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Being a book about statistics (and baseball) that has been turned into a successful Hollywood movie, I was very interested to read "Moneyball", by business author Michael Lewis. Despite knowing very little about baseball, I found it an interesting lesson in the application of statistical analysis in a business context.

The book discusses the Californian baseball team, the Oakland A's. Despite having a limited budget to acquire expensive baseball players, the Oakland A's manage to play a lot better than their team budget would predict, thanks to selection of players based on their statistical performance rather than the subjective views of baseball scouts.

According to the book, the response of other baseball teams is one of two:

1)            Continue to rely on subjective assessment. The author notes in an afterword (of the later edition I read) that some of the managers of competing teams were proud to proclaim that they had never read "Moneyball" despite its popular success. In fact the whole field of "sabermetrics", or the statistical analysis of baseball, was largely developed outside the world of professional baseball.

2)            Continue to rely on indirect rather than direct statistics when they do use them. For example, many baseball managers judged baseball pitchers partially on their speed of their fast balls, rather than purely on their 'earned run average' which records how many runs the other team is able to hit off their pitching. Similarly batters were judged on their 'batting average' (how well they hit the ball) rather than 'on-base percentage, which also takes into account when they obtained 'walks' from the pitcher (batters get a free walk to the next base if the pitcher throws three no balls at them). In both cases, the latter measure is a direct measure of the outcomes of the pitcher and batter respectively, rather than their athletic performance. Sure, their athletic performance may have contributed to their outcomes, but ultimately it is the outcomes that count 

This of course is a blog about patents and not baseball. But I see parallels between the comments that we have seen to our Network Patent Analysis (NPA) service and the above comments:

1)            Some patent professionals have refused to believe that objective patent analysis can ever replace their subject assessment of patents. Maybe.

2)            Other patent professionals have suggested a range of quite indirect measures of patent quality. For example, somebody recently suggested that the length of the patent prosecution file wrapper could be a useful guide to the legal quality of a patent. Again, my response is 'maybe' – but I would also suggest that this particular statistic reflects whether the patent examiner thought that the patent should be granted or not, and the patent prosecution strategy being used by the applicant. These may not always correlate with the quality or value of the patent. Similar observations can be made about many other indirect measures.

Another parallel between patent ownership and baseball is that both are very competitive fields. And as such good ideas should drive out bad ideas under the pressure of competition. For this reason I have strong faith in the ability of the right patent analysis methods to replace weaker objective and subjective analysis methods over the fullness of time.

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