I think about data a lot. I think about football a lot too. Sometimes I think deeply about both at the same time! I read all kinds of books and articles on both topics and look for ways to fuse them together. During a search I found the book 'Moneyball', by Michael Lewis, which ticked all my boxes.
This is my favorite summary of the Moneyball story, delivered by Lewis himself:
I particularly like this section:
“There can't be any corporation in America, any industry, where the employees are as scrutinised as professional baseball players. They do what they do in front of millions of people, many of whom just assume they are experts in valuing baseball players. They have statistics, sometimes the wrong statistics, but nevertheless statistics, attached to every move they make on the baseball field. They’ve been doing basically the same thing for 100 years and more or less the same thing for 150 years. If that employee can be so badly mis-valued that you can build a juggernaut [the Oakland As] out of the rejects of the profession, the defective parts, then who can’t be mis-valued?”
This story, for me more than any other, depicts the holy grail for all data and business intelligence disciplines. Here is a situation where conventional wisdom, established for over one hundred years, was being shattered by well-formed predictive data. Prejudice, self-interest and emotion were all taken out of the equation to be replaced by objectivity and creative ability. A sporting juggernaut was built thanks to the work of a couple of skinny graduates armed with nothing more than a laptop and a talent for data collection and analysis.
How often does that really happen? I wonder how many people are considered experts in markets that they really don't understand - and will never have the opportunity to understand (be that through a lack of talent or a lack of incentives). How much effort (and money) goes into counting things that don't really count, or trying to count things that can't really be counted?
As we look to navigate the future of 'big data' that's well on the way, I can't help but feel like it'll be more important than ever for analysts and designers to identify 'what counts', or what 'will count', and to ensure sufficient investment is aimed at those areas - even if it means feeling a little isolated from time-to-time.
