Analytics Magazine Analytics Magazine, November/December 2014 - Page 14

Analy ze T h i s ! After analyzing a great deal of historical data, they find that a team’s late season winning percentage is not a significant predictor of post-season success. The Major League Baseball playoffs, it seems, are (at least statistically) a whole new season. surprising (e.g., “data scientists tend to work with larger data sets integrated across more sources”), there were some interesting insights that emerged (e.g., “data scientists are far more likely to use prototypes to garner support for their projects” and “data scientists are much more likely to be focused on helping their organizations develop a unified view of their customers”). Anyone interested in seeing a summary of these findings should feel free to contact me via e-mail (vmehrotra@usfca.edu). As part of this project, we also examined best practices for managing data scientists. Our findings in this area are presented in a paper entitled “Getting Value from Your Data Scientists” that was recently published in the MIT Sloan Management Review. The paper can be accessed online. Feel free to send me an e-mail with your thoughts, reactions and comments. San Francisco Giants. As I write this, my beloved San Francisco Giants are playing in the World Series, trying for their third championship in the last five years. Like the rest of the orange-clad Giants faithful, I am ecstatic at this year’s post-season success, but I must confess to also being a bit surprised, for this year’s team won only 88 of 162 games (the lowest of any team that qualified for this year’s post-season). Moreover, these Giants finished a distant six games behind Los Angeles Dodgers, their perennial rivals who once again captured the National League Western Division championship. Worse yet, the Giants struggled down the stretch, winn