activity
There’s a fascinating piece in the November issue of Popular Science re the Santa Cruz Ca police department’s use of datasets to predict tomorrow’s crimes today. Not quite the “Minority Report”, but definitely aligned with Reggie Henry’s (ASAE’s CIO) mantra ” we need to be present at the moment of need”.
Especially interesting is the discussion of a process called “self-exciting” in which one crime leads to another. The program has also been featured in a number of media, though not in anywhere near the detail in the Popular Science article which is not available on line yet (e.g. see http://www.nytimes.com/2011/08/16/us/16police.html).
Not sure exactly how this can be applied to the association world, but I suspect the application of predictive algorithms to the increasingly deep and sophisticated datasets we’re developing around our members will not only allow us to be “present at the moment of need”, but by identifying “self-exciting” member activities (those that tend to generate others), we’ll be able to predict and react to that moment well before it happens.
P.S. This is not to suggest that our members are criminals…other than those who fail to pay their dues.