The N=1 Problem

Recently read this article from ESPN about how the Angels are trying to rebuild their minor league system.

http://m.espn.go.com/mlb/story?storyId=10470778&src=desktop

One of the subtle reasons I love reading articles like this is that at the core, major league baseball teams are no different than other national or multi-national corporations.  All the same management, mentoring, training, recruiting, and retainment issues all organizations face are the same in baseball as everywhere.  It's just that when spoken about in a baseball context, the article is way more interesting than some droll tale of organizational synergy.
 
There's two chunks of the article I love the best:

Most of the lessons of the sabermetric revolution are based on what's called large-N analysis: looking at all the players who ever played and finding, in millions of data points, answers about player tendencies and optimal strategy, and meta-answers about the reliability of statistics. But developing a prospect is an N=1 problem: Each player's combination of skills, genes, experience, health, neurology, psychology, size and style makes him unlike any other player.

then later

How a coach teaches pitchers to back up a base isn't, ultimately, all that important. What's important is that no coach has to spend more than two minutes of his life thinking about it. That frees him to focus on the N=1 problems

In other words, if a coach has to waste his time dealing with "stupid stuff", then the coach can't concentrate on what's important, namely teaching the player what they need to be taught to reach the next level.

I can't help but think about this within the context of a lot of major companies.  Every employee will have different opinions on what are "annoyances" or "interruptions".  It's likely impossible to remove all of them for every employee, but the hope is that most organizations limit it to a N=2 or N=3 problem for most employees.  Unfortunately, I suspect many employees are dealing with N=9 or N=11 problems.