Speaker "Brian D'alessandro" Details Back



Data Economics and Predictive Modeling


Many firms depend on third-party vendors to supply data for commercial predictive modeling applications. An issue that has received very little attention in the research literature is the estimation of a fair price for purchased data. In this session we present a methodology for estimating the economic value of adding incremental data to predictive modeling applications and present two cases studies. The methodology starts with estimating the effect that incremental data has on model performance in terms of common classification evaluation metrics. This effect is then translated into economic units, which gives an expected economic value that the firm might realize with the acquisition of a particular data asset. With this estimate a firm can then set a data acquisition price that targets a particular return on investment.


Brian d'Alessandro is a technologist who sits in the intersection of marketing and data science. He is currently SVP of Digital Intelligence at Dstillery, where he leads the company’s data product strategy. Prior to this role, Brian was VP of Data Science and led research and development of Dstillery’s patented machine learning technology. Brian’s research interests include causal attribution, the economics of data and scaling up machine learning applications. Outside of Dstillery, Brian is also an adjunct Professor for the NYU Data Science program and is an active organizer and participant in various conferences involving data, marketing and technology. He is a long-time volunteer for Datakind where he regularly advises or leads data mining projects for various non-profit organizations. Brian is also the drummer for the critically acclaimed indie rock band Coastgaard.