MLB and Technology
I read this article in the Harvard Business Review this month where they compared Innovation managers with MLB General Managers. I am going to extend this article a little further by discussing the step before making decisions in innovation or in the major leagues.
Innovation comes in many different sorts, most of the time innovation comes from things that you already have in the market and you are looking at trends in the consumer use and then practical application of the product to real world situations. The only way you can get this kind of information is by data analysis (i.e. Statistical research just like in the MLB).
Take the Swiffer as an example, all it is, is a paper towel draped over a rectangle that has a handle attached to it. It is pretty obvious, however genius because it’s another use case of something that P&G already had, probably didn’t cost too much to manufacture. The real cost was in creating the brand, which is a huge success. How did P&G determine that Swiffer could be successful? They did data and use case analysis. I am willing to bet they had a team of business analysts working with product managers to determine what the marketability of Swiffer would be, and it came out to be a green light.
Now, apply that same process to an MLB team. As a GM you have a bench of players, each with different skills. You have scouting reports (the data) on the teams you will be playing, you also have the stats for your current players. Going into a game there is not much a manager doesn’t know about what’s on the other team. Instead it’s the prediction of the market that you need to be concerned with. The way you can predict is by analyzing the data you have available to you and being able to make educated decisions. If the team you are going to be playing against has a lot of left-handed batters in their line-up you would obviously want a strong arm in right field. It is much more complex than that though, probably why I’m not a GM in the MLB.
The point is you can determine what your success might be by looking at arranging the same objects you have already created in a different sort and applying a strategy to it, to me that is what innovation is, rearranging information to make a completely different decision, a case of the whole being far more valuable than the sum of its parts.
I thought the article was really fascinating and I have been waiting for an article that would tie the MLB to business, but being in technology I apply the article to the technology world and good data analysis is step 0 for innovation.
Next time I will discuss runtime events and exception handling in the major leagues!
posted on
10/16/2009
by
Michael Taylor
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