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Coming Out of Left Field

Coming Out of Left Field

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Baseball is the arguably the most hallowed game in America. Trying to redefine baseball is almost like trying to redesign the American flag. It’s practically sacrosanct.

Since the 19th century, a player’s performance has been determined by the insider opinions of players, managers, coaches and scouts using traditional statistics such as stolen bases and batting averages. Moneyball, a book and a film, chronicled the efforts of a baseball team, the Oakland A’s, to change this by analyzing in-game activity such as on-base and slugging percentages as better indicators of a team’s potential for success.

Thanks to this, the Oakland A’s were able to win more games with less money than wealthier clubs by attracting undervalued talent. But challenging orthodoxies is seldom easy and early pioneers are often rewarded more by arrows than accolades.

Their approach has since become adopted by many other teams revolutionizing the way the game is played. It arguably helped the Red Sox eliminate the Curse of the Bambino.

A large retailer recently discovered a major competitor was steadily gaining market share across many profitable lines of business. A closer look revealed the competitor had made massive investments in its ability to collect, integrate, analyze and absorb data from each store. At the same time, it had linked this information to suppliers’ databases, making it possible to alter prices in real time, reorder fast-selling items automatically, and shift items from store to store more easily. By taking a different approach to managing data the competitor had rewritten the rules of the retailing game.[i]

Financial services firms have long made money out of information. But while banking data often remains siloed, stale and incomplete, the nature of data has dramatically changed. Today there is more to analyze, it moves faster and comes in many different forms.  And it comes from different sources, from social networks, sensors and web traffic. Almost every major bank today has a ‘big data’ project trying to get its data house in order.

But when it comes to managing ‘big data’ social networks leave banks far behind. Creating huge data franchises by connecting people through new forums, relationships and associations requires a very different approach to data management than banks have traditionally employed.

Social networks have taken the management of large amounts of structured and unstructured data to a new level. Hadoop, which is hosted at the Apache Software Foundation, was formed by Yahoo and is based partly on the MapReduce programming model developed by Google. It is a software framework for managing and distributing large amounts of data across multiple computer clusters.

Microsoft has announced great plans about Hadoop adoption to deliver enterprise class Apache Hadoop based distributions on both Windows Server and Windows Azure. Customers will be able to interchange data between Hadoop environments, SQL Server, and Parallel Data Warehouse.

Can the technology of social networks help banks redefine the rules of the game? Perhaps by tapping and managing different data sets more creatively than before.

 

 



[i][i] McKinsey Quarterly, October, 2011