New developments in data science offer a tremendous opportunity to improve decision-making. Machine learning, pattern recognition, and other predictive analytics tools can constitute a source of competitive advantage for those companies that adopt them early on; but like any new capability, there is an enormous gulf between awareness, intent and early engagement, and achieving significant business impact.

How can companies better manage the process of converting the potential of data science to real business outcomes?  How can companies go beyond merely generating new insights to changing behaviors — not only of their employees, but customers too? We would like to offer some lessons from AIG’s early experiences with deploying new analytical tools to leaders across industries who may be considering embarking on a similar journey.

To read this article in its entirety, please click here: http://blogs.hbr.org/2014/10/how-aig-moved-toward-evidence-based-decision-making/

    Citation:

    Reposted with permission.  Copyright 2014 by Harvard Business Publishing; all rights reserved. 
    This HBR Blog was originally published on October 1, 2014 at:

    http://blogs.hbr.org/2014/10/how-aig-moved-toward-evidence-based-decision-making/