May/June 2011

As the banking sector gradually rebounds from the global recession, many bank executives and boards are focused on incorporating the painful lessons learned during the past three years into their business operations. Chief among those lessons learned is the need to strengthen the management of credit risk as economic conditions fluctuate.

• Andrew Jennings
• Carolyn Wang

Most of us go about our daily actions in our personal lives constantly evaluating risk vs. reward elements. Most actions are based on decisions that are made quickly and sub-consciously with barely a thought regarding risk vs. reward, but others are more deliberate and calculating as, say, financial decisions to invest in the stock market.

• Param Singh

To marketers, it is fairly well established that enticing all customers with the same offer or campaign is useless. The No. 1 reason why people unsubscribe or opt-out is due to irrelevant messaging. A while back marketers moved to grouping customers on the basis of certain metrics that gave a bit more context to the marketing strategies. Example: offering an entertainment service to customers who: 1. use a lot of MMS for sending videos and pictures, 2. download songs using GPRS, and 3. have a very high ARPU (average revenue per user).

• Talha Omer

For four years, Rexer Analytics has conducted annual surveys of the data mining community to assess the experiences and perspectives of data miners in a variety of areas. In 2010, Rexer sent out more than 10,000 invitations, and the survey was promoted in a variety of newsgroups and blogs. Each year the number and variety of respondents has increased, from the 314 in the inaugural year (2007) to 735 respondents in 2010. [Rexer Analytics did not specifically define “data miner” or “data mining”; the decision to participate in the survey was an individual choice.]

• Karl Rexer
• Heather Allen
• Paul Gearan

As highlighted by James C. Cochran in the January/February 2010 issue of Analytics and a forthcoming special issue of Interfaces co-edited by Michael J. Fry and Jeffrey W. Ohlman, the sports industry has firmly embraced the use of analytics in the decision-making process. Such methods have similarly been adopted in sports law, a corollary field inextricably intertwined with the dynamic sports business. As a prime example, Shaun Assael of ESPN [1] recently described the ongoing litigation involving the National Collegiate Athletic Association’s (NCAA) licensing of former student-athletes’ names and likenesses in video games (a now-consolidated case [2] that started with the filing of two separate actions — Keller v. NCAA, et al and O’Bannon v. NCAA, et al) as one of “five lawsuits that will change sports,” giving credence to the relevancy and importance of how analytics can and will be used in furthering specific arguments arising in the lawsuit. The purpose of this article is to provide an overview of sports law analytics and discuss the role of analytics in sports law cases moving forward, with a pointed discussion of the aforementioned consolidated Keller and O’Bannon case and the U.S. Supreme Court’s recent decision in American Needle v. NFL, et al [3].

• Ryan Rodenberg
• Anastasios Kaburakis

Regardless of the organization that you work for, chances are that you use dashboards to display and deploy metrics. The technology for building dashboards has continuously evolved, so much so that it is now possible for a non-technical person to “build” a dashboard. Despite their ubiquity, whether dashboards have been able to achieve their utmost potential is subject to debate.

• Subir Mansukhani
• Zubin Dowlaty
• Keshav Athreya