Gather the right quantitative data and qualitative data from the start - Sports analytics and the CIO: Five lessons from the sports data craze

Sports analytics and the CIO: Five lessons from the sports data craze

Gather the right quantitative data and qualitative data from the start

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Superstar statistician Nate Silver, center, was one of five speakers in the Source: Rachel Lebeaux

As in the enterprise, one of the first questions analytics-driven sports teams must answer for themselves is what data they need to gather and analyze, and in what quantity.

There are technologies today that allow teams to capture an immense number of data points -- optical tracking of player movement on the basketball court, for instance, which captures 25 frames per second. But it's still a jungle out there, and CIOs need to make sure their organizations are collecting the right quantitative data and qualitative data from the get-go.

That's where having data scientists and analysts on your IT staff becomes critical. These individuals are trained not only in knowing what quantitative and qualitative data to collect, but also in the way to properly analyze this information to extract the most business value. As CIO, make sure you and your data analytics experts know how to apply their metrics to improving your IT operations.

But in your effort to be conscientious, don't over-collect quantitative or qualitative data, either. Take it from Nate Silver, the much-celebrated statistician and New York Times contributor who correctly predicted nearly 100% of the voting results of the 2012 U.S. presidential election. "In almost any field, there are diminishing returns as you add complexity to an analytics model," he said during a presentation at this year's MIT Sloan Sports Analytics Conference.

Stan Van Gundy, a former NBA head coach of the Orlando Magic and Miami Heat, made similar rumblings, noting that "cluttered minds" make for "slow feet" on the basketball court.

In other words: Be smart in what you collect and analyze. Bog down your people with numbers and metrics they don't need, and their productivity and IT innovation might screech to a halt.

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