As the Eagles readied to celebrate the franchise’s first Vince Lombardi trophy, an unlikely candidate basked in the glow of being declared the game’s Most Valuable Player. Surely it was Nick Foles who, on his way to upsetting one of the NFL’s elite franchises threw and caught a touchdown in the same big game, was the true MVP. But was he?

In the days leading up to the Super Bowl, the New York Times published an article about how the Eagles leveraged analytics to secure a Super Bowl berth. The team relied, in part, on probabilistic models that leveraged years of play data to calculate likely outcomes, given a specific set of circumstances. They found that while enumerating outcomes and optimizing for success, the models would, in many cases, recommend plays that bucked the common wisdom. Indeed, we saw the Eagles run plays and make decisions throughout the season that, to the outside observer, may have seemed mind-boggling, overly-aggressive, or risky. Of course, the outside observer did not have access to the play-by-play analytics. Yet, in many instances, these data-driven decisions produced favorable results. So it seems that analytics were the real MVP, right? Well, not entirely.

As we have written in the past, the most effective analytics platforms provide guidance and should never be solely relied upon by employers when making decisions. This analytics concept rings as true in football as it does in business. The New York Times article talks about how mathematical models can serve to defend a playmaking decision that defies traditional football logic. For example, why would any team go for it on fourth and one, deep in their own zone, during their first possession in overtime? What if the analytics suggested going for it was more likely to result in success? If it fails, well, the football pundits will have a lot to talk about.

Coaches and players weigh the analytics, examine the play conditions, and gauge on-field personnel’s ability to perform. In order words, the team uses analytics as a guide and, taking into account other “soft” variables and experience, makes a decision that is right for the team at that time. This same strategy leads to success in the business world. Modern companies hold a wealth of data that can be used to inform decisions with cutting edge analytics, but data-driven insights must be balanced with current business conditions in order to contribute to success. If this balancing act works on the grand stage of professional football, it can work for your organization.

Indeed, we may soon see a day when football stars raise the Super Bowl MVP trophy locked arm-in-arm with their data science team. Until then, congratulations, Mr. Foles.

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Photo of Eric J. Felsberg Eric J. Felsberg

Eric J. Felsberg is a Principal in the Long Island, New York, office of Jackson Lewis P.C. and the National Director of JL Data Analytics Group.

As the National Director of JL Data Analytics Group, Mr. Felsberg leads a team of multi-disciplinary lawyers…

Eric J. Felsberg is a Principal in the Long Island, New York, office of Jackson Lewis P.C. and the National Director of JL Data Analytics Group.

As the National Director of JL Data Analytics Group, Mr. Felsberg leads a team of multi-disciplinary lawyers, statisticians, data scientists, and analysts with decades of experience managing the interplay of data analytics and the law. Under Mr. Felsberg’s leadership, the Data Analytics Group applies proprietary algorithms and state-of-the-art modeling techniques to help employers evaluate risk and drive legal strategy. In addition to other services, the team offers talent analytics for recruitment, workforce management and equity and policy assessments through predictive modeling, partners with employers in the design of data-driven solutions that comply with applicable workplace law, manages and synthesizes large data sets from myriad sources into analyzable formats, provides compliance assessment and litigation support services including damage calculations, risk assessments, and selection decision analyses, and offers strategic labor relations assistance including determination of long term costs of collective bargaining agreements, review of compliance with collectively bargained compensation plans and assessment of the efficacy of training programs. The JL Data Analytics Group designs its service delivery models to maximize the protections afforded by the attorney-client and other privileges.

Mr. Felsberg also provides training and daily counsel to employers in various industries on day-to-day employment issues and the range of federal, state, and local affirmative action compliance obligations. Mr. Felsberg works closely with employers to prepare affirmative action plans for submission to the Office of Federal Contract Compliance Programs (OFCCP) during which he analyzes and investigates personnel selection and compensation systems. Mr. Felsberg has successfully represented employers during OFCCP compliance reviews, OFCCP individual complaint investigations, and in matters involving OFCCP claims of class-based discrimination. He regularly evaluates and counsels employers regarding compensation systems both proactively as well as in response to complaints and enforcement actions.

Mr. Felsberg is an accomplished and recognized speaker on issues of workplace analytics and affirmative action compliance.

While at Hofstra University School of Law, Mr. Felsberg served as the Editor-in-Chief of the Hofstra Labor & Employment Law Journal.