Moneyball and the lesson for Privacy

If you haven’t read the book, Moneyball: the Art of Winning an Unfair Game, or seen the movie staring Brad Pitt and Jonah Hill, I highly encourage you to see them out. I tend to be a “privacy” subject matter expert, but one of the most important aspects of that expertise is the ability to consume diverse content from other expects and apply it to the world of privacy. Whether its behavioral economics (from sources like the Freakonomics and Hidden Brain podcasts), how people learn (from YouTube channel Vertasium), or use of statistics and probability in baseball (i.e. Moneyball).

                I see a huge parallel between Baseball management in the pre-2000 era and the privacy management today. For a hundred plus years, Baseball team management was governed by intuition. Managers and scouts thought they knew what made up a good team. Baseball statistics were published for decades, but wasn’t used in a way that really optimized team performance. The concept of Sabermetrics (the empircal analysis of in game acitivity) began in the 1960s, grew in 1970s, but then transformed the business of Baseball in the 2000s (as chronicled in the book and movie; also see this podcast). Sabremetrics took the “intuition” out of Baseball and turned it into a science, one based on statistics and probability. Science can’t tell you a particular batter will hit a home run against a particular pitcher, but probability can show that you, if you make the same choices, game after game, you’re going to end up with result in a certain range.

                Similar transformations have hit other industries. I believe, the privacy profession is in line for this sort of refactoring. Attempts have been made for decades to create KPI (Key Performance Indicators) for privacy. One of my earliest introductions was a talk by Tracy Ann Kosa at an IAPP conference about a decade ago.  But most privacy program KPIs, in my opinion, still follow the Baseball analogy. Scouts were looking at player stats, but ultimately they were looking at the wrong statistics to determine game outcome. As Jonah Hill says in the movie, “Your goal is not to buy players, its to buy wins.” The privacy profession has, for its short life, relied mostly on heuristics, shortcuts that we intuitively sense, improve desired outcomes. Those shortcuts (such as GAPP, FIPPs, Principles, etc.) have become goals themselves and the metrics tied to those intermediary goals. But, like Baseball, the goal is not the player, the goal is the game. Analogously, a goal in privacy is not transparency, but rather whether a person has the ability to make decisions about things that affect them (with full knowledge and without being overwhelmed). Transparency is a sideshow. Transparency is worthless if it overwhelms or doesn’t support meaningful decision making.

                The point of this post is that metrics are important, rigorously important. Privacy needs to step out of the dark ages of intuition, superstition, and old wives tales.

The author is principal at Enterprivacy Consulting Group, a boutique consulting firm focused on privacy engineering, privacy by design and the NIST Privacy Framework.