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January 23, 2014 By Sanjay Sarathy

The Oakland A's, the Enterprise and the Future of Data Innovation

Remember Moneyball? Moneyball is the story of how the performance of the Oakland A’s skyrocketed when they started to vet players based on sabermetrics principles, a data-driven solution that defied conventional wisdom. The team’s success with a metrics-driven approach only came about because GM Billy Beane and one of his assistants, Paul DePodesta, identified the value in player statistics and trusted these insights over what other baseball teams had accepted was true. Any business can learn a significant lesson from Billy Beane and Paul DePodesta, and it is a lesson that speaks volumes about the future of data in business.

If a business wants their data to drive innovation, they need to manage that data like the Oakland A’s did. Data alone does not reveal actionable business insights; experienced analysts and IT professionals must interpret it. Furthermore it’s up to business leaders to put their faith in their data, even if it goes against conventional wisdom.

Of course, the biggest problem companies confront with their data is the astronomical volume. While the A’s had mere buckets of data to pour through, the modern enterprise has to deal with a spewing fire hose of data. This constant influx of data generated by both humans and machines has paralyzed many companies who often never analyze the data available to them or just analyze the data reactively. Reactive data analysis, while useful to interpret what happened in the past, can't necessarily provide insights into what might occur in the future. Remember your mutual fund disclaimer?

Innovation in business will stem from companies creating advantages via proactive use of that data. Case in point: Amazon’s new initiative to anticipate customers’ purchases and prepare shipping and logistics "ahead of time.”

The ability to be proactive with machine data won’t be driven simply by technology. It will instead stem from companies implementing their own strategic combination of machine learning and human knowledge. Achieving this balance to generate proactive data insights has been the goal of Sumo Logic since day one. While we have full confidence in our machine data intelligence technologies to do just that, we also know that is not the only solution that companies require. The future of data in the enterprise depends on how companies manage their data. If Billy Beane and Paul DePodesta effectively managed their data to alter the trajectory of the Oakland A’s, there is no reason that modern businesses cannot do the same.

This blog was published in conjunction with 'Data Innovation Day'

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Sanjay Sarathy

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